Mechanics-Aware Modeling of Cloth Appearance.

Micro-appearance models have brought unprecedented fidelity and details to cloth rendering. Yet, these models neglect fabric mechanics: when a piece of cloth interacts with the environment, its yarn and fiber arrangement usually changes in response to external contact and tension forces. Since subtle changes of a fabric's microstructures can greatly affect its macroscopic appearance, mechanics-driven appearance variation of fabrics has been a phenomenon that remains to be captured. We introduce a mechanics-aware model that adapts the microstructures of cloth yarns in a physics-based manner. Our technique works on two distinct physical scales: using physics-based simulations of individual yarns, we capture the rearrangement of yarn-level structures in response to external forces. These yarn structures are further enriched to obtain appearance-driving fiber-level details. The cross-scale enrichment is made practical through a new parameter fitting algorithm for simulation, an augmented procedural yarn model coupled with a custom-design regression neural network. We train the network using a dataset generated by joint simulations at both the yarn and the fiber levels. Through several examples, we demonstrate that our model is capable of synthesizing photorealistic cloth appearance in a mechanically plausible way.

Systematic meta-analyses, field synopsis and global assessment of the evidence of genetic association studies in colorectal cancer.

OBJECTIVE: To provide an understanding of the role of common genetic variations in colorectal cancer (CRC) risk, we report an updated field synopsis and comprehensive assessment of evidence to catalogue all genetic markers for CRC (CRCgene2). DESIGN: We included 869 publications after parallel literature review and extracted data for 1063 polymorphisms in 303 different genes. Meta-analyses were performed for 308 single nucleotide polymorphisms (SNPs) in 158 different genes with at least three independent studies available for analysis. Scottish, Canadian and Spanish data from genome-wide association studies (GWASs) were incorporated for the meta-analyses of 132 SNPs. To assess and classify the credibility of the associations, we applied the Venice criteria and Bayesian False-Discovery Probability (BFDP). Genetic associations classified as 'positive' and 'less-credible positive' were further validated in three large GWAS consortia conducted in populations of European origin. RESULTS: We initially identified 18 independent variants at 16 loci that were classified as 'positive' polymorphisms for their highly credible associations with CRC risk and 59 variants at 49 loci that were classified as 'less-credible positive' SNPs; 72.2% of the 'positive' SNPs were successfully replicated in three large GWASs and the ones that were not replicated were downgraded to 'less-credible' positive (reducing the 'positive' variants to 14 at 11 loci). For the remaining 231 variants, which were previously reported, our meta-analyses found no evidence to support their associations with CRC risk. CONCLUSION: The CRCgene2 database provides an updated list of genetic variants related to CRC risk by using harmonised methods to assess their credibility.

Gene-environment interactions and colorectal cancer risk: An umbrella review of systematic reviews and meta-analyses of observational studies.

The cause of colorectal cancer (CRC) is multifactorial, involving both genetic variants and environmental risk factors. We systematically searched the MEDLINE, EMBASE, China National Knowledge Infrastructure (CNKI) and Wanfang databases from inception to December 2016, to identify systematic reviews and meta-analyses of observational studies that investigated gene-environment (G×E) interactions in CRC risk. Then, we critically evaluated the cumulative evidence for the G×E interactions using an extension of the Human Genome Epidemiology Network's Venice criteria. Overall, 15 articles reporting systematic reviews of observational studies on 89 G×E interactions, 20 articles reporting meta-analyses of candidate gene- or single-nucleotide polymorphism-based studies on 521 G×E interactions, and 8 articles reporting 33 genome-wide G×E interaction analyses were identified. On the basis of prior and observed scores, only the interaction between rs6983267 (8q24) and aspirin use was found to have a moderate overall credibility score as well as main genetic and environmental effects. Though 5 other interactions were also found to have moderate evidence, these interaction effects were tenuous due to the lack of main genetic effects and/or environmental effects. We did not find highly convincing evidence for any interactions, but several associations were found to have moderate strength of evidence. Our conclusions are based on application of the Venice criteria which were designed to provide a conservative assessment of G×E interactions and thus do not include an evaluation of biological plausibility of an observed joint effect.

Effect of childhood BMI on asthma: a systematic review and meta-analysis of case-control studies.

BACKGROUND: Asthma is a multifactorial syndrome that threatens the health of children. Body mass index (BMI) might be one of the potential factors but the evidence is controversial. The aim of this study is to perform a comprehensive meta-analysis to investigate the association between asthma and BMI. METHODS: Electronic databases including, Web of Science, Pubmed, Scopus, Science Direct, ProQuest, up to April 2017, were searched by two researchers independently. The keywords "asthma, body mass index, obesity, overweight, childhood and adolescence" were used. Random and fixed effects models were applied to obtain the overall odds ratios (ORs) and standardized mean difference (SMD). Heterogeneity between the studies was examined using I2 and Cochrane Q statistics. RESULTS: After reviewing 2511 articles, 16 studies were eligible for meta-analysis according to inclusion/exclusion criteria. A meta-analysis from 11 case-control studies revealed OR of asthma and overweight as OR = 1.64; (95% Confidence Interval (CI): 1.13-2.38) and from 14 case-control studies, OR for asthma and obesity was OR = 1.92 (95% CI: 1.39-2.65), which indicated that risk of asthma in overweight and obese children and adolescence was significantly higher (1.64 and 1.92 times) than that of individuals with (p-value < 0.01 for underweight/normal weight in both cases). Furthermore, there was a significant relationship between asthma and BMI > 85 percentile according to SMD SMD = 0.21; (95%CI: 0.03-0.38; p-value = 0.021). CONCLUSIONS: The results showed a significant relationship between BMI (obesity/overweight) and asthma among children and adolescents. It is important to study the confounding factors that affect the relationship between asthma and BMI in future epidemiological researches.

Prevalence of low back pain in Iranian nurses: a systematic review and meta-analysis.

BACKGROUND: Low back pain (LBP) as a musculoskeletal disorder is one of the most common occupational injuries in nurses but there isn't any valid measure of the prevalence of LBP in Iranian nursing. In order to increase the power and improve the estimates of the prevalence of LBP in Iranian nurses, a comprehensive meta-analysis was carried out. A summary measure of all studies conducted in this field was found and distributions of LBP were evaluated based on different variables. METHODS: Inclusion criteria included articles with prevalence of LBP in Iranian nurses, who had at least six months of work experience without any trauma, injuries to spine, or any underlying disease. The keywords"prevalence, low back pain, nurses", and "Iran" were used as part of this search. Databases such as Pubmed, Web of Science, Science direct, Scopus, IranMedex, Irandoc, Magiran, SID, CIVILICA, IMEMR and Google scholar were searched up to and including 15 June 2016. For data extraction a form was designed that included the following variables: Author names, province, sample size, age, gender, marital status, work experience, body mass index, job type, smoking status, work schedule, year of publication, type of standard questionnaire, prevalence of LBP, studies' quality score and climate classifications. Data analysis was carried out using fixed and random effects model. Heterogeneity between studies was assessed by using the I2 and Q tests. RESULTS: In all 1250 articles were identified and 22 articles with 9347 participants met the inclusion criteria for meta-analyses after filtering. The prevalence of low back pain during their working life and during the last year, was estimated at 63% (95% Confidence Interval (CI): 57.4-68.5) and 61.2% (95% CI: 55.7-66.7) respectively. The prevalence rate of this disorder was 58.7% (95% CI: 35.8-81.7) and 60.4% (95% CI: 52.2-68.6) among men and women respectively. Furthermore, prevalence's of LBP were 59.5% in wards nurses, 50.3% in operating room technicians, and 39.4% in aid nurses. CONCLUSIONS: The results showed the high prevalence of LBP injury in nurses, especially female nurses. The effect of musculoskeletal disorders such as LBP may be reduced by considering proper observation of the principles of ergonomics in the workplace, performing physical examinations on a regular basis, identifying risk factors in the advancement of musculoskeletal disorders and then trying to fix them.

Waterpipe smoking and cancer: systematic review and meta-analysis.

OBJECTIVE: Although accumulating evidence suggests harmful effects of waterpipe smoking, there is limited information about its direct association with chronic diseases, notably cancer. We provide an up-to-date systematic review and meta-analysis of the association between waterpipe smoking and cancer. DATA SOURCES: Systematic search of articles indexed in main biomedical databases: Pubmed, EmBase, Google Scholar and Web of Science, published between 1962 and September 2014. Search keywords included a combination of waterpipe or hookah, sheesha, nargile, hubble-bubble, goza or gaylan, and cancer. STUDY SELECTION: Focus on observational studies (cohort, case-control, cross-sectional) that evaluated the association between waterpipe smoking and cancer. Studies with mixed exposures excluded. DATA EXTRACTION: Two investigators independently extracted data and reached consensus on all items. DATA SYNTHESIS: 13 case-control studies met the inclusion criteria and were considered for meta-analysis. The methodological quality of included studies was assessed using the Newcastle-Ottawa Scale (NOS). Meta-analysis revealed a positive association between waterpipe smoking and lung cancer (OR=4.58 (2.61 to 8.03); I2=44.67%), and oesophageal cancer (OR=3.63 (1.39 to 9.44); I2 =94.49%). The majority of studies had a NOS score of 5-6 or 7, indicating 'fair' or 'good' quality, respectively. CONCLUSIONS: Our findings support a positive association between waterpipe smoking and cancer risk. However, high-quality studies with standardised exposure measurements are needed to clarify the contribution of waterpipe smoking to chronic diseases. More investments in initiatives for surveillance, intervention and regulatory policy for waterpipe smoking are urgently warranted.

Systematic meta-analyses and field synopsis of genetic association studies in colorectal adenomas.

BACKGROUND: Low penetrance genetic variants, primarily single nucleotide polymorphisms, have substantial influence on colorectal cancer (CRC) susceptibility. Most CRCs develop from colorectal adenomas (CRA). Here we report the first comprehensive field synopsis that catalogues all genetic association studies on CRA, with a parallel online database [http://www.chs.med.ed.ac.uk/CRAgene/]. METHODS: We performed a systematic review, reviewing 9750 titles, and then extracted data from 130 publications reporting on 181 polymorphisms in 74 genes. We conducted meta-analyses to derive summary effect estimates for 37 polymorphisms in 26 genes. We applied the Venice criteria and Bayesian False Discovery Probability (BFDP) to assess the levels of the credibility of associations. RESULTS: We considered the association with the rs6983267 variant at 8q24 as 'highly credible', reaching genome-wide statistical significance in at least one meta-analysis model. We identified 'less credible' associations (higher heterogeneity, lower statistical power, BFDP > 0.02) with a further four variants of four independent genes: MTHFR c.677C>T p.A222V (rs1801133), TP53 c.215C>G p.R72P (rs1042522), NQO1 c.559C>T p.P187S (rs1800566), and NAT1 alleles imputed as fast acetylator genotypes. For the remaining 32 variants of 22 genes for which positive associations with CRA risk have been previously reported, the meta-analyses revealed no credible evidence to support these as true associations. CONCLUSIONS: The limited number of credible associations between low penetrance genetic variants and CRA reflects the lower volume of evidence and associated lack of statistical power to detect associations of the magnitude typically observed for genetic variants and chronic diseases. The CRA gene database provides context for CRA genetic association data and will help inform future research directions.

Deamination intensity profiling of human APOBEC3 protein activity along the near full-length genomes of HIV-1 and MoMLV by HyperHRM analysis.

Enzymatic deamination of cytidines in DNA is an intrinsic component of antibody maturation and retroviral resistance, but can also be a source of HIV drug resistance and cancer-causing mutations. Here, we developed a high-throughput method based on high resolution melt (HRM) analysis called HyperHRM that can screen genomic DNA for rare hypermutated proviral sequences and accurately quantify the number of C-to-T or G-to-A mutations in each sequence. We demonstrate the effectiveness of the approach by profiling in parallel the intensity of the DNA mutator activity of all seven human APOBEC3 proteins on the near full-length sequence of HIV-1 and the Moloney murine leukemia virus. Additionally, HRM was successfully used to identify hypermutated proviral sequences in peripheral blood mononuclear cells from an HIV-1 patient. These results exemplify the effectiveness of HRM-based approaches for hypermutation quantification and for the detection of hypermutated DNA sequences potentially associated with disease or retroviral drug resistance.

Systematic meta-analyses and field synopsis of genetic association studies in colorectal cancer.

BACKGROUND: Colorectal cancer is a major global public health problem, with approximately 950,000 patients newly diagnosed each year. We report the first comprehensive field synopsis and creation of a parallel publicly available and regularly updated database (CRCgene) that catalogs all genetic association studies on colorectal cancer (http://www.chs.med.ed.ac.uk/CRCgene/). METHODS: We performed two independent systematic reviews, reviewing 10 145 titles, then collated and extracted data from 635 publications reporting on 445 polymorphisms in 110 different genes. We carried out meta-analyses to derive summary effect estimates for 92 polymorphisms in 64 different genes. For assessing the credibility of associations, we applied the Venice criteria and the Bayesian False Discovery Probability (BFDP) test. RESULTS: We consider 16 independent variants at 13 loci (MUTYH, MTHFR, SMAD7, and common variants tagging the loci 8q24, 8q23.3, 11q23.1, 14q22.2, 1q41, 20p12.3, 20q13.33, 3q26.2, 16q22.1, and 19q13.1) to have the most highly credible associations with colorectal cancer, with all variants except those in MUTYH and 19q13.1 reaching genome-wide statistical significance in at least one meta-analysis model. We identified less-credible (higher heterogeneity, lower statistical power, BFDP >0.2) associations with 23 more variants at 22 loci. The meta-analyses of a further 20 variants for which associations have previously been reported found no evidence to support these as true associations. CONCLUSION: The CRCgene database provides the context for genetic association data to be interpreted appropriately and helps inform future research direction.

Shrinkage estimation of effect sizes as an alternative to hypothesis testing followed by estimation in high-dimensional biology: applications to differential gene expression.

Research on analyzing microarray data has focused on the problem of identifying differentially expressed genes to the neglect of the problem of how to integrate evidence that a gene is differentially expressed with information on the extent of its differential expression. Consequently, researchers currently prioritize genes for further study either on the basis of volcano plots or, more commonly, according to simple estimates of the fold change after filtering the genes with an arbitrary statistical significance threshold. While the subjective and informal nature of the former practice precludes quantification of its reliability, the latter practice is equivalent to using a hard-threshold estimator of the expression ratio that is not known to perform well in terms of mean-squared error, the sum of estimator variance and squared estimator bias. On the basis of two distinct simulation studies and data from different microarray studies, we systematically compared the performance of several estimators representing both current practice and shrinkage. We find that the threshold-based estimators usually perform worse than the maximum-likelihood estimator (MLE) and they often perform far worse as quantified by estimated mean-squared risk. By contrast, the shrinkage estimators tend to perform as well as or better than the MLE and never much worse than the MLE, as expected from what is known about shrinkage. However, a Bayesian measure of performance based on the prior information that few genes are differentially expressed indicates that hard-threshold estimators perform about as well as the local false discovery rate (FDR), the best of the shrinkage estimators studied. Based on the ability of the latter to leverage information across genes, we conclude that the use of the local-FDR estimator of the fold change instead of informal or threshold-based combinations of statistical tests and non-shrinkage estimators can be expected to substantially improve the reliability of gene prioritization at very little risk of doing so less reliably. Since the proposed replacement of post-selection estimates with shrunken estimates applies as well to other types of high-dimensional data, it could also improve the analysis of SNP data from genome-wide association studies.

Gene network reconstruction from transcriptional dynamics under kinetic model uncertainty: a case for the second derivative.

MOTIVATION: Measurements of gene expression over time enable the reconstruction of transcriptional networks. However, Bayesian networks and many other current reconstruction methods rely on assumptions that conflict with the differential equations that describe transcriptional kinetics. Practical approximations of kinetic models would enable inferring causal relationships between genes from expression data of microarray, tag-based and conventional platforms, but conclusions are sensitive to the assumptions made. RESULTS: The representation of a sufficiently large portion of genome enables computation of an upper bound on how much confidence one may place in influences between genes on the basis of expression data. Information about which genes encode transcription factors is not necessary but may be incorporated if available. The methodology is generalized to cover cases in which expression measurements are missing for many of the genes that might control the transcription of the genes of interest. The assumption that the gene expression level is roughly proportional to the rate of translation led to better empirical performance than did either the assumption that the gene expression level is roughly proportional to the protein level or the Bayesian model average of both assumptions. AVAILABILITY: http://www.oisb.ca points to R code implementing the methods (R Development Core Team 2004). SUPPLEMENTARY INFORMATION: http://www.davidbickel.com.