Data from controlled trials indicate that Web-based interventions generally suffer from low engagement and high attrition. This is important because the level of exposure to intervention content is linked to intervention effectiveness. However, data from real-life Web-based behavior change interventions are scarce, especially when looking at physical activity promotion.The aims of this study were to (1) examine the engagement with the freely available physical activity promotion program 10,000 Steps, (2) examine how the use of a smartphone app may be helpful in increasing engagement with the intervention and in decreasing nonusage attrition, and (3) identify sociodemographic- and engagement-related determinants of nonusage attrition.Users  were grouped based on which platform  they logged their physical activity: Web only, app only, or Web and app. Groups were compared on sociodemographics and engagement parameters  using ANOVA and chi-square tests. For a subsample of users that had been members for at least 3 months , Kaplan-Meier survival curves were estimated to plot attrition over the first 3 months after registration. A Cox regression model was used to determine predictors of nonusage attrition.P<.001) and app-only users  showed a reduced attrition risk compared to Web-only users. Further, having a higher number of individual challenges , workplace challenges , physical activity logging days , and steps logged per day  were associated with reduced nonusage attrition risk as well as older age , being male , and being non-Australian .In the overall sample, user groups differed significantly in all sociodemographics and engagement parameters. Engagement with the program was highest for Web-and-app users. In the subsample, 50.00%  of users stopped logging physical activity through the program after 30 days. Cox regression showed that user group predicted nonusage attrition: Web-and-app users (hazard ratio=0.86, 95% CI 0.81-0.93, Compared to other freely accessible Web-based health behavior interventions, the 10,000 Steps program showed high engagement. The use of an app alone or in addition to the website can enhance program engagement and reduce risk of attrition. Better understanding of participant reasons for reducing engagement can assist in clarifying how to best address this issue to maximize behavior change. Insufficient physical activity has been identified as the fourth-leading risk factor for global mortality . PreviouEysenbach  calls foSeveral intervention characteristics have shown to enhance engagement and/or decrease attrition of interventions including the provision of personally tailored content, interactive components, social networking, and reminders -22. BesiThe aim of this study is to examine engagement with a Web-based physical activity intervention in real life because findings from controlled settings may not translate into real-life settings. Therefore, this study examines engagement and nonusage attrition in the freely available 10,000 Steps Australia program ,28, whicThe 10,000 Steps program is a freely available physical activity promotion program that encourages users to record and monitor their physical activity using pedometers. It was initially developed as a whole-community multilevel program based on the socioecological framework. Further information on the development of the program has been reported elsewhere ,28. A maIn addition to the opportunity to use the program via the 10,000 Steps website, there is also a smartphone app available on the iOS mobile platform . InitialData were extracted from the database of the 10,000 Steps program for users aged at least 18 years, who registered between July 8, 2013 and April 30, 2014, and who logged physical activity for at least 1 day in this period either through the website or the smartphone app . Although the website and app were available before July 8, 2013, this date was chosen as the start date for data extraction because prior to this date the available version of the app had reduced functionality; specifically, it did not allow users to join or view progress of challenges. No major changes in app functionality have occurred since this date, only minor updates have happened. Therefore, this study was delimited to users who registered during this 297-day period between July 8, 2013 and April 30, 2014 excluding those users who registered before this time. Thus, the maximum membership length in this study was 297 days. Website and app usage data were automatically recorded while using the 10,000 Steps program. When registering with the 10,000 Steps program, participants provided informed consent for usage of their data for research purposes.Date of birth, gender, and country of residence were assessed when participants registered to the 10,000 Steps program. Users were also asked how they heard about the 10,000 Steps program . Length of membership was calculated as the number of days between the date of registration for the program and April 30, 2014.Engagement was defined as the duration and frequency of involvement with the program. Four measures of engagement were used: (1) the duration of program use calculated as the number of calendar days from the first to the last time the physical activity log was used, (2) the number of individual challenges initiated, (3) the number of workplace challenges initiated, and (4) the total number of days physical activity was recorded in the step log (both website and app). The number of individual and workplace challenges participated in was determined from the 10,000 Steps database, which encompassed website and app usage information.The total number of days of physical activity recorded in the step log and duration of program usage differed. For example, a user may have used the program for 50 days (time from first to last step log), but only logged steps on 30 occasions during this time.Duration of program usage was also applied as an indicator of nonusage attrition. Participants were coded as “nonusage attrition was observed” when they did not log physical activity for at least 14 days   and when inconsistencies in data were detected; that is, users logged on average less than 100 steps per day (n=16) or logged physical activity on more days than it would be possible based on their duration of program use (n=9). The final number of users included in the analysis of user characteristics and engagement was N=16,948 and is referred to as the overall sample. Attrition analysis was based on a subsample of users as described subsequently. Based on the platform used to log steps, 3 groups were defined: Web-only users who logged steps solely via the 10,000 Steps website , app-only users who logged steps solely via the 10,000 Steps smartphone app , and Web-and-app users who logged steps via the 10,000 Steps website and the smartphone app .First, means and standard deviations for sociodemographics, engagement parameters, and logged physical activity were calculated to describe the overall sample and the 3 user groups.To assess which personal characteristics of 10,000 Steps users may facilitate choosing the app over the website, differences between the user groups regarding sociodemographics were analyzed. Further, user groups were compared regarding engagement parameters and logged physical activity. Group comparisons were performed using 1-way ANOVAs with Bonferroni-corrected post hoc comparisons (for continuous variables) and chi-square tests .2) were calculated for linear regression because even small differences tend to reach significance with high numbers of participants such as in our study. According to Cohen [2>.01. Therefore, in this study, differences were considered meaningful when effect sizes reached these thresholds. Further, duration of usage, number of individual and workplace challenges started, and number of days physical activity was logged for were presented for different membership lengths.Because engagement parameters are likely to depend on sociodemographics, length of membership, and physical activity level, we also examined the effect of user group on the engagement parameters using linear regression adjusting for those variables. Four regression analyses were fitted, each using an engagement parameter  as the dependent variable. User group was used as the independent variable along with age, gender, country of residency, length of membership, and physical activity as covariates. Standardized regression coefficients were calculated. Effect sizes  who were a 10,000 Steps member for at least 3 months (90 days) at the time of data extraction . This was done to ensure that all participants had the same chance to use the program and to enable comparability with other published attrition curves 1 who wer,33. This of <.25  were selOf 16,040 users who answered the “Where did you hear about us?” question, most users  indicated that they heard about the program through their workplace. Further, 12.42%  heard about 10,000 Steps from a friend; 4.3%  from a webpage; 2.9%  from a health professional; 0.9%  from Facebook; 0.41%  from other media including TV, newspaper, and radio; and 5.1%  indicated other sources.P<.001) with app-only users being also younger than Web-and-app users (P<.04). Web-only users (P=.004) and Web-and-app users (P<.001) had longer durations of membership in the 10,000 Steps program compared to the app-only users, with no difference between Web-only and Web-and-app users (P=.28).Descriptions of the overall sample and the subsample regarding sociodemographics, engagement data, and logged physical activity are shown in In the overall sample, users utilized the program between 1 and 296 days  with 6.51%  and 81.89%  participating at least in 1 individual challenge (range 0-8) and 1 workplace challenge (range 0-8), respectively. Users logged on average 30.8 days of physical activity (range 1-290 days) with 97.77%  of users logging physical activity more than once. With increasing length of membership, the average duration of usage, the number of individual and workplace challenges, as well as the number of days physical activity was logged per week decreased . For exaP<.001). App-only users showed a longer duration of usage (P<.001), a higher number of individual challenges (P<.001), a lower number of workplace challenges (P<.001), and a higher number of days they logged physical activity (P<.001) compared to Web-only users (P<.001), higher number of individual  challenges, as well as a higher number of days they logged physical activity (P<.001). Regarding workplace challenges, Web-and-app users had higher numbers compared to app-only users (P<.001), but were not significantly different from Web-only users (P=.07).All engagement parameters differed significantly across user groups (ly users . CompareP<.001) with lower numbers of steps per day for Web-only users compared to Web-and-app users (P=.01). Web-and-app users logged a mean of 67.4% (SD 29.94) of their total steps through the app.More than half of participants  logged at least 10,000 steps on average per day. However, app-only users had significantly lower numbers of steps per day compared to Web-only and Web-and-app users . Web-and-app users showed a longer duration of usage , more individual challenges , and more days of physical activity logged  compared to Web-only users; however, comparisons between app-only and Web-only users regarding duration of usage, number of individual challenges, and physical activity log days did not reach the threshold for a meaningful effect .22=161.3, P<.001). Estimated median lifetime usage  was 30 days for all groups combined . combined . For allP<.001 and hazard ratio=0.63, 95% CI 0.81-0.93, P<.001, respectively). Being a resident of a country other than Australia , being male , and being of higher age  also reduced the risk of attrition. Regarding the engagement parameters, the risk of attrition decreased when the number of individual challenges , workplace challenges , and number of days physical activity was logged for  increased. Furthermore, the more steps logged per day lowered the risk for attrition . All variables that had a P<.25 in the univariate analysis were included in the multivariate analysis. Results from the multivariate analysis showed a similar pattern (P=.59) and there was no effect of workplace challenges on attrition risk  when controlling for other variables in the analysis.User groups, sociodemographics, engagement, and physical activity as potential predictors of nonusage attrition in the subsample are presented in  pattern  except tThe aim of the present study was to examine program engagement with a freely accessible Internet-delivered physical activity intervention  and test for a possible positive effect of using a smartphone app on engagement parameters and attrition. Results indicate a high program engagement and that the use of the app alone or in addition to the website can enhance program engagement and lower attrition. Further, this study extends previous research on individual challenges  by showiThe present study reported high levels of program engagement. Nearly all (97%) users logged physical activity at least twice. Whereas most users engaged in at least 1 workplace challenge (81%), only 7% used individual challenges.Although some studies conducted within controlled settings reported higher program engagement and lower attrition than the 10,000 Steps program ,35, studThere has been some research examining engagement with Web-based interventions in real-life settings including interventions on depression, panic disorder, weight loss, physical activity, drinking behavior, and smoking -17,41-46The second aim of this study was to examine the effect of a smartphone app on program engagement. In general, app users were younger and more likely to be female compared to Web-only users, which aligns with research showing that the percentage of smartphone owners decreased with age and that young adults are more likely to use health apps . Our resAlthough our results are promising, it should be noted that the majority of users still were Web-only users  with only 16.13%  using the app alone or in addition to the website. These uneven group sizes may be because the app is only available on the iOS mobile platform. Even though rates are increasing, in 2011 the proportion of US adults reporting to own either a smartphone or tablet was 50%, with 38% of smartphone owners and 52% of tablet owners saying their device used the iOS platform [Personal factors associated with reduced nonusage attrition risk were being male, non-Australian, and older age. Differences in nonusage attrition by country of residency may be seen as an effect of weather because poor and extreme weather has been identified as barriers of physical activity  and, in Even though Web-based interventions are capable of reaching large parts of the population, a notable percentage never starts to use or accesses only a small part of the intervention . BecauseA strength of this study is that we obtained a large sample from a freely available physical activity intervention and examined usability efficacy as recommended by previous literature . HoweverOur study provides insight into the engagement with a freely available physical activity intervention. Results indicate that smartphone apps may be powerful tools in enhancing program engagement and lower attrition. Future research should experimentally examine reasons of low engagement and attrition to enable development of interventions that ensure long-term engagement with the intervention. Further, our data elucidate that rating the success of online interventions by engagement parameters is highly dependent on the time window measured; therefore, study length has to be considered when comparing studies in regard to engagement parameters.


The development of linkage disequilibrium (LD) maps and the characterization of haplotype block structure at the population level are useful parameters for guiding genome wide association (GWA) studies, and for understanding the nature of non-linear association between phenotypes and genes. The elucidation of haplotype block structure can reduce the information of several single nucleotide polymorphisms (SNP) into the information of a haplotype block, reducing the number of SNPs in a coherent way for consideration in GWA and genomic selection studies.2 varied between 0.33 to 0.40 at a distance of < 2.5 kb, and the minimum average values of r2 varied between 0.05 to 0.07 at distances ranging from 400 to 500 kb, clearly showing that the average r2 reduced with the increase in SNP pair distances. The persistence of LD phase showed higher values at shorter genomic distances, decreasing with the increase in physical distance, varying from 0.96 at a distance of < 2.5 kb to 0.66 at a distance from 400 to 500 kb. A total of 78% of all SNPs were clustered into haplotype blocks, covering 1,57 Mb of the total autosomal genome size.The maximum average LD, measured by rThis study presented the first high density linkage disequilibrium map and haplotype block structure for a composite beef cattle population, and indicates that the high density SNP panel over 700 k can be used for genomic selection implementation and GWA studies for Canchim beef cattle. With the advance in high-throughput single nucleotide polymorphism (SNP) detection and genotyping technologies, genome-wide association (GWA) and genomic selection (GS) studies in livestock have become of great interest. Nonetheless, both types of studies rely on the extent of linkage disequilibrium between markers across the genome. Linkage disequilibrium (LD) can be defined as the non-random relationship of alleles between two loci within a population. The development of LD maps and the characterization of haplotype block structure at the population level are useful parameters for guiding GWA, candidate gene and candidate region studies , as wellA variety of studies can be found regarding linkage disequilibrium in cattle populations. The first genome-wide LD study was conducted in a Dutch black-and-white dairy cattle population based on 284 microsatellite markers . From thHaplotype block studies are not as common as LD map studies in cattle. The elucidation of haplotype block structure can bring important considerations for GWA and GS studies, such as the possibility of selecting a set of SNPs with the prospect of reducing the information of several SNPs into the information of a haplotype block, reducing the number of SNPs in a coherent way , and optBos primigenius indicus (zebu) and Bos primigenius taurus (Charolais) animals [With the new releases of commercial high density SNP panels with over 700 k SNPs, it is possible to build high definition LD maps and haplotype blocks. In this study, we used the Illumina BovineHD BeadChip to investigate LD and persistence of LD phase patterns, as well as the haplotype block structure for Canchim, a composite breed of beef cattle. Canchim was originated in the early 1960's in Brazil from crosses between  animals . The fin animals .In respect to the Canchim composition particularity, a sample of 399 animals  was selected, and Canchim animals will be referred to as CA, the MA animals as MA, and the joint group of Canchim and MA animals as CAN. These 399 animals belong to seven herds located in two Brazilian states (São Paulo and Goiás), and are registered in the Canchim Breeding Association database. This study has been performed with the approval of the Embrapa Southeast Livestock Ethical Committee of Animal Use (CEUA-CPPSE) under protocol number 02/2009.The Canchim population is considered to be rather small, especially when compared to other breeds in Brazil. The herd is estimated to contain approximately 30,000 animals, according to data from the Canchim Breeding Association , and supThe 399 animals described above were genotyped using the BovineHD BeadChip , which consists of 786,799 SNPs evenly distributed along the bovine genome with an average distance of 3 kb. In this study, sex chromosomes and loci without an assigned position in the Cattle Genome Assembly UMD 3.1  were dis2 [The data set was divided into Canchim and MA animals for an exploratory analysis of persistence of LD phase between both genetic groups, and LD estimation was performed using the SNPPLD tool available in the gebv software . The LD 2 , which iij pis the frequency of the two-marker haplotype, and ip, and j pare the marginal allelic frequencies in the th iand th jSNP, respectively [2 can vary from 0 to 1, where zero means no correlation between SNP pairs, and 1 means perfect correlation between the SNP pairs. Due to the significant amount of possible SNP pair-wise comparisons, the r2 calculation was limited to SNPs within maximum distances of 500 kb from each other, since r2-values obtained using SNPs with distances over 500 kb presented low LD values (data not shown), and to estimate all SNPs pair-wise comparisons would exponentially increase computing processing. Paternal and maternal haplotypes were utilized for the estimation of LD.where ectively . The val2 (r), by attributing the appropriate sign based on the calculated D value, called signed r. Persistence of LD phase calculation was performed according to the following equation:The persistence of LD phase was evaluated across genetic groups (CA and MA) by the Pearson correlation of the square root of rij, pip, and j pwere defined as stated above. The results were ordered by chromosome (chr) and distance between SNPs.where Haplotype block refers to a combination of alleles linked along a chromosome, which are inherited together from a common ancestor . The hap2 of 0.40 was obtained for CA animals at a distance of < 2.5 kb, while MA animals obtained an average r2 of 0.33, and the joint population (CAN) resulted in an average r2 of 0.38  were obtained at a distance from 400 to 500 kb  passed the quality control filters from the SNPPLD software, yielding a total of 716,089 SNPs for CA, 658,132 SNPs for MA, and 713,615 SNPs for CAN animals. The number of SNP pairs showed small variation among CA, MA, and CAN due to the quality control filtering, in which some SNPs were included for CA, MA, and CAN, and some other SNPs were not included, as shown in Table The quality control filtering for the haplotype block study was performed using the PLINK v1.07 software , which p2 instead of D' for assessing LD measurements was due to the fact that it is less affected by allele frequencies in a finite population size compared to D', which tends to overestimate LD in small samples and low frequency alleles [2-values above 0.30 can be considered a strong LD and useful for QTL mapping [2-value of 0.20 is considered enough to achieve an accuracy of 0.85 for genomic breeding value (GBV) estimation [2=0.30 and above were found in CA animals extending to the physical genomic distance of 10 kb, being followed by CAN animals at a distance of 7.5 kb, and lastly by MA animals to the physical genomic distance of 5 kb  higher than 0.30 for SNP markers spanning to a physical genomic distance of 3 kb, and an r2 higher than 0.20 for SNP markers continuing to a physical genomic distance of 20 kb [The choice of using r alleles ,30,31. Atimation . Mean va history , the resof 20 kb .Animals from the MA genetic group showed lower levels of LD compared to CA animals Table . This mi2 between two populations, but in different LD phases [signed r value represents the degree of genetic relationship between populations [2 = 0.20 to achieve an accuracy of 0.85 for genomic breeding value estimation [The understanding of the persistence of LD phase is essential for effective genomic selection across admixed populations or crossbred animals, as a pair of SNPs can exhibit the same value of rD phases . The corulations , and betulations ,37, hightimation , the pertimation , which aThere are many published studies on LD and haplotype block properties for cattle, which vary in many aspects , yielding average haplotype block sizes from a few kb in length .The authors declare that they have no competing interests.FBM, MEB: contributed equally for the development of this research with data analysis, interpretation, figure compositions, manuscript writing and revision. MAM: data analysis, manuscript discussion and revision. DAG: data analysis, interpretation of results, manuscript revision. RHH: data analysis, manuscript discussion and revision. RVV: data analysis, interpretation. AOL: data analysis, interpretation of results, manuscript revision. MS: provided the SNPPLD software, interpretation. SLCM: experimental design, manuscript revision. FSS: results interpretation and discussion. MVGBS: experimental design, manuscript revision. SCMN: experimental design, DNA handling, manuscript revision. MMA: experimental design. DPM: data interpretation. LCAR: experimental design, interpretation, and manuscript revision.


We evaluated the association between Asian American ethnicity and age at diagnosis for type 2 diabetes using data from the California Health Interview Survey. Survey-weighted unadjusted and adjusted linear regressions were used to obtain mean estimates of age at diagnosis. In the adjusted regression model, ages at diagnosis were 10.5, 8.7, 8.4, and 4.2 years earlier among South Asian, Vietnamese, Filipino, and Korean populations, respectively, as compared to non-Hispanic whites; no significant difference in age at diagnosis was noted for Chinese and Japanese populations. Recommendations for diabetes screening and preventive measures specific to Asian American populations are warranted. Asian Americans are the fastest-growing population in the United States . The litWe used the public access adult portion of the 2003–2011 California Health Interview Survey (CHIS). CHIS, a biennial survey using random-digit–dialing, is the largest state health survey and is conducted in several languages, including several Asian languages (5). In this study, we used data for adults who self-identified as Chinese, Filipino, South Asian, Japanese, Korean, or Vietnamese and compared them with data for adults who self-identified as non-Hispanic white, reporting diagnosis of type 2 diabetes. This study was approved by the institutional review board of California State University, San Bernardino.The primary outcome variable for this study was age at diagnosis of type 2 diabetes, and the primary exposure variable of interest was ethnicity (Asian American subgroup compared with non-Hispanic white). We further included control variables of sex , education , country of birth (United States or foreign), and survey year .2 test of independence was used to assess significant differences in sociodemographic characteristics among Asian Americans and non-Hispanic whites, and survey-weighted multiple linear regression was used to assess age at diagnosis of type 2 diabetes. Relevant interaction terms were further assessed with significance established for analyses (α = .05).We weighted all data and used SAS version 9.4 , allowing for population estimates. A survey-weighted χMost Asian Americans (51.8%) and non-Hispanic whites (54.0%) were female, and a higher percentage for both populations had less than a bachelor’s degree . Most AsIn the unadjusted model, Filipinos, South Asians, and Vietnamese were diagnosed with type 2 diabetes 5.5 years, 6.9 years, and 5.2 years earlier, respectively, as compared to non-Hispanic whites . After aOur study noted that Filipinos, Koreans, South Asians, and Vietnamese adults are likely to be diagnosed with type 2 diabetes significantly earlier than non-Hispanic white adults. Earlier ages at diagnosis indicate the premature presence of clinical risk factors and in turn may explain the increased cardiovascular disease risk noted in some Asian American subgroups . AlthougSuch earlier age at diagnosis could be due to differing molecular predisposing factors. For example, Yajnik and colleagues  reportedAge at diagnosis, however, may not reflect age of onset, so the true burden of the disease may be even more severe among Asian Americans than noted in our study. Future studies addressing age of onset and not just age at diagnosis are critical, because such studies could further identify the groups most at risk, allowing for targeted preventive measures. CHIS does not provide assessment of age of onset, family history, or other sociodemographic variables during the time of diagnosis; lack of such data are a limitation of our study. In addition, our findings are generalizable only to Asian Americans in California; further studies are needed for other regions. Nevertheless, the substantial disparity in age at diagnosis for type 2 diabetes among some Asian American subgroups not only confirms the heterogeneity among the population, but also demonstrates the need to consider developing diabetes screening recommendations that are ethnicity-specific to mitigate the chronic disease burden among this growing population.


Arabidopsis thaliana became the model organism for plant studies because of its small diploid genome, rapid lifecycle and short adult size. Its genome was the first among plants to be sequenced, becoming the reference in plant genomics. However, the Arabidopsis genome is characterized by an inherently complex organization, since it has undergone ancient whole genome duplications, followed by gene reduction, diploidization events and extended rearrangements, which relocated and split up the retained portions. These events, together with probable chromosome reductions, dramatically increased the genome complexity, limiting its role as a reference. The identification of paralogs and single copy genes within a highly duplicated genome is a prerequisite to understand its organization and evolution and to improve its exploitation in comparative genomics. This is still controversial, even in the widely studied Arabidopsis genome. This is also due to the lack of a reference bioinformatics pipeline that could exhaustively identify paralogs and singleton genes. We describe here a complete computational strategy to detect both duplicated and single copy genes in a genome, discussing all the methodological issues that may strongly affect the results, their quality and their reliability. This approach was used to analyze the organization of Arabidopsis nuclear protein coding genes, and besides classifying computationally defined paralogs into networks and single copy genes into different classes, it unraveled further intriguing aspects concerning the genome annotation and the gene relationships in this reference plant species. Since our results may be useful for comparative genomics and genome functional analyses, we organized a dedicated web interface to make them accessible to the scientific community Furthergenomics ,12,13,14genomics , whereasnization ,17,18,19dization ,28,29,30portions ,31,32,33portions ,35. Suppe genome ,36,37.A. thaliana [A. thaliana genes that may support similar studies and comparative genomics. On the other hand, our approach revealed still intriguing aspects concerning the gene annotation of A. thaliana that are worthwhile to be considered by the interested scientific community.Over the last ten years, several studies aimed at clarifying the evolutionary history of thaliana ,41,42,43thaliana ,25,26,40thaliana , or aginthaliana  and famithaliana  analysesthaliana ,48,49,50thaliana ,53,54,55thaliana , and thethaliana , Ensemblthaliana  and Plazthaliana  are threthaliana ,59, enri2.2.1.Arabidopsis thaliana genome  was downloaded from the TAIR website [non-protein-coding genes the pseudogenes, the small nuclear RNAs (snRNAs), the small nucleolar RNAs (snoRNAs), the micro RNAs (miRNAs), the transfer RNAs (tRNAs), the ribosomial RNAs (rRNAs), the other RNAs, and the transposable elements. All these RNAs were classified according to the locus type assigned by TAIR. Intergenic regions were also downloaded from the TAIR website. The complete set of A. thaliana Expressed Sequence Tag (EST) sequences was downloaded from the GenBank release of 8 April 2010. Arabidopsis gene family information was downloaded from the TAIR website. To enrich the list of gene families, we considered the non-redundant collection obtained from transcription factor families reference databases [The  website . TAIR9 catabases ,62.2.2.All-against-all protein sequence similarity searches were performed using the BLASTp (protein BLAST) program  considerE) cutoffs were used: a more stringent threshold (E ≤ 10−10) and a less stringent one (E ≤ 10−5) [E ≤ 10−3).The Expect-value cut-off. To detect different levels of sequence similarity among protein-coding genes, two different Expect-value  ,65. To en = 5, according to Li et al., [The Rost's formula. To determine whether two proteins in a genome are paralogs when the similarity between them is in the so-called twilight zone (20%–30% of identity/length ratio), the Rost's formula ,58 was a et al., . The useE ≤ 10−5) was performed without the masking filter, to identify genes that could have been masked hiding similarities to other genes. Sequences showing similarity when unmasked were not included in the subsequent analyses, since they cannot be considered as singletons and their similarity with other proteins may not be necessarily associated with a paralogy relationship.The low-complexity BLAST filter. The BLAST analysis applies by default a masking of low-complexity regions in the query sequence . Indeed,2.3.Arabidopsis transcript sequences were aligned vs. the Arabidopsis protein collection with a BLASTx analysis (E ≤ 10−5).To check for possible similarities hidden by different open reading frame (ORF) assignments, 2.4.E ≤ 10−5). The resulting alignments were manually curated considering the intron-exon structure of the query: in particular, we distinguished alignments involving only intronic regions of the query and alignments involving coding regions of the query and covering at least half of its length. To determine any further significant sequence similarity of a protein coding gene within the genome, a BLASTn analysis (E ≤ 10−5) was performed, searching against all the Arabidopsis intergenic regions.In order to consider nucleotide-based similarities of protein-coding genes with other regions of the entire genome, the full-length genes (queries) were searched against both non-protein-coding genes and intergenic regions, using the nucleotide BLAST (BLASTn) tool  [E ≤ 10−5. However, the E-value threshold itself cannot be enough to confirm the association of a transcript to an EST. Since ESTs represent sequence tags of a transcript, we generally expected an EST sequence to be shorter than the transcript length, but this was not always the case. Therefore, we imposed further criteria to validate the alignments: we considered match lengths greater or equal to 60% of the shortest sequence between the two alignment . An EST sequence should be 100% identical to the transcript in the region of a match, though 95% of the identity should better ensure the consideration of possible sequencing errors . We decided to consider a cutoff at 90% identity This also permits us to strictly determine those transcripts that cannot be reliably associated with ESTs when showing an alignment score lower than the cutoff. Alignments with a scoring higher or equal to the cutoff were analyzed in terms of the relative length of the transcript and the corresponding best matching EST. We defined the parameter, delta, as the EST length minus the transcript length, to verify if the EST is shorter or equal to the transcript length (Δ ≤ 0), as it should be. In the case of positive deltas, we accepted those alignments with Δ ≤ 20 nucleotides, since we assumed that the presence of an EST longer than the transcript of a maximum of 20 nucleotides can be ascribed to EST regions not trimmed and/or still containing contaminations.We confirmed the functionality of the genes by looking for EST evidence. Transcript sequences from singleton genes were aligned  cutoff) . This peA. thaliana accessions (GSE30795), downloaded from the Gene Expression Omnibus (GEO) database [i.e., RPKM (Reads per Kilo Base per Million) values, were also downloaded. An RPKM threshold of one was applied to consider a gene/transcript as expressed in at least one tissue, as in [RNA-sequencing (RNA-seq) data were used to further verify the expression of these singletons. We based our analyses on a multiple tissue RNA sequencing experiment of two database . These de, as in .2.6.Arabidopsis lyrata and Brassica rapa) and distant  plant species.To confirm our findings, we used the BioMart tool and the Ensembl plants database (plant Mart Release 5) ,70 for t2.7.Arabidopsis protein-coding gene collection as an undirected graph with the vertex representing genes (nodes) and edges representing paralogies. Networks correspond to the connected components of the graph and were extracted with a recursive depth-first search on it.The network extraction process was based on considering the 2.8.The website has been implemented with a PHP (Hypertext Preprocessor)  interfac3.3.1.Arabidopsis protein-coding gene collection (release TAIR9 [E) cutoffs were used: a more stringent threshold (E ≤ 10−10) and a less stringent one (E ≤ 10−5) [We analyzed the whole se TAIR9 ), and wese TAIR9 . Two dif ≤ 10−5) ,65.vs. another protein in the collection  and the less conservative (E ≤ 10−5) ones. The first set consists of 3, 017 networks, while the second set consists of 2, 754 ones  and in their complexity , as shown in the examples in The networks show differences, both in their size . The amount of genes belonging to two-gene networks per chromosome and their mutual distribution among the upper (U) and lower (L) arms  are sumi.e., half of the resulting maximum value. The use of this threshold highlights the most relevant inter- and intra-chromosome patterns. The paralogy distributions for two-gene networks are also shown in Arabidopsis genome organization, in the frame of the proposed whole genome duplications and subsequent diploidization, reshuffling and reduction events [The table also highlights (in bold) the topmost seven values, obtained using a threshold of 55, n events ,39,40,413.4.Arabidopsis gene families. Six-thousand six-hundred and forty-seven genes are classified into gene families on the TAIR website [exclusive families, since they have all the members arranged into one network, confirming the reliability of the networks' organization for the classification of paralogs. The other 30% of the families are instead classified as split families, since their members are distributed among different networks or are classified as singletons. Hence, networks containing only one family are classified as exclusive networks, to distinguish them from the mixed ones, i.e., those containing genes belonging to different families and/or family-not-associated genes ; see Split families represent heterogeneous families, and their organization in exclusive networks indicates a self-consistent structure similarity of sub-groups of the family, which is often confirmed by the classification available from TAIR . The splInterestingly, 2, 787 out of 5, 305 genes still annotated as coding for “unknown proteins”, belong to networks (with the less stringent threshold). This means that their functional annotation can be improved thanks to the relationships with other members of the same network.E ≤ 10−5) threshold is used, while they are split into two distinct exclusive ones, when the more conservative threshold (E ≤ 10−10) is applied.The use of at least two different E-value cutoffs, as proposed here, also provides further information on the structural peculiarities of the families. As shown in unknown. The use of the domains from the PFAM (Protein Families) database [This strategy can be extended to improve the gene family classification for a species annotation, promoting the identification of novel families and the annotation of family-not-associated genes, as well as of genes annotated as database  confirms3.5.Arabidopsis genes having no statistically significant protein sequence similarity with other nuclear protein-coding genes was further investigated, also to define a suitable strategy for the detection of those genes that we will eventually call true singletons, i.e., genes without any similarity vs. the entire genome sequence. We defined as paralogs those genes having at least one duplicate when using the less stringent E-value cutoff of E ≤ 10−5  [unassigned genes due to ORF annotation error. Once we explored the similarity among protein-coding genes, we further investigated the collection of the 3,587 still unclassified remaining genes to discard nucleotide-based similarities with other regions of the entire genome. The full-length genes (exon plus introns) were independently compared vs. both non-protein-coding genes and intergenic regions (BLASTn [E ≤ 10−5).The  ≤ 10−5)  to ident . No significant hits were found in the comparison of the 3,409 remaining genes vs. the intergenic regions, thus excluding the presence of duplicates in genome regions not annotated as genes. These protein-coding genes were defined as true singletons, since they share no similarity vs. the entire Arabidopsis genome sequence. Besides listing the analyses that determined the assignments of the entire protein-coding gene collection of Arabidopsis to different classes, Specifically, 250 genes shared similarity with at least one 3.6.vs. the complete set of A. thaliana ESTs  [singletons not confirmed by ESTs (no EST trace).We confirmed the functionality of the genes by comparing the true singletons  cutoff) . Among tE < 10−5). Six-hundred eighty-eight out of 3,409 were classified as singletons not confirmed by ESTs , since the alignment of the correspondent transcripts with the ESTs did not satisfy the considered cutoff. However, to confirm the association of a transcript to an EST, alignments involving the remaining 2,697 genes were further investigated, considering parameters, such as the match length and the number of identities (see the Methods section). This analysis allowed us to classify 201 genes as singletons not confirmed by ESTs (discarded by coverage and identity requirements). The remaining 2,496 alignments were analyzed in terms of the relative length of the transcript and the corresponding best matching EST using the Δ parameter. Considering the distribution of the alignments with positive Δ (data not shown), two classes are evident: one in which Δ ≤ 20 nucleotides and the other with Δ > 20 nucleotides. Nine alignments with Δ ≤ 20 nucleotides are considered as confirmed by ESTs, since the presence of an EST longer than the transcript of a maximum of 20 nucleotides can be ascribed to EST regions not trimmed and/or still containing contaminations. One-hundred transcripts have ESTs much longer than the annotated region and are therefore classified as singletons not confirmed by ESTs (EST longer than the transcript). Since the majority of the genes considered are described by only one isoform (only four of the 100 genes presented multiple transcripts), the observed matches with longer ESTs are not ascribable to misassigned ESTs and may therefore represent limited annotations of the entire gene structure. In conclusion, 1,013 transcripts were singletons not confirmed by ESTs. The expression of the unconfirmed true singleton genes was further validated using RNA-seq data from three different tissues . Using an RPKM threshold of one, we detected 818 out of 1,013 singleton genes not confirmed by ESTs as not expressed in any of these tissues. The remaining 195 genes show a low expression in one or more tissues (data not shown). We also confirmed by RNA-seq the expression of 2, 178 out of 2, 396 singletons confirmed by ESTs.We then considered the statistically significant alignments (3.7.Arabidopsis lyrata and Brassica rapa) and in other plant species .The 3, 409 true singletons were analyzed to search for ortholog genes in two closely-related species , the list of all the genes included in the network and the graphical representation of the network itself. The networks at the less stringent thresholds were named NETxGy_z, where NET stands for network and G for genes, x indicates the number assigned when sorting the total amount of networks by decreasing network size, y indicates the network size  and z is the number of networks or singletons in which the network is split when the more stringent cutoff is applied. This naming convention was established to (1) support the immediate understanding of the network structure and (2) help in associating the networks obtained at the two different thresholds. Please note that each gene belongs to one and only one network at each threshold. For genes without paralogs, the associated classification is reported. (See the help file on the website for more information.)We set up a web-based resource to make all the data so far described accessible to the scientific community . The web4.Arabidopsis thaliana genome was evident since its first release, primarily for its role as a reference in plant comparative genomics [A. thaliana is essential, though these approaches are not a novelty in genomics, as well as in plant genomics [Arabidopsis and other plant genomes [A. thaliana protein coding gene collection. The main results of the pipeline are lists of paralogs (including about 80% of the whole Arabidopsis protein-coding gene collection) and singleton genes (∼20%). The organization of paralogs into networks of genes provides a suitable support to their mining, their investigation and their management, to face both annotation and evolutionary issues. Indeed, as shown in unknown genes, or to investigations on gene family relationships. Other evolutionary insights can also be inferred. As an example, one quarter of the genome has zero or at most only one paralog, which is rather intriguing in a widely duplicated genome [Arabidopsis reported their amount as being about 5, 000 genes [A. thaliana related collections. Despite the relevance of the manifold resources already available [A. thaliana, none of them reveals the relationship between the two metal ion binding MT1A (AT1G07600) and MT1B (AT5G56795) genes, which are paralogs. Indeed, these two genes are reported as singletons in all similar resources, since they are exclusively based on protein sequence analyses. The paralogy relationship that emerges from the nucleotide sequence similarities of proteins encoded on different frames, in fact, is only detectable by deeper investigations, such as the one here described, which expands the conventional protein-based paralog search to transcript analyses.The need for further investigations on the complexity of the genomics ,36,37,81genomics . Indeed, genomes ,46,47,57 genomes ,52,53,63 genomes ,67,74,82d genome ,26,40,4100 genes . Here, wvailable ,46,47,57E ≤ 10−5) provided a coarse-grained view of the gene distribution into networks, whereas a more stringent one  gave rise to reduced gene sets per network, separating those subsets sharing lower similarity. We also considered the presence of low-complexity regions [vice versa, hide true similarities.We also overviewed several methodological issues, addressing the main aspects that may strongly affect the results, their quality and reliability, trying to contribute to the definition of a widely accepted strategy for reproducible results. For example, most studies set one pre-defined E-value threshold to filter significant resulting alignments between proteins, in a BLASTp analysis. Indeed, it is well-known that the E-value cutoff is critical in the definition of whether genes are true paralogs ,82. Ther regions ,83, sincA. thaliana nuclear protein-coding gene collection and the whole bioinformatics pipeline description provide a unique comprehensive reference, to our knowledge, for similar efforts and for plant comparative genomics.The detailed classification of the 5.The list of duplicated genes, together with their organization into networks of paralogs, and the list of singletons, as well as the gene classification introduced here may represent an univocally defined, reproducible and reliable collection in plant genomics. Indeed, the proposed methodology, which includes several steps of BLAST-based approaches on both protein, gene and intergenic regions, is described with all the details, thus representing a valid support for similar efforts in different contexts. Since the classification and the results we provided can be a reference, as well as the starting point for further analyses in structural and evolutionary genomics, they were made freely accessible through a web resource .A. thaliana gene annotation and pave the way for novel analyses relevant for plant genomics.Our results highlight the strong need for further investigations on the


To develop a simple and accurate delirium prediction score that would allow identification of individuals with a high probability of postoperative delirium on the basis of preoperative and immediate postoperative data.Postoperative delirium, although transient, is associated with adverse outcomes after surgery. However, there has been no appropriate tool to predict postoperative delirium.This was a prospective observational single-center study, which consisted of the development of the DELirium Prediction based on Hospital Information (Delphi) score (n = 561) and its validation (n = 533). We collected potential risk factors for postoperative delirium, which were identified by conducting a comprehensive review of the literatures.Age, low physical activity, hearing impairment, heavy alcoholism, history of prior delirium, intensive care unit (ICU) admission, emergency surgery, open surgery, and increased preoperative C-reactive protein were identified as independent predictors of postoperative delirium. The Delphi score was generated using logistic regression coefficients. The maximum Delphi score was 15 and the optimal cut-off point identified with the Youden index was 6.5. Generated area under the (AUC) of the receiver operating characteristic (ROC) curve was 0.911 (95% CI: 0.88–0.94). In the validation study, the calculated AUC of the ROC curve based on the Delphi score was 0.938 (95% Cl: 0.91–0.97). We divided the validation cohort into the low-risk group (Delphi score 0–6) and high-risk group (7–15). Sensitivity of Delphi score was 80.8% and specificity 92.5%.Our proposed Delphi score could help health-care provider to predict the development of delirium and make possible targeted intervention to prevent delirium in high-risk surgery patients. Thus, a predictive model for delirium is necessary to identify high-risk patients for monitoring and proactive implementation of preventive strategies.Postoperative delirium, although transient, is associated with adverse outcomes, which range from a minor functional decline to postoperative death in the hospital and consequently increased health care costs.15 In addition, the use of all previously developed delirium prediction scoring systems is complicated because they incorporate other scoring systems.17Although several scoring systems for predicting delirium have been developed and used, they have some limitations for their application in general surgery practice. Because some systems have been developed for medical patients, they are not appropriate to predict postoperative delirium in surgical patients.The aim of this study was to develop a simple and accurate delirium prediction score that would allow identification of the individuals with a high probability of postoperative delirium on the basis of preoperative and immediate postoperative data.This was a prospective observational single-center study, which consisted of two parts: the development of the DELirium Prediction based on Hospital Information (Delphi) score using data from patients who underwent major general surgery and validation of the developed Delphi score in a different prospective cohort in the same hospital.www.ncbi.nlm.nih.gov/pubmed), Ovid (gateway.ovid.com), EMBASE (www.elsevier.com), and Cochrane (www.cochranelibrary.com) in February 2013. The keywords were as follows “(delirium OR confusion) AND (risk factors OR factors) AND (surgery OR operation OR postoperative)” Patient recruitment started in June 2013 and was completed in January 2014. The eligible patients were as follows: patients of either sex above the age of 60 years, patients admitted with an expected duration of hospital stay of at least 3 days after major general surgery . Exclusion criteria were as follows: patients unable to perform cognitive or psychometric tests for any reason, patients who had cognitive dysfunction or scored less than 24 in mini-mental status examination, patients who showed delirium on admission, and patients who were treated with mechanical ventilation under sedation.After informed consent was obtained, data were collected from 561 patients. We collected demographic variables and information on 48 potential risk factors identified by reviewing previous studies , and negative predictive value (NPV) of the Delphi score.20 As 48 risk factors were identified, at least 480 patients were needed. We expected a drop-out rate of 20% and planned to enroll 600 patients in each part of the study. Of the 600 eligible patients, 39 patients were dropped and 561 patients (93.5%) were enrolled in the development study . For descriptive statistics, continuous variables were expressed as mean ± SD. Categorical data were expressed as number and percentage. For two-group comparisons, We used a backward stepwise logistic regression model to develop the Delphi score by assessing the association between each potential risk factor and the presence or absence of delirium. To calculate the Delphi score, regression coefficients for significant independent predictors were rounded to the nearest whole integer.The area under the curve (AUC) was calculated using receiver operating characteristic (ROC) curve analysis. Using the Youden index, we chose the optimal cut-off point as having the highest sensitivity and specificity to discriminate between high and low probability of postoperative delirium.In the validation study, we calculated the Delphi score of each patient in the validation cohort and calculated an AUC based on the new ROC. Finally, sensitivity, specificity, PPV, and NPV were calculated to examine how well the model performed for the prediction of delirium.The study protocol was approved by the ethical committee of Dong San Medical Center Hospital (IRB No. 2013-05-29-001). The study was performed according to the Declaration of Helsinki.The overall prevalence of delirium in the development cohort was 20.0% (112/561). Delirium developed in 50.0% of the patients on the day of operation, in 33.9% on postoperative day 1, in 8.9% on day 2, in 5.4% on day 3, and in 1.8% on day 4. The mean duration of delirium was 3.2 ± 2.5 days.2), low nutritional risk screening score, hearing impairment, atrial fibrillation, history of cerebrovascular accident, chronic kidney disease, sleep disorders, depression, multiple comorbidities, history of delirium, high ASA score, benzodiazepine medication, neuroleptic medication, opioid analgesics, and multiple medications. Precipitating factors were emergency surgery, open surgery, multiple indwelling catheters, postoperative opioid analgesics, intensive care unit (ICU) admission, and admission to emergency room. Analysis of preoperative laboratory test results showed that high levels of C-reactive protein, leukocytosis, increased urine specific gravity, low hemoglobin, hyponatremia, hypokalemia, low serum protein, and low serum albumin were significant risk factors for postoperative delirium  Figure A. The maWe validated the developed Delphi score prospectively. No statistical differences were found between the development and validation cohorts in terms of the distribution of the 9 predictors of postoperative delirium Table . The calWe divided the validation group into low- and high-risk groups with the Delphi scores of 0 to 6 and 7 to 15, respectively. The sensitivity of the delirium prediction model was 80.8%, specificity 92.5%, positive predictive value 70.2%, and negative predictive value 95.7%  score. We found that prognostic information was contained in 9 predictors: age, low physical activity, hearing impairment, heavy alcoholism, history of prior delirium, ICU admission, emergency surgery, open surgery, and increased preoperative CRP. If a patient had a Delphi score 7 or more, the probability of delirium development was 80.8%.21 Nonpharmacological prevention is widely accepted as an effective strategy for delirium in older hospital patients. Marcantonio et al suggested that proactive intervention reduces delirium by over 1/3 and severe delirium by over 1/2.22 Recent guidelines recommended delirium prevention activity in persons at risk.23 Since medical resources are limited, it is important to determine for whom intervention is required to prevent delirium, and this can be achieved by using the Delphi score.Studies of pharmacological approaches to delirium prevention did not have convincing and reproducible evidence of effectiveness yet.This study was started by reviewing the published literature to search for potential risk factors for postoperative delirium because we thought that the delirium prediction score would be more reliable if it includes already identified risk factors. All of the 9 identified predictors were described in the prior literature as risk factors for postoperative delirium. Other factors evaluated in this study had no added value for the prediction of postoperative delirium when the nine predictors were taken into account, which, however, does not mean that these factors are not important.This study has several limitations. First, as it did not include orthopedic, obstetric, or neurosurgery patients, our results cannot be easily generalized to all surgical patients. The departments that treat the above groups of patients had a similar increase in the numbers of elderly patients, and we need to validate the Delphi score for patients from these departments. Second, the Delphi score has been validated internally but not yet externally in another population. Third, we used a cut-off value to discriminate between high- and low-risk patients. However, the risk of postoperative delirium is actually not dichotomous but continuous. Last, there could be a potential misdiagnosis for the hypoactive delirium without psychomotor behavioral changes, because their symptoms are passive and might be delayed.An important strength of this study is that it was a prospective study that enrolled general surgery patients and that the predictors in our model are well-defined and easily measured clinical variables. Although this model has not yet been validated externally in other hospitals, the Delphi score showed a high predictive value in our internal validation study.Our proposed Delphi score, which is based on easily available patients’ and clinical information, could help surgeons and nursing staff to predict the development of delirium in postoperative patients and make possible targeted delirium prevention in the high-risk group. Further studies are needed to validate this score and to assess its clinical usefulness.


Creating a supportive environment encourages charity services to help risk groups and individuals which has magnificent impacts on reducing their harm.According to this plan, the purpose of this study was to investigate the mental health status in the staff of harm reduction centers.The clustered sample of this comparative study consisted of 49 staff of harm reduction centers. The study was supported by the United Nations Development Program in Tehran, Iran. The participants completed GHQ-28 and DASS-21 questionnaires along with sociologic forms and the results were evaluated by descriptive statistics indexes and independent sample t-test.One-hundred percent of the participants in this study showed the symptoms of psychological disorders, and approximately 16 percent suffered from moderate to high degree of anxiety, depression and stress. The level of anxiety (P ˂ 0.04) and stress (P ˂ 0.01) in the younger staff (less than 40 years) was significantly higher than older staff (more than 40 years old). In addition, somatic symptoms (P ˂ 0.05) and social withdrawal (P ˂ 0.01) were significantly higher in women than men.Accordingly, major mental disorders in the staff of harm reduction centers, especially women and younger people need to be considered more than before. In 2004, the World Health Organization (WHO) suggested to perform developed interventions for harm reduction to prevent HIV outbreak in all countries. One of the harm reduction programs in Iran is run jointly by AIDS Prevention and Control Committee, Welfare Organization State, Behavioral Sciences Research Center, Baqiyatallah University of Medical Sciences and backed by the financial support of global fund to fight aids, tuberculosis and malaria (GFATM) and United Nations Development Programme (UNDP). In these centers HIV/AIDS prevention education is provided for people with high risk behaviors such as intravenous drug use or unprotected sex. Harm reduction among high risk behavior people with HIV/AIDS is one of the preventive strategies to reduce unhealthy impacts on the society and economy. Harm reduction interventions include educating the people with high risk behavior and providing them with syringes, condoms, and alternative treatments for opioids and so on , 2. RegaEffective approaches to reduce harms are as follows: - Promoting health actions through applying the general policies of health promotion and AIDS prevention.- Creating a supportive environment for people at risk and/or with high risk behaviors.- Familiarizing health centers with AIDS prevention services and principles.- Contributing actively in the developing and strengthening personal skills in decision making.- Communicating with others, adopting assertive decision and changing high risk behaviors .Therefore, creating a supportive environment  to build trust and provide services have a significant effect on HIV prevalence reduction ; a signiBut, one of the main problems of addicts is communicating with non-addicts who live with them , so dealSince mental health is a significant factor in preventing social problems such as addiction to alcohol, drugs, and gambling , the curAccording to this plan, the purpose of this study was to investigate the mental health status in the staff of harm reduction centers.In the current comparative study, the subjects were the staff of harm reduction centers of UNDP Global Fund project in Iran selected by cluster sampling method: 49 subjects including 34 (69.4%) men and 15 (30.6%) women. The centers were as follows: Shosh, Fallah, Rey-Nafarabad, Rey-Sarcheshme, Khaniabad, Valiasr Town, Jannatabad, Ostad Moein and Sadeghieh. Data collection tools were general health questionnaire (GHQ-28), and depression, anxiety and stress scale (DASS-21). This questionnaire was designed by Goldberg and Hillier in 1979 and is the most widely used tool for general screening in mental health which included 28 questions with Likert scoring as A = 0, B = 1, C = 2, and D = 3 . The valGibbons et al. identified four factors including physical symptoms, anxiety, insomnia, social functioning disorder, and depression among a student population sample . The higIn the current study, according to the Fathiashtiani and Dastani  and YaghValidity and reliability of this scale have been evaluated in Iranian population by Asghari Moghaddam et al. . They coThe correlation between DASS depression subscale and Beck’s depression scale was 0.69, and between DASS depression subscale and anxiety subscale, four-system anxiety, was 0.62. In factor analysis results, the three-factor model  was able to explain the data better than other models. Generally, three-factor model explained 54.04% of variance. In the current study, according to Fathiashtiani and Dastani DASS-21 cut-off points are higher than 10.5 for depression subscale, higher than 7.5 for anxiety subscale, and higher than 13 for stress subscale which showed the higher level of the disorder .The results of statistical descriptive tests and t test in independent groups were evaluated by statistical package for the social science version 18.Descriptive results from demographic features indicated that 49% of subjects were single, 46.9% married, and 2% divorced. Also, 12.5% had a bachelor or higher degrees, 8.2% associate degree, 26.5% high school diploma and 38.13% lower degrees . Analyzing descriptive indexes of depression, anxiety and stress (DASS-21) scores of staff of harm reduction centers showed that 16% suffered from severe and higher level of anxiety, 16.3% had severe and higher level of depression, and 16.3% with severe and higher level of stress. Also, according to the GHQ questionnaire, 100% of the subjects suffered from some symptoms of psychological disorders, such as physical disorders, anxiety, socio-occupational disorders and depression . Comparing the level of anxiety, depression, stress and general health among the staff of harm reduction centers, according to the demographic features showed that the level of anxiety (P ˂ 0.04) and stress (P ˂ 0.01) among the staff younger than 40 were significantly higher than those of over 40. Level of physical disorders and insomnia (P ˂ 0.05), and socio-occupational disorders (P ˂ 0.01) in women staff of harm reduction centers were significantly higher than men . Investigation on mental health status of the staff of Tehran harm reduction centers showed that all of them suffered from mental health disorders, and almost 16% experienced serious levels of depression, anxiety and stress. Also, the levels of physical and socio-occupational disorders in women were significantly higher than fellow men. Besides, the results of the present study showed that the levels of anxiety and stress among staff younger than 40 years old were significantly higher than staff over 40 years old.According to the 23 cut-off point  and FathIn the current study, mental health status of women staff was worse than that of fellow men. Asad Zandi et al. reported that psychological problems of women staff were more severe than those of men staff; a finding that is consistent with our present study . RegardiIn this study, women showed more physical-insomnia and socio-occupational disorders. Mohammadian et al.  in theirThis study showed that the staff of harm reduction centers suffered from considerable psychological problems. Accordingly, it seems reasonable that taking actions is necessary to improve the level of mental health in their staff. Thereby, the status of mental health in the staff of harm reduction centers , was sigMental health differences between men and women staff of harm reduction centers are compatible with the findings of the previous researches who studied this subject from theoretical aspect, or in other words, socio-occupational disorders. Thus, female nurses suffer from mental health disorders more than men , and theHence, it is necessary to consider more protective strategies for women staff in harm reduction centers, and preferably choose men for such jobs. Finally, Garousifarshi and Mani  showed t


Trifolium repens L. and in tree canopies of peach orchards with and without the ground cover plant T. repens. No significant differences were found in the abundances of the main groups of arthropod pests and predators in T. repens between Hudai and Xinchang. The abundance, richness, Simpson's index, Shannon-Wiener index, and Pielou evenness index of canopy predators in ground cover areas increased by 85.5, 27.5, 3.5, 16.7, and 7.9% in Xinchang, and by 87.0, 27.6, 3.5, 17.0 and 8.0% in Hudai compared to those in the controls, respectively. The average abundance of Lepidoptera, Coleoptera, Homoptera, true bugs and Acarina canopy pests in ground cover areas decreased by 9.2, 10.2, 17.2, 19.5 and 14.1% in Xinchang, and decreased by 9.5, 8.2, 16.8, 20.1 and 16.6% in Hudai compared to that in control areas, respectively. Our study also found a higher density of arthropod species resources in T. repens, as some omnivorous pests and predators residing in T. repens could move between the ground cover and the orchard canopy. In conclusion, ground cover in peach orchards supported the enemies hypothesis, as indicated by the fact that ground cover T. repens promoted the abundance and diversity of predators and reduced the number of arthropod pests in tree canopies in both geographical areas.Many studies have supported the enemies hypothesis, which suggests that natural enemies are more efficient at controlling arthropod pests in polyculture than in monoculture agro-ecosystems. However, we do not yet have evidence as to whether this hypothesis holds true in peach orchards over several geographic locations. In the two different geographic areas in eastern China  during a continuous three-year (2010–2012) investigation, we sampled arthropod pests and predators in  The enemies hypothesis argues that natural enemies are more effective at controlling arthropod pests in diverse ecosystems than in simple ones Ground cover vegetation, as an important diversified plantation model 4 ha and peach yield of 1.8×108 kg, and Jiangsu, with an annual peach cultivation area of 3.2×104 ha and a peach yield of 3.5×108 kg, have acquired national recognition as peach growing areas.China has the largest peach plantings and the largest production of peaches in the world. Shanghai municipality and Jiangsu province in eastern China are the two most important peach-growing regions: both Shanghai, with an annual peach cultivation area of 1.5×10Trifolium repens L.) was selected as a useful approach to enhance soil fertility in orchards The use of ground cover vegetation in peach orchards began in China in the 1990s and was gradually applied nationwide. Recently, the use of a clover ground cover , Lepidoptera, true bugs, Acarina and Coleoptera, while the predators in T. repens mainly included Araneida, Coleoptera, Neuroptera, Diptera and Hemiptera. In additional, we found that these species provided an excellent pool for canopy arthropods in peach orchards T. repens and in the peach canopy differing between the two different geographic locations in eastern China have not been examined, and whether T. repens ground cover enhances the level of control exerted by predators on the abundance of key pests in the orchard canopies has not been tested.In our former study in Shanghai municipality and Jiangsu province in eastern China, we observed that the arthropod pests in T. repens played, and whether the abundance of the main groups of arthropod pests and predators in T. repens were different between the two geographical areas studied; (2) whether the abundance and diversity of predators in canopy orchards were enhanced by the use of clover ground cover and whether this difference varied between the two locations; and (3) whether the abundance of the main groups of arthropod pests in canopy orchards was inhibited by manipulation of T. repens ground cover and whether this differed between the two locations. If this hypothesis proved true, the use of ground cover to favor indigenous predators would be a more sustainable approach to controlling arthropod pests than the input of insecticides or exotic control agents in eastern China, or indeed in other agricultural areas.This study, therefore, sought to test the enemies hypothesis in peach orchards in the two different sites in eastern China. In particular, we sought to determine: (1) what effect the pool of predators and pests in The Guoyuan village of Xinchang town in Shanghai municipality and Longyan village of Hudai town in Jiangsu province issued permission for the experiments in each location. No vertebrates were studied, as our study involved only arthropods .This experiment was conducted in two locations: one in Xinchang town, Pudong district, Shanghai municipality of China , and the other in Hudai town, Wuxi district, Jiangsu Province of China . The two sites were both located in the Yangtze River delta alluvial plain, the Hudai site near Taihu Lake (the second largest freshwater lake in China), and the Xinchang site near the Yangtze River, 20 kilometers away from the first site. The sites share a similar climate, both belonging to the prevailing zone of the East Asian monsoon in the southern rim of North Asian tropics. Peach varieties were “Hujing” honey peach in Hudai and “Xinfeng” honey peach in Xinchang, both mid-season maturing varieties with 8–10 year-old trees that were 2–2.5 m high, and arranged in a 4×4 m grid.2), and separated from adjacent plots by a 100 m long isolation belts. Treatment areas were seeded with a ground cover of the biennial clover T. repens, which was mowed twice a year to a height of about 10 cm. Control areas in the orchards were bare ground without weeds (which were pulled by hand) under the trees. Farm management and operation methods, including pest management, were identical between treatment and control plots in each orchard. Pest management in peach orchards mainly relies on physical and manual means, such as trimming of diseased and pest-infested peach branches and shoots in winter, fruit bagging in June, trapping insect pests in pheromone traps, and spraying with 4–5 Baume lime sulfur during the dormant period.A randomized block design was used in this experiment, and each treatment and the control were replicated three times in both Xinchang and Hudai. Thirty peach trees were sampled for each replicate to calculate the abundance and diversity of predators and the abundances of pest arthropods. Each plot was 100 m wide and 52 m long  in the area beneath each treatment in each peach orchard. Sample locations were spaced equidistant along the Z transect, at 12 m intervals. Each sampling location was a 1 m2 area defined by a wire frame. The arthropods in the T. repens ground cover were beaten by hand into a white porcelain tray (0.3 m×0.4 m) and were then immediately classified to species and the numbers of individuals within orders was counted.Sampling to measure the densities of the predators and pests in the T. repens ground cover at each of the seven sample points per treatment replicate. Any unidentified species in the orchards and in the T. repens were collected in vials of 80% alcohol, counted and labeled for later identification in the laboratory. Sampling was done ca every 10 days, from late March to early October in 2010, 2011, and 2012 (with some delays because of rain or other contingencies), for a total of nineteen sample dates per year.Approximately 3–5 minutes were needed to collect the canopy arthropods and count the individuals of each species at each canopy level, choosing one representative twig (20–30 cm long) from each zone in each tree. Each twig from the base to the tip was intensively examined to count all the arthropods present. In addition, 3–5 minutes were taken to collect the arthropods in the T. repens ground cover into five main groups  and similarly for the predators from the T. repens ground cover as Araneida, Coleoptera, Neuroptera, Diptera, or Hemiptera. The species composition of arthropod pests and predators collected from the T. repens ground cover can be found in In most cases, we classified the arthropod pests collected in the T. repens. Abundance, species richness, Simpson's index, Shannon-Wiener index, and the Pielou evenness index were used to measure the diversity of predators. We also classified the arthropod pests collected in tree canopies into five main groups as Lepidoptera, mainly including Ortricidae, Lyonetiidae, Pyralididae, Sphingidae, Carposinidae, Noctuidae, Cossidae, Limacodidae, Psychidae, Lymantridae, Saturniidae, Pieridae and Carposinidae: Coleoptera, mainly including Curculionidae, Cetoniidae, Rutelidae, Melolonthidae and Cerambycidae: Homoptera mainly including Aphididae, Cicadellidae, Cicadidae, Fulgoridae, Coccidae, Margarodidae, Diaspididae and Aleyrodidae: true bugs, mainly including Pentatomidae, Miridae, Tingidae and Coreidae and Acarina, mainly including Tetranychidae. The species composition of arthropod pests and predators in tree canopies can be found in Data from each canopy sample in each plot were collated and entered into a relational database with basic information on the predators  and on the samples . Results from the thirty sampled peach trees for each replicate in each of treatment and control area over three years (2010–2012) in Xinchang and Hudai were used to calculate the diversity indices of predators in the canopy of peach orchards with or without the ground cover plant T. repens ground cover. The sites were Xinchang and Hudai; the years were 2010, 2011, and 2012; the orchard types were ground cover or bare ground, and the interactive effects involved were site × year, site × orchard type, year × orchard type, and site × year × orchard type. If the values of the diversity indices of canopy predators and the abundance of canopy pests were not significantly affected by the years with the above three-factor analysis of variance, we took the three years of data as a whole to compare the differences among means related to treatment and control in Xinchang and in Hudai, respectively, with Tukey's Honestly Significant Difference (HSD) test at the 0.05 level. If the values of the abundance of the main groups of arthropod pests and predators in T. repens ground cover plots were not significantly affected by the years with the above two-factor analysis of variance, we again took the three years of data as a whole to compare the differences among means between Xinchang and Hudai, respectively, with independent samples t-test at the 0.05 level.Statistical analyses were performed using the Statistical Analysis Systems software . Normal distribution and homocedasticity of all data were checked by the Kolmogorow-Smirnov test and Levene test, respectively. Three-factor analysis of variance with General Linear Model was adopted to analyze the diversity indices of canopy predators and the number of the main groups of canopy arthropod pests, so as to compare the interactive effects of different sites, years, and orchard types on the diversity of canopy predators and the abundance of the main arthropod pests. Two-factor (site and year) analysis of variance with General Linear Model was used to analyze the number of the main groups of arthropod pests and predators in The factors of site and year had no significant effects on the abundance of arthropod pests of Lepidoptera, Homoptera, true bugs, Acarina or Coleoptera, and the same effects were indicated by the interactions of the two factors . NeitherT. repens ground cover in Xinchang were all lower, while that of Coleoptera was slightly higher, than that in Hudai, but these differences were not significant   .T. repens ground cover were both lower in Xinchang than in Hudai, these differences were not significant   .T. repens ground cover were similar for Xinchang and Hudai. In both sites, the abundances of pest Homoptera, Lepidoptera, true bugs, Acarina, and Coleoptera, as well as that of the predacious Araneida, Coleoptera, Neuroptera, Diptera, and Hemiptera increased during spring but stabilized thereafter  and of all three factors (site × year × orchard type) on the diversity indices were also not significant, respectively .F3, 224 = 31.694, P<0.001; richness: F3, 224 = 149.374, P<0.001; Simpson's index: F3, 224 = 241.408, P<0.001; Shannon-Wiener index: F3, 224 = 304.400, P<0.001; Evenness: F3, 224 = 674.945, P<0.001)  .The five diversity indices of canopy predator communities were consistently higher in ground cover areas than control areas. Irrespective of ground cover, all diversity indices increased during spring but stabilized thereafter in both sites .T. repens in peach orchards had significant effects on the numbers of pest Coleoptera, Homoptera, and true bugs, but no significant effects on the numbers of pest Lepidoptera or Acarina. The single factor of site had a significant effect on the number of Coleoptera pests, but no significant effect on the number of the other four groups of pests, while the single factor of year had no significant effect on the numbers of pests in any of the five groups. Similarly, none of the interactive factors  had any significant effects on the numbers of pests in any of the five groups   . HoweverP = 0.986; Coleoptera, P = 0.255; Homoptera, P = 0.984; true bug, P = 0.996; Acarina, P = 0.994). However, in control areas, while the difference in the number of Lepidoptera, Homoptera, true bugs, or Acarina pests between Xinchang and Hudai was not significant, the difference in the number of Coleoptera was significant   .The abundances of pests of all five groups of arthropods were consistently lower in ground cover than control areas. Irrespective of ground cover, the abundances of Coleoptera and true bugs increased during spring but stabilized thereafter, while the abundance of Acarina pests was relatively higher in the 7th–9th month with higher temperature, the abundance of Homoptera pests was highest in June, and the abundance of Lepidoptera pests was highest in August at both sites .Root T. repens, the richness and abundance of canopy predators increased by 27.5 and 85.5% in Xinchang and by 27.6 and 87.0% in Hudai, respectively. Similar studies found that the richness and abundance of predators increased by ground cover in pecan orchards Elymus trachycaulus) in maize fields Our results indicated that when the ground beneath peach orchards was covered with T. repens ground cover in Xinchang and in Hudai to be 53.7 and 49.0 individuals per m2, respectively, which provided a strong pool of predators potentially able to forage in tree canopies in peach orchards. The principal value of ground cover in orchards might be the movement of predators from the orchard floor to the trees, thus augmenting the richness and abundance of predators in trees. We observed, for instance, that predators such as spiders, ladybirds, lacewings, carabid beetles, and hoverflies could readily disperse from T. repens ground cover to the peach tree canopy, which might explain the higher diversity of predators in the orchard canopy.Ground cover vegetation can create a suitable ecological structure within the agricultural landscape to provide food resources for predators to feed and reproduce Medicago sativa) provided refuge to a range of coccinellid and hemipteran predators T. repens ground cover to avoid man-made disturbance when pathogen-infested peach branches or shoots were trimmed, and that adverse meteorological conditions (such as an abrupt drops of temperatures or severe rain) likewise caused predators to take shelter in the ground cover stratum.In addition, ground cover vegetation could also offer refuge for predators avoiding adverse influences from alien disturbance to ecosystems T. repens ground cover, such as harmful mites, noctuids, and whitefly Bemisia tabaci (Gennadius) , could transfer from T. repens to peach trees for feeding. Similarly, Gruys Tetranychus urticae Koch moved from clover into pecan trees.Some omnivorous arthropod pests resident in T. repens ground cover enhanced the ecological functions of predators to control pests in peach orchards Grapholitha molesta (Busck)) which makes peach shoots wither are the most serious insect pests in eastern China G. molesta decreased respectively by more than 30% both in Shanghai and Jiangsu. Meanwhile, the rate of pests bored into the peach sarcocarp  was decreased by more than 8% and the peach yield was increased by more than 5% in both sites.Among the main groups of arthropod pests, the aphids which make peach leaves curl and the oriental fruit moth  and 27 species of predators belonging to 16 families (5 orders) in Xinchang, and 45 species of arthropod pests belonging to 27 families (8 orders) and 29 species of predators belonging to 16 families (5 orders) in Hudai. The abundance of the main groups of arthropod pests and predators in T. repens was likewise not significantly affected by the two geographical locations. A more comprehensive, long-term and large-scale geographical distribution investigation of the potential ground cover vegetation in peach orchards is the logical next area of study.While geographical distribution might have a certain influence on species diversity and abundance Table S1The species composition of arthropod pest and predatory arthropod in T. repens in Xinchang  and in Hudai .(DOC)Click here for additional data file.Table S2The species composition of arthropod pests and predatory arthropods in peach orchards with and without ground cover T. repens in Xinchang  and in Hudai .(DOC)Click here for additional data file.