Correcting misclassification errors in crowdsourced ecological data: A Bayesian perspective

Many research domains use data elicited from "citizen scientists" when a direct measure of a process is expensive or infeasible. However, participants may report incorrect estimates or classifications due to their lack of skill. We demonstrate how Bayesian hierarchical models can be used to learn about latent variables of interest, while accounting for the participants' abilities. The model is described in the context of an ecological application that involves crowdsourced classifications of georeferenced coral-reef images from the Great Barrier Reef, Australia. The latent variable of interest is the proportion of coral cover, which is a common indicator of coral reef health. The participants' abilities are expressed in terms of sensitivity and specificity of a correctly classified set of points on the images. The model also incorporates a spatial component, which allows prediction of the latent variable in locations that have not been surveyed. We show that the model outperforms traditional weighted-regression approaches used to account for uncertainty in citizen science data. Our approach produces more accurate regression coefficients and provides a better characterization of the latent process of interest. This new method is implemented in the probabilistic programming language Stan and can be applied to a wide number of problems that rely on uncertain citizen science data.Comment: 18 figures, 5 table

Clinical and genetic characterisation of dystrophin-deficient muscular dystrophy in a family of Miniature Poodle dogs

Four full-sibling intact male Miniature Poodles were evaluated at 4–19 months of age. One was clinically normal and three were affected. All affected dogs were reluctant to exercise and had generalised muscle atrophy, a stiff gait and a markedly elevated serum creatine kinase activity. Two affected dogs also showed poor development, learning difficulties and episodes of abnormal behaviour. In these two dogs, investigations into forebrain structural and metabolic diseases were unremarkable; electromyography demonstrated fibrillation potentials and complex repetitive discharges in the infraspinatus, supraspinatus and epaxial muscles. Histopathological, immunohistochemical and immunoblotting analyses of muscle biopsies were consistent with dystrophin-deficient muscular dystrophy. DNA samples were obtained from all four full-sibling male Poodles, a healthy female littermate and the dam, which was clinically normal. Whole genome sequencing of one affected dog revealed a >5 Mb deletion on the X chromosome, encompassing the entire DMD gene. The exact deletion breakpoints could not be experimentally ascertained, but we confirmed that this region was deleted in all affected males, but not in the unaffected dogs. Quantitative polymerase chain reaction confirmed all three affected males were hemizygous for the mutant X chromosome, while the wildtype chromosome was observed in the unaffected male littermate. The female littermate and the dam were both heterozygous for the mutant chromosome. Forty-four Miniature Poodles from the general population were screened for the mutation and were homozygous for the wildtype chromosome. The finding represents a naturally-occurring mutation causing dystrophin-deficient muscular dystrophy in the dog

Exploring matrix factorization techniques for significant genes identification of Alzheimer’s disease microarray gene expression data

<p>Abstract</p> <p>Background</p> <p>The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets.</p> <p>Methods</p> <p>Unsupervised machine learning approaches provide new and efficient analysis of gene expression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA) and nonnegative matrix factorization (NMF) are integrated to identify significant genes and related pathways in microarray gene expression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized gene expression profiles.</p> <p>Results</p> <p>In our work, we performed FastICA and non-smooth NMF methods on DNA microarray gene expression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and the biological analysis of the identified significant genes and their related pathways demonstrated that these genes play a prominent role in AD and relate the activation patterns to AD phenotypes. It is validated that the combination of these two methods is efficient.</p> <p>Conclusions</p> <p>Unsupervised matrix factorization methods provide efficient tools to analyze high-throughput microarray dataset. According to the facts that different unsupervised approaches explore correlations in the high-dimensional data space and identify relevant subspace base on different hypotheses, integrating these methods to explore the underlying biological information from microarray dataset is an efficient approach. By combining the significant genes identified by both ICA and NMF, the biological analysis shows great efficient for elucidating the molecular taxonomy of Alzheimer’s disease and enable better experimental design to further identify potential pathways and therapeutic targets of AD.</p

Genetic analysis of the vitamin D receptor gene in two epithelial cancers: melanoma and breast cancer case-control studies

<p>Abstract</p> <p>Background</p> <p>Vitamin D serum levels have been found to be related to sun exposure and diet, together with cell differentiation, growth control and consequently, cancer risk. Vitamin D receptor (<it>VDR</it>) genotypes may influence cancer risk; however, no epidemiological studies in sporadic breast cancer (BC) or malignant melanoma (MM) have been performed in a southern European population. In this study, the <it>VDR </it>gene has been evaluated in two epithelial cancers BC and MM.</p> <p>Methods</p> <p>We have conducted an analysis in 549 consecutive and non-related sporadic BC cases and 556 controls, all from the Spanish population, and 283 MM cases and 245 controls. Genotyping analyses were carried out on four putatively functional SNPs within the <it>VDR </it>gene.</p> <p>Results</p> <p>An association with the minor allele A of the non-synonymous SNP rs2228570 (rs10735810, <it>Fok</it>I, Met1Thr) was observed for BC, with an estimated odds ratio (OR) of 1.26 (95% CI = 1.02–1.57; p = 0.036). The synonymous variant rs731236 (<it>Taq</it>I) appeared to be associated with protection from BC (OR = 0.80, 95%CI = 0.64–0.99; p = 0.047). No statistically significant associations with MM were observed for any SNP. Nevertheless, sub-group analyses revealed an association between rs2228570 (<it>FokI</it>) and absence of childhood sunburns (OR = 0.65, p = 0.003), between the 3'utr SNP rs739837 (<it>Bgl</it>I) and fair skin (OR = 1.31, p = 0.048), and between the promoter SNP rs4516035 and the more aggressive tumour location in head-neck and trunk (OR = 1.54, p = 0.020).</p> <p>Conclusion</p> <p>In summary, we observed associations between SNPs in the <it>VDR </it>gene and BC risk, and a comprehensive analysis using clinical and tumour characteristics as outcome variables has revealed potential associations with MM. These associations required confirmation in independent studies.</p

A post-trial survey to assess the impact of dissemination of results and unmasking on participants in a 13-year randomised controlled trial on age-related cataract

<p>Abstract</p> <p>Background</p> <p>The Italian-American Clinical Trial of Nutritional Supplements and Age-Related Cataract was designed to assess the impact of a multivitamin-mineral supplement on age-related cataract. Trial results showed evidence of a beneficial effect of the supplement on all types of cataract combined, opposite effects on two of the three types of cataract (beneficial for nuclear opacities and harmful for posterior sub-capsular opacities) and no statistically significant effect on cortical opacities. No treatment recommendations were made. A post-trial survey was conducted on 817 surviving elderly participants to assess their satisfaction, their understanding of treatment assignment to supplement or placebo and the success of masking.</p> <p>Methods</p> <p>Trial results were communicated by letter and the level of satisfaction and of understanding of the results was assessed by a questionnaire. Participants were offered the option of being unmasked: a second questionnaire was administered to this subset to assess their understanding of the randomisation process and the success of masking.</p> <p>Results</p> <p>610 participants (74.7%) responded to the survey:</p> <p>94.6% thought the description of the results was "very clear" or "quite clear", 5.4% "not clear" or "do not know"; 89.8% considered the results "very interesting" or "quite interesting", 10.2% "not interesting" or "do not know"; 60.3% expressed "satisfaction", 17.2% "both satisfaction and concern", 2.6% "concern", 19.9% "indifference" or "do not know".</p> <p>480 participants (78.7%) accepted the offer to be unmasked to their treatment assignment: 395 (82.3%) recalled/understood the possibility of assignment to vitamins or placebo, 85 (17.7%) did not. 68 participants (17.2%) thought they had taken vitamins (79.4% were correct; p = 0.0006), 47 (11.9%) thought they had taken placebo (59.6% were correct; p = 0.46) and 280 (70.9%) declared they did not know.</p> <p>Conclusions</p> <p>The results were made difficult to explain to study participants by the qualitatively different effect of treatment on the two most visually significant types of cataract. Although the study did not lead to a recommendation to use the dietary supplement, the vast majority of participants reported satisfaction after they received the results but almost 20% of the participants expressed some concern. Masking to treatment assignment was successful in the majority of participants.</p

Pleiotropic functions of the tumor- and metastasis-suppressing Matrix Metalloproteinase-8 in mammary cancer in MMTV-PyMT transgenic mice

Matrix metalloproteinase-8 (MMP-8; neutrophil collagenase) is an important regulator of innate immunity which has onco-suppressive actions in numerous tumor types