Flexible pooling in gene expression profiles: design and statistical modeling of experiments for unbiased contrasts.

Pooling is an important resource in microarray gene expression experiments. Due to restrictions imposed by the statistical analysis it is widespread practice to employ a fixed pool size over the whole experiment. But this limits the efficient use of experimental material. In this paper we propose a design with flexible pool sizes for mRNA pooling which includes varying numbers of experimental units per pool. Enforcing balance between the pool sizes of every treatment level, we show the unbiasedness of the generalized least squares estimator of a contrast testing for differences in gene expression between treatments. In order to model the variability of pooled observations we include random biological effects as well as a special kind of technical error (random effect for mixtures), induced by inaccuracies in blending aliquots of mRNA from different individuals into common pools. Results for one-color arrays are also extended to two-color arrays.

Survey of student attitudes toward digital technology in practical technical dental education using the AR-Demonstrator-App.

PURPOSE/OBJECTIVES: More and more creative applications are used in the field of dentistry for clinical practice, patient orientation, teaching, and learning, in order to awake the students' interest and to enable a deep learning and its retention. The aim of this study was to demonstrate the impact and the effectiveness of the current simulation laboratories on the practical dental education. For this purpose, a survey on a new developed "AR-Demonstrator-App" was conducted during the orthodontic technical courses in 2017, 2018, and 2020 in the Department of Orthodontics (C.G. Carus, TU Dresden, Germany). METHODS: With this application, the students had the opportunity to see every single step with instructions on how to manufacture a removable orthodontic device in a compulsory technical course. At the end of these courses, the students were asked to anonymously fill out a printed questionnaire with 12 questions regarding the learning progress related to the app. RESULTS: The yearly mean Likert scores and their bootstrapped 95% confidence intervals as well as the yearly median Likert scores suggest a very positive feedback about the use of the new application as an educational instrument. Despite the recognized predominant benefits of this app, the students concluded that they do not prefer the total replacement of the physical plaster casts and that a combination of conventional and computer-based education provided the optimum approach to acquisition of dental practical skills. CONCLUSIONS: This survey indicates a generally positive attitude toward computer-assisted simulation systems, providing the facility for acquisition of knowledge and practical skills in a multimedia environment.

Death by SARS-CoV 2: a Romanian COVID-19 multi-centre comorbidity study.

Evidence regarding the relation between SARS-CoV-2 mortality and the underlying medical condition is scarce. We conducted an observational, retrospective study based on Romanian official data about location, age, gender and comorbidities for COVID-19 fatalities. Our findings indicate that males, hypertension, diabetes, obesity and chronic kidney disease were most frequent in the COVID-19 fatalities, that the burden of disease was low, and that the prognosis for 1-year survival probability was high in the sample. Evidence shows that age-dependent pairs of comorbidities could be a negative prognosis factor for the severity of disease for the SARS-CoV 2 infection.

A Microglial Signature Directing Human Aging and Neurodegeneration-Related Gene Networks.

Aging is regarded as a major risk factor for neurodegenerative diseases. Thus, a better understanding of the similarities between the aging process and neurodegenerative diseases at the cellular and molecular level may reveal better understanding of this detrimental relationship. In the present study, we mined publicly available gene expression datasets from healthy individuals and patients affected by neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, and Huntington's disease) across a broad age spectrum and compared those with mouse aging and mouse cell-type specific gene expression profiles. We performed weighted gene co-expression network analysis (WGCNA) and found a gene network strongly related with both aging and neurodegenerative diseases. This network was significantly enriched with a microglial signature as imputed from cell type-specific sequencing data. Since mouse models are extensively used for the study of human diseases, we further compared these human gene regulatory networks with age-specific mouse brain transcriptomes. We discovered significantly preserved networks with both human aging and human disease and identified 17 shared genes in the top-ranked immune/microglia module, among which we found five human hub genes TYROBP, FCER1G, ITGB2, MYO1F, PTPRC, and two mouse hub genes Trem2 and C1qa. Taken together, these results support the hypothesis that microglia are key players involved in human aging and neurodegenerative diseases, and suggest that mouse models should be appropriate for studying these microglial changes in human.

Determinants of consumption-day amounts applicable for the estimation of usual dietary intake with a short 24-h food list.

Next to the information on frequency of food consumption, information on consumption-day amounts is important to estimate usual dietary intake in epidemiological studies. Our objective was to identify determinants of consumption-day amounts to derive person-specific standard consumption-day amounts applicable for the estimation of usual dietary intake using separate sources to assesss information on consumption probability and amount consumed. 24-h Dietary recall data from the German National Nutrition Survey II (n = 8522; aged 20-80 years) conducted between 2005 and 2007 were analysed for determinants of consumption-day amounts of thirty-eight food and beverage groups using LASSO variable selection for linear mixed-effects models. Determinants included sex, age, BMI, smoking status, years of education, household net income, living status and employment status. Most often, sex, age and smoking status were selected as predictors for consumption-day amounts across thirty-eight food groups. In contrast, living with a partner, employment status and household net income were less frequently chosen. Overall, different determinants were of relevance for different food groups. The number of selected determinants ranged from eight for coffee and juice to zero for cabbage, tea, root vegetables, leafy vegetables, fruit vegetables, legumes, offal, vegetable oils, and other fats. For the estimation of usual dietary intake in a combined approach with a 24-h food list, person-specific standard consumption-day amounts could be used. Sex, age and smoking status were shown to be the most relevant predictors in our analysis. Their impact on the estimation of usual dietary intake needs to be evaluated in future studies.

Genome-wide association analysis identifies variation in vitamin D receptor and other host factors influencing the gut microbiota.

Human gut microbiota is an important determinant for health and disease, and recent studies emphasize the numerous factors shaping its diversity. Here we performed a genome-wide association study (GWAS) of the gut microbiota using two cohorts from northern Germany totaling 1,812 individuals. Comprehensively controlling for diet and non-genetic parameters, we identify genome-wide significant associations for overall microbial variation and individual taxa at multiple genetic loci, including the VDR gene (encoding vitamin D receptor). We observe significant shifts in the microbiota of Vdr-/- mice relative to control mice and correlations between the microbiota and serum measurements of selected bile and fatty acids in humans, including known ligands and downstream metabolites of VDR. Genome-wide significant (P < 5 × 10-8) associations at multiple additional loci identify other important points of host-microbe intersection, notably several disease susceptibility genes and sterol metabolism pathway components. Non-genetic and genetic factors each account for approximately 10% of the variation in gut microbiota, whereby individual effects are relatively small.