Mad Is Required for Wingless Signaling in Wing Development and Segment Patterning in Drosophila

A key question in developmental biology is how growth factor signals are integrated to generate pattern. In this study we investigated the integration of the Drosophila BMP and Wingless/GSK3 signaling pathways via phosphorylations of the transcription factor Mad. Wingless was found to regulate the phosphorylation of Mad by GSK3 in vivo. In epistatic experiments, the effects of Wingless on wing disc molecular markers (senseless, distalless and vestigial) were suppressed by depletion of Mad with RNAi. Wingless overexpression phenotypes, such as formation of ectopic wing margins, were induced by Mad GSK3 phosphorylation-resistant mutant protein. Unexpectedly, we found that Mad phosphorylation by GSK3 and MAPK occurred in segmental patterns. Mad depletion or overexpression produced Wingless-like embryonic segmentation phenotypes. In Xenopus embryos, segmental border formation was disrupted by Smad8 depletion. The results show that Mad is required for Wingless signaling and for the integration of gradients of positional information

Transcriptional adaptations following exercise in Thoroughbred horse skeletal muscle highlights molecular mechanisms that lead to muscle hypertrophy

<p>Abstract</p> <p>Background</p> <p>Selection for exercise-adapted phenotypes in the Thoroughbred racehorse has provided a valuable model system to understand molecular responses to exercise in skeletal muscle. Exercise stimulates immediate early molecular responses as well as delayed responses during recovery, resulting in a return to homeostasis and enabling long term adaptation. Global mRNA expression during the immediate-response period has not previously been reported in skeletal muscle following exercise in any species. Also, global gene expression changes in equine skeletal muscle following exercise have not been reported. Therefore, to identify novel genes and key regulatory pathways responsible for exercise adaptation we have used equine-specific cDNA microarrays to examine global mRNA expression in skeletal muscle from a cohort of Thoroughbred horses (<it>n = </it>8) at three time points (before exercise, immediately post-exercise, and four hours post-exercise) following a single bout of treadmill exercise.</p> <p>Results</p> <p>Skeletal muscle biopsies were taken from the <it>gluteus medius </it>before (T₀), immediately after (T₁) and four hours after (T₂) exercise. Statistically significant differences in mRNA abundance between time points (T₀<it>vs </it>T₁and T₀<it>vs </it>T₂) were determined using the empirical Bayes moderated <it>t</it>-test in the Bioconductor package Linear Models for Microarray Data (LIMMA) and the expression of a select panel of genes was validated using real time quantitative reverse transcription PCR (qRT-PCR). While only two genes had increased expression at T₁(<it>P </it>< 0.05), by T₂932 genes had increased (<it>P </it>< 0.05) and 562 genes had decreased expression (<it>P </it>< 0.05). Functional analysis of genes differentially expressed during the recovery phase (T₂) revealed an over-representation of genes localized to the actin cytoskeleton and with functions in the MAPK signalling, focal adhesion, insulin signalling, mTOR signaling, p53 signaling and Type II diabetes mellitus pathways. At T₁, using a less stringent statistical approach, we observed an over-representation of genes involved in the stress response, metabolism and intracellular signaling. These findings suggest that protein synthesis, mechanosensation and muscle remodeling contribute to skeletal muscle adaptation towards improved integrity and hypertrophy.</p> <p>Conclusions</p> <p>This is the first study to characterize global mRNA expression profiles in equine skeletal muscle using an equine-specific microarray platform. Here we reveal novel genes and mechanisms that are temporally expressed following exercise providing new knowledge about the early and late molecular responses to exercise in the equine skeletal muscle transcriptome.</p

Equity in mathematics and science outcomes: characteristics associated with high and low achievement on PISA 2006 in Ireland

Equity in education is a key concern internationally; however, it is rare that this issue is examined separately for low- and high-achieving students and concurrently across different subject domains. This study examines student and school background characteristics associated with low and high achievement in mathematics and science on the Programme for International Student Assessment. Based on the results of a multilevel multinomial model of achievement for each domain, findings indicate that a greater number of the variables examined are associated with low rather than high achievement. At student level, home language, intention to leave school early, socioeconomic status, grade level, cultural capital, and books in the home are significantly associated with achievement in mathematics and science. At school level, only school average socioeconomic status is statistically significant in the models. Significant gender differences are found in the distribution of high and low achievers, which vary across the domains. In mathematics, females are more likely to be low achievers while males are more likely to be high achievers. In science, gender interacts with early school-leaving intent whereas males intending to leave school early are more likely to be in the low-achieving group than females intending to leave early. Conclusions emphasise the need for targeting resources aimed at promoting equity in outcomes at student level as well as at school level. Future work may extend the current analyses by incorporating domain-specific variables or examining cross-country differences

Protective immune trajectories in early viral containment of non-pneumonic SARS-CoV-2 infection

The antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remains unclear. Here, we combine a multi-omics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype associated with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies

Multiomic analyses uncover immunological signatures in acute and chronic coronary syndromes

Acute and chronic coronary syndromes (ACS and CCS) are leading causes of mortality. Inflammation is considered a key pathogenic driver of these diseases, but the underlying immune states and their clinical implications remain poorly understood. Multiomic factor analysis (MOFA) allows unsupervised data exploration across multiple data types, identifying major axes of variation and associating these with underlying molecular processes. We hypothesized that applying MOFA to multiomic data obtained from blood might uncover hidden sources of variance and provide pathophysiological insights linked to clinical needs. Here we compile a longitudinal multiomic dataset of the systemic immune landscape in both ACS and CCS (n = 62 patients in total, n = 15 women and n = 47 men) and validate this in an external cohort (n = 55 patients in total, n = 11 women and n = 44 men). MOFA reveals multicellular immune signatures characterized by distinct monocyte, natural killer and T cell substates and immune-communication pathways that explain a large proportion of inter-patient variance. We also identify specific factors that reflect disease state or associate with treatment outcome in ACS as measured using left ventricular ejection fraction. Hence, this study provides proof-of-concept evidence for the ability of MOFA to uncover multicellular immune programs in cardiovascular disease, opening new directions for mechanistic, biomarker and therapeutic studies