13 Criteri particolari di valutazione

Scientia Horticulturae 174(2014)126–132Contents lists available at ScienceDirectScientiaHorticulturaej o u r n a l h o m e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /s c i h o r tiMapping of quantitative trait loci corroborates independent genetic control of apple size and shapeYuansheng Chang a ,Rui Sun a ,Huanhuan Sun a ,Yongbo Zhao b ,Yuepeng Han c ,Dongmei Chen b ,Yi Wang a ,Xinzhong Zhang a ,∗,Zhenhai Han a ,∗aInstitute for Horticultural Plants,College of Agronomy and Biotechnology,China Agricultural University,Beijing 100193,China bChangli Institute for Pomology,Hebei Academy of Agricultural and Forestry Science,Changli,Heibei 066600,China cWuhan Botanical Garden,The Chinese Academy of Sciences,Wuhan 430074,Chinaa r t i c l ei n f oArticle history:Received 3April 2014Received in revised form 18May 2014Accepted 19May 2014Available online 9June 2014Keywords:Fruit shape Fruit size QTLMalus domesticaa b s t r a c tFruit size and shape are important external quality traits in commercial crops.To determine the genetic relationship between the size and shape of apple fruits,quantitative trait loci (QTLs)for apple size (average weight),length,diameter,and shape (length/diameter ratio)were identified and mapped in progeny of a ‘Jonathan’בGolden Delicious’cross.Fruit size,length,and diameter followed a normal distribution.There was no correlation between apple size and shape,but both variables were significantly correlated with length and diameter.Forty-five QTLs for apple size,length,diameter,and shape were mapped to 13chromosomes of the two parent cultivars.Of these,12QTLs for fruit length and diameter either overlapped or were closely associated with QTLs for fruit size,whereas three co-localized with QTLs for fruit shape.No QTLs for fruit size mapped to the same or neighboring regions as QTLs for fruit shape,suggesting that size and shape are under independent genetic control.©2014Elsevier B.V.All rights reserved.1.IntroductionFruit size and shape are important external quality traits in commercial fruit crops.Fruit size is usually quantified by average weight and determined by fruit length and diameter.Fruit shape can be quantified morphometrically by length and diameter or can be described using morphological attributes,such as the fruit shape index (FSI;length:diameter ratio),indentation area,and boundary angles (Brewer et al.,2006;Gonzalo et al.,2009).New apple (Malus domestica )varieties,with improved and novel quality traits,for use in apple breeding programs should satisfy consumers (Meneses and Orellana,2013).The market usually demands large fruit.Con-sumers prefer fruit with a relatively larger longitudinal length and smaller latitudinal diameter (Tabatabaeefar et al.,2000;Waseem et al.,2002;Sadrnia et al.,2007).Apple size and shape are under polygene control and are quan-titatively inherited (Brown,1960).The heritability for apple fruit shape aspect (ratio of height to maximum width)is estimated to be 0.79;fruit aspect is best predicted by the ratio of length to∗Corresponding authors.Tel.:+861062734391;fax:+861062734391.E-mail addresses:zhangxinzhong999@ (X.Zhang),rschan@ (Z.Han).diameter (R 2=0.97)(Currie et al.,2000).In our previous work,we identified five major genes involved in the segregation of FSI,and the heritability of these genes was as high as 75.0%(Sun et al.,2012).The heritability of length and diameter in strawberry (Fragaria ×ananassa Duch.)is reported as 0.51and 0.21,respec-tively (Lerceteau-Köhler et al.,2012).In hybrid crosses of European pears,the heritability of fruit shape is estimated to be 0.66from parent–offspring regression,and 0.68from variance component analysis (White et al.,2000).The heritability of apple size has been estimated to be as low as 0.33,whereas estimates for fruit weight are higher (0.56–0.61)(Durel et al.,1998;Oraguzie et al.,2001;Alspach and Oraguzie,2002).Phytohormones and environmental factors have different effects on apple fruit length and diameter.Young seeds likely provide a source of gibberellins during the early stages of fruit development (Garcia-Martinez et al.,1987).Application of exoge-nous gibberellic acid (GA 4+7)during blooming or early fruit developmental stages produces longer apples at ripening,with a FSI >1.0in the ‘Golden Delicious’variety (Eccher and Boffelli,1981).In contrast,foliar application of the plant growth retardant paclobu-trazol (PP333)at 1500or 3000ppm,administered 21days after full blooming,resulted in a significantly lower FSI in ripe fruit compared with control fruit;the reduced FSI persisted until the fourth year after spraying (Greene,1986).Foliar application of GA 3or GA 4+7/10.1016/j.scienta.2014.05.0190304-4238/©2014Elsevier B.V.All rights reserved.Y.Chang et al./Scientia Horticulturae174(2014)126–132127counteracted the effect of PP333(Curry and Williams,1983).Con-tinuous fruit growth,from cell division to ripening,is primarily associated with auxin-related cell expansion(Devoghalaere et al., 2012).The harvest weight of apples is closely correlated with seed number(including aborted seeds),and increased fruit weight is attributed to increased cell number rather than cell size(Denne, 1963).Environmental factors can also affect apple fruit shape, specifically temperature and humidity.Shaw(1914)observed that fruit length was longer when temperatures were lower following full bloom.Tromp(1990)reported that the FSI of‘Golden Delicious’was lower in apples grown at a relative humidity between40and 50%than in apples grown at80–90%relative humidity.Developmental rhythms differ for fruit length vs.diameter.The expression of genes important in cell division(e.g.,MdANT1and MdANT2)is high from bloom until15days after full blooming(Dash and Malladi,2012),a period coinciding with active cell division and rapid longitudinal fruit growth(Skene,1966).Quantitative trait loci(QTLs)are important in the investiga-tion of the genetic control of economically valuable traits.Genetic linkage maps enable the identification of chromosome regions con-taining one or more genes associated with QTLs(Meneses and Orellana,2013;Tanksley,1993).Since the generation of thefirst integrated apple linkage map (Rome Beauty×White Angel;Hemmat et al.,1994),several genetic linkage maps have been reported in apple(Conner et al.,1997; Maliepaard et al.,1998;Liebhard et al.,2002,2003;Baldi et al., 2004;Silfverberg-Dilworth et al.,2006;Calenge et al.,2004;Kenis et al.,2008;Zhang et al.,2012).Saturated and high-density genetic linkage maps are useful for genetic research,and many traits have been mapped in apple (Conner et al.,1997;Weeden et al.,1994;Stankiewicz-Kosyl et al., 2005;Fernández-Fernández et al.,2008;Gao et al.,2005).In apple,QTLs for fruit length have been mapped on linkage group(LGs)2,6,15,and17;and QTLs for apple diameter on LGs2, 5,9,10,and17(Kenis et al.,2008).However,mapping results in dif-ferent years(2004and2005)were found to be inconsistent(Kenis et al.,2008).Several QTLs for apple fruit size have been identified in different mapping populations,including‘Fiesta’בDiscovery,’‘Telamon’בBraeburn’,‘Royal Gala’בBraeburn,’and‘Starkrim-son’בGranny Smith’(Liebhard et al.,2003;Kenis et al.,2008; Devoghalaere et al.,2012).We previously mappedfive major gene loci involved in the determination of FSI using bulked segregant analysis in a ‘Jonathan’בGolden Delicious’mapping population;these were located on LGs11,12,and13of the female parent‘Jonathan’,and on LG10of the male parent‘Golden Delicious’(Sun et al.,2012). However,we did not obtain any QTLs without linkage maps at that time.In this study,to clarify the genetic relationships among fruit weight,length,diameter,and FSI,and we analyzed the inheritance of these external quality traits,and identified QTLs associated with them.2.Materials and methods2.1.Plant materialsThe apple cultivars‘Jonathan’(J)and‘Golden Delicious’(G),with ‘Jonathan’as the female parent were crossed in spring2002at the Changli Institute of Pomology(Hebei Province,China)to obtain hybrid progeny.Seedlings were planted in2003at a density of one per0.5m×2m plot,resulting in a J×G F1population of1733 seedlings.After planting,the seedlings were subjected to conven-tionalfield management and pest control procedures(Sun et al., 2012).2.2.PhenotypingApples sufficient for phenotyping were harvested in1162 seedlings in2008.Due to alternate bearing,ripening fruit from971 seedlings were collected in2009.A vernier caliper was used for the measurements of fruit diameter(D)and fruit length(L).The phenotypic value used for further analysis was represented by the average values of at leastfive apples per seedling each year.FSI was calculated using the formula FSI=L/D.Fruit size was recorded as the average fruit weight,and the phenotypic data of fruit size were the average values offive apples,which were determined by weighing the fruit on an analytical balance.2.3.Inheritance analysisTo evaluate the quality of phenotypic data to obtain reliable results of QTL identification,data of fruit length and fruit diame-ter were subjected to analysis of variance(ANOVA,F-test)using Microsoft Excel2003with30randomly selected seedlings,which bear sufficient amounts of fruit(n=10apples per plant)in both 2008and2009.The correlations of fruit length,diameter,shape, and size were analyzed using data collected from983seedlings in 2008and from789seedlings in2009.Inheritance was analyzed using frequency-distribution analysis,Shapiro–Wilk tests(SPSS v.12.0;SPSS Inc.,Chicago,IL,USA),and chi-square tests(Microsoft Excel2003).This protocol has been previously described by Sun et al.(2012).Phenotypic variance(S)was defined as the sum of genotypic variance(Sg)and environmental variance(Se).Heritabil-ity was calculated as(S−Se)/S×100%,and S was calculated using the variance among the30seedlings.Environmental variance was represented by the average variance among the10apples from each seedling(Sun et al.,2012).2.4.QTL analysisQTL analysis was performed using our previously published genetic linkage maps(Zhang et al.,2012),which consisted of 242individuals and251simple sequence repeat(SSR)markers. Phenotypic data on fruit length,diameter,FSI and size for the map-ping population(n=242seedlings)were collected in2008(n=144 seedlings)and2009(n=140seedlings).MapQTL 6.0(Van Ooijen et al.,2009)was used to analyze QTLs.Interval mapping was performed,and the genome-and chromosome-wide threshold for QTL significance of logarithm of odds(LOD)was calculated by performing1000iterations using the MapQTL Permutation Test.The genome-wide threshold was LOD=2.80at the95%confidence interval.3.Results3.1.Phenotype evaluationThere was significant variation in fruit diameter,length,and FSI among the seedlings and between the sampling years,but there were no significant differences among apples from individ-ual seedlings(Table1).Unfortunately,ANOVA could not be used for fruit size because phenotypic data were obtained by averaging the weight of10apples from each seedling.Fruit length and diameter were significantly correlated(r>0.70) in both2008and2009.FSI was positively correlated with fruit length,and negatively correlated with fruit diameter.The abso-lute values of correlation coefficients between FSI and fruit length were larger than those between FSI and fruit diameter,suggesting that length was a more pronounced trait than diameter.Although both length and diameter were positively correlated with fruit size, the correlation was stronger for diameter,indicating that fruit size128Y.Chang et al./Scientia Horticulturae 174(2014)126–132Fig.1.Frequency distributions of fruit length,diameter,and size (weight)in progenies from the ‘Jonathan’בGolden Delicious’hybrid cross.Phenotypic data were collected in 2008and 2009.The parental values are indicated on the figures with vertical dash lines.(weight)was more a function of diameter than of length.No signif-icant correlation was detected between FSI and fruit size (Table 2).Fruit size,length,and diameter followed normal distribution patterns in both sampling years,and they showed features typical of quantitative traits controlled by polygenes without major gene segregation (Fig.1).The broad-sense heritability of fruit length and diameter were estimated as 91%and 93%,respectively in 2008;and as 82%and 85%in 2009.These values indicated that environmental effects had a greater effect on fruit quality in 2009(Table 3).3.2.QTL analysisNineteen QTLs for fruit size,shape,length,and diameter were identified at the whole-genome level based on a LOD thresh-old ≥2.80in both sampling years (Table 4).Twenty-six additionalTable 1F -tests of phenotypic traits in apple fruit.VariationTraitYearFF 0.01Seedlings Length 2008106.62* 1.78200947.57* 1.78Diameter2008142.01* 1.78200960.69*1.78ReplicatesLength20080.22 2.4720090.70 2.47Diameter20080.147 2.4720090.542.47YearsLength 56.53* 6.68Diameter23.05*6.68*Significant difference at P ≤0.01as determined using Duncan’s test.QTLs were identified,based on a permutation test at P =0.05,at the single-chromosome-based LOD threshold (Table 4,Fig.2).Of these,eight QTLs related to fruit length were detected in 2008;no QTLs for fruit length were detected in 2009.Eleven and two QTLs for fruit size were identified in 2008and 2009,respec-tively.Nine QTLs in 2008and two QTLs in 2009for fruit diameter mapped onto the two parental linkage groups.In addition,we also detected seven and six QTLs associated with FSI in 2008and 2009,respectively.For FSI,one QTL,fsij08.11.2/fsij09.11on LG11of the female parent ‘Jonathan,’and one QTL fsig08.15/fsig09.15.1in the male parent ‘Golden Delicious’were observed in both years (Fig.2).Four QTLs for fruit size,four for diameter,and three for length co-localized and clustered on chromosome 8of ‘Golden Delicious.’The fszg08.11.1QTL for fruit size was tightly linked to flg08.11forTable 2Correlations between apple length,diameter,shape index,and size in a ‘Jonathan’בGolden Delicious’hybrid population.Fruit traitFruit lengthFruit diameterFruit shape2008Fruit diameter 0.77*Fruit shape 0.48*−0.19*Fruit size0.76*0.87*−0.0332009Fruit diameter 0.76*Fruit shape 0.42*−0.27*Fruit size0.78*0.89*−0.084983seedlings in 2008and 789in 2009were used to analyze the correlations of fruit length,diameter,shape and size (r 0.05=0.0625and r 0.01=0.082in 2008;r 0.05=0.07and r 0.01=0.09in 2009).*Significance at P =0.05.Y.Chang et al./Scientia Horticulturae174(2014)126–132129 Table3Estimated heredity parameters for apple length and diameter in a‘Jonathan’בGolden Delicious’hybrid population.Trait Year Average±SD(mm)Population variance(S)Genetic variance(Sg)Environmental variance(Se)Heritability(%) Fruit length200858.66±5.48123.41112.4310.9891.10 200952.88±4.5828.3823.24 5.1481.89Fruit diameter200868.70±5.69156.63145.9610.6793.20 200963.27±5.1540.3334.39 5.9485.30length and to fdg08.11for diameter on LG11of‘Golden Delicious’(Table4,Fig.2).The QTL fszj08.15(fruit size)overlappedflj08.15 (fruit length)exactly on chromosome15of‘Jonathan’.The fszg08.3 QTL for fruit-size coincided with fdg08.11.3(fruit diameter)and QTL fszj08.5(fruit size),and partially overlapped fdj08.5(fruit diame-ter)on LG5of‘Jonathan’(Table4,Fig.2).For FSI,fsij08.4partially overlappedflj08.4(fruit length)on LG4of Jonathan;fsij09.9was co-localized with fdj09.9on LG9;and fsij08.17was closely linked to flj08.17on LG17of‘Jonathan’(Table4,Fig.2).4.DiscussionFruit size and shape indices were closely associated with length and diameter,whereas the inheritance of fruit size,shape,length, and diameter differed.The normal distribution of phenotypic traits suggests that apple length,diameter,and size are under polygenetic control.However,variation in FSI is associated with segregation in both major genes and polygenes,and the heritability of major genes was found to be as high as75%(Sun et al.,2012).Table4Quantitative trait loci(QTLs)and mapping information for apple size,shape,length,and diameter in segregated progeny of‘Jonathan’בGolden Delicious’.Trait Year QTL LG Location Nearest marker LOD Contribution to totalvariance(%)Fruit length2008flj08.15J150.000WBGCAS50 3.5010.10flj08.17J17-20.000NZmsEB137525 2.337.60flj08.4J40.000Hi23g08 2.01 6.20flj08.8J871.700Hi23g12 1.797.30flg08.8.1G869.141H20b03 3.9812.10flg08.8.2G837.552BACSSR46 3.0411.80flg08.8.3G830.644CTG1069672 3.3013.00flg08.11G1116.788CH05c02 2.347.70Fruit diameter2008fdj08.5J591.033NZmsCN898349 2.809.20fdj08.13J1321.582CTG1075622 2.087.20fdg08.2G258.212CH03d10 2.387.30fdg08.3G382.408WBGCAS27 2.258.10fdg08.8.1G868.660Hi20b03 3.1710.1fdg08.8.2G853.250CH05a02 3.0212.5fdg08.8.3G837.552BACSSR46 2.8510.90fdg08.8.4G830.644CTG1069672 3.0311.30fdg08.11G1120.788BACSSR10 2.539.202009fdj09.9J927.391CTG1067792 2.739.10fdg09.4G4 5.000CH01b01b 1.80 6.30Fruit shape index2008fsij08.4J40.000Hi23g08 2.878.40fsij08.17J17-2 5.000CN938125 1.91 6.20fsig08.15G15-1 1.000CH02c09 2.598.00fsij08.11.1J1114.813Hi23d02 4.0012.80fsij08.11.2J117.371CH02d12 3.4210.30fsij08.11.3J11 3.000CH02d08 3.7613.70fsij08.5J57.000CN881672 1.817.702009fsij09.9J924.391CTG1067792 2.659.20fsij09.13J1332.087CTG1075622 2.2110.00fsij09.7J715.069CTG1060504 1.817.20fsig09.15.1G15-1 3.000CH02c09 1.95 6.70fsig09.15.2G15-151.249NZmsEB117266 1.85 5.50fsij09.11J117.371CH02d12 4.0210.20Fruit size2008fszg08.8.1G869.141Hi20b03 4.2912.80fszg08.8.2G851.250CH04g12 3.0712.60fszg08.8.3G837.552BACSSR46 3.1311.50fszg08.8.4G828.644CTG1069672 3.3112.60fszg08.11.1G1124.788BACSSR10 2.979.70fszg08.11.2G119.930CH04a12 2.447.30fszg08.11.3G110.000CH02d08 2.147.10fszj08.5J595.033Hi02a03 2.517.7fszj08.15J150WBGCAS50 2.227.2fszj08.12J1257.944CH03c02 2.019.6fszg08.3G384.408WBGCAS27 1.72 6.42009fszg09.12G1245.311WBGCAS37 2.02 6.7fszg09.14G1494.33NZmsEB146613 1.858.9LG:linkage group;LOD:logarithm of odds.QTLs detected at whole-genome LOD threshold≥2.8are indicated in bold fonts.130Y.Chang et al./Scientia Horticulturae 174(2014)126–132Fig.2.Internal mapping of quantitative trait loci (QTLs)for fruit length,diameter,shape index (FSI),and size using the ‘Jonathan’בGolden Delicious’hybrid population.The letters J and G on the top of the linkage maps represent the maternal parent ‘Jonathan’and pollen parent ‘Golden Delicious’,respectively.The number following J and G indicates the number of linkage groups.Homologs between parents on corresponding linkage groups (LGs)are joined to each other with solid black lines.The solid color bars indicate the QTLs identified on the most likely position of the linkage groups,while the thin lines represent the confidence interval at the 95%level.QTLs for fruit length,diameter,size,and FSI are marked by the black,blue,red,and yellow color bars,respectively.F11-1and F11-2,on LG11of ‘Jonathan’,represent the two major gene loci for FSI detected by Sun et al.(2012).(For interpretation of the references to color in this legend,the reader is referred to the web version of the article.)Our findings contrasted with previous reports that apple fruit size is a quantitative trait with relatively low heritability (0.33–0.61)(Durel et al.,1997;Oraguzie et al.,2001;Alspach and Oraguzie,2002).The heritability of fruit length and diameter was relatively high (82–93%)during the two years of evaluation.Both FSI and fruit size correlated with fruit length and diameter.QTLs for closely correlated traits should map to the same or simi-lar positions (Paterson et al.,1991;Kenis et al.,2008).Thus,QTLs associated with FSI or fruit size,at least in part,should overlap or be linked to those for fruit length and diameter.Indeed,the three QTLs for fruit size (fszg08.8.1,fszg08.8.3,and fszg08.8.4)completely overlapped QTLs for fruit length (flg08.8.1,flg08.8.3,and flg08.8.4),and those for fruit diameter (fdg08.8.1,fdg08.8.3,and fdg08.8.4).In ‘Telamon’and ‘Braeburn’progeny,QTLs for apple weight,height,and diameter on LG17partially overlapped with QTLs for fruit height and diameter on LG2.Furthermore,year-stable QTLs for fruit weight and diameter overlapped on LG10of the two par-ents (Kenis et al.,2008).Similarly,the QTL for FSI (fsij08.4)precisely overlapped the one for fruit length (flj08.4),whereas fsij09.9and fsij08.17for FSI were closely linked to fdj09.9and flj08.17,respec-tively.These co-localizations confirmed the correlation analysis that indicated that fruit length strongly affects FSI.In our hybrid population,QTLs for fruit length (on LGs 15and 17)and diameter(on LGs 2,5,and 9)were located on the same LGs as QTLs in the ‘Telamon’בBraeburn’cross (Kenis et al.,2008).Using two map-ping populations,Devoghalaere et al.(2012)identified six QTLs for fruit size,on LGs 5,8,11,15,16,and 17;of these,QTLs on LGs 8and 15were conserved across both populations.In hybrid populations derived from European and Chinese pears,QTLs for FSI,weight,and length co-localized on LG8;interestingly,some QTLs clustered on LG7of the female parent (Zhang et al.,2013).However,we did not detect significant correlations between FSI and fruit size.Thus,the QTLs for these traits did not map close to each other on the same chromosomes.Rather,QTLs for FSI over-lapped with or were linked to QTLs for fruit length and diameter on chromosomes that were not linked to fruit size,thus demonstrat-ing that FSI and fruit size are controlled by different genes.Such independent genetic control differs fundamentally from other fruit species,such as pear (Zhang et al.,2013).In muskmelon (Cucumis melo L.),the major QTL for fruit shape (fs2.2)is co-localized with a major gene (andromonoecious );this effect is detectable in com-parisons of ovary and fruit length,but not ovary and fruit width (Périn et al.,2002).Another major QTL for fruit shape,fs12.1,co-segregates with another major gene,pentamerous ,and this effect is detectable in comparisons of ovary and fruit width,but not ovary and fruit length (Périn et al.,2002).Y.Chang et al./Scientia Horticulturae174(2014)126–132131We observed a significant correlation between fruit length and diameter,and a close relationship between fruit diameter and size. Four QTLs for fruit diameter,compared with only one QTL for fruit length,co-segregated with or closely linked to QTLs for fruit size. Four QTLs also contributed simultaneously to fruit size,length, and diameter.Instability of QTLs between different years of detec-tion has been reported for many species(Liebhard et al.,2003; Zhang et al.,2013).However,only two QTLs,fsij08.11.2/fsij09.11 and fsig08.15/fsig09.15.1,were stable across the two-year study.The variation in fruit length and diameter between the sampling years indicates that environmental effects or genotype–environment interactions affect the robustness of QTLs between years.Kenis et al.(2008)also observed that QTLs for fruit weight,diameter,and height differed among years.QTL-mapping software provides a powerful tool for detecting major genes for qualitative and quantitative traits(Jones et al., 1997).Our previous study used the same data sets to identifyfive major gene loci involved in apple FSI(Sun et al.,2012).Of thesefive loci,F11-1(Fig.2),flanked by CH02d08and CH04a12,mapped to the same region as the year-stable QTL fsij08.11.2/fsij09.11at7.371 cM on chromosome11of the female parent‘Jonathan’,closest to CH02d12.The major gene locus F13was located in the same region as the QTL fsij09.13(Sun et al.,2012).In the apple genome,more than10genes related to fruit growth and development,including genes involved in cell division and auxin signaling,are scattered in the region of CH02d12,at7.371 cM on LG11.An auxin response factor gene,ARF106,which modu-lates cell division and expansion,is co-localized with a stable QTL for fruit weight in duplicated regions on LGs8and15of the apple genome(Devoghalaere et al.,2012).In conclusion,45QTLs for apple fruit size,shape,length,and diameter were identified from a‘Jonathan’×’Golden Delicious’population.Of the19QTLs for fruit length and diameter,12over-lapped with or tightly linked to QTLs for fruit size,and another three co-localized with QTLs for fruit shape.None of the QTLs for fruit size mapped to the same region as QTLs for fruit shape,indicating that fruit size and shape are under independent genetic control.AcknowledgmentsThis work was supported by the Hi-Tech Research and Devel-opment(863)Program of China(2011AA001204);National Special Funds for Scientific Research on Public Causes(Agriculture)Project 200903044;Modern Agricultural Industry Technology System (Apple)(CARS-28);and Key Laboratory of Biology and Genetic Improvement of Horticultural Crops(Nutrition and Physiology), Ministry of Agriculture,P.R.China.Appendix A.Supplementary dataSupplementary data associated with this article can be found,in the online version,at /10.1016/j.scienta. 2014.05.019.ReferencesAlspach,P.A.,Oraguzie,N.C.,2002.Estimation of genetic parameters of apple(Malus domestica)fruit quality from open-pollinated families.New Zeal.J.Crop Hortic.Sci.30,219–228.Baldi,P.,Patocchi,A.,Zini,E.,Toller,C.,Velasco,R.,Komjanc,M.,2004.Cloning and linkage mapping of resistance gene homologues in apple.Theor.Appl.Genet.109,231–239.Brewer,M.T.,Lang,L.,Fujimura,K.,Dujmovic,N.,Gray,S.,Van der Knaap,E.,2006.Development of a controlled vocabulary and software application to analyze fruit shape variation in tomato and other plant species.Plant Physiol.141,15–25. 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Gonzalo,M.J.,Brewer,M.T.,Anderson,C.,Sullivan,D.,Gray,S.,Van der Knaap,E.,2009.Tomato fruit shape analysis using morphometric and morphologyattributes implemented in tomato analyzer software program.J.Am.Soc.Hortic.Sci.134,77–87.Hemmat,M.,Weeden,N.F.,Manganaris,A.G.,Lawson,D.M.,1994.Molecular marker linkage map for apple.J.Hered.85,4–11.Jones,N.,Ougham,H.,Thomas,H.,1997.Markers and mapping:we are all geneticists now.New Phytol.137,165–177.Kenis,K.,Keulemans,J.,Davey,M.W.,2008.Identification and stability of QTLs for fruit quality traits in apple.Tree Genet.Genomes4,647–661.Lerceteau-Köhler,E.,Moing,A.,Guérin,G.,Renaud,C.,Petit,A.,Rothan,C.,Denoyes,B.,2012.Genetic dissection of fruit quality traits in the octoploid cultivatedstrawberry highlights the role of homoeo-QTL in their control.Theor.Appl.Genet.124,1059–1077.Liebhard,R.,Gianfranceschi,L.,Koller,B.,Ryder,C.D.,Tarchini,R.,Van De Weg,E., Gessler,C.,2002.Development and characterisation of140new microsatellites in apple(Malus×domestica Borkh.).Mol.Breeding10,217–241.Liebhard,R.,Kellerhals,M.,Pfammatter,W.,Jertmini,M.,Gessler,C.,2003.Mapping quantitative physiological traits in apple(Malus×domestica Borkh.).Plant Mol.Biol.52,511–526.Maliepaard,C.,Alston,F.H.,Van Arkel,G.,Brown,L.M.,Chevreau,E.,Dunemann,F., Evans,K.M.,Gardiner,S.,Guilford,P.,Van Heusden,A.W.,Janse,J.,Laurens,F., Lynn,J.R.,Manganaris,A.G.,Den Nijs,A.P.M.,Periam,N.,Rikkerink,E.,Roche, P.,Ryder,C.,Sansavini,S.,Schmidt,H.,Tartarini,S.,Verhaegh,J.J.,Vrielink-van Ginkel,M.,King,G.J.,1998.Aligning male and female linkage maps of apple (Malus pumila Mill.)using multi-allelic markers.Theor.Appl.Genet.97,60–73. 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n engl j med 350;10march 4, 2004 The new england journal of medicine1005The Body-Mass Index, Airflow Obstruction, Dyspnea, and Exercise Capacity Index in Chronic Obstructive Pulmonary DiseaseBartolome R. Celli, M.D., Claudia G. Cote, M.D., Jose M. Marin, M.D., Ciro Casanova, M.D., Maria Montes de Oca, M.D., Reina A. Mendez, M.D.,Victor Pinto Plata, M.D., and Howard J. Cabral, Ph.D.From the COPD Center at St. Elizabeth’s Medical Center, Tufts University School of Medicine, Boston (B.R.C., V .P.P.); Bay Pines Veterans Affairs Medical Center, Bay Pines,Fla. (C.G.C.); Hospital Miguel Servet, Zara-goza, Spain (J.M.M.); H ospital Nuestra Senora de La Candelaria, Tenerife, Spain (C.C.); Hospital Universitario de Caracas and Hospital Jose I. Baldo, Caracas, Vene-zuela (M.M.O., R.A.M.); and Boston Uni-versity School of Public H ealth, Boston (H.J.C.). Address reprint requests to Dr.Celli at Pulmonary and Critical Care Medi-cine, St. Elizabeth’s Medical Center, 736Cambridge St., Boston, MA 02135, or at bcelli@.N Engl J Med 2004;350:1005-12.Copyright © 2004 Massachusetts Medical Society.backgroundChronic obstructive pulmonary disease (COPD) is characterized by an incompletely re-versible limitation in airflow. A physiological variable — the forced expiratory volume in one second (FEV 1 ) — is often used to grade the severity of COPD. However, patients with COPD have systemic manifestations that are not reflected by the FEV 1 . We hypoth-esized that a multidimensional grading system that assessed the respiratory and sys-temic expressions of COPD would better categorize and predict outcome in these pa-tients.methodsWe first evaluated 207 patients and found that four factors predicted the risk of death in this cohort: the body-mass index (B), the degree of airflow obstruction (O) and dys-pnea (D), and exercise capacity (E), measured by the six-minute–walk test. We used these variables to construct the BODE index, a multidimensional 10-point scale in which higher scores indicate a higher risk of death. We then prospectively validated the index in a cohort of 625 patients, with death from any cause and from respiratory caus-es as the outcome variables.resultsThere were 25 deaths among the first 207 patients and 162 deaths (26 percent) in the validation cohort. Sixty-one percent of the deaths in the validation cohort were due to respiratory insufficiency, 14 percent to myocardial infarction, 12 percent to lung can-cer, and 13 percent to other causes. Patients with higher BODE scores were at higher risk for death; the hazard ratio for death from any cause per one-point increase in the BODE score was 1.34 (95 percent confidence interval, 1.26 to 1.42; P<0.001), and the hazard ratio for death from respiratory causes was 1.62 (95 percent confidence inter-val, 1.48 to 1.77; P<0.001). The C statistic for the ability of the BODE index to predict the risk of death was larger than that for the FEV 1 (0.74 vs. 0.65).conclusionsThe BODE index, a simple multidimensional grading system, is better than the FEV 1at predicting the risk of death from any cause and from respiratory causes among pa-tients with COPD.The new england journal of medicine1006hronic obstructiv e pulmonarydisease (COPD), a common disease char-acterized by a poorly reversible limitationin airflow,1 is predicted to be the third most fre-quent cause of death in the world by 2020.2 Therisk of death in patients with COPD is often gradedwith the use of a single physiological variable, theforced expiratory volume in one second (FEV1).1,3,4However, other risk factors, such as the presenceof hypoxemia or hypercapnia,5,6 a short distancewalked in a fixed time,7 a high degree of functionalbreathlessness,8 and a low body-mass index (theweight in kilograms divided by the square of theheight in meters),9,10 are also associated with anincreased risk of death. We hypothesized that a mul-tidimensional grading system that assessed the res-piratory, perceptive, and systemic aspects of COPDwould better categorize the illness and predict theoutcome than does the FEV1 alone. We used datafrom an initial cohort of 207 patients to identifyfour factors that predicted the risk of death: thebody-mass index (B), the degree of airflow ob-struction (O) and functional dyspnea (D), and exer-cise capacity (E) as assessed by the six-minute–walk test. We then integrated these variables into amultidimensional index — the BODE index — andvalidated the index in a second cohort of 625 pa-tients, with death from any cause and death from859 outpatients with a wide range in the severityof COPD were recruited from clinics in the UnitedStates, Spain, and Venezuela. The study was ap-proved by the human-research review board at eachsite, and all patients provided written informed con-sent. COPD was defined by a history of smokingthat exceeded 20 pack-years and a ratio of FEV1 toforced vital capacity (FVC) of less than 0.7 measured20 minutes after the administration of albuterol.1All patients were in clinically stable condition andreceiving appropriate therapy. Patients who werereceiving inhaled oxygen had to have been takinga stable dose for at least six months before studyentry. The exclusion criteria were an illness otherthan COPD that was likely to result in death withinthree years; asthma, defined as an increase in theFEV1 of more than 15 percent above the base-linevalue or of 200 ml after the administration of a bron-chodilator; an inability to take the lung-functionand six-minute–walk tests; a myocardial infarctionwithin the preceding four months; unstable angi-na; or congestive heart failure (New York Heart As-sociation class III or IV).variables selected for the bode indexWe determined the following variables in the first207 patients who were recruited between 1995 and1997: age; sex; pack-years of smoking; FVC; FEV1,measured in liters and as a percentage of the pre-dicted value according to the guidelines of theAmerican Thoracic Society11; the best of two six-minute–walk tests performed at least 30 minutesapart12; the degree of dyspnea, measured with theuse of the modified Medical Research Council(MMRC) dyspnea scale13; the body-mass index9,10;the functional residual capacity and inspiratorycapacity11; the hematocrit; and the albumin level.The validated Charlson index was used to deter-mine the degree of comorbidity. This index hasbeen shown to predict mortality.14 The differenc-es in these values between survivors and nonsur-vivors are shown in Table 1.Each of these possible explanatory variableswas independently evaluated to determine its as-sociation with one-year mortality in a stepwise for-ward logistic-regression analysis. A subgroup offour variables had the strongest association — thebody-mass index, FEV1 as a percentage of the pre-dicted value, score on the MMRC dyspnea scale,and the distance walked in six minutes (general-ized r2=0.21, P<0.001) — and these were includ-ed in the BODE index (Table 2). All these variablespredict important outcomes, are easily measured,and may change over time. We chose the post-bron-chodilator FEV1 as a percent of the predicted value,classified according to the three stages identifiedby the American Thoracic Society, because it can beused to predict health status,15 the rate of exacer-bation of COPD,16 the pharmacoeconomic costs ofthe disease,17 and the risk of death.18,19 We chosethe MMRC dyspnea scale because it predicts thelikelihood of survival among patients with COPD8and correlates well with other scales and health-status scores.20,21 We chose the six-minute–walktest because it predicts the risk of death in patientswith COPD,7 patients who have undergone lung-reduction surgery,22 patients with cardiomyopa-thy,23 and those with pulmonary hypertension.24In addition, the test has been standardized,12 theclinically significant thresholds have been deter-mined,25 and it can be used to predict resource uti-cn engl j med 350; march 4, 2004n engl j med 350;10march 4, 2004 a multidimensional grading system in chronic obstructive pulmonary disease1007lization. 26 Finally, there is an inverse relation be-tween body-mass index and survival 9,10 that is not linear but that has an inflection point, which was 21 in our cohort and in another study. 10validation of the bode indexThe BODE index was validated prospectively in two ways in a different cohort of 625 patients who were recruited between January 1997 and January 2003. First, we used the empirical model: for each threshold value of FEV 1 , distance walked in six min-utes, and score on the MMRC dyspnea scale shown in Table 2, the patients received points ranging from 0 (lowest value) to 3 (maximal value). For body-mass index the values were 0 or 1, because of the unique relation between body-mass index and survival described above. The points for each varia-ble were added, so that the BODE index ranged from 0 to 10 points, with higher scores indicating a greater risk of death. In an exploratory analysis, the various components of the BODE index were as-signed different weights, with no corresponding increase in predictive value.study protocolIn the cohort, patients were evaluated with the use of the BODE index within six weeks after enroll-ment and were seen every three to six months for at least two years or until death. The patient and family were contacted if the patient failed to return for appointments. Death from any cause and from specific respiratory causes was recorded. The cause of death was determined by the investigators at each site after reviewing the medical record and death certificate.statistical analysisData for continuous variables are presented as means ± SD. Comparison among the three coun-tries was completed with the use of one-way analy-sis of variance. The differences between survivors and nonsurvivors in pulmonary-function variables and other pertinent characteristics were established with the use of t-tests for independent samples.To evaluate the capacity of the BODE index to pre-dict the risk of death, we performed Cox propor-tional-hazards regression analyses. 27 We estimat-ed the hazard ratio, 95 percent confidence interval,and P value for the BODE score, before and after adjustment for coexisting conditions as measured by the Charlson index. We repeated these analyses using the BODE index as the predictor of interest in*FVC denotes forced vital capacity, FEV 1 forced expiratory volume in one sec-ond, and FRC functional residual capacity.†Scores on the modified Medical Research Council (MMRC) dyspnea scale can range from 0 to 4, with a score of 4 indicating that the patient is too breathless to leave the house or becomes breathless when dressing or undressing.‡The body-mass index is the weight in kilograms divided by the square of the height in meters.§Scores on the Charlson index can range from 0 to 33, with higher scores indi- cating more coexisting conditions.*The cutoff values for the assignment of points are shown for each variable. The total possible values range from 0 to 10. FEV 1 denotes forced expiratory volume in one second.†The FEV 1 categories are based on stages identified by the American Thoracic Society.‡Scores on the modified Medical Research Council (MMRC) dyspnea scale can range from 0 to 4, with a score of 4 indicating that the patient is too breathless to leave the house or becomes breathless when dressing or undressing.§The values for body-mass index were 0 or 1 because of the inflection point in the inverse relation between survival and body-mass index at a value of 21.The new england journal of medicine1008dummy-variable form, using the first quartile as thereference group. These analyses yielded estimatesof risk similar to those obtained from analyses us-ing the BODE score as a continuous variable. Thus,we focus our presentation on the predictive charac-teristics of the BODE index and present only bivari-ate results for survival according to quartiles of theBODE index in a Kaplan–Meier analysis. The statis-tical significance was evaluated with the use of thelog-rank test. We also performed bivariate analysison the stage of COPD according to the validatedstaging system of the American Thoracic Society.3In the Cox regression analysis, we assessed thereliability of the model with the body-mass index,degree of airflow obstruction and dyspnea, and ex-ercise capacity score as the predictor of the time todeath by computing bootstrap estimates using thefull sample for the hazard ratio and its 95 percentconfidence interval (according to the percentilemethod). This approach has the advantage of notrequiring that the data be split into subgroups andis more precise than alternative methods, such ascross-validation.28Finally, in order to determine how much moreprecise the BODE index is than the FEV1 alone, wecomputed the C statistics29 for a model containingFEV1 or the BODE score as the sole independentvariable. We compared the survival times and esti-mated the probabilities of death up to 52 months.In these analyses, the C statistic is a mathematicalfunction of the sensitivity and specificity of theBODE index in classifying patients by means of theCox model as either dying or surviving. The nullvalue for the C statistic is 0.5, with a maximum of29patients (Tables 3 and 4) with all degrees of severityof COPD. The FEV1 was slightly lower among pa-tients in the United States than among those in Ven-ezuela or Spain. The U.S. patients also had morefunctional impairment, more severe dyspnea, andmore coexisting conditions. The 27 patients (4 per-cent) lost to follow-up were evenly distributed ac-cording to the severity of COPD and did not differsignificantly from the rest of the cohort with respectto any measured characteristic. There were 162deaths (26 percent) over a median follow-up of 28months (range, 4 to 68). The majority of patients(61 percent) died of respiratory insufficiency, 14percent died of myocardial infarction, 12 percentof lung cancer, and the rest of miscellaneouscauses. The BODE score was lower among survi-vors than among those who died from any cause(3.7±2.2 vs. 5.9±2.6, P<0.005). The score was alsolower among survivors than among those whodied of respiratory causes, and the difference be-tween the scores was larger (3.6±2.2 vs. 6.7±2.3,P<0.001).Table 5 shows the BODE index as a predictor ofdeath from any cause after correction for coexistingconditions. There were significantly more deathsin the United States (32 percent) than in Spain (15percent) or Venezuela (13 percent) (P<0.001). How-ever, when the analysis was done separately foreach country, the predictive power of the BODE in-dex was similar; therefore, the data are presentedtogether. Table 5 shows that the BODE index wasalso a predictor of death from respiratory causesafter correction for coexisting conditions (hazardratio, 1.63; 95 percent confidence interval, 1.48 to1.80; P<0.001). The Kaplan–Meier analysis of sur-*Because of rounding, percentages do not total 100. Thethree stages of chronic obstructive pulmonary disease(COPD) were defined by the American Thoracic Society.FEV1 denotes forced expiratory volume in one second.†Higher scores on the body-mass index, degree of airflowobstruction and dyspnea, and exercise capacity (BODE)index indicate a greater risk of death. Quartile 1 was de-fined by a score of 0 to 2, quartile 2 by a score of 3 to 4,quartile 3 by a score of 5 to 6, and quartile 4 by a scoreof 7 to 10.n engl j med 350; march 4, 2004n engl j med 350;10march 4, 2004 a multidimensional grading system in chronic obstructive pulmonary disease1009vival (Fig. 1A) shows that each quartile increase in the BODE score was associated with increased mor-tality (P<0.001). Thus, the highest quartile (a BODE score of 7 to 10) was associated with a mortality rate of 80 percent at 52 months. These same data are shown in Figure 1B in relation to the severity of COPD according to the staging system of the Amer-ican Thoracic Society. The C statistic for the ability of the BODE index to predict the risk of death was 0.74, as compared with a value of 0.65 with the use of FEV 1 alone (expressed as a percentage of the pre-dicted value). The computation of 2000 bootstrap samples for these data and estimation of the haz-ard ratios for death indicated that for each one-point increment in the BODE score the hazard ratio for death from any cause was 1.34 (95 percent confi-dence interval, 1.26 to 1.42) and the hazard ratio for death from a respiratory cause was 1.62 (95 per-the BODE index — and validated its use by show-ing that it is a better predictor of the risk of death from any cause and from respiratory causes than is the FEV 1 alone. We believe that the BODE index is useful because it includes one domain that quan-tifies the degree of pulmonary impairment (FEV 1 ),one that captures the patient’s perception of symp-toms (the MMRC dyspnea scale), and two indepen-dent domains (the distance walked in six minutes and the body-mass index) that express the systemic consequences of COPD. The FEV 1 is essential for the diagnosis and quantification of the respirato-ry impairment resulting from COPD. 1,3,4 In addi-tion, the rate of decline in FEV 1 is a good marker of disease progression and mortality. 18,19 Howev-er, the FEV 1 does not adequately reflect all the sys-temic manifestations of the disease. For example,the FEV 1 correlates weakly with the degree of dys-pnea, 20 and the change in FEV 1 does not reflect the rate of decline in patients’ health. 30 More impor-tant, prospective observational studies of patients with COPD have found that the degree of dyspnea 8 and health-status scores 31 are more accurate pre-dictors of the risk of death than is the FEV 1 . Thus,although the FEV 1 is important to obtain and essen-tial in the staging of disease in any patient with COPD, other variables provide useful information that can improve the comprehensibility of the eval-uation of patients with COPD. Each variable should*Plus–minus values are means ±SD.†Analysis of variance was used to calculate the P values.‡Scores on the modified Medical Research Council (MMRC) dyspnea scale can range from 0 to 4, with a score of 4 indicating that the patient is too breathless to leave the house or becomes breathless when dressing or undressing.§Scores on the Charlson index can range from 0 to 33, with higher scores indi-cating more coexisting conditions.¶Scores on the body-mass index, degree of airflow obstruction and dyspnea, and exercise capacity (BODE) index can range from 0 to 10, with higher scores indicating a greater risk of death.*The Cox proportional-hazards models for death from any cause include 162 deaths. The Cox proportional-hazards models for death from specific respira-tory causes include 96 deaths. Model I includes the body-mass index, degree of airflow obstruction and dyspnea, and exercise capacity (BODE) index alone. The hazard ratio is for each one-point increase in the BODE score. Model II includes coexisting conditions as expressed by each one-point increase in the Charlson index. CI denotes confidence interval.The new england journal of medicine1010correlate independently with the prognosis ofCOPD, should be easily measurable, and shouldserve as a surrogate for other potentially importantvariables.In the BODE index, we included two descriptorsof systemic involvement in COPD: the body-massindex and the distance walked in six minutes. Bothare simply obtained and independently predict therisk of death.7,9,10 It is likely that they share somecommon underlying physiological determinants,but the distance walked in six minutes contains adegree of sensitivity not provided by the body-massindex. The six-minute–walk test is simple to per-form and has been standardized.12 Its use as a clin-ical tool has gained acceptance, since it is a goodpredictor of the risk of death among patients withother chronic diseases, including congestive heartfailure23 and pulmonary hypertension.24 Indeed, thedistance walked in six minutes has been acceptedas a good outcome measure after interventions suchas pulmonary rehabilitation.32 The body-mass in-dex was also an independent predictor of the riskof death and was therefore included in the BODEindex. We evaluated the independent prognosticpower of body-mass index in our cohort using dif-ferent thresholds and found that values below 21were associated with an increased risk of death, anobservation similar to that reported by Landbo andcoworkers in a large population study.10The Global Initiative for Chronic ObstructiveLung Disease and the American Thoracic Societyrecommend that a patient’s perception of dyspneabe included in any new staging system for COPD.1,3Dyspnea represents the most disabling symptomof COPD; the degree of dyspnea provides informa-tion regarding the patient’s perception of illnessand can be measured. The MMRC dyspnea scale issimple to administer and correlates with other dys-pnea scales20 and with scores of health status.21Furthermore, in a large cohort of prospectively fol-lowed patients with COPD, which used the thresh-old values included in the BODE index, the scoreon the MMRC dyspnea scale was a better predictorof the risk of death than was the FEV1.8The BODE index combines the four variables bymeans of a simple scale. We also explored whetherweighting the variables included in the index im-proved the predictive power of the BODE index. In-terestingly, it failed to do so, most likely becauseeach variable included has already proved to be agood predictor of the outcome of COPD.Our study had some limitations. First, relative-ly few women were recruited, even though enroll-ment was independent of sex. It probably reflectsthe problem of the underdiagnosis of COPD inwomen. Second, there were differences among thethree countries. For example, patients in the UnitedStates had a higher mortality rate, more severe dys-pnea, more functional limitations, and more co-n engl j med 350; march 4, 2004n engl j med 350; march 4, 2004a multidimensional grading system in chronic obstructive pulmonary disease1011existing conditions than patients in Venezuela or Spain, even though the severity of airflow obstruc-tion was relatively similar among the patients as a whole. The reasons for these differences are un-known, because there have been no systematic com-parisons of the regional manifestations of COPD.In all three countries, the BODE index was the best predictor of survival, an observation that renders our findings widely applicable.Three studies have reported the effects of the grouping of variables to express the various do-mains affected by COPD.33-35 These studies did not include variables now known to be important pre-dictors of outcome, such as the body-mass index.However, as we found in our study, they showedthat the FEV 1, the degree of dyspnea, and exercise performance provide independent information regarding the degree of compromise in patients with COPD.Besides its excellent predictive power with re-gard to outcome, the BODE index is simple to cal-culate and requires no special equipment. This makes it a practical tool of potentially widespread applicability. Although the BODE index is a predic-tor of the risk of death, we do not know whether it will be a useful indicator of the outcome in clinical trials, the degree of utilization of health care re-sources, or the clinical response to therapy.We are indebted to Dr. Gordon L. Snider, whose guidance, com-ments, and criticisms were fundamental to the final manuscript.1.Pauwels RA, Buist AS, Calverley PM,Jenkins CR, Hurd SS. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease:NHLBI/WHO Global Initiative for Chronic Obstructive Lung Disease (GOLD) Work-shop summary. Am J Respir Crit Care Med 2001;163:1256-76.2.Murray CJL, Lopez AD. Mortality by cause for eight regions of the world: Global Burden of Disease Study. Lancet 1997;349:1269-76.3.Definitions, epidemiology, pathophys-iology, diagnosis, and staging. Am J Respir Crit Care Med 1995;152:Suppl:S78-S83.4.Siafakas NM, Vermeire P, Pride NB, et al. Optimal assessment and management of chronic obstructive pulmonary disease (COPD). Eur Respir J 1995;8:1398-420.5.Nocturnal Oxygen Therapy Trial Group.Continuous or nocturnal oxygen therapy in hypoxemic chronic obstructive pulmonary disease: a clinical trial. Ann Intern Med 1980;93:391-8.6.Intermittent positive pressure breathing therapy of chronic obstructive pulmonary disease: a clinical trial. Ann Intern Med 1983;99:612-20.7.Gerardi DA, Lovett L, Benoit-Connors ML, Reardon JZ, ZuWallack RL. Variables re-lated to increased mortality following out-patient pulmonary rehabilitation. Eur Res-pir J 1996;9:431-5.8.Nishimura K, Izumi T, Tsukino M, Oga T. Dyspnea is a better predictor of 5-year sur-vival than airway obstruction in patients with COPD. Chest 2002;121:1434-40.9.Schols AM, Slangen J, Volovics L, Wout-ers EF. Weight loss is a reversible factor in the prognosis of chronic obstructive pulmo-nary disease. Am J Respir Crit Care Med 1998;157:1791-7.ndbo C, Prescott E, Lange P, Vestbo J,Almdal TP. Prognostic value of nutritional status in chronic obstructive pulmonary dis-ease. Am J Respir Crit Care Med 1999;160:1856-61.11.American Thoracic Society Statement.Lung function testing: selection of reference values and interpretative strategies. Am Rev Respir Dis 1991;144:1202-18.12.ATS Committee on Proficiency Stan-dards for Clinical Pulmonary Function Lab-oratories. ATS statement: guidelines for the six-minute walk test. Am J Respir Crit Care Med 2002;166:111-7.13.Mahler D, Wells C. Evaluation of clinical methods for rating dyspnea. Chest 1988;93:580-6.14.Charlson M, Szatrowski T, Peterson J,Gold J. Validation of a combined comor-bidity index. J Clin Epidemiol 1994;47:1245-51.15.Ferrer M, Alonso J, Morera J, et al. Chron-ic obstructive pulmonary disease stage and health-related quality of life. Ann Intern Med 1997;127:1072-9.16.Dewan NA, Rafique S, Kanwar B, et al.Acute exacerbation of COPD: factors associ-ated with poor treatment outcome. Chest 2000;117:662-71.17.Friedman M, Serby CW , Menjoge SS,Wilson JD, Hilleman DE, Witek TJ Jr. Phar-macoeconomic evaluation of a combination of ipratropium plus albuterol compared with ipratropium alone and albuterol alone in COPD. Chest 1999;115:635-41.18.Anthonisen NR, Wright EC, Hodgkin JE. Prognosis in chronic obstructive pulmo-nary disease. Am Rev Respir Dis 1986;133:14-20.19.Burrows B. Predictors of loss of lung function and mortality in obstructive lung diseases. Eur Respir Rev 1991;1:340-5.20.Mahler DA, Weinberg DH, Wells CK ,Feinstein AR. The measurement of dyspnea:contents, interobserver agreement, and phys-iologic correlates of two new clinical index-es. Chest 1984;85:751-8.21.Hajiro T, Nishimura K, Tsukino M, Ike-da A, Koyama H, Izumi T. Comparison of discriminative properties among disease-specific questionnaires for measuring health-related quality of life in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med 1998;157:785-90.22.Szekely LA, Oelberg DA, Wright C, et al.Preoperative predictors of operative mor-bidity and mortality in COPD patients under-going bilateral lung volume reduction sur-gery. Chest 1997;111:550-8.23.Shah M, Hasselblad V , Gheorgiadis M,et al. Prognostic usefulness of the six-min-ute walk in patients with advanced conges-tive heart failure secondary to ischemic and nonischemic cardiomyopathy. Am J Car-diol 2001;88:987-93.24.Miyamoto S, Nagaya N, Satoh T, et al.Clinical correlates and prognostic signifi-cance of six-minute walk test in patients with primary pulmonary hypertension: compari-son with cardiopulmonary exercise testing.Am J Respir Crit Care Med 2000;161:487-92.25.Redelmeier DA, Bayoumi AM, Gold-stein RS, Guyatt GH. Interpreting small dif-ferences in functional status: the Six Minute Walk test in chronic lung disease patients.Am J Respir Crit Care Med 1997;155:1278-82.26.Decramer M, Gosselink R, Troosters T,Verschueren M, Evers G. Muscle weakness is related to utilization of health care resourc-es in COPD patients. Eur Respir J 1997;10:417-23.27.Cox DR. Regression models and life-tables. J R Stat Soc [B] 1972;34:187-220.28.Harrell FE Jr, Lee KL, Mark DB. Multi-variate prognostic models: issues in devel-oping models, evaluating assumptions and adequacy, and measuring and reducing er-rors. Stat Med 1996;15:361-87.29.Nam B-H, D’Agostino R. Discrimina-tion index, the area under the ROC curve. In:Huber-Carol C, Balakrishnan N, Nikulin MS,Mesbah M, eds. Goodness-of-fit tests and。

New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)新版实体瘤疗效评价标准：修订的RECIST指南（1.1版本）Abstract摘要Background背景介绍Assessment of the change in tumour burden is an important feature of the clinical evaluation of cancer therapeutics: both tumour shrinkage (objective response) and disease progression are useful endpoints in clinical trials. Since RECIST was published in 2000, many investigators, cooperative groups, industry and government authorities have adopted these criteria in the assessment of treatment outcomes. However, a number of questions and issues have arisen which have led to the development of a revised RECIST guideline (version 1.1). Evidence for changes, summarised in separate papers in this special issue, has come from assessment of a large data warehouse (>6500 patients), simulation studies and literature reviews.临床上评价肿瘤治疗效果最重要的一点就是对肿瘤负荷变化的评估：瘤体皱缩（目标疗效）和病情恶化在临床试验中都是有意义的判断终点。

个人所得税英文参考文献个人所得税英语参考文献一：[1]José Félix Sanz-Sanz. The Laffer curve in schedular multi-rate income taxes with non-genuine allowances: An application to Spain[J]. Economic Modelling,2019,.[2]Craig Brett,John A. Weymark. Voting over selfishly optimal nonlinear income tax schedules[J]. Games and Economic Behavior,2019,.[3]Mónica Unda Gutiérrez. A Tale of Two Taxes: the Diverging Fates of the Federal Property and Income Tax Decrees in post-Revolutionary Mexico[J]. Investigaciones de Historia Económica - Economic History Research,2019,.[4]Sim Choon Ling,Abdullah Osman,Safizal Muhammad,Sin Kit Yeng,Lim Yi Jin. Goods and Services Tax （GST） Compliance among Malaysian Consumers: The Influence of Price, Government Subsidies and Income Inequality[J]. Procedia Economics and Finance,2019,35.[5]Martin Lopez-Daneri. NIT Picking: The Macroeconomic Effects of a Negative Income Tax[J]. Journal of Economic Dynamics and Control,2019,.[6]Tad Miller,Lindsay Miller,Jeffrey Tolin. Provision for income tax expense ASC 740: A teaching note[J]. Journal of Accounting Education,2019,35.[7]Petr David,Lucie Formanová。

Applied Economics Letters,2006,13,569–574Club convergence inEuropean regionsRita De Siano a and Marcella D’Uva b,*a Department of Economic Studies,University of Naples‘Parthenope’,Via Medina40,80133Naples,Italyb Department of Social Sciences,University of Naples L’Orientale,Largo S.Giovanni Maggiore30,80134Naples,ItalyThis study investigates the‘club convergence’hypothesis applying the stochastic notion of convergence to groups of European regions.In order to avoid the group selection bias problem,the innovative regression tree technique was applied to select endogenously the most important variables in achieving the best identification of groups on the base of per capita income and productive specialization.Tests on stochastic convergence in each group evidences a strong convergence among the wealthiest regions of the European Union and a trend of weak convergence among the remaining groups,confirming Baumol’s hypothesis of convergence.I.IntroductionOver the past decade many authors have explored the evolution of output discrepancies,at both national and regional levels.In particular,starting with Baumol(1986)it has been widely hypothesized that convergence may hold not for all economies but within groups of them showing similar characteristics (Azariadis and Drazen,1990).This evidence is referred to as the‘club convergence’hypothesis which implies that a set of economies may converge with each other,in the sense that in the long run they tend towards a common steady state position, but there is no convergence across different sets. In seeking to test the club convergence hypothesis (Qing Li,1999;Feve and Le Pen,2000;Su,2003,for example)two main questions arise:(a)which frame-work of convergence to use,and(b)how to identify the economies belonging to each club.Initially,a cross-section notion of convergence was used in order to verify the existence of a negative relationship between initial per capita income and its growth rate. In contrast with this notion a stochastic definition of convergence(Carlino and Mills,1993)was proposed and explored by using time series analyses. According to this framework there is stochastic convergence if per capita income disparities between economies follow a stationary process.Bernard and Durlauf(1996)found that when economies show multiple long run equilibria,cross-sectional tests tend to spuriously reject the null hypothesis of no convergence and,as a consequence,represent a weaker notion of convergence than that of the time series.As regards the second point,two methods can be used in order to create different groups of economies.The first sorts of economies follows some a priori criteria(initial level of GDP,education, technology,capital accumulation,etc.)while the second follows an endogenous selection method (Durlauf and Johnson,1995).Finally,the switching regression with the contribution of additional infor-mation on the sample separation followed by Feve and Le Pen(2000)can be mentioned as an intermediate method in modelling convergence clubs. This study investigates the‘club convergence’hypothesis applying the stochastic notion of conver-gence to groups of European regions sorted accord-ing to their initial levels of per capita income and*Corresponding author.E-mail:mduva@unior.itApplied Economics Letters ISSN1350–4851print/ISSN1466–4291onlineß2006Taylor&Francis569/journalsDOI:10.1080/13504850600733473productive specialization(De Siano and D’Uva, 2004,2005)through the application of an innovative methodology known as Classification and Regression Tree Analysis(CART).Unlike other partitioning methods,CART allows a regression to be performed together with a classification analysis on the same ‘learning’dataset,without requiring particular speci-fication of the functional form for the predictor variables which are selected endogenously.The importance of similarities in the initial productive specialization has been highlighted by several theore-tical contributions(Jacobs,1969;Marshall,1980; Romer,1986;Lucas,1988;Helg et al.,1995;Bru lhart, 1998;Ottaviano and Puga,1998)which found that it can be crucial in determining both the nature and size of responses to external shocks.The paper is organized as follows:Section II introduces the methodology of the empirical analysis, Section III displays the dataset,Section IV shows the results of econometric analysis and Section V concludes.II.MethodologyThe empirical analysis is carried out in two parts:first regions are grouped through the classification and regression tree analyses(CART),then convergence is tested within‘clubs’using the time series analysis. CART methodology(Breiman et al.,1984)provides binary recursive partitioning using non-parametric approaches in order to construct homogeneous groups of regions using splitting variables which minimize the intra-group‘impurity’as predictors. The final outcome is a tree with branches and ‘terminal nodes’,as homogeneous as possible,where the average value of the node represents the predicted value of the dependent variable.In this analysis the regression is carried out through the least squares method using the regional GDP growth rate as dependent variable and initial GDP and specializa-tion indexes as explicative variables.In the second part of the study Carlino and Mills(1993)notion of stochastic convergence is applied in each group identified by CART methodology.It follows that if the logarithm of a region’s per capita income relative to the group’s average does not contain a unit root,the region converges.The model(Ben-David, 1994;Qing Li,1999)is the following:y j i,t ¼ iþ i tþ’y i,tÀ1þ"i,tð1Þwhere y j i,t is the log of region i per capita income inyear t,j is the region’s group and"is white noise errorwith0mean.Summing Equation1over j for eachgroup and dividing the outcome by the number ofregions within the group,the following equation isobtained:"y t¼" þ" tþ’"y tÀ1þ"tð2Þwhere"y t is the group’s average per capita incomein year t(the group superscript is suppressed).Subtracting Equation2from Equation1one has:RI i,t¼AþBtþ’RI i,tÀ1þ"tð3Þwhere RI i,t is the logarithm of region i per capitaincome relative to the group’s average at time t(y j i,tÀ"y t).For each region of the sample we apply theAugmented Dickey–Fuller(ADF)test(Dickey andFuller,1979)using the ADF regression ofEquation3:ÁRI t¼ þ tþ RI tÀ1þX kj¼1c jÁRI tÀjþ"tð4ÞAt this point,considering the low power of the ADFtest in the case of short time series,we run alsothe Kwiatkowski et al.(1992)test(KPSS)for trendstationarity.The null hypothesis of the KPSS test isthe trend stationarity against the unit root alter-native.If the KPSS statistic is larger than the criticalvalues the null hypothesis is rejected.The combinedanalysis of KPSS and ADF tests results leads on thefollowing possibilities(Qing Li,1999):.rejection by ADF tests and failure to reject byKPSS!strong convergence;.failure to reject by both ADF and KPSS!weakconvergence;.rejection by KPSS test and failure to rejectADF!no convergence;.rejection by both ADF and KPSS tests invitesto perform further analyses.III.Data DescriptionThis section presents the dataset used both to groupthe sample regions and to run the econometricanalysis.Data for GDP and employment are fromthe Eurostat New Cronos Regio database at NUTS2level.1Annual values for GDP per inhabitant in termsof Purchasing Power Parity(PPP)and the number of1According to EC Regulation No.1059/2003.570R.De Siano and M.D’Uvaemployees in the NACE92productive branches from1981to 2000are used.The sample consists of 123regions belonging to nine countries:11Belgian,8Dutch,29German,222French,20Italian,18Spanish,5Portuguese,2Greek,38British.4For each region (i )the following initial productivespecialization indexes (SP)were built for all theconsidered branches 5(j ):SP ij ¼E ij P n j ¼1ij P m i ¼1E ij P n j ¼1P mi ¼1ijð5Þwhere E indicates the number of employees.IV.Empirical ResultsThe main purpose of the study is to test the ‘clubconvergence’hypothesis across the European regions.In particular,the study aims to investigate whethera region’s per capita income converges to the averageof the group to which it belongs.In order to avoidthe group selection bias problem,the regressiontree technique was applied to select endogenouslythe most important variables in achieving thebest identification of groups (De Siano and D’Uva,2005).If the majority of regions in a groupconverges,the group may be considered a conver-gence ‘club’.The CART method allowed a tree to be built withfour terminal nodes including regions showing a morehomogeneous behaviour of per capita GDP growthrate and productive specialization.Results of CARTanalysis together with the stochastic convergence tests for each group are presented in what follows.The first group consists of 11regions (from Spain,Greece and Portugal)characterized by:the highest estimated mean value of GDP growth rate (126.08%)despite the lowest initial income level (average equal to 4144.3);strong specialization in the agriculture sector (the highest and equal to 3.75),construction branch (2.09)and food and beverages compartment (1.93);the minimum specialization in chemical,energy,and machinery branches and the highest in food-beverages-tobacco,mineral and construction.More than 80%of these regions display ‘weak’convergence while remaining regions show ‘strong’convergence (Table 1).The second group includes 23regions (mainly from Belgium,Spain,Italy and the United Kingdom)characterized by:an average GDP growth rate equal to 111.36%and the second highest initial income level (5788.78);strong specialization in agriculture (2.68)sector,food and beverage (1.26),construction (1.52)and energy (1.20)compartments;the highest specialization in chemical products (0.98);the second highest level of specialization in agricul-ture construction and energy.Almost all these regions present ‘weak’convergence (Table 2).The third group is formed by 21regions from Belgium,France,Germany,the Netherlands,Spain,the UK and Italy (only Abruzzo)characterized by:an estimate for the GDP growth rate of 106%and an average initial level of income equal to 6920.6;main specializations in manufacturing (1.03),mineral products (1.13),construction (1.22),food and beverage (1.45)and energy (1.21);the highest 2The analysis starts from 1984due to the lack of data in the respective regional labour statistics.3During the period 1983–1987there has been a different aggregation of Greek regions at NUTS2level.Kriti and Thessalia are the only regions which presents data for the period 1984–2000.4The geographic units for UK are at NUTS1level of Eurostat classification because of the lack of data for NUTS2units.5Agricultural-forestry and fishery,manufacturing,fuel and power products,non-metallic minerals and minerals,food-beverages-tobacco,textiles-clothing-leather and footwear,chemical products,metal products,machinery-equipment and electrical goods,various industries,building and construction,transport and communication,credit and insurance services.Table 1.Convergence test results of group 1Regions group 1ADF statistics KPSS statistics l ¼4Regions group 1ADF statistics KPSS statistics l ¼4Castilla-la ManchaÀ2.9780.099gr 43Kriti À4.05ÃÃ0.080ExtremaduraÀ3.320.097Pt11Norte À4.03ÃÃ0.126AndaluciaÀ2.630.094Pt12Centro (P)À2.290.123Ceuta y MelillaÀ1.770.123Pt14Alentejo À2.770.104CanariasÀ1.940.121Pt15Algarve À2.010.086ThessaliaÀ1.760.137Notes :ÃÃdenote statistical significance using unit root critical values at the 5%(À3.645).Club convergence in European regions571specialization in energy and manufacturing branches.Except for Abruzzo and Noord Brabant,which donot converge,all the other regions ‘weakly’convergeto the group’s average (Table 3).The fourth group contains 68regions (almost allGerman,French and Italian (North-Centre)andsome Belgian and Dutch)characterized by thelowest estimation of the GDP growth rate (97.8%),despite their highest initial GDP level (8893.9);thehighest specialization in the branches of the servicessector (1.16and 1.07,respectively)and in machinery(1.01);the lowest specialization in agriculture,foodand beverages,textile and construction activities.These regions present the highest percentage of‘strong’convergence to the group’s average (morethan 60%,Table 4).Table 5presents the summary of convergence testsresults (percentage are in parentheses).The main outcome of this study is the evidence of strong convergence among the wealthiest regions of the European Union.Besides,it appears that there is a trend of weak convergence also among the remaining groups (percentages are considerably over 80%).Therefore,Baumol’s hypothesis of conver-gence within clubs showing similar characteristics is confirmed.V.Conclusion This study tests the ‘club convergence’hypothesis applying the stochastic notion of convergence to groups of European regions.In order to avoid the group selection bias problem,the innovative regression tree technique was applied to selectTable 3.Convergence test results of group 3Regions group 3ADF statistics KPSS statistics l ¼4Regions group 3ADF statistics KPSS statistics l ¼4LimburgÀ1.680.116Abruzzo 2.600.153ÃÃHainautÀ0.800.091Friesland À3.620.142NamurÀ1.840.094Noord-Brabant À2.590.148ÃÃNiederbayernÀ1.270.104Limburg (NL)À2.980.128OberpfalzÀ1.400.097Yorkshire and The Humber À1.610.085TrierÀ1.430.119East Midlands À2.190.091Comunidad Foral de NavarraÀ2.750.071West Midlands À1.920.080La RiojaÀ1.770.119East Anglia À2.150.134BalearesÀ2.960.108South West À1.950.091LimousinÀ2.410.083Scotland 2.220.093Languedoc-RoussillonÀ3.390.105Notes :ÃÃdenote statistical significance using KPSS stationary critical values at the 5%level (0.146).Table 2.Convergence test results of group 2Regions group 2ADF statistics KPSS statistics l ¼4Regions group 2ADF statistics KPSS statistics l ¼4Vlaams BrabantÀ1.220.100Murcia À1.530.124Brabant WallonÀ1.600.111Molise À2.170.078Luxembourg1.190.122Campania À3.220.078Lu neburgÀ0.280.114Puglia À2.820.115GaliciaÀ1.690.140Basilicata À2.100.140Principado de AsturiasÀ1.550.146ÃÃCalabria À5.07ÃÃÃ0.106CantabriaÀ1.080.133Sicilia À2.980.142Aragon À1.580.142Sardegna À2.210.141Comunidad de MadridÀ1.380.091Lisboa e Vale do Tejo À2.620.141Castilla y Leon À2.580.138Wales À2.120.098Cataluna À1.550.097Northern Ireland À1.790.120Comunidad Valenciana À1.420.105Notes :ÃÃand ÃÃÃdenote statistical significance using KPSS stationary critical values at the 5%level (0.146)and 1%level (0.216)respectively,using unit root critical values at the 5%(À3.645)and 1%(À4.469).572R.De Siano and M.D’Uvaendogenously the most important variables inachieving the best identification of groups.Testson stochastic convergence in each group identifiedby CART evidence strong convergence among thewealthiest regions of the European Union and atrend of weak convergence among the remaininggroups.References Azariadis,C.and Drazen,A.(1990)Threshold externalities in economic development,Quarterly Journal of Economics ,105,501–26.Baumol,W.J.(1986)Productivity growth,convergence and welfare:what the long run data show,AmericanEconomic Review ,76,1072–85.Table 5.Convergence test resultsGroupsNo.of regions Strong convergence Weak convergence No convergence 1112(18,19)9(81,81)2231(4.35)21(91.3)1(4.35)32119(90.48)2(9.52)46843(63.23)20(29.41)4(5.88)Table 4.Convergence test results of group 4Regions group 4ADF statistics KPSS statistics l ¼4Regions group 4ADF statistics KPSS statistics l ¼4RegionBruxelles capitale À2.650.112Haute-Normandie À4.11ÃÃ0.102AntwerpenÀ2.770.102Centre (FR)À5.13ÃÃÃ0.099Oost-VlaanderenÀ3.150.078Basse-Normandie À3.86ÃÃ0.101West-VlaanderenÀ3.030.097Bourgogne À5.03ÃÃÃ0.113Licge À3.060.089Nord-Pas-de-Calais À4.37ÃÃ0.130StuttgartÀ4.22ÃÃ0.123Lorraine À4.41ÃÃ0.139KarlsruheÀ4.51ÃÃÃ0.088Alsace À4.13ÃÃ0.094FreiburgÀ5.11ÃÃÃ0.092Franche-Comte À5.20ÃÃÃ0.145Tu bingenÀ4.94ÃÃÃ0.104Pays de la Loire À4.34ÃÃ0.116OberbayernÀ4.17ÃÃ0.094Bretagne À4.41ÃÃ0.124MittelfrankenÀ3.79ÃÃ0.089Poitou-Charentes À4.74ÃÃÃ0.102UnterfrankenÀ0.420.140Aquitaine À3.290.104SchwabenÀ4.11ÃÃ0.084Midi-Pyre ne es À5.48ÃÃÃ0.103BremenÀ3.76ÃÃ0.121Rho ne-Alpes À4.93ÃÃÃ0.104HamburgÀ3.350.097Auvergne À4.43ÃÃ0.135DarmstadtÀ3.150.125Provence-Alpes-Co te d’Azur À5.10ÃÃÃ0.109GießenÀ3.020.088Corse À2.560.166ÃÃKasselÀ3.0120.094Piemonte À3.460.112BraunschweigÀ3.82ÃÃ0.116Valle d’Aosta À4.36ÃÃ0.080HannoverÀ3.96ÃÃ0.083Liguria À4.26ÃÃ0.117Weser-EmsÀ3.400.084Lombardia À4.04ÃÃ0.101Du sseldorfÀ3.94ÃÃ0.097Trentino-Alto Adige À3.84ÃÃ0.109Ko lnÀ3.96ÃÃ0.084Veneto À3.68ÃÃ0.106Mu nsterÀ4.04ÃÃ0.087Friuli-Venezia Giulia À4.20ÃÃ0.116DetmoldÀ4.06ÃÃ0.099Emilia-Romagna À3.120.136ArnsbergÀ3.98ÃÃ0.096Toscana À3.190.121KoblenzÀ3.88ÃÃ0.113Umbria À3.560.146ÃÃRheinhessen-PfalzÀ4.18ÃÃ0.107Marche À3.250.136SaarlandÀ4.35ÃÃ0.090Lazio À3.96ÃÃ0.098Schleswig-HolsteinÀ3.360.089Drenthe À1.850.134Pais VascoÀ3.630.159ÃÃUtrecht À2.400.155ÃÃI le de FranceÀ4.61ÃÃÃ0.110Noord-Holland À1.990.137Champagne ArdenneÀ3.79ÃÃ0.157ÃÃZuid-Holland À2.200.138Picardie À4.44ÃÃ0.142Zeeland À3.78ÃÃ0.093Notes :ÃÃand ÃÃÃdenote statistical significance using KPSS stationary critical values at the 5%level (0.146)and 1%level (0.216)respectively,using unit root critical values at the 5%(À3.645)and 1%(‘4.469).Club convergence in European regions573Ben-David, D.(1994)Convergence clubs and diverging economies,unpublished manuscript,University of Houston,Ben-Gurion University and CEPR. 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B.and Durlauf,S.N.(1996)Interpreting tests of the convergence hypothesis,Journal of Econometrics,71,161–73.Breiman,L.,Friedman,J.L.,Olshen,R.A.and Stone,C.J.,(1984)Classification and Regression Trees,Wadsworth,Belmont,CA.Bru lhart,M.(1998)Economic geography,industrial location and trade:the evidence,World Economy,21, 775–801.Carlino,G.A.and Mills,L.O.(1993)Are US regional incomes converging?A time series analysis,Journal of Monetary Economics,32,335–46.De Siano,R.and D’Uva,M.(2004)Specializzazione e crescita:un’applicazione alle regioni dell’Unione Monetaria Europea,Rivista Internazionale di Scienze Sociali,4,381–98.De Siano,R.and D’Uva,M.(2005)Regional growth in Europe:an analysis through CART methodology, Studi Economici,87,115–28.Dickey,D.A.and Fuller,W.A.(1979)Distribution of the estimators for autoregressive time series with a unit root,Journal of The American Statistical Association, 74,427–31.Durlauf,S.N.and Johnson,P.A.(1995)Multiple regimes and cross-country growth behaviour,Journal of Applied Econometrics,10,365–84.Feve,P.and Le Pen,Y.(2000)On modelling convergence clubs,Applied Economic Letters,7,311–14.Helg,R.,Manasse,P.,Monacelli,T.and Rovelli,R.(1995) How much(a)symmetry in Europe?Evidence from industrial sectors,European Economic Review,39, 1017–41.Jacobs,J.(1969)The Economy of Cities,Jonathen Cape, London.Kwiatkowski, D.,Phillips,P. 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Per caricare la batteria, collegare il cavo USB al router mobile, quindi collegarlo a una presa a muro utilizzando l'adattatore di alimentazione CA o una porta USB del computer.Assicurarsi che l'orientamento della scheda nano SIM coincida con l'orientamento indicato sull'etichetta del dispositivo e inserirla delicatamente, quindi posizionare la batteria e il coperchio posteriore.NOTA: utilizzare solo le dita per inserire o rimuovere la scheda nano SIM. L'utilizzo di altri oggetti potrebbe danneggiare il dispositivo.1. COM'È FATTO IL DISPOSITIVO2. INSTALLAZIONE DELLA SIM E DELLA BATTERIAIl router mobile viene fornito con i seguenti componenti:• Router mobile Nighthawk® M6 o M6 Pro 5G*• Coperchio della batteria • Batteria• Cavo USB Tipo C• Alimentatore (varia in base all’area geografica)• Adattatori con presa Tipo C (per la maggior parte dei Paesi europei)•Adattatori con presa Tipo G (per il Regno Unito)*Illustrazioni del modello Nighthawk M6 per scopi illustrativi.antenna esterna (TS-9)antenna esterna (TS-9)USB Tipo CEthernetCONFORMITÀ NORMATIVA E NOTE LEGALIPer informazioni sulla conformità alle normative, compresala Dichiarazione di conformità UE, visitare il sito Web https:///it/about/regulatory/.Prima di collegare l'alimentazione, consultare il documento relativo alla conformità normativa.Può essere applicato solo ai dispositivi da 6 GHz: utilizzare il dispositivo solo in un ambiente al chiuso. L'utilizzo di dispositivi a 6 GHz è vietato su piattaforme petrolifere, automobili, treni, barche e aerei, tuttavia il suo utilizzo è consentito su aerei di grandi dimensioni quando volano sopra i 3000 metri di altezza. L'utilizzo di trasmettitori nella banda 5.925‑7.125 GHz è vietato per il controllo o le comunicazioni con sistemi aerei senza equipaggio.SUPPORTO E COMMUNITYDalla pagina del portale di amministrazione Web, fare clic sull'icona con i tre puntini nell'angolo in alto a destra per accedere ai file della guida e del supporto.Per ulteriori informazioni, visitare il sito netgear.it/support per accedere al manuale dell'utente completo e per scaricare gli aggiornamenti del firmware.È possibile trovare utili consigli anche nella Community NETGEAR, alla pagina /it.GESTIONE DELLE IMPOSTAZIONI TRAMITE L'APP NETGEAR MOBILEUtilizzare l'app NETGEAR Mobile per modificare il nome della rete Wi-Fi e la password. È possibile utilizzarla anche per riprodurre e condividere contenutimultimediali e accedere alle funzioni avanzate del router mobile.1. Accertarsi che il dispositivo mobile sia connesso a Internet.2. Eseguire la scansione del codice QR per scaricare l'appNETGEAR Mobile.Connessione con il nome e la password della rete Wi-Fi 1. Aprire il programma di gestione della rete Wi‑Fi deldispositivo.2. Individuare il nome della rete Wi‑Fi del router mobile(NTGR_XXXX) e stabilire una connessione.3. Only Connessione tramite EthernetPer prolungare la durata della batteria, l'opzione Ethernet è disattivata per impostazione predefinita. Per attivarla, toccare Power Manager (Risparmio energia) e passare a Performance Mode (Modalità performance).4. CONNESSIONE A INTERNETÈ possibile connettersi a Internet utilizzando il codice QR del router mobile da uno smartphone oppure selezionando manualmente il nome della rete Wi‑Fi del router e immettendo la password.Connessione tramite codice QR da uno smartphone 1. Toccare l'icona del codice QR sulla schermata inizialedello schermo LCD del router mobile.NOTA: quando è inattivo, lo schermo touch si oscura per risparmiare energia. Premere brevemente e rilasciare il pulsante di alimentazione per riattivare lo schermo.3. CONFIGURAZIONE DEL ROUTER MOBILETenere premuto il pulsante di accensione per due secondi, quindi seguire le istruzioni visualizzate sullo schermo per impostare un nome per la rete Wi‑Fi e una password univoci.La personalizzazione delle impostazioni Wi‑Fi consente di proteggere la rete Wi‑Fi del router mobile.Impostazioni APNIl router mobile legge i dati dalla scheda SIM e determina automaticamente le impostazioni APN (Access Point Name) corrette con i piani dati della maggior parte degli operatori. Tuttavia, se si utilizza un router mobile sbloccato con un operatore o un piano meno comune, potrebbe essere necessario immettere manualmente le impostazioni APN.Se viene visualizzata la schermata APN Setup Required (Configurazione APN richiesta), i dati APN dell’operatore non sono presenti nel nostro database ed è necessario inserirli manualmente. Immettere i valori fornitidall’operatore nei campi corrispondenti, quindi toccare Save (Salva) per completare la configurazione.NOTA: l’operatore determina le proprie informazioni APN e deve fornire le informazioni per il proprio piano dati. Si consiglia di contattare il proprio operatore per le impostazioni APN corrette e di utilizzare solo l’APN suggerito per il piano specifico.Schermata inizialeAl termine della configurazione, il router visualizza la schermata iniziale:Wi‑FiPotenza Carica Rete Codice QR connessione rapida Wi‑FiNome e Wi‑FiIcona del codice QR。

圭堡医堂羞堂麓嶷盘查垫塑生！！魍整！§盎筮！塑￡ｂ虹ＬＭ趟△！！！ｂ坠鱼§璎￡！！Ｑ￡！Ｑ鲢１２塑２：ＹＱｌ：；§：艘２：§欧洲标准变应原联合化妆品筛选变应原对女性面部皮炎患者的斑贴试验周成霞李械李利【摘要ｌ蹦的采矮蚊溯标准嶷辙鳆联合化妆赫筛遴燮应原对女性ｌｌｌｉ鄙发炎患者进行斑贴试验，薅壹主要致竣藤；方法霹弱诊女瞧露帮安炎患者果弼讫绶曩蘩选变绽琢联合黢鞘标灌变应蘸送行褒雅试验，按嚣繇接魅建皮炎瓣究组捶荐标准巅潦缝祭。

结果４ｉ灏焱褴患者逢幸亍了３８静德妆酷筛选变虑原和２６种欧洲标准变腹原的斑贴试验。

熊巾阳性率最高ｆｆ缸他妆鼎筛选变应原计裔鸟洛托品（１２．２０％）、硫柳汞（９．７６％）、双咪唑烷基脲（７．３２％）及ＤＭＤＭ海因（７．３２％），阳性率躐高的欧洲标准嶷成原汁有硫酸镍（２２．２０％）、甲醛（１４．６３％）、对苯二胺（９．７６％）及香料混骨芍势ｆ９。

弱％）。

绥谂辘臻耱，争鏊、岛渗托瑟、骧秘汞、对答：藏、蚕辫浸合耢，双曝迹靛基骣，ＤＭＤＭ海毽等是女瞧嚣零瘦灸患毒主要簸被骧。

【关键词ｌ欧渊标准变琏原；化妆品筛选变赢愿＃巅部皮炎；疆髂试簸ＰａｔｃｈｔｅｓｔｉｎｇｆｏｒｓｅｌｅｃｔｉｏｎｏｆｃｏｓｍｅｔｉｃａｌｌｌｅｒｇｅｎｓｉｎｆｅｍａｌｅｆａｅｉａｌｄｅｒｍａｔｉｔｉｓｂｙＥｕｒｏｐｅａｎｓｔａｎｄａｒｄｏｆｃ０８ｍｍｅｔｉｃａｌｌｅｒｇｅｎｓｚＨ（彤Ｃｈｅｎｇ－ｘｉａ，Ｌ｛ｗ武，乙ｉＬｉ．ＤｅｐａｒｔｍｅｎｔｏｆＤｅｒｍａｔｏｌｏｇｙ，Ｗｅ啦ＣｈｉｎａＨｏｓ“ｐｉｔａｔ，Ｓｉ商＃口镕汝ｉｖｅｒＭｔＹ，酝ｏｎｇｄｕ§１００４１，Ｃｈｉｎａ［Ａｂｓｔｒａｃｔ］ＯｂｊｅｃｔｉｖｅＴｏｉｄｅｎｔｉｆｙｔｈｅｅｏｍｎｑｏｎａｌｌｅｒｇｅｎｓｏｆｔｈｅｆｅｍａｌｅｐａｔｉｅｎｔｓｗｋｈｆａｅｉａｉｄｅｆ—ｍａｔｉｔｉｓｗｉｔｈＥｕｒｏｐｅａｎｓｔａｎｄａｒｄｏｆｃｏｓｍｅｔｉｃａｌｌｅｒｇｅｎｓ．ＭｅｔｈｏｄｓＦｅｍａｌｅｐａｔｉｅｎｔｓｗｉｔｈｆａｃｉａｉｄｅｒｍａｔｉｔｉｓｗｅｒｅｔｅｓｔｅｄｗｉｔｈＥｕｒｏｐｅａｎｓｔａｎｄａｒｄｏｆｃｏｓｍｅｔｉｃａｌｌｅｒｇｅｎｓ．ＴｈｅｒｅａｃｔｉｏｎｓｔｏａｌｌｅｒｇｅｎｓｗｅｒｅｄｏｃｕｍｅｎｔｅｄｈｙｆｏｌｌｏｗｉｎｇｔｈｅＩｎｔｅｒｎａｔｉｏｎａｌＣｏｎｔａｅｔＤｅｒｍａｔｉｔｉｓＲｅｓｅａｒｃｈＧｒｏｕｐｒｅｃｏｍｍｅｎｄａｔｉｏｎｓ．ＲｅｓｕｌｔｓＴｏｔａｌ４ｌｆｅｍａｌｅｐａｔｉｅｎｔｓｗｉｔｈｆａｃｉａｌｄｅｒｍａｔｉｔｉｓｗｅｒｅｔｅｓｔｅｄｗｉｔｈＥｕｒｏｐｅａｎｓｔａｎｄａｒｄｏｆｃｏｓｍｅｔｉｃａｌｌｅｒｇｅｎｓ，ｔｈｅｍａｉｎｃｏｓｍｅｔｉｃａｌｌｅｒｇｅｎｓｖｃｅｒｅｈｅｘａｍｉｎｅ（１２，２０），ｔｈｉｍｅｒｏｓａｌ（９。

DIRECTIVE NUMBER: CPL 02-00-150 EFFECTIVE DATE: April 22, 2011 SUBJECT: Field Operations Manual (FOM)ABSTRACTPurpose: This instruction cancels and replaces OSHA Instruction CPL 02-00-148,Field Operations Manual (FOM), issued November 9, 2009, whichreplaced the September 26, 1994 Instruction that implemented the FieldInspection Reference Manual (FIRM). The FOM is a revision of OSHA’senforcement policies and procedures manual that provides the field officesa reference document for identifying the responsibilities associated withthe majority of their inspection duties. This Instruction also cancels OSHAInstruction FAP 01-00-003 Federal Agency Safety and Health Programs,May 17, 1996 and Chapter 13 of OSHA Instruction CPL 02-00-045,Revised Field Operations Manual, June 15, 1989.Scope: OSHA-wide.References: Title 29 Code of Federal Regulations §1903.6, Advance Notice ofInspections; 29 Code of Federal Regulations §1903.14, Policy RegardingEmployee Rescue Activities; 29 Code of Federal Regulations §1903.19,Abatement Verification; 29 Code of Federal Regulations §1904.39,Reporting Fatalities and Multiple Hospitalizations to OSHA; and Housingfor Agricultural Workers: Final Rule, Federal Register, March 4, 1980 (45FR 14180).Cancellations: OSHA Instruction CPL 02-00-148, Field Operations Manual, November9, 2009.OSHA Instruction FAP 01-00-003, Federal Agency Safety and HealthPrograms, May 17, 1996.Chapter 13 of OSHA Instruction CPL 02-00-045, Revised FieldOperations Manual, June 15, 1989.State Impact: Notice of Intent and Adoption required. See paragraph VI.Action Offices: National, Regional, and Area OfficesOriginating Office: Directorate of Enforcement Programs Contact: Directorate of Enforcement ProgramsOffice of General Industry Enforcement200 Constitution Avenue, NW, N3 119Washington, DC 20210202-693-1850By and Under the Authority ofDavid Michaels, PhD, MPHAssistant SecretaryExecutive SummaryThis instruction cancels and replaces OSHA Instruction CPL 02-00-148, Field Operations Manual (FOM), issued November 9, 2009. The one remaining part of the prior Field Operations Manual, the chapter on Disclosure, will be added at a later date. This Instruction also cancels OSHA Instruction FAP 01-00-003 Federal Agency Safety and Health Programs, May 17, 1996 and Chapter 13 of OSHA Instruction CPL 02-00-045, Revised Field Operations Manual, June 15, 1989. This Instruction constitutes OSHA’s general enforcement policies and procedures manual for use by the field offices in conducting inspections, issuing citations and proposing penalties.Significant Changes∙A new Table of Contents for the entire FOM is added.∙ A new References section for the entire FOM is added∙ A new Cancellations section for the entire FOM is added.∙Adds a Maritime Industry Sector to Section III of Chapter 10, Industry Sectors.∙Revises sections referring to the Enhanced Enforcement Program (EEP) replacing the information with the Severe Violator Enforcement Program (SVEP).∙Adds Chapter 13, Federal Agency Field Activities.∙Cancels OSHA Instruction FAP 01-00-003, Federal Agency Safety and Health Programs, May 17, 1996.DisclaimerThis manual is intended to provide instruction regarding some of the internal operations of the Occupational Safety and Health Administration (OSHA), and is solely for the benefit of the Government. No duties, rights, or benefits, substantive or procedural, are created or implied by this manual. The contents of this manual are not enforceable by any person or entity against the Department of Labor or the United States. Statements which reflect current Occupational Safety and Health Review Commission or court precedents do not necessarily indicate acquiescence with those precedents.Table of ContentsCHAPTER 1INTRODUCTIONI.PURPOSE. ........................................................................................................... 1-1 II.SCOPE. ................................................................................................................ 1-1 III.REFERENCES .................................................................................................... 1-1 IV.CANCELLATIONS............................................................................................. 1-8 V. ACTION INFORMATION ................................................................................. 1-8A.R ESPONSIBLE O FFICE.......................................................................................................................................... 1-8B.A CTION O FFICES. .................................................................................................................... 1-8C. I NFORMATION O FFICES............................................................................................................ 1-8 VI. STATE IMPACT. ................................................................................................ 1-8 VII.SIGNIFICANT CHANGES. ............................................................................... 1-9 VIII.BACKGROUND. ................................................................................................. 1-9 IX. DEFINITIONS AND TERMINOLOGY. ........................................................ 1-10A.T HE A CT................................................................................................................................................................. 1-10B. C OMPLIANCE S AFETY AND H EALTH O FFICER (CSHO). ...........................................................1-10B.H E/S HE AND H IS/H ERS ..................................................................................................................................... 1-10C.P ROFESSIONAL J UDGMENT............................................................................................................................... 1-10E. W ORKPLACE AND W ORKSITE ......................................................................................................................... 1-10CHAPTER 2PROGRAM PLANNINGI.INTRODUCTION ............................................................................................... 2-1 II.AREA OFFICE RESPONSIBILITIES. .............................................................. 2-1A.P ROVIDING A SSISTANCE TO S MALL E MPLOYERS. ...................................................................................... 2-1B.A REA O FFICE O UTREACH P ROGRAM. ............................................................................................................. 2-1C. R ESPONDING TO R EQUESTS FOR A SSISTANCE. ............................................................................................ 2-2 III. OSHA COOPERATIVE PROGRAMS OVERVIEW. ...................................... 2-2A.V OLUNTARY P ROTECTION P ROGRAM (VPP). ........................................................................... 2-2B.O NSITE C ONSULTATION P ROGRAM. ................................................................................................................ 2-2C.S TRATEGIC P ARTNERSHIPS................................................................................................................................. 2-3D.A LLIANCE P ROGRAM ........................................................................................................................................... 2-3 IV. ENFORCEMENT PROGRAM SCHEDULING. ................................................ 2-4A.G ENERAL ................................................................................................................................................................. 2-4B.I NSPECTION P RIORITY C RITERIA. ..................................................................................................................... 2-4C.E FFECT OF C ONTEST ............................................................................................................................................ 2-5D.E NFORCEMENT E XEMPTIONS AND L IMITATIONS. ....................................................................................... 2-6E.P REEMPTION BY A NOTHER F EDERAL A GENCY ........................................................................................... 2-6F.U NITED S TATES P OSTAL S ERVICE. .................................................................................................................. 2-7G.H OME-B ASED W ORKSITES. ................................................................................................................................ 2-8H.I NSPECTION/I NVESTIGATION T YPES. ............................................................................................................... 2-8 V.UNPROGRAMMED ACTIVITY – HAZARD EVALUATION AND INSPECTION SCHEDULING ............................................................................ 2-9 VI.PROGRAMMED INSPECTIONS. ................................................................... 2-10A.S ITE-S PECIFIC T ARGETING (SST) P ROGRAM. ............................................................................................. 2-10B.S CHEDULING FOR C ONSTRUCTION I NSPECTIONS. ..................................................................................... 2-10C.S CHEDULING FOR M ARITIME I NSPECTIONS. ............................................................................. 2-11D.S PECIAL E MPHASIS P ROGRAMS (SEP S). ................................................................................... 2-12E.N ATIONAL E MPHASIS P ROGRAMS (NEP S) ............................................................................... 2-13F.L OCAL E MPHASIS P ROGRAMS (LEP S) AND R EGIONAL E MPHASIS P ROGRAMS (REP S) ............ 2-13G.O THER S PECIAL P ROGRAMS. ............................................................................................................................ 2-13H.I NSPECTION S CHEDULING AND I NTERFACE WITH C OOPERATIVE P ROGRAM P ARTICIPANTS ....... 2-13CHAPTER 3INSPECTION PROCEDURESI.INSPECTION PREPARATION. .......................................................................... 3-1 II.INSPECTION PLANNING. .................................................................................. 3-1A.R EVIEW OF I NSPECTION H ISTORY .................................................................................................................... 3-1B.R EVIEW OF C OOPERATIVE P ROGRAM P ARTICIPATION .............................................................................. 3-1C.OSHA D ATA I NITIATIVE (ODI) D ATA R EVIEW .......................................................................................... 3-2D.S AFETY AND H EALTH I SSUES R ELATING TO CSHO S.................................................................. 3-2E.A DVANCE N OTICE. ................................................................................................................................................ 3-3F.P RE-I NSPECTION C OMPULSORY P ROCESS ...................................................................................................... 3-5G.P ERSONAL S ECURITY C LEARANCE. ................................................................................................................. 3-5H.E XPERT A SSISTANCE. ........................................................................................................................................... 3-5 III. INSPECTION SCOPE. ......................................................................................... 3-6A.C OMPREHENSIVE ................................................................................................................................................... 3-6B.P ARTIAL. ................................................................................................................................................................... 3-6 IV. CONDUCT OF INSPECTION .............................................................................. 3-6A.T IME OF I NSPECTION............................................................................................................................................. 3-6B.P RESENTING C REDENTIALS. ............................................................................................................................... 3-6C.R EFUSAL TO P ERMIT I NSPECTION AND I NTERFERENCE ............................................................................. 3-7D.E MPLOYEE P ARTICIPATION. ............................................................................................................................... 3-9E.R ELEASE FOR E NTRY ............................................................................................................................................ 3-9F.B ANKRUPT OR O UT OF B USINESS. .................................................................................................................... 3-9G.E MPLOYEE R ESPONSIBILITIES. ................................................................................................. 3-10H.S TRIKE OR L ABOR D ISPUTE ............................................................................................................................. 3-10I. V ARIANCES. .......................................................................................................................................................... 3-11 V. OPENING CONFERENCE. ................................................................................ 3-11A.G ENERAL ................................................................................................................................................................ 3-11B.R EVIEW OF A PPROPRIATION A CT E XEMPTIONS AND L IMITATION. ..................................................... 3-13C.R EVIEW S CREENING FOR P ROCESS S AFETY M ANAGEMENT (PSM) C OVERAGE............................. 3-13D.R EVIEW OF V OLUNTARY C OMPLIANCE P ROGRAMS. ................................................................................ 3-14E.D ISRUPTIVE C ONDUCT. ...................................................................................................................................... 3-15F.C LASSIFIED A REAS ............................................................................................................................................. 3-16VI. REVIEW OF RECORDS. ................................................................................... 3-16A.I NJURY AND I LLNESS R ECORDS...................................................................................................................... 3-16B.R ECORDING C RITERIA. ...................................................................................................................................... 3-18C. R ECORDKEEPING D EFICIENCIES. .................................................................................................................. 3-18 VII. WALKAROUND INSPECTION. ....................................................................... 3-19A.W ALKAROUND R EPRESENTATIVES ............................................................................................................... 3-19B.E VALUATION OF S AFETY AND H EALTH M ANAGEMENT S YSTEM. ....................................................... 3-20C.R ECORD A LL F ACTS P ERTINENT TO A V IOLATION. ................................................................................. 3-20D.T ESTIFYING IN H EARINGS ................................................................................................................................ 3-21E.T RADE S ECRETS. ................................................................................................................................................. 3-21F.C OLLECTING S AMPLES. ..................................................................................................................................... 3-22G.P HOTOGRAPHS AND V IDEOTAPES.................................................................................................................. 3-22H.V IOLATIONS OF O THER L AWS. ....................................................................................................................... 3-23I.I NTERVIEWS OF N ON-M ANAGERIAL E MPLOYEES .................................................................................... 3-23J.M ULTI-E MPLOYER W ORKSITES ..................................................................................................................... 3-27 K.A DMINISTRATIVE S UBPOENA.......................................................................................................................... 3-27 L.E MPLOYER A BATEMENT A SSISTANCE. ........................................................................................................ 3-27 VIII. CLOSING CONFERENCE. .............................................................................. 3-28A.P ARTICIPANTS. ..................................................................................................................................................... 3-28B.D ISCUSSION I TEMS. ............................................................................................................................................ 3-28C.A DVICE TO A TTENDEES .................................................................................................................................... 3-29D.P ENALTIES............................................................................................................................................................. 3-30E.F EASIBLE A DMINISTRATIVE, W ORK P RACTICE AND E NGINEERING C ONTROLS. ............................ 3-30F.R EDUCING E MPLOYEE E XPOSURE. ................................................................................................................ 3-32G.A BATEMENT V ERIFICATION. ........................................................................................................................... 3-32H.E MPLOYEE D ISCRIMINATION .......................................................................................................................... 3-33 IX. SPECIAL INSPECTION PROCEDURES. ...................................................... 3-33A.F OLLOW-UP AND M ONITORING I NSPECTIONS............................................................................................ 3-33B.C ONSTRUCTION I NSPECTIONS ......................................................................................................................... 3-34C. F EDERAL A GENCY I NSPECTIONS. ................................................................................................................. 3-35CHAPTER 4VIOLATIONSI. BASIS OF VIOLATIONS ..................................................................................... 4-1A.S TANDARDS AND R EGULATIONS. .................................................................................................................... 4-1B.E MPLOYEE E XPOSURE. ........................................................................................................................................ 4-3C.R EGULATORY R EQUIREMENTS. ........................................................................................................................ 4-6D.H AZARD C OMMUNICATION. .............................................................................................................................. 4-6E. E MPLOYER/E MPLOYEE R ESPONSIBILITIES ................................................................................................... 4-6 II. SERIOUS VIOLATIONS. .................................................................................... 4-8A.S ECTION 17(K). ......................................................................................................................... 4-8B.E STABLISHING S ERIOUS V IOLATIONS ............................................................................................................ 4-8C. F OUR S TEPS TO BE D OCUMENTED. ................................................................................................................... 4-8 III. GENERAL DUTY REQUIREMENTS ............................................................. 4-14A.E VALUATION OF G ENERAL D UTY R EQUIREMENTS ................................................................................. 4-14B.E LEMENTS OF A G ENERAL D UTY R EQUIREMENT V IOLATION.............................................................. 4-14C. U SE OF THE G ENERAL D UTY C LAUSE ........................................................................................................ 4-23D.L IMITATIONS OF U SE OF THE G ENERAL D UTY C LAUSE. ..............................................................E.C LASSIFICATION OF V IOLATIONS C ITED U NDER THE G ENERAL D UTY C LAUSE. ..................F. P ROCEDURES FOR I MPLEMENTATION OF S ECTION 5(A)(1) E NFORCEMENT ............................ 4-25 4-27 4-27IV.OTHER-THAN-SERIOUS VIOLATIONS ............................................... 4-28 V.WILLFUL VIOLATIONS. ......................................................................... 4-28A.I NTENTIONAL D ISREGARD V IOLATIONS. ..........................................................................................4-28B.P LAIN I NDIFFERENCE V IOLATIONS. ...................................................................................................4-29 VI. CRIMINAL/WILLFUL VIOLATIONS. ................................................... 4-30A.A REA D IRECTOR C OORDINATION ....................................................................................................... 4-31B.C RITERIA FOR I NVESTIGATING P OSSIBLE C RIMINAL/W ILLFUL V IOLATIONS ........................ 4-31C. W ILLFUL V IOLATIONS R ELATED TO A F ATALITY .......................................................................... 4-32 VII. REPEATED VIOLATIONS. ...................................................................... 4-32A.F EDERAL AND S TATE P LAN V IOLATIONS. ........................................................................................4-32B.I DENTICAL S TANDARDS. .......................................................................................................................4-32C.D IFFERENT S TANDARDS. .......................................................................................................................4-33D.O BTAINING I NSPECTION H ISTORY. .....................................................................................................4-33E.T IME L IMITATIONS..................................................................................................................................4-34F.R EPEATED V. F AILURE TO A BATE....................................................................................................... 4-34G. A REA D IRECTOR R ESPONSIBILITIES. .............................................................................. 4-35 VIII. DE MINIMIS CONDITIONS. ................................................................... 4-36A.C RITERIA ................................................................................................................................................... 4-36B.P ROFESSIONAL J UDGMENT. ..................................................................................................................4-37C. A REA D IRECTOR R ESPONSIBILITIES. .............................................................................. 4-37 IX. CITING IN THE ALTERNATIVE ............................................................ 4-37 X. COMBINING AND GROUPING VIOLATIONS. ................................... 4-37A.C OMBINING. ..............................................................................................................................................4-37B.G ROUPING. ................................................................................................................................................4-38C. W HEN N OT TO G ROUP OR C OMBINE. ................................................................................................4-38 XI. HEALTH STANDARD VIOLATIONS ....................................................... 4-39A.C ITATION OF V ENTILATION S TANDARDS ......................................................................................... 4-39B.V IOLATIONS OF THE N OISE S TANDARD. ...........................................................................................4-40 XII. VIOLATIONS OF THE RESPIRATORY PROTECTION STANDARD(§1910.134). ....................................................................................................... XIII. VIOLATIONS OF AIR CONTAMINANT STANDARDS (§1910.1000) ... 4-43 4-43A.R EQUIREMENTS UNDER THE STANDARD: .................................................................................................. 4-43B.C LASSIFICATION OF V IOLATIONS OF A IR C ONTAMINANT S TANDARDS. ......................................... 4-43 XIV. CITING IMPROPER PERSONAL HYGIENE PRACTICES. ................... 4-45A.I NGESTION H AZARDS. .................................................................................................................................... 4-45B.A BSORPTION H AZARDS. ................................................................................................................................ 4-46C.W IPE S AMPLING. ............................................................................................................................................. 4-46D.C ITATION P OLICY ............................................................................................................................................ 4-46 XV. BIOLOGICAL MONITORING. ...................................................................... 4-47CHAPTER 5CASE FILE PREPARATION AND DOCUMENTATIONI.INTRODUCTION ............................................................................................... 5-1 II.INSPECTION CONDUCTED, CITATIONS BEING ISSUED. .................... 5-1A.OSHA-1 ................................................................................................................................... 5-1B.OSHA-1A. ............................................................................................................................... 5-1C. OSHA-1B. ................................................................................................................................ 5-2 III.INSPECTION CONDUCTED BUT NO CITATIONS ISSUED .................... 5-5 IV.NO INSPECTION ............................................................................................... 5-5 V. HEALTH INSPECTIONS. ................................................................................. 5-6A.D OCUMENT P OTENTIAL E XPOSURE. ............................................................................................................... 5-6B.E MPLOYER’S O CCUPATIONAL S AFETY AND H EALTH S YSTEM. ............................................................. 5-6 VI. AFFIRMATIVE DEFENSES............................................................................. 5-8A.B URDEN OF P ROOF. .............................................................................................................................................. 5-8B.E XPLANATIONS. ..................................................................................................................................................... 5-8 VII. INTERVIEW STATEMENTS. ........................................................................ 5-10A.G ENERALLY. ......................................................................................................................................................... 5-10B.CSHO S SHALL OBTAIN WRITTEN STATEMENTS WHEN: .......................................................................... 5-10C.L ANGUAGE AND W ORDING OF S TATEMENT. ............................................................................................. 5-11D.R EFUSAL TO S IGN S TATEMENT ...................................................................................................................... 5-11E.V IDEO AND A UDIOTAPED S TATEMENTS. ..................................................................................................... 5-11F.A DMINISTRATIVE D EPOSITIONS. .............................................................................................5-11 VIII. PAPERWORK AND WRITTEN PROGRAM REQUIREMENTS. .......... 5-12 IX.GUIDELINES FOR CASE FILE DOCUMENTATION FOR USE WITH VIDEOTAPES AND AUDIOTAPES .............................................................. 5-12 X.CASE FILE ACTIVITY DIARY SHEET. ..................................................... 5-12 XI. CITATIONS. ..................................................................................................... 5-12A.S TATUTE OF L IMITATIONS. .............................................................................................................................. 5-13B.I SSUING C ITATIONS. ........................................................................................................................................... 5-13C.A MENDING/W ITHDRAWING C ITATIONS AND N OTIFICATION OF P ENALTIES. .................................. 5-13D.P ROCEDURES FOR A MENDING OR W ITHDRAWING C ITATIONS ............................................................ 5-14 XII. INSPECTION RECORDS. ............................................................................... 5-15A.G ENERALLY. ......................................................................................................................................................... 5-15B.R ELEASE OF I NSPECTION I NFORMATION ..................................................................................................... 5-15C. C LASSIFIED AND T RADE S ECRET I NFORMATION ...................................................................................... 5-16。

Analytical MethodsAntioxidant capacity,polyphenolic content and tandem HPLC–DAD–ESI/MS profiling of phenolic compounds from the South American berries Luma apiculata and L.chequénMario J.Simirgiotis a ,⇑,Jorge Bórquez a ,Guillermo Schmeda-Hirschmann ba Laboratorio de Productos Naturales,Departamento de Química,Facultad de Ciencias Básicas,Universidad de Antofagasta,Casilla 170,Antofagasta,Chile bLaboratorio de Química de Productos Naturales,Instituto de Química de Recursos Naturales,Universidad de Talca,Casilla 747,Talca,Chilea r t i c l e i n f o Article history:Received 16January 2012Received in revised form 26December 2012Accepted 28January 2013Available online 13February 2013Keywords:Luma apiculata Luma chequén Myrtaceae ArrayánSouth American berries HPLC–DAD–MS Phenolics Antioxidantsa b s t r a c tNative Myrtaceae fruits were gathered by South American Amerindians as a food source.At present,there is still some regional consume of the small berries from trees belonging to genus Luma that occurs in southern Chile and Argentina.The aerial parts and berries from Luma apiculata and Luma chequen were investigated for phenolic constituents and antioxidant capacity.A high performance electrospray ionisa-tion mass spectrometry method was developed for the rapid identification of phenolics in polar extracts from both species.Thirty-one phenolic compounds were detected and 27were identified or tentatively characterised based on photodiode array UV–vis spectra (DAD),ESI–MS–MS spectrometric data and spik-ing experiments with authentic standards.Twelve phenolic compounds were detected in L.apiculata fruits and 12in the aerial parts while L.chequen yielded 10compounds in fruits and 16in aerial parts,respectively.From the compounds occurring in both Luma species,seven were identified as tannins or their monomers,15were flavonol derivatives and five were anthocyanins.The whole berry and aerial parts extracts presented high antioxidant capacity in the DPPH assay (IC 50of 10.41±0.02and 2.44±0.03l g/mL for L.apiculata ,12.89±0.05and 3.22±0.05for L.chequen ,respectively),which can be related to the diverse range of phenolics detected.The antioxidant capacity together with the high polyphenolic contents and compounds identified can support at least in part,their use as botanical drugs.From the compounds identified in both species,3-O -(600-O -galloyl)-hexose derivatives of myricetin,quer-cetin,laricitrin and isorhamnetin are reported for the first time for the genus Luma .Ó2013Elsevier Ltd.All rights reserved.1.IntroductionThe consumption of fruits belonging to the Myrtaceae family is a common and ancient practice in South America.The Amerindian populations gathered the fruits and the largest in size with the best taste were incorporated into South American culinary traditions all over the continent.Several edible Myrtaceae fruits including the Chilean berry ‘‘murtilla’’(Ugni molinae Turczaninov)and the murtilla-like berry Myrteola nummularia (Poiret)Berg.have been shown to be a good source of polyphenolic antioxidants (Arancibia-Avila et al.,2011;Reynertson,Yang,Jiang,Basile,&Kennelly,2008).The Myrtaceae Luma apiculata (DC.)Burret and Luma chequén (Molina) A.Gray are trees with edible black-coloured berries occurring in southern Chile and Argentina.The berries from both are half the size of commercial blueberries with a more intense col-our but similar aspect and consistence,and have been employed to prepare ‘‘chicha’’,a Mapuche fermented beverage (Hoffmann,1995;Muñoz,Barrera,&Meza,1981).Despite the well known uses and health benefits (Murillo,1889)of these berries,especially L.apiculata ,their polyphenolic composition and antioxidant activity have not been reported.The medicinal properties of ‘‘Arrayan’’leaves (L.apiculata ,syn.Eugenia apiculata DC.or Myrceugenella apiculata (DC.)Kausel,Hoffmann,1995),include aromatic,astringent,balsamic and anti-inflammatory activity (Murillo,1889).In addition,inhibitory activity of the xanthine oxidase enzyme has been reported for these and other Chilean Myrtaceae with similar medicinal uses,including the treatment of gout,in Chile and Paraguay (Theoduloz,Franco,Ferro,&Schmeda Hirschmann,1988;Theoduloz,Pacheco,&Schmeda Hirschmann,1991).Leaves from the related species L.chequén A.Gray (syn:Myrceugenella chequen (Mol.)Kaus have been used as an astringent (de Mösbach,1991).In the last few years,several biological samples such as alcoholic plant and fruit extracts containing complex mixtures of small and medium size phenolic and other molecules including very polar and thermally labile constituents have been analysed with the development of reliable LC–MS/MS equipment (Steinmann &Ganz-era,2011;Wright,2011).Indeed,the use of liquid chromatography0308-8146/$-see front matter Ó2013Elsevier Ltd.All rights reserved./10.1016/j.foodchem.2013.01.089Corresponding author.Tel.:+5655637229;fax:+5655637457.E-mail address:mario.simirgiotis@uantof.cl (M.J.Simirgiotis).(HPLC,UPLC)coupled to diverse mass spectrometers such as hybrid quadrupole time offlight(Q-TOF)or electrospray ionization-ion trap(Q-ESI)analyzers with complementary properties have been used in the last years for metabolic profiling and biological analysis (Aliferis&Chrysayi-Tokousbalides,2011;Kang et al.,2011;Mattoli et al.,2011).The LC–MS methods proved to be superior to GC–MS since no prior derivatisation of polar samples(bearing hydroxyl and car-boxyl groups)is required(Hao,Zhao,&Yang,2007).Quality con-trol of herbal drugs and medicinal plants is currently performed with ESI–MS(Steinmann&Ganzera,2011).HPLC–ESI–MS was used to analyse carotenoids(Maoka,2009),anthocyanins(Barnes, Nguyen,Shen,&Schug,2009),phenolic acids(Fischer,Carle,& Kammerer,2011)and alkaloids(He et al.,2011)in edible fruits. Chilean native berries such as calafate(Berberis spp.)(Ruiz et al., 2010)maqui(Aristotelia chilensis)and murta(U.molinae)(Rubilar et al.,2006)were also analysed using this precise technique.Despite the traditional use of L.apiculata and L.chequen,we were not able tofind studies about phenolics constituents or antioxidant capacity of edible fruits from either species.The main goals and nov-elty of this work is the profiling of phenolics as well as the measure-ment of antioxidant capacity and polyphenolic content of extracts from the berry fruits and leaves of the native Chilean L.apiculata and L.chequen,which is a continuation of our studies on South American food plants(Simirgiotis&Schmeda-Hirschmann,2010a).2.Materials and methods2.1.Chemicals and plant materialFolin–Ciocalteu phenol reagent(2N),Na2CO3,AlCl3,FeCl3, NaNO2,NaOH,D(+)glucose,D(+)galactose,L(+)rhamnose,D(À)ri-bose,quercetin,sodium acetate,HPLC-grade water,HPLC-grade acetonitrile,thin layer chromatography(TLC,Kieselgel F254)plates, reagent grade MeOH and formic acid were obtained from Merck (Darmstadt,Germany).Myricetin3-O-rhamnoside(myricitrin), quercetin3-O-rhamnoside(quercitrin),cyanidin,myricetin,isorh-amnetin,syringetin,petunidin,pelargonidin,peonidin,malvidin and their3-O-glucosides(all standards with purity higher than 95%by HPLC)were purchased either from ChromaDex(Santa Ana,CA,USA)or Extrasynthèse(Genay,France).Gallic acid,TPTZ (2,4,6-tri(2-pyridyl)1,3,5-triazine),Trolox and DPPH(1,1-diphe-nyl-2-picrylhydrazyl radical)were purchased from Sigma–Aldrich Chemical Co.(USA).Aerial parts and ripe fruits of L.apiculata(DC.)Burret(local name: Arrayán),and L.chequén(Molina)A.Gray(local name:Chequén), were collected by Luis Bermedo Guzmán and Mario J.Simirgiotis in Re-Re,Región del Bio-Bio,Chile in May2011.Voucher herbarium specimens and fruit samples were deposited at the Laboratorio de Productos Naturales,Universidad de Antofagasta,Antofagasta,Chile, with the numbers La-111505-1and Lc-111505-2,respectively.2.2.Sample preparationFresh Luma fruits and aerial parts(leaves and stems)were sep-arately homogenised in a blender and freeze-dried(Labconco Freezone4.5L,Kansas,MO,USA).One gram of lyophilised material wasfinally pulverised in a mortar and extracted thrice with25mL of0.1%HCl in MeOH in the dark for1h each time.The extracts were combined,filtered and evaporated in vacuo(40°C).The ex-tracts were suspended in10mL ultrapure water and loaded onto a reverse phase solid phase extraction cartridge(SPE,Varian Bond Elut C-18,500mg/6mL).The cartridge was rinsed with water (10mL)and phenolic compounds were eluted with10mL MeOH acidified with0.1%HCl.The solutions were evaporated to dryness under reduced pressure to give73.60mg of L.apiculata fruits, 93.60mg of L.apiculata aerial parts,67.4mg of L.chequén fruits and40.6mg of L.chequén aerial parts,respectively(for extraction yields see Table1).The extracts were then dissolved in2mL0.1% HCl in MeOH,filtered through a0.45l m micropore membrane (PTFE,Waters)before use and10l l were injected into the HPLC instrument for analysis.2.3.HPLC analysisA Merck-Hitachi(LaChrom,Tokyo,Japan)instrument equipped with an L-7100pump,an L-7455UV diode array detector,a D-7000 chromato-integrator and a column compartment was used for analyses.The sample was separated on a Purospher star-C18col-umn(250mmÂ5mm,4.6mm i.d.,Merck,Germany).The mobile phase consisted of10%formic acid in water(A)and acetonitrile(B).A gradient program was used for HPLC–DAD and ESI-MS as fol-lows:90%A in thefirst4min,linear gradient to75%A over 25min,then linear gradient back to initial conditions for other 15min.The mobile phaseflow rate was1mL/min.The column temperature was set at25°C;the detector was monitored at 520nm for anthocyanins and320–280nm for other compounds while UV spectra from200to600nm were recorded for peak characterisation.2.4.Mass spectrometric conditionsAn Esquire4000Ion Trap mass spectrometer(Bruker Daltoniks, Germany)was connected to an Agilent1100HPLC instrument via ESI interface for HPLC–ESI-MS analysis.Full scan mass spectra were measured between m/z150and2000u in positive ion mode for anthocyanins and negative ion mode for other compounds. High purity nitrogen was used as nebuliser gas at27.5psi,350°C and at aflow rate of8l/min.The mass spectrometric conditions for negative ion mode were:electrospray needle,4000V;end plate offset,À500V;skimmer1,À56.0V;skimmer2,À6.0V;capillary exit offset,À84.6V;and the operating conditions for positive ion mode were:electrospray needle,4000V;end plate offset,À500V;skimmer1,56.0V;skimmer2,6.0V;capillary exit offset, 84.6V;capillary exit,140.6V.Collisionally induced dissociation (CID)spectra were obtained with a fragmentation amplitude of1.00V(MS/MS)using ultrahigh pure helium as the collision gas.2.5.Alkaline and acid hydrolysis of MeOH extractsTo verify acylation of theflavonol glycoside derivatives18,23, 24and28from the HPLCfingerprint,the SPE MeOH extractsTable1Total phenolic content(TPC),totalflavonoid content(TFC),total anthocyanin content(TAC),ferric reducing antioxidant power(FRAP),scavenging of the free radical DPPH and percent w/w extraction yield of Luma methanolic extracts on the basis of freeze-dried starting material.Species and plant part a TPC(mg/g)TFC(mg/g)TAC(mg/g)FRAP(l mol/g)DPPH(IC50,l g/mL)w/w extraction yield(%)L.apiculata fruits29.44±0.1013.31±0.0121.03±2.1493.4±0.010.41±0.027.36L.chequén fruits 5.15±0.00 1.51±0.00 1.57±0.0076.2±0.012.89±0.059.36L.apiculata aerial parts179.83±0.38139.70±1.48-170.5±0.1 2.44±0.03 6.74L.chequen aerial parts327.09±0.80126.54±1.15-135.6±0.3 3.22±0.05 4.06a Measurements are expressed as mean±SD of three parallel determinations(All values are significantly different at p<0.05).290M.J.Simirgiotis et al./Food Chemistry139(2013)289–299obtained as explained above(2mL)was hydrolysed with2mL of 2mol/L sodium hydroxide as previously reported(Simirgiotis,Cal-igari,&Schmeda-Hirschmann,2009).The mixture was kept for 16h at room temperature,neutralised with concentrated hydro-chloric acid,filtered(0.45l m,PTFE Waters)and directly analysed (10l l)by HPLC–DAD and ESI–MS–MS.Another portion of pro-cessed SPE MeOH extracts(2mL)was dissolved in4mol/L HCl (2mL)in order to further confirm the identity offlavonol aglycones by HPLC.After stirring the solution at90°C for60min,water was added(10mL),the solvent and hydrochloric acid were removed under reduced pressure and the remaining aqueous solution (10mL)was again submitted to SPE to wash the remaining acid and sugars.The identification of the sugars in the aqueous solution was performed by TLC using different sugars as standards as re-ported by Figueirinha,Paranhos,Pérez-Alonso,Santos-Buelga, and Batista(2008).After SPE,the resulting methanolic solution (2mL)wasfiltered(0.45l m,PTFE Waters)and directly analysed (10l l)by HPLC–DAD–ESI/MS.In order to measure the recovery of phenolics for the total extraction procedure,a standard anthocy-anin(pelargonidin,0.5mg/mL)a standardflavonoid(quercetin, 0.5mg/mL)and a standard phenolic acid(gallic acid,0.5mg/mL) were added to a fresh sample(one gram)of freeze-dried L.apicula-ta fruits(three times)used as matrix,extracted,SPE processed as above and recovery was calculated using HPLC–DAD.2.6.Antioxidant assessment2.6.1.Free radical scavenging activityThe free radical scavenging activity of the extracts was deter-mined by the DPPHÅassay as previously described(Simirgiotis& Schmeda-Hirschmann,2010a),with some modifications.DPPH radical absorbs at517nm,but upon reduction by an antioxidant compound its absorption decreases.Briefly,50l L of processed SPE MeOH extract or pure compound prepared at different concen-trations was added to2mL of fresh0.1mM solution of DPPH in methanol and allowed to react at37°C in the dark.After30min the absorbance was measured at517nm.The DPPH scavenging ability as percentage was calculated as:DPPH scavenging abil-ity=(A controlÀA sample/A control)Â100.Afterwards,a curve of%DPPH bleaching activity versus concentration was plotted and IC50values were calculated.IC50denotes the concentration of sample required to scavenge50%of DPPH free radicals.The lower the IC50value the more powerful the antioxidant capacity.If IC50650l g/mL the sample has high antioxidant capacity,if50l g/mL<IC506100l g/ mL the sample has moderate antioxidant capacity and if IC50>200-l g/mL the sample has no relevant antioxidant capacity.Gallic acid (from1.0to125.0l g/mL,R2=0.991)and quercetin(from1.0to 125.0l g/mL,R2=0.993)were used as standard antioxidant com-pounds,and were determined to have IC50values of1.1l g/ml (6.8l mol/L)and7.5l g/ml(24.8l mol/L),respectively.2.6.2.Ferric reducing antioxidant powerThe determination of ferric reducing antioxidant power or ferric reducing ability(FRAP assay)of the extracts was performed as de-scribed by(Benzie&Strain,1996)with some modifications.The stock solutions prepared were300mM acetate buffer pH 3.6, 10mM TPTZ(2,4,6-tri(2-pyridyl)-s-triazine)solution in40mM HCl,and20mM FeCl3Á6H2O solution.Plant extracts or standard methanolic Trolox solutions(150l L)were incubated at37°C with 2mL of the FRAP solution(prepared by mixing25mL acetate buf-fer,5mL TPTZ solution,and10mL FeCl3Á6H2O solution)for30min in the dark.Absorbance of the blue ferrous tripyridyltriazine complex formed was then read at593nm.Quantification was per-formed using a standard calibration curve of antioxidant Trolox (from0.2to2.5l mol/mL,R2:0.995).Samples were analysed in triplicate and results are expressed in l mol TE/gram dry mass.2.7.Polyphenol,flavonoid and anthocyanin contents’The total polyphenolic contents(TPC)of Luma fruits and leaves were determined by the Folin–Ciocalteau method(Simirgiotis, Caligari,et al.,2009;Simirgiotis,Theoduloz,Caligari,and Schme-da-Hirschmann,2009)with some modifications.An aliquot of each processed SPE extract(200l l),was added to the Folin–Ciocalteau reagent(2mL,1:10v/v in purified water)and after5min of reac-tion at room temperature(25°C),2mL of a100g/L solution of Na2-CO3was added.Sixty minutes later the absorbance was measured at710nm.A calibration curve was performed with the standard gallic acid(concentrations ranging from16to500l g/mL, R2=0.999)and the results expressed as mg gallic acid equiva-lents/g dry mass.Determination of totalflavonoid content(TFC)of the methano-lic extracts was performed as reported previously(Simirgiotis et al.,2008)using the AlCl3colorimetric method.Quantification was expressed by reporting the absorbance in the calibration graph of quercetin,which was used as theflavonoid standard(from0.1to 65.0l g/mL,R2=0.994).Results are expressed as mg quercetin equivalents/g dry mass.The assessment of total anthocyanin con-tent(TAC)was carried out as described by(Lee,Durst,&Wrolstad, 2005).Absorbance was measured at510and700nm in buffers at pH1.0and4.5.Pigment concentration is expressed as mg cyanidin 3-glucoside equivalents/g dry mass and calculated using the formula:TAðmg=gÞ¼AÂMWÂDFÂ103eÂ1where A=(A510nmÀA700nm)pH1.0À(A510nmÀA700nm)pH4.5; MW(molecular weight)=449.2g/mol;DF=dilution factor; 1=cuvette pathlength in cm;e=26,900L/mol cm,molar extinc-tion coefficient for cyanidin3-O-b-D-glucoside.103:factor to con-vert g to mg.All spectrometric measurements were performed using a Unico2800UV–vis spectrophotometer(Shangai,Unico instruments,Co.,Ltd.).2.8.Statistical analysisThe statistical analysis was carried out using the originPro9.0 software packages(Originlab Corporation,Northampton,MA, USA).The determination was repeated at least three times for each sample solution.Analysis of variance was performed using ANOVA. Significant differences between means were determined by stu-dent’s t-test(p values<0.05were regarded as significant).3.Results and discussionIn the present study,we assessed the polyphenolic profile of aerial parts and fruits of L.apiculata and L.chequen collected in the Bio-Bio Region,Chile,and evaluated its antioxidant capacity as well as the total phenolic,totalflavonoid and total anthocyanin content by spectrophotometric methods.The fresh fruits and aerial parts were extracted with methanol and the resulting extracts were processed by solid phase extraction.The weight/weight extraction yields of the extracts were7.36%,9.36%, 6.74%and 4.06%for L.apiculata fruits,L.chequén fruits,L.apiculata aerial parts and L.chequen aerial parts,respectively.The identity of phenolic compounds from the extracts was investigated by high-perfor-mance liquid chromatography paired with UV photodiode array (HPLC–DAD)and triple quadrupole ion trap-electrospray ionisa-tion tandem mass spectrometry(HPLC–ESI/MS).Anthocyanins were monitored in ESI positive mode while other compounds were measured in negative mode.While L.chequén is reported to pro-duce severalflavanones(Labbe et al.,1992),these compoundsM.J.Simirgiotis et al./Food Chemistry139(2013)289–299291were not identified in our Luma samples.The pattern of methoxy-latedflavonoids glycosides(laricitrin,myricetin,isorhamnetin)de-tected in Luma resembles that reported in Vitis vinifera cv.Petit Verdot grapes(Castillo-Muñoz et al.,2009).3.1.Total phenolic,anthocyanin andflavonoid contents and antioxidant capacity of Luma extractsIn this study,the phenolic profiles of methanolic extracts from Luma fruits and aerial parts were compared by HPLC–DAD (Fig.1).Antioxidant capacity of the extracts was measured and cor-the different antioxidant capacity(10.41±0.02/12.89±0.05l g/mL in the DPPH assay and93.4±0.0/76.2±0.0l mol Trolox/g in the FRAP assay,respectively,Table1).The TAC value for L.apiculata fruits(21.03±2.14mg/g)was almost three times of that reported for the blueberries Vaccinium uliginosum(9.01±0.06mg/g of freeze-dried powder)(Li et al.,2011).The small Korean fruits(Lir-iope platyphylla)of a comparable shape,size and colour to Luma fruits(Fig.2)produced similar HPLC–DAD anthocyaninfingerprint (Lee&Choung,2011).The phenolic content correlated with antioxidant capacity(R2: 0.778for TP/DPPH assay)while the antioxidant assays correlatedchromatograms of Luma extracts.(a)Chromatograms at280nm.(A)L.apiculata fruits,(B)L.chequén fruits,(C)L.apiculata leaves,(D)L.at520nm.(E)L.apiculata fruits,(F)L.chequén fruits.292M.J.Simirgiotis et al./Food Chemistry139(2013)289–299those reported for seven black and fresh tea leaves from Asia where the highest value reported was for the brand Ouvagalia tea with 110±10mg/g GAE and80±7mg/g quercetin equivalents(Luxi-mon-Ramma et al.,2005).L.apiculata aerial parts showed a pheno-lic content close to that reported for Rosa chinensis methanol extract(189mg±13GAE/g dry weight)(Cai,Xing,Sun,Zhan,& Corke,2005).3.2.Identification of phenolic constituentsPhenolics occurring in Luma fruits and aerial parts extracts were separated by HPLC and UV–vis spectra were obtained using a diode-array detector.HPLCfingerprints were generated(Fig.1) and phenolic compounds subsequently analysed by ESI–MS–MS.A preliminary analysis of DAD spectrum obtained for the peaks gave afirst indication of the family of phenolic compounds(Simir-giotis,Caligari,et al.,2009;Simirgiotis,Theoduloz,et al.,2009). Some compounds were identified by co-elution with standard phenolics.For those compounds not commercially available,full scan mode followed by ESI–MS–MS experiments in negative mode was a powerful tool for their characterisation.The31compounds detected and27identified or tentatively identified are listed in Ta-ble2,along with UV–vis and MS data.Fig.2shows structures of several compounds identified while Fig.3shows structures and full MS and MS–MS spectra of some representative compounds.Peaks 1–8and10–12were tentatively identified as tannins(hydrolysable or proanthocyanins)or their monomers,peaks30and31were simpleflavonols while peaks15,16,18,20–29were glycosylflavo-nol derivatives,and among those,peaks15,20,21and25were flavonols acylated with gallic acid.Peaks9,13,14,17and19were anthocyanins,and peaks2,8,10and12remain as unidentified phenolics.The identification of peaks is listed below.3.3.Tannins andflavanol derivativesPeaks1–8and10–12were tentatively identified as hydrolysa-ble tannins,epimeric procyanidins orflavanol derivatives.Peak1 was identified as the hydrolysable tannin hexahydroxydiphenoyl-glucose(HHDP-glucose,(Fig.2)with a MW482,a[MÀH]Àionat Fig.1.(continued)m /z 481yielding diagnostic fragments at m /z 301,283,257and 229)as reported (Salminena,Ossipova,&Pihlajaa,2002;Simirgio-tis &Schmeda-Hirschmann,2010a ).Peak 3was also a hydrolysable tannin with a molecular ion at m /z 783,an MS 2ion at m /z 481,pro-ducing a daughter MS 3ion at m /z 301(with MS 4ions at m /z 283,257and 229assigned to one HHDP unit or ellagic acid)identified as a bis-HHDP-glucose/hexose as previously reported (Fischer et al.,2011;Simirgiotis &Schmeda-Hirschmann,2010b ).Peak 4was assigned as the ellagitannin castalagin or its isomer vescalagin both with a [M ÀH]Àat m /z 933(Figs.2and 3a)and MS ions at m /z 631(Fig 2,loss of HHDP unit),481(loss of gallic acid moiety)and 301(loss of galloyl-glucosyl moiety from the parent MS 2ion at m /z 631(Simirgiotis &Schmeda-Hirschmann,2010b ).Peak 5was iden-tified as an ellagic acid hexoside (pedunculagin I)showing an [M ÀH]Àion at m /z 633and fragment ions at m /z 615,481and 301(Fischer et al.,2011).Furthermore,peak 6was identified as an-other bis-HHDP-hexose derivative with a mass difference of 32U ([M ÀH]Àion at m /z 815,C 34H 23O 24)and the same UV data andMS–MS fragments as for compounds 3and 5.This compound was characterised as the ellagitannin furosinin (Takuo,2005).Peak 7showed a [M ÀH]Àion at m /z 577(Fig.3a)and MS n ions at m /z 425(RDA rearrangement from one heterocicle of the dimer),m /z 407(loss of water from fragment at m /z 425)and m /z 289(epicat-echin,diagnostic fragments at m /z 245,205and 179(Stoggl,Huck,&Bonn,2004)and was identified as procyanidin B1by comparison with literature (Sun,Liang,Bin,Li,&Duan,2007)and spiking experiments with authentic compound.MS/MS analysis of peak 11with a molecular ion at m /z 457showed MS 2ions at m /z 331,169(gallic acid moiety),and 305(deprotonated epigallocatechin).This compound was identified as epigallocatechin gallate (Mark-owicz Bastos et al.,2007)by comparison with an authentic sample.3.4.AnthocyaninsFive known anthocyanins were identified in the fruits,(peaks 9,13,14,17and 19,Fig.3b)with molecular ions in positive modeatcompounds identified in Chilean Luma berries.(a)Tannins,peaks 1,5,6and 7and corresponding fragmentation pattern.(b)Flavonol/glycoside derivatives:peaks 15,16,18,20–31.m/z465,449,479,463and493and showing characteristic MS2 ions at m/z303(MS3ion at m/z257),287(MS3ions at m/z213, 147),317(MS3ion at m/z302),301(MS3ion at m/z286)and 331(MS3ion at m/z299,179)respectively,corresponding to delphinidin3-O-glucoside(k max:275-341sh-512),cyanidin-3-O-glucoside,(k max:278-503),petunidin-3-O-glucoside(k max:275-343sh-512),peonidin-3-O-glucoside,(k max:268-357sh-503),and malvidin-3-O-glucoside(k max:275-343sh-512),respectively.The identity was corroborated by co-elution with standard anthocya-nins and literature data.After extraction and SPE method the recovery of an external standard compound(pelargonidin)was 97±7%by HPLC.3.5.Flavonol derivativesPeaks15,16,18,20–31were identified asflavonol derivatives since the shape of the UV spectra were similar to those reported (Mabry,Markham,&Thomas,1970;Simirgiotis,Caligari,et al., 2009;Simirgiotis,Theoduloz,et al.,2009;Sun et al.,2007).The linkages of gallic acid moieties for the3-O-acylatedflavonols were located in position600of the sugar hydroxyl by characteristic MS fragmentation(Ferreres et al.,2008).MS–MS analysis of all of those compounds showed characteristic ions at m/z179and151(Fig.3c) which were confirmed to be produced by RDA rearrangement of 5,7-dihydroxy-flavon-3-ols such quercetin,isorhamnetin and myricetin using deuterium labelling experiments(McNab,Ferreira, Hulme,&Quye,2009).Peaks16,18(Fig3c)and22showed similar UV spectra and[MÀH]Àions at m/z449,479and463respectively all yielding a MS2daugther ion at m/z317(myricetin)and were tentatively identified as myricetin3-O-pentose,3-O-hexose and 3-O-rhamnose(Michodjehoun-Mestres et al.,2009).Peak24with a MW494(full ESI–MS main peak:493U,Fig.3c)was tentatively identified as a methyl-myricetin hexoside derivative(laricitrin derivative).Aflavonol derivative with a[MÀH]Àion of493U was identified as quercetin3-methoxy-hexoside in blueberries (Cho,Howard,Prior,&Clark,2005).However,MS–MS data of com-pound27is in agreement with laricitrin3-O-hexose(Castillo-Muñoz et al.,2009)or myricetin30methyl ether-3-O-hexose (Min et al.,2010).Further fragmentation of the ion at m/z493 yielded an ion at m/z331(laricitrin,or myricetin50methyl ether), which in turn,yielded an ion at m/z316(myricetin-2H).In the same manner,compound21with UV spectral data of255,293, 358nm and a[MÀH]Àion at645(Fig.3c,MS n ions at493and 331U)was tentatively identified as myricetin50methyl ether-(600 galloyl)3-O-hexose(Min et al.,2010).Full scan MS main peak for compound28(m/z477[MÀH]À) was consistent with the molecular formula C22H22O12.MS–MS fragmentation pattern(Fig3c,MS2315U and MS3300U)was coin-cident with that reported for isorhamnetin-3-O-glucoside(Gutzeit, Wray,Winterhalter,&Jerz,2007).In the same manner,peak25 was characterised as isorhamnetin-3-O-(600-O-galloyl)-glucose (Fig.3c)and peak31was characterised as the aglycon isorhamne-tin since it showed the characteristic UV spectra and has an [MÀH]Àion at m/z315consistent with a molecular anionof Fig.2.(continued)。

General Notices apply to all monographs and other texts.See the information section on general monographs .01/2022:2631ROSUVASTATIN CALCIUMRosuvastatinum calcicumC H CaF N O S M 1001[147098-20-2]DEFINITIONCalcium bis[(3R ,5S ,6E )-7-[4-(4- uorophenyl)-2-(N -methylmethanesulfonamido)-6-(propan-2-yl)pyrimidin-5-yl]-3,5-dihydroxyhept-6-enoate].Content : 97.0 per cent to 102.0 per cent (anhydrous substance).CHARACTERSAppearance : white or almost white, hygroscopic powder.Solubility : slightly soluble in water, freely soluble in methylene chloride, practically insoluble in anhydrous ethanol.IDENTIFICATIONA.Infrared absorption spectrophotometry (2.2.24).Comparison : rosuvastatin calcium CRS .B.Enantiomeric purity (see Tests).C.It gives reaction (b) of calcium (2.3.1).TESTSEnantiomeric purity . Liquid chromatography (2.2.29). Carry out the test protected from light.Solvent mixture : acetonitrile R , water R (25:75 V/V ).Test solution . Dissolve 25.0 mg of the substance to be examined in 6 mL of acetonitrile R and dilute to 25.0 mL with water R .Reference solution (a). Dilute 1.0 mL of the test solution to 100.0 mL with the solvent mixture. Dilute 1.0 mL of this solution to 10.0 mL with the solvent mixture.Reference solution (b). Dissolve the contents of a vial of rosuvastatin impurity G CRS in 1 mL of the test solution.Column :–size : l = 0.15 m, Ø = 4.6 mm;–stationary phase : cellulose derivative of silica gel for chiral separation R (5 µm);–temperature : 35 °C.445426122rMobile phase : acetonitrile for chromatography R , 0.1 per cent V/V solution of tri uoroacetic acid R (25:75 V/V ).Flow rate : 0.5 mL/min.Detection : spectrophotometer at 242 nm.Injection : 10 µL.Run time : 2.6 times the retention time of rosuvastatin.Identi cation of impurities : use the chromatogram obtained with reference solution (b) to identify the peak due to impurity G.Relative retention with reference to rosuvastatin (retention time = about 29 min): impurity G = about 0.9.System suitability : reference solution (b):–resolution : minimum 1.5 between the peaks due to impurity G and rosuvastatin.Calculation of percentage content :–for impurity G, use the concentration of rosuvastatin calcium in reference solution (a).Limit :–impurity G : maximum 0.15 per cent.Impurity L . Liquid chromatography (2.2.29). Carry out the test protected from light.Solvent mixture : acetonitrile R , water R (50:50 V/V ).Test solution . Dissolve 20.0 mg of the substance to be examined in 50 mL of acetonitrile R and dilute to 100.0 mL with water R .Reference solution (a). Dissolve 5 mg of rosuvastatin for impurity L identi cation CRS in 10 mL of acetonitrile R and dilute to 20 mL with water R .Reference solution (b). Dilute 1.0 mL of the test solution to 100.0 mL with the solvent mixture. Dilute 1.0 mL of this solution to 10.0 mL with the solvent mixture.Column :–size : l = 0.15 m, Ø = 4.6 mm;–stationary phase : end-capped solid core octylsilyl silica gel for chromatography R (2.7 µm).Mobile phase : to 650 mL of a 0.02 per cent V/V solution of tri uoroacetic acid R , add 350 mL of a mixture of 1 volume of ethanol (96 per cent) R and 2 volumes of acetonitrile for chromatography R .Flow rate : 0.7 mL/min.Detection : spectrophotometer at 243 nm.Injection : 10 µL.Run time : 3 times the retention time of rosuvastatin.Identi cation of impurities : use the chromatogram supplied with rosuvastatin for impurity L identi cation CRS and the chromatogram obtained with reference solution (a) to identify the peak due to impurity L.Relative retention with reference to rosuvastatin (retention time = about 22 min): impurity L = about 1.1.System suitability : reference solution (a):–peak-to-valley ratio : minimum 2.5, where H = height above the baseline of the peak due to impurity L and H = height above the baseline of the lowest point of the curve separating this peak from the peak due to rosuvastatin.Calculation of percentage content :–correction factor : multiply the peak area of impurity L by 1.8;–for impurity L, use the concentration of rosuvastatin calcium in reference solution (b).Limit :–impurity L : maximum 0.15 per cent.Related substances . Liquid chromatography (2.2.29). Carry out the test protected from light and prepare the solutions immediately before use.Solvent mixture : acetonitrile R , water R (25:75 V/V ).Test solution . Dissolve 35.0 mg of the substance to be examined in 12 mL of acetonitrile R and dilute to 50.0 mL with water R .Reference solution (a). Dissolve 35.0 mg of rosuvastatin calcium CRS in 12 mL of acetonitrile R and dilute to 50.0 mL with water R .Reference solution (b). Dilute 1.0 mL of the test solution to 100.0 mL with the solvent mixture. Dilute 1.0 mL of this solution to 10.0 mL with the solvent mixture.p vReference solution (c). Dissolve 7 mg of rosuvastatin for system suitability CRS (containing impurities A, B and C) in 2.5 mL of acetonitrile R and dilute to 10 mL with water R.Reference solution (d). Dissolve the contents of a vial of rosuvastatin impurity mixture CRS (impurities D and K) in 1 mL of the solvent mixture.Reference solution (e). Dissolve 7 mg of rosuvastatin for peak identi cation CRS (containing impurity M) in 2.5 mL of acetonitrile R and dilute to 10 mL with water R.Column:–size: l = 0.15 m, Ø = 3.0 mm;–stationary phase: base-deactivated end-capped octadecylsilyl silica gel for chromatography R (3 µm);–temperature: 40 °C.Mobile phase:–mobile phase A: 1 per cent V/V solution of tri uoroacetic acid R, acetonitrile for chromatography R, water for chromatography R (1:29:70 V/V/V);–mobile phase B: 1 per cent V/V solution of tri uoroacetic acid R, water for chromatography R, acetonitrile for chromatography R (1:24:75 V/V/V);Time (min)Mobile phase A(per cent V/V)Mobile phase B(per cent V/V)0 - 30100030 - 50100 → 600 → 4050 - 6060 → 040 → 10060 - 700100Flow rate: 0.75 mL/min.Detection: spectrophotometer at 242 nm.Injection: 10 µL of the test solution and reference solutions (b), (c), (d) and (e).Identi cation of impurities: use the chromatogram supplied with rosuvastatin for system suitability CRS and the chromatogram obtained with reference solution (c) to identify the peaks due to impurities A, B and C; use the chromatogram supplied with rosuvastatin impurity mixture CRS and the chromatogram obtained with reference solution (d) to identify the peaks due to impurities D and K; use the chromatogram supplied with rosuvastatin for peak identi cation CRS and the chromatogram obtained with reference solution (e) to identify the peak due to impurity M.Relative retention with reference to rosuvastatin (retention time = about 25 min): impurity M = about 0.8; impurity A = about 0.9; impurity B = about 1.1; impurity C = about 1.5; impurity D = about 1.9; impurity K = about 2.0.System suitability: reference solution (c):–resolution: minimum 2.0 between the peaks due to rosuvastatin and impurity B.Calculation of percentage contents:–correction factor: multiply the peak area of impurity C by 1.4;–for each impurity, use the concentration of rosuvastatin calcium in reference solution (b).Limits:–impurity C: maximum 0.8 per cent;–impurity B: maximum 0.5 per cent;–impurity A: maximum 0.2 per cent;–impurities D, K, M: for each impurity, maximum 0.15 per cent;–unspeci ed impurities: for each impurity, maximum 0.10 per cent;–total: maximum 1.2 per cent;–reporting threshold: 0.05 per cent.Water (2.5.12): maximum 6.1 per cent, determined on 0.100 g.ASSAYLiquid chromatography (2.2.29) as described in the test for related substances with the following modi cation. Injection: test solution and reference solution (a).Calculate the percentage content of C H CaF N O S taking into account the assigned content of rosuvastatin calcium CRS .STORAGEIn an airtight container, protected from light, at a temperature of 2 °C to 8 °C.IMPURITIESSpeci ed impurities: A, B, C, D, G, K, L, M.Other detectable impurities (the following substances would, if present at a su cient level, be detected by one or other of the tests in the monograph. They are limited by the general acceptance criterion for other/unspeci ed impurities and/or by the general monograph Substances for pharmaceutical use (2034). It is therefore not necessary to identify these impurities for demonstration of compliance. See also 5.10. Control of impurities insubstances for pharmaceutical use ): E, F, J , N .A.(3R ,5S,6E )-7-[2-(2,N -dimethyl-2-hydroxypropane-1-sulfonamido)-4-(4- uorophenyl)-6-(propan-2-yl)pyrimidin-5-yl]-3,5-dihydroxyhept-6-enoic acid,B.(3RS ,5RS ,6E )-7-[4-(4- uorophenyl)-2-(N -methylmethanesulfonamido)-6-(propan-2-yl)pyrimidin-5-yl]-3,5-dihydroxyhept-6-enoic acid,C.(3R ,6E )-7-[4-(4- uorophenyl)-2-(N -methylmethanesulfonamido)-6-(propan-2-yl)pyrimidin-5-yl]-3-hydroxy-5-oxohept-6-enoic acid,445426122D.N-[4-(4- uorophenyl)-5-[(1E)-2-[(2S,4R)-4-hydroxy-6-oxooxan-2-yl]ethen-1-yl]-6-(propan-2-yl)pyrimidin-2-yl]-N-methylmethanesulfonamide,E.(3R,5S,6E)-7-[4-(4- uorophenyl)-2-[(2Ξ)-2-[4-(4- uorophenyl)-2-(N-methylmethanesulfonamido)-6-(propan-2-yl)pyrimidin-5-yl]-2-hydroxy-N-methylethane-1-sulfonamido]-6-(propan-2-yl)pyrimidin-5-yl]-3,5-dihydroxyhept-6-enoic acid,F.tert-butyl[(4R,6S)-6-[(1E)-2-[4-(4- uorophenyl)-2-(N-methylmethanesulfonamido)-6-(propan-2-yl)pyrimidin-5-yl]ethen-1-yl]-2,2-dimethyl-1,3-dioxan-4-yl]acetate,G.(3S,5R,6E)-7-[4-(4- uorophenyl)-2-(N-methylmethanesulfonamido)-6-(propan-2-yl)pyrimidin-5-yl]-3,5-dihydroxyhept-6-enoic acid,J.(3R,5S,6E)-7-[4-(4- uorophenyl)-2-[(1E)-2-[4-(4- uorophenyl)-2-(N-methylmethanesulfonamido)-6-(propan-2-yl)pyrimidin-5-yl]-N-methylethene-1-sulfonamido]-6-(propan-2-yl)pyrimidin-5-yl]-3,5-dihydroxyhept-6-enoic acid,K.( 2Z ,5S,6E)-7-[4-(4- uorophenyl)-2-(N-methylmethanesulfonamido)-6-(propan-2-yl)pyrimidin-5-yl]-5-hydroxyhepta-2,6-dienoic acid,L.(3Ξ,5Ξ)-7-[4-(4- uorophenyl)-2-(N-methylmethanesulfonamido)-6-(propan-2-yl)pyrimidin-5-yl]-3,5-dihydroxyheptanoic acid,M.(3R,5S,6E)-7-[2-(N-methylmethanesulfonamido)-4-phenyl-6-(propan-2-yl)pyrimidin-5-yl]-3,5-dihydroxyhept-6-enoic acid ,N.(2E,5S,6E)-7-[4-(4- uorophenyl)-2-(N-methylmethanesulfonamido)-6-(propan-2-yl)pyrimidin-5-yl]-5-hydroxyhepta-2,6-dienoic acid.。

ORIGINAL PAPERLow Frequency Pulsed Electromagnetic Field AffectsProliferation,Tissue-Specific Gene Expression,and Cytokines Release of Human Tendon CellsL.de Girolamo •D.Stanco •E.Galliera •M.Vigano`•A.Colombini •S.Setti •E.Vianello •M.M.Corsi Romanelli •V.SansonePublished online:24January 2013ÓSpringer Science+Business Media New York 2013Abstract Low frequency pulsed electromagnetic field (PEMF)has proven to be effective in the modulation of bone and cartilage tissue functional responsiveness,but its effect on tendon tissue and tendon cells (TCs)is still underinves-tigated.PEMF treatment (1.5mT,75Hz)was assessed on primary TCs,harvested from semitendinosus and gracilis tendons of eight patients,under different experimental conditions (4,8,12h).Quantitative PCR analyses were conducted to identify the possible effect of PEMF on ten-don-specific gene transcription (scleraxis,SCX and type I collagen,COL1A1);the release of pro-and anti-inflam-matory cytokines and of vascular endothelial growth factor(VEGF)was also assessed.Our findings show that PEMF exposure is not cytotoxic and is able to stimulate TCs’proliferation.The increase of SCX and COL1A1in PEMF-treated cells was positively correlated to the treatment length.The release of anti-inflammatory cytokines in TCs treated with PEMF for 8and 12h was significantly higher in comparison with untreated cells,while the production of pro-inflammatory cytokines was not affected.A dramati-cally higher increase of VEGF-A mRNA transcription and of its related protein was observed after PEMF exposure.Our data demonstrated that PEMF positively influence,in a dose-dependent manner,the proliferation,tendon-specific marker expression,and release of anti-inflammatory cytokines and angiogenic factor in a healthy human TCs culture model.Keywords Tendon ÁTendon cells ÁPulsed electromagnetic field ÁTendon specific markers ÁAnti-inflammatory cytokines ÁVascular endothelial growth factorsIntroductionThe aim of this study is to evaluate the in vitro effects of a specific low frequency pulsed electromagnetic field (PEMF)on primary human tendon resident cells (TCs)to shed light on the biologic response of tendons to bio-physical stimulation,providing new evidence on the effectiveness of PEMF for the treatment of tendon disor-ders.Our results show that PEMF does not affect viability of TCs,but it is able to modulate their immune and angiogenic response and to stimulate TCs proliferation and tendon-specific gene transcription.Among biophysical therapeutic modalities,electromag-netic stimulation has been studied extensively.Despite itL.de Girolamo (&)ÁD.Stanco ÁE.Galliera ÁM.Vigano`Orthopaedic Biotechnologies Lab,IRCCS Istituto Ortopedico Galeazzi,Via R.Galeazzi,4,20161Milan,Italy e-mail:laura.degirolamo@grupposandonato.itE.GallieraDipartimento di Scienze Biomediche,Chirurgiche edOdontoiatriche,Universita`degli Studi di Milano,Milan,Italy A.ColombiniLaboratory of Experimental Biochemistry and Molecular Biology,IRCCS Istituto Ortopedico Galeazzi,Milan,Italy S.SettiIGEA SpA,Clinical Biophysics,Carpi,ItalyE.Vianello ÁM.M.Corsi Romanelli ÁV.SansoneDipartimento di Scienze Biomediche per la Salute,Universita`degli Studi di Milano,Milan,ItalyM.M.Corsi RomanelliIRCCS Policlinico San Donato,San Donato Milanese,Italy V.SansoneOrthopaedic Department,IRCCS Istituto Ortopedico Galeazzi,Milan,ItalyCell Biochem Biophys (2013)66:697–708DOI 10.1007/s12013-013-9514-yhas been demonstrated that they can be a successful adju-vant therapy,above all in the management of bone and cartilage disorders[1–8],all available reviews agree on the fact that the biophysical interactions between these low-energy signals and biologic tissues are still not completely understood[5,9].However,the most recognized results suggest that external electromagnetic stimuli interact with cells either via transmembrane receptors or ion channels, thereby initiating one or more signal transduction cascades or cell functions[10,11].In particular,as demonstrated by Brighton et al.[12],PEMF determines signal transduction through the intracellular release of Ca2?leading to an increase in cytosolic Ca2?and an increase in activated cytoskeletal calmodulin.Through this mechanism,PEMF modifies some important physiologic parameters of cells, such as proliferation,transduction,transcription,synthesis, and secretion of growth factors[10,13].It has been already shown that PEMF exposure is able to induce cell prolif-eration and a dose-dependent increase in bone differentia-tion and upregulation of mRNA expression of specific extracellular matrix molecules in human osteoblasts[14, 15].Similarly,in vitro studies on cartilage have demon-strated that PEMF is able to stimulate chondrocyte prolif-eration[16]and to modulate production and release of cytokines and growth factors like IL-1b and insulin-like growth factor-I[17–19].On the contrary,few and sometimes conflicting studies on the effect of PEMFs on tendons have been conducted; most of them are in vivo and demonstrate that PEMF treated groups show better collagen alignment,a greater reduction of inflammation,with a better return of tendons to histologic normality,thus suggesting a positive influence of PEMF on tendon healing[20].Indeed,in a manner similar to bone and wound repair,tendon repair involves an inflammatory phase,angiogenesis,cell proliferation,col-lagen production,and remodelling stages,intrinsically via proliferation of epitenon and endotenon tenocytes,or extrinsically,by invasion of cells from the surrounding sheath and synovium[20].So,in vitro studies exploring the effects of PEMF on human tenocytes would help in the comprehension of the possible mechanisms of action of this treatment.It is known that tendon tissue is poorly cellularized(5%of the normal tendon tissue volume). These few tendon resident cells(TCs)represent a mixed population,made up mostly by tenocytes and tendon stem/ progenitor cells,which together are responsible for the tissue homeostasis[21,22],for the production and the remodelling of the abundant and strictly organized extra-cellular matrix.To our knowledge,only one study describing the behavior of tenocytes after long and con-tinuous PEMF exposure has been published[23].In this study,authors used a peculiar in vitro wound closure assay, investigating the effects of PEMF(0.4mT,frequency 50Hz)on the speed of wound closure.Our study aims to provide a more detailed analysis of the in vitro effect of PEMF with specific physical parameters,already used in clinical practice(1.5mT,frequency75Hz),on the resident tendon cell clonogenic ability,viability,proliferation,and on the gene expression of specific tendon markers,such as SCX and COL1A1.Moreover,we have investigated the release of pro-and anti-inflammatory cytokines to evaluate the feasibility of activating an anti-inflammatory pathway. Since it has been recently demonstrated that vascular endothelial growth factor(VEGF)has a fundamental role in the tendon healing process,we have evaluated its release by PEMF-treated cells and compared it to untreated cells. Although Denaro et al.[23]showed positive results starting from12h of PEMF exposure,we chose to treat cells also for shorter periods since other studies,even if concerning other cellular models[24,25]showed the efficacy of PEMF already after4–8h.All the experiments have been performed on eight dif-ferent cell populations isolated from small portions of the healthy semitendinosus and gracilis tendons of eight patients who had undergone anterior cruciate ligament (ACL)reconstruction at our Institute.Materials and MethodsTCs Isolation and Culture ExpansionAll the procedures were carried out with the Institutional Review Board approval.Discarded fragments of semiten-dinosus and gracilis tendons were collected from8healthy young donors(mean age35±12years;mean body mass index24±1)who underwent ACL reconstruction with autologous hamstrings at Galeazzi Orthopaedic Institute, Milan,under written consent.To isolate tendon cells(TCs), the tendon tissue was minced and digested enzymatically with0.3%type I collagenase(Worthington,Lakewood, NJ,USA)in DMEM(Sigma-Aldrich,St.Louis,MO,USA) with continuous agitation for15h at37°C as reported by Rui et al.[22]with minor modifications.The isolated nucleated cells were then plated at59103cells/cm2in complete medium composed of:DMEM,10%fetal bovine serum(FBS;Sigma-Aldrich),50U/ml Penicillin,50l g/ml Streptomycin,2mM L-glutamine(Sigma-Aldrich),and supplemented with5ng/ml basicfibroblast growth factor (b-FGF;Peprotech,Rocky Hill,NJ,USA)just for cell expansion.They were maintained at37°C in humidified atmosphere with5%CO2,changing culture medium every 3days.TCs remained quiescent for several days before starting to proliferate rapidly;when they reached80–90% of confluence,the cells were detached by incubation with trypsin/EDTA(0.5%trypsin/0.2%EDTA;Sigma-Aldrich)and then cultured at a density of39103cells/cm2.Cells from passages2–4(P2–P4)were used for the experiments. Fibroblast Colony-Forming Unit AssayA colony-forming unitfibroblast(CFU-F)assay was per-formed as previously described[26].TCs were plated in six-well plates at low density by limiting dilution(starting dilution:10cells/cm2,final dilution: 1.5cells/cm2)and cultured for14days.After7days the medium was replaced,and at the end of the culture period the cells were fixed with10%paraformaldehyde and stained with Crystal Violet(Sigma-Aldrich).The frequency of CFU-F was established by scoring the individual colonies composed of at least50cells and expressed as a percentage relative to the seeded cells.PEMF StimulationThe TCs were exposed to PEMF generated by a pair of rectangular horizontal coils(18913cm),each made of1,000turns of copper wire,placed opposite each other.The cultureflask was placed between this pair of coils so that the plane of the coils was parallel to the cultureflasks, directly inside the incubator(Fig.1).The coils were powered by a PEMF generator system(IGEA,Carpi,Italy) already used in previous studies[17,19,27,28].This produced a pulsed signal with the following parameters: pulse duration of1.3ms and frequency of75Hz,yielding a0.1duty cycle.Before starting the experiments,the peak intensity of the magneticfield and the peak intensity of the induced electric voltage were measured in air between two coils from one side to the other,at the level of the culture flasks.The peak values measured between two coils in air had a maximum variation of1%in the whole area in which the cultureflasks were placed.The peak intensity of the magneticfield was1.5±0.2mT and it was detected using the Hall probe(HTD61-0608-05-T,F.W.Bell,Sypris Solutions,Louisville,KY,USA)of a gaussmeter(DG500, Laboratorio Elettrofisico,Milan,Italy)with a reading sensitivity of0.2%.The corresponding peak amplitude of the induced electric voltage was 2.0±0.5mV.It was detected using a standard coil probe(50turns,0.5-cm internal diameter of the coil probe,0.2-mm copper diam-eter)and the temporal pattern of the signal was displayed using a digital oscilloscope(Le Croy,Chestnut Ridge,NY, USA).The shape of the induced electric voltage and its impulse length were kept constant.Passage4cells were seeded intoflasks or multiwells the day before starting the PEMF treatment.They were exposed to PEMF for4,8,or12h,under the same con-ditions of temperature,humidity,and CO2concentration as the untreated cells and then analyzed.Live and Dead AssayA live/dead assay was performed on the untreated and treated cells,seeded at a density of105cells/cm2in24-well plate, after4,8,and12h of PEMF exposure.The cell culture medium was removed and a solution containing2l M cal-cein and4l M ethidium homodimer-1(Invitrogen,Ltd., Paisley,UK)was added to each sample.The cells were then observed byfluorescence microscopy(Microscope OLYM-PUS IX71).Live cells stained green and dead cells red.The percentage of live cells was measured and was defined as PLive=NLive/(NLive?NDead),where NLive is the number of live cells and NDead is the number of dead cells in the same image.Three randomly chosenfields of view were photographed for two sample of each population(n=3). Cell Apoptosis Analysis by Annexin V-FITCand Propidium Iodide(PI)Apoptosis induced by PEMF treatment was analyzed by flow cytometry utilizing annexin V-FITC and PI staining (Sigma-Aldrich).In brief,4.09105cells were trypsini-zed,washed with PBS,and resuspended with500l L of a specific binding buffer containing10l L of PI,and5l L of annexin V-FITC[29,30].After exactly10min of incu-bation in the dark at room temperature,cells were analyzed for annexin V and PI staining byflow cytometry.Each experiment was run in triplicate.Excitation wavelength was488nm and emitted greenfluorescence of annexin V (FL-1)and redfluorescence of PI(FL-2)were collected using,respectively,a525and a575nm band passfilter. Early apoptosis and late apoptosis/necrosis wereexpressed Fig.1Pulsed electromagneticfield device used for all the experi-ments,placed in a5%CO2and37°C incubator.TCs seeded in T25 cultureflasks(like in the picture)or in24-well plates were placed between the pair of coils so that the plane of the coils was parallel to the culture layer.The peak values measured between the two coils in air had a maximum variation of1%in the whole area in which the cultureflasks were placed.Cell were exposed to PEMF for4,8or 12has the percentages of annexin V?/PI-and annexin V?/PI?positive cells.Viability and Proliferation AssayTCs at passage4were plated at a concentration of 1.59104cells/cm2in complete medium in96-well plates and then exposed to PEMF,according to the experimental protocol.Both untreated and treated cells were monitored immediately after exposition(0day)and after2,7,and 10days(2,7,and10days),adding MTT(3-[4,5-dimeth-ylthiazol-2-yl]-2,5-diphenyltetrazolium bromide,Sigma-Aldrich)in the culture medium at afinal concentration of 0.5mg/ml and incubated for4h at37°C.The resulting formazan precipitate was then solubilized using100% DMSO and the absorbance was read at570nm(VictorX3, Perkin Elmer microplate,Waltham,MA,USA)[31]. Similarly, 5.09103TCs/cm2were placed in24-well plates and received an identical PEMF treatment.At the same time points,they were analyzed for the DNA content (Triton X-1000.1%in ddH2O as lysis buffer)using the CyQUANTÒCell Proliferation Assay Kit(Invitrogen, Ltd.);fluorescence was read at520nm(excitation k=480nm)(VictorX3,Perkin Elmer microplate).RNA Extraction,RT,and Real-Time PCRTotal RNA was isolated from the untreated cells and from the cells exposed for4,8,and12h to PEMF using the RNeasy Mini kit(Qiagen,Duesseldorf,Germany)and the isolated RNA was quantified spectrophotometrically (Nanodrop,Thermo Scientific,Rockford,IL,USA).100ng of RNA were reverse-transcripted to cDNA employing the iScriptcDNA Synthesis Kit(Bio-Rad Laboratories,Beni-cia,CA,USA).Thefinal volume of20l L included a59reaction mix containing oligo(dT),random hexamer primers,and reverse transcriptase pre-blended with RNase inhibitor. The reaction mix was incubated for5min at25°C,30min at42°C,and5min at85°C.10ng of cDNA was used as a template for real-time PCR, performed using a Rotor Gene RG3000system(Qiagen).The PCR mixture included TaqMan Universal PCR Master Mix and Assays-on-Demand Gene expression probes(Life Tech-nologies,Grand Island,NY,USA)in afinal volume of20l L. Amplification and real-time data acquisition were performed using the following cycle conditions:2min at50°C,10min at95°C,followed by40cycles of15s at95°C,and1min at 60°C.The genes analyzed were glyceraldehydes-3-phos-phate dehydrogenase(GAPDH)(Hs99999905_m1),SCX (Hs03054634_g1),COL1A1(Hs01076777_m1),and vascu-lar endothelial growth factor A(VEGF-A)(Hs00900055_m1). The fold change in the expression of the different genes in the control and treated cells was normalized on the expression of the housekeeping GAPDH gene.Cytokines and VEGF DeterminationLevels of soluble IL-1b,IL-6,IL-10,TNF-a,TGF b,and VEGF-A in cell culture medium after0,24,and48h from the end of PEMF treatment were determined by commer-cially available ELISA assays according to the manufac-turers’instructions(R&D System,Minneapolis,MN, USA).For VEGF detection assay,the sensitivity of the test was5pg/ml;intra-and inter-assay coefficients of variation were 6.6and 6.7%,respectively.For IL-1b detection assay,the sensitivity of the test was less than1pg/ml, intra-and inter-assay coefficients of variation were2.8and 4.1%,respectively.For IL-6detection assay,the sensi-tivity of the test was2pg/ml,intra-and inter-assay coef-ficients of variation were5.8and3.1%,respectively.For IL-10detection assay,the sensitivity of the test was less than0.5pg/ml,intra-and inter-assay coefficients of vari-ation were6.6and8.1%,respectively.For TNF-a detec-tion assay,the sensitivity of the test was1.6pg/ml,intra-and inter-assay coefficients of variation were 5.0and 7.3%,respectively.For TGF b detection assay,the sensi-tivity of the test was less than pg/ml,intra-and inter-assay coefficients of variation were2.7and4.3%,respectively. Statistical AnalysisStatistical analysis was performed by GraphPad Prism v5.0 software(GraphPad Software Inc.,La Jolla,CA,USA).All values are expressed as the mean±SD.Normal distribu-tion of values were assayed by Kolmogorov–Smirnov normality test,while one-way Analysis of Variance (ANOVA)for repeated measures,with the Bonferroni’s correction,was used to compare data over time.Paired comparisons were performed by two-tailed t test.In the case of not normally distributed values,repeated measures were compared with the Kruskal–Wallis test with the Dunns’correction.Correlation analysis was performed by the two-tailed Pearson correlation test(Spearman’s test for not normally distributed values);the same test was con-ducted to evaluate the correlation between the trends of these parameters across the time-points.The significance level was set at p value lower than0.05.ResultsExplants of eight human hamstring tendons(1.5±0.6g) were digested and cultured in a cultureflask with growth medium.The average yield of TCs was 4.5±8.59 105cells/g of tissue(n=8).After about10days ofinactivity,where the cell population was not morphologi-cally homogeneous,typical fibroblastoid-like cells began to proliferate actively,forming a compact monolayer.In \4weeks,from an average of 1.99±1.29105at pas-sage 1,the TCs increased to 1.02±0.299107at passage 4(Fig.2a).The mean doubling time of the TCs slightly increased with the passage in culture,starting from 64±27h at passage 2to 97±28h at passage 4(Fig.2b).CFU-F assay showed that an average of 12.8±10.8%of P3cells were able to produce colonies;this ability slightly decreased with passage in culture (P4:6.4±7.4%)(Fig.2b).Effect of PEMF on Viability and DNA ContentThe cells at passage 4were exposed to PEMF for 4,8,or 12h and then analyzed.Regardless of the length of treatment they received,the cells did not change their morphology and remained viable when compared to the untreated cells (Fig.3).Similarly,no differences in apoptosis between the control and the treated cells were detected (Fig.4).TCs viability was slightly affected by PEMF stimula-tion;in particular,12h of exposure was able to produce mild,not significant increases (?17%)in viability when compared to the untreated cells,2days after treatment.Shorter PEMF treatment (4and 8h)did not affect TCs viability (Fig.5).Eight hours of PEMF treatment provoked a prompt significant increase of the TCs total DNA content (?22%,p =0.020)immediately after treatment (day 0).Analyses performed at the following time points (2and 7days)showed more pronounced effects,although notsignificant,in cells treated with PEMF for 12h,as already observed for the viability parameter (Fig.5),while shorter treatments didn’t affect DNA content at these time points.However,the effect of PEMF on cell viability and DNA content progressively decreased as the time from the expo-sure increased,and at 10days no effects were observed,probably because cells reached 100%confluence.Effect of PEMF on Gene ExpressionThe expression of transcripts of SCX,collagen I (COL1A1)and (VEGF-A)was determined by real-time PCR at two time points (0and 2days from the end of the treatment).The fold change in the different gene expression in the treated and untreated TCs was normalized on the expression of the GAPDH gene.Immediately after the treatment (day 0),the SCX up-regulation was clearly dependent on the length of PEMF treatment:the TCs treated for 4h showed a mild increase with respect to the untreated cells (?25%);this effect was then more pronounced in cells treated for 8h (?58%)and 12h (?95%,p =0.0156)(Fig.6).The same trend was observed for COL1A1expression,where 4,8,and 12h of treatment were able to induce increases of 22,49,and 97%,respectively,although,due to the interdonor vari-ability,this effect was not statistically significant (Fig.6).Both SCX and collagen I expression in PEMF-treated cells remained slightly upregulated 2days after the end of the exposure (day 2),even if these increases were not statistically significant (Fig.6).VEGF-A expression of TCs was also upregulated by PEMF at day 0,but the increases were statistically significant only after 8and 12h of exposure (?41%,p =0.0187for 8h;?34%,p =0.0303for 12h)(Fig.6).On the other hand,at day 2VEGF-A expression of all the PEMF-treated cells returned to basal level (Fig.6).Effect of PEMF on Cytokine ReleaseCytokines and growth factors were assayed in the condi-tioned medium of cells exposed for 8and 12h to PEMF.IL-1b and TNF a levels were greatly variable among the dif-ferent cell populations.Both IL-1b and TNF a were not significantly affected by the treatments (both 8and 12h)at all the time points (day 0,1,and 2)with the exception of a small,although significant,increase observed for IL-1b after one day after 12h PEMF treatment (Fig.7).On the contrary,the release in the culture medium of IL-6by both the cells exposed to 8and to 12h was significantly higher compared to the control cells,starting from day 1and especially at day 2(360%,p \0.001for 8h;427%and p \0.001for 12h,respectively)(Fig.7).IL-10production was also strongly upregulated by PEMF:already at day 1,the levels were significantly increased both for theTCsFig.2Features of human TCs used in the experiments.Proliferation ability,expressed as number of cells (a )and average doubling time (b )during passages in culture.Percentage of clonogenic TCs at passage 3and 4(b ).Data are expressed as mean ±SD.For all data,n =8treated for 8and 12h (133and 191%,p \0.001,respec-tively)and this effect was maintained until day 2for both treatments (162%for 8h and 197%for 12h,p \0.001)(Fig.7).The increase of TGF-b concentration in medium was faster and more evident:the differences between trea-ted and untreated TCs progressively increased,starting immediately after treatment and showing a more than 11-fold increase both for the 8and 12h treated cells after 2days (p \0.001)(Fig.7).No significant difference in IL-6,IL-10,or TGF-b was observed between the TCs treated with PEMF for 8or 12h.The same scenario was observed for VEGF-A,which immediately after the PEMF treatment (day 0)was released in a significantly higher amount by cells treated both for 8and 12h,compared to untreated cells.This difference accelerated over time with more than 60-and 90-fold increases observed both for 8and 12h treated cells after1Fig.3Morphology of untreated cells and of cells exposed to PEMF for different duration (4,8,or 12h)(optical microscopy 910,scale bar 200l m)(upper panel );Live and Dead staining for viable (green )and dead cells (red )in treated and untreated cells (fluorescencemicroscopy,910,scale bar 200l m,merged images).Percentages in pictures report rates of viable cells indicated as mean ±SD (n =3)(Color figureonline)Fig.4Apoptosis analysis by flow cytometry at day 2of untreated and treated cells after 12h of PEMF exposure.Cells were detected using annexin V-FITC and PI probes.Cell populations FITC -/PI -(Q3),FITC ?/PI -(Q4),and FITC ?/PI ?(Q2),FITC -/PI ?(Q1)were living,early apoptotic,and late apoptotic/necrotic cells and necrotic cells,respectively (n =3)Fig.5Effect of PEMF exposure on cell viability (a )and DNA content of TCs after 0,2,7,and 10days (b ).Values are indicated as fold increase respect to untreated cells represented by a fixed line setat 1;data are expressed as mean ±SD.*p \0.05,PEMF-treated cells versus untreated cells,n =8Fig.6Effect of PEMFexposure on scleraxis (SCX),collagen type I (COL1A1),and vascular endothelial growth factor A (VEGF-A)gene expression,determined by quantitative real-time PCR at day 0and day 2from the end of treatment,both in untreated and treated TCs.Data werenormalized on the expression of the housekeeping GAPDH gene and are expressed asmean ±SD.*p \0.05,PEMF 12-h treated cells versus untreated cells,n =8and 2days,respectively (p \0.001),but without any sig-nificant differences between the two groups of treated cells (Fig.7).DiscussionThe major finding of our paper is that 8-h PEMF exposure (1.5mT,75Hz)is able to induce the modulation of TCs’proliferation,tendon-specific marker expression,and the release of anti-inflammatory cytokines and angiogenic factor.Over the last decades,extensive in vitro,pre-clinical,and clinical researches have revealed some insights into thebiologic effects of electromagnetic stimulation and the effectiveness of PEMFs treatment in bone and joint dis-orders.However,most of these studies lack homogeneity since they present a high variability in terms of magnetic flux density (the component of the magnetic field passing through a surface),signal type,frequency,duration,and the number of treatment sessions [20,23,32,33].In our study,we used the same parameters of pulsed electromagnetic field that was used in other ones,which showed that this extremely low frequency PEMF (1.5mT,75Hz)was able to stimulate anabolic processes and limit IL-1b catabolic effects in chondrocytes and cartilage explants [17,19]and,to enhance the proliferation and the tissue-specific marker expressions in osteoblasts [14,34,35].Moreover,asshownFig.7Release of cytokines and VEGF-A in cell culture medium of untreated and treated TCs (PEMF 8and 12h),after 0,1,and 2days from the end of the treatment.Data are expressed as mean ±SD.***,p \0.001PEMF 8-h treated cells versus untreated cells.§,p \0.05;§§§,p \0.001PEMF 12-h treated cells versus untreated cells,n =8in preclinical studies,these parameters of PEMF preserve the morphology of articular cartilage and retard the development of osteoarthritic lesions in guinea pigs[1]. Finally,in humans,this stimulation positively affected the recovery after surgical procedures of the knee by reducing the joint inflammation[36,37].Despite all these extensive researches,this is one of thefirst studies which aimed to investigate the possible effects of PEMF on TCs.Since mechanostimuli play an essential role in tendon homeo-stasis,tendon healing,and tenocyte survival[38,39],it is interesting to evaluate the mechanoresponsiveness of TCs to biophysical stimuli.Resident cells make up around only 5%of the normal tendon tissue volume;this scarcity is confirmed by the low yield of cells from tendon digestion that we obtained from our experiments.Recently,stem cells have been discovered in human and mouse tendon tissue(TSPCs,tendon stem progenitor cells);they exhibit universal stem cell characteristics,including clonogenicity, self-renewal,and multi-lineage differentiation capacities, even after extended expansion in vitro[21,22].In partic-ular,human hamstring tendons contain3–4%of TSPCs with respect to the total nucleated cells[21].Since we did not use any specific methods to select only tenocytes,our experiment was conducted on a non-homogeneous cell population,which probably better reflects the physiologic tendon cell environment.The presence of a subpopulation of tendon stem cells could explain the high proliferation rate and the corresponding short doubling time that we observed in our experiment,together with a consistent percentage of clonogenic cells in our cell cultures(12%).PEMF exposure did not exert any cytotoxic effects on TCs,as demonstrated by the absence of apoptotic cells and the similarity in terms of viability of treated cells from untreated ones.Immediately after treatment,a significant increase in DNA content of8-h PEMF-treated cells was observed;this result is particularly important since PEMF treatment could be able to stimulate cell proliferation with a consequent positive effect on tendon recovery.However, this effect on cell proliferation was very short-lasting, probably also due to the experimental model where cells progressively reached100%confluence and were not able to further grow.In any case,regardless of the length of exposure,the effect on viability and DNA content lasted for a week at most,thus suggesting that repeated daily PEMF exposures could be probably necessary to achieve a durable result.For this reason,it would be interesting to re-treat the same cells to assess if this is able to prolong or enhance the observed effects.It is important to note that 4h of treatment did not induce any response in the TCs. Moreover,we hypothesize that the lack of considerable differences between PEMF-treated and untreated cells could be due to the origin of the cells:indeed,since they were derived from healthy hamstring tendons,the effect of PEMF on viability and DNA content could have been masked since these parameters were already optimal in untreated TCs.Our results are partially in contrast with previously published data on the in vitro effect of PEMF on tenocytes[23],which did not show any positive influence of PEMF on cell proliferation.This difference could be due to the different features of PEMF treatment,in term of dosage and physical parameters since they used a lower magnetic intensity(0.4mT)and the cells were exposed to an uninterrupted stimulation for longer time,until for seven continuous days.As already demonstrated,PEMF exposure is also able to act on the expression of specific tissue markers[40–42]and thus we assessed the expression of SCX and collagen I,both specific markers of tendon.In particular,collagen I gives tendon its resilience and bio-mechanical stability,whereas SCX is a transcription factor family continuously expressed through differentiation into the mature tenocytes and ligament cells[43,44],involved in the regulation of growth and differentiation of numerous cell types[45]and expressed by the tendon progenitor population that forms the fourth somitic compartment(the ‘‘syndetome’’).In our experiment,immediately after PEMF treatment,we observed a progressive,dose-dependent upregulation in both the SCX and COL1A1expression, suggesting a very rapid and strong effect of PEMF.The similar behavior of PEMF-induced expression of these two tendon markers could be explained as SCX regulates transcription of COL1A1through binding to tendon-spe-cific element2[46].Two days later,the upregulation of mRNA synthesis appeared to be maintained although it was no longer statistically significant.At this time point, the TCs treated with PEMF for4h were not assayed since they did not show any relevant differences from the untreated cells not only in terms of SCX and COL1A1 expression but also in terms of viability and proliferation. This implies that a short length of exposure is not sufficient to trigger a functional response in this cell model.For the same reason,the release of cytokines in cells treated with PEMF for4h was not analyzed.As for other tissue and organs,tendon healing is char-acterized by an initial inflammatory response[47].In our study,the release of the main inflammatory,anti-inflam-matory,and regulatory cytokines,involved in tissue heal-ing,was positively affected by PEMF exposure.Normally, in vivo most of the cytokines are produced by infiltrating leukocytes and resident macrophages andfibroblasts although an endogenous production of several cytokines by TCs has been recently demonstrated[48].We did not observe any increase in TNF a level,which is usually involved in several aspects of tendon degeneration[49]. The absence of a PEMF-related increase of this cytokine indicates that PEMF does not damage tenocytes,in accordance with the absence of apoptosis and the increase。

Traducción del manual original 1Documentos aplicablesTodos los documentos disponibles sobre el producto è/pk.DocumentosProducto, tipoContenidoInstruccionesEscuadra de fijación, MS2-WRMontajeTab. 12Seguridad 2.1Instrucciones de seguridad–Utilizar el producto únicamente en su estado original, sin efectuar modifica-ciones no autorizadas.–Utilizar el producto únicamente en perfectas condiciones técnicas.–Tener en cuenta las identificaciones que se encuentran en el producto. –Tener en cuenta las condiciones ambientales en el lugar de utilización. –Antes de realizar trabajos de montaje, instalación o mantenimiento, desco-nectar la alimentación de aire comprimido y asegurarla contra una reconexión accidental.–Respetar los pares de apriete. Si no hay indicaciones especiales, la toleranciaes de ± 20 %.2.2Uso previstoEl regulador de presión LR ha sido diseñado para regular el aire comprimido, delramal aguas abajo, a la presión de salida establecida. La función incluye una pur-ga secundaria integrada y una purga primaria con comportamiento al retorno.2.3Cualificación del personal técnicoEl montaje, la puesta a punto, el mantenimiento y el desmontaje solo deben ser realizados por personal técnico cualificado.3Más información–Accesorios è /catalogue.–Documentación è /sp.4Servicio de postventaAnte cualquier problema técnico, póngase en contacto con el representante regio-nal de Festo è .5Estructura del producto1Botón giratorio 2Manómetro3Tornillo de cierre (lado posterior)Fig. 1 Estructura del producto6Montaje 6.1Distancias de montaje•Mantener el espacio suficiente por encima y por debajo del producto.–Espacio necesario por encima del producto: 20 mm –Espacio necesario por debajo del producto: 30 mm Con montaje en panel frontal:•Respetar el espesor de pared máximo admisible. Espesor de pared: £ 2,5mm.6.2Tipos de fijaciónMontar el producto empleando uno de los siguientes tipos de fijación en función de la utilidad que se la vaya a dar:Tipo de fijaciónMás sobre la descripciónMontaje mural con escuadra de fijación–Instrucciones de montaje è 1 Documentos aplicables.–è 6.5 Instalación.En panel frontal–è 6.1 Distancias de montaje.–Accesorios è /catalogue.Tab. 2 Tipos de fijación 6.3Preparación1.Respetar la posición de montaje è 13 Especificaciones técnicas.2.Respetar el sentido de flujo de acuerdo con las cifras indicadas sobre el cuer-po: de 1 a 2.3.Para descargar de aire el sistema antes de realizar trabajos de mantenimien-to:Emplear la válvula de cierre de la línea de alimentación de aire comprimido. 4.Emplear el material de fijación del catálogo de Festoè /catalogue.5.Respetar el tipo de fijación.6.4Montaje del manómetro1.Girar el manómetro 2 en sentido horario hasta hacer tope. La junta del ma-nómetro está premontada en el bulón de conexión de la rosca.–Se puede realizar una conversión a la variante Z. Para ello, cambiar deposición el tornillo de cierre y emplear la conexión alternativa en el lado posterior del equipo. Par de apriete: 0,5 Nm2.Alinear la escala. Aflojar el manómetro en sentido antihorario y alinear la es-cala del manómetro verticalmente (tras enroscar hasta el tope, aflojar máx.1 vuelta).6.5Instalación1.Colocar el producto en el lugar dónde vaya a utilizarse.2.Respetar las distancias de montaje è 6.1 Distancias de montaje.3.Colocar la escuadra de fijación sobre el producto.4.Apretar la escuadra de fijación con la tuercaè 1 Documentos aplicables è Instrucciones de montaje.5.Fijar la escuadra de fijación sobre la superficie de montaje.7Instalación neumática1.Emplear racores, juntas y tubos flexibles adecuados del catálogo de Festoè /catalogue.2.Enroscar los racores en las conexiones neumáticas.3.Respetar la profundidad máxima de enroscado de la rosca de conexión. Unenroscado profundo reduce el caudal. Profundidad de roscado: £ 6,5 mm 4.Unir los tubos flexibles adecuados hasta hacer tope en el racor.–Los tubos flexibles deben quedar en posición axial respecto a las cone-xiones neumáticas.–Los tubos flexibles no deben presentar ningún radio de curvatura.8Ajustar la presión de salida1.Desbloquear el botón giratorio 1 (tirar).2.Girar el botón giratorio hasta el máximo en el sentido –.3.Presurizar el sistema lentamente: girar el botón giratorio en el sentido +, has-ta alcanzar la presión deseada.Respetar la gama de regulación de la presión è %getreference.La presión de entrada p1 deberá ser siempre, como mínimo, 0,5 bar superior que la presión de salida p2 ajustada.4.Bloquear 1 el botón giratorio (presionar).9Limpiar el producto•Limpiar el exterior del producto con un paño suave cuando sea necesario. Co-mo producto de limpieza puede considerarse cualquier producto de limpieza no abrasivo.10Eliminación de fallosDescripción del falloCausaSoluciónCaudal reducido (la presión de funcionamiento desciende mu-cho cuando hay consumo de ai-re).Estrechamiento en el conducto de alimentaciónComprobar el conducto.La presión sobrepasa el valor ajustado de presión de trabajo.Disco de la válvula defectuoso en el asiento selladorSustituir el producto.8090025MS2-LRRegulador de presión80900252019-01[8090028]Festo AG & Co. KG Ruiter Straße 8273734 Esslingen Alemania+49 711 Descripción del fallo Causa SoluciónAsiento de la válvula dañado Sustituir el producto. Escape de aire audible y cons-tante en el botón giratorioTab. 3 Eliminación de fallos11Desmontaje completo1.Purgar la instalación y el producto por completo.2.Soltar el bloqueo del racor presionando y extraer las tuberías flexibles.3.Aflojar los racores de la brida de unión y desenroscarlos.12Eliminación•Una vez terminada la vida útil del producto, reciclar el embalaje y el propio producto conforme a las disposiciones legales vigentes medioambientales. 13Especificaciones técnicas13.1Especificaciones técnicas, parte mecánicaTab. 413.2Especificaciones técnicas, neumáticaTab. 5。