High-throughput functional analysis of autism genes in zebrafish identifies convergence in dopaminergic and neuroimmune pathways

Advancing from gene discovery in autism spectrum disorders (ASDs) to the identification of biologically relevant mechanisms remains a central challenge. Here, we perform parallel in vivo functional analysis of 10 ASD genes at the behavioral, structural, and circuit levels in zebrafish mutants, revealing both unique and overlapping effects of gene loss of function. Whole-brain mapping identifies the forebrain and cerebellum as the most significant contributors to brain size differences, while regions involved in sensory-motor control, particularly dopaminergic regions, are associated with altered baseline brain activity. Finally, we show a global increase in microglia resulting from ASD gene loss of function in select mutants, implicating neuroimmune dysfunction as a key pathway relevant to ASD biology

Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19.

Dysregulated immune responses against the SARS-CoV-2 virus are instrumental in severe COVID-19. However, the immune signatures associated with immunopathology are poorly understood. Here we use multi-omics single-cell analysis to probe the dynamic immune responses in hospitalized patients with stable or progressive course of COVID-19, explore V(D)J repertoires, and assess the cellular effects of tocilizumab. Coordinated profiling of gene expression and cell lineage protein markers shows that S100

Characteristics of Rotary Sprinkler Water Distribution under Dynamic Water Pressure

In order to explore water distribution in sprinkler irrigation systems under dynamic water pressure, an irrigation test was conducted in a sprinkler irrigation system equipped with the Hunter MP2000 full circular rotator ray sprinkler under “trapezoidal” waveform pressure to explore the influencing factors such as basic water pressure, dynamic pressure period, and the sprinkler combination spacing. The result shows that the basic pressure, sprinkler combination spacing, and their interaction significantly affected the coefficient of variation, average intensity, and coefficient of uniformity. The normalized comprehensive evaluation indexes were selected as the measurement standards. The optimal factor combination was found to be the basic pressure of 250 kPa, the dynamic pressure period of 200 s, and the sprinkler combination spacing of 6 m, and the corresponding evaluation index values were 0.08, 10.54 mm/h, and 93.20%, respectively. The uniformity coefficient was increased by 6.54% compared with the constant pressure of the same flow rate. Compared with the constant pressure of the same flow rate, the sprinkler area and the average intensity increased by 39.67% and decreased by 8.62% when the basic pressure was 250 kPa and the dynamic pressure period was 200 s. The average uniformity coefficient increased by 11.76% at the combined spacing of 6.0, 6.5, 7.0, 7.5, and 8.0 m. The results provide a theoretical basis for sprinkler irrigation decisions under dynamic pressure

Improved glomerular filtration rate estimation by an artificial neural network.

BACKGROUND: Accurate evaluation of glomerular filtration rates (GFRs) is of critical importance in clinical practice. A previous study showed that models based on artificial neural networks (ANNs) could achieve a better performance than traditional equations. However, large-sample cross-sectional surveys have not resolved questions about ANN performance. METHODS: A total of 1,180 patients that had chronic kidney disease (CKD) were enrolled in the development data set, the internal validation data set and the external validation data set. Additional 222 patients that were admitted to two independent institutions were externally validated. Several ANNs were constructed and finally a Back Propagation network optimized by a genetic algorithm (GABP network) was chosen as a superior model, which included six input variables; i.e., serum creatinine, serum urea nitrogen, age, height, weight and gender, and estimated GFR as the one output variable. Performance was then compared with the Cockcroft-Gault equation, the MDRD equations and the CKD-EPI equation. RESULTS: In the external validation data set, Bland-Altman analysis demonstrated that the precision of the six-variable GABP network was the highest among all of the estimation models; i.e., 46.7 ml/min/1.73 m(2) vs. a range from 71.3 to 101.7 ml/min/1.73 m(2), allowing improvement in accuracy (15% accuracy, 49.0%; 30% accuracy, 75.1%; 50% accuracy, 90.5% [P<0.001 for all]) and CKD stage classification (misclassification rate of CKD stage, 32.4% vs. a range from 47.3% to 53.3% [P<0.001 for all]). Furthermore, in the additional external validation data set, precision and accuracy were improved by the six-variable GABP network. CONCLUSIONS: A new ANN model (the six-variable GABP network) for CKD patients was developed that could provide a simple, more accurate and reliable means for the estimation of GFR and stage of CKD than traditional equations. Further validations are needed to assess the ability of the ANN model in diverse populations

Hyaluronan and TLR4 promote surfactant-protein-C-positive alveolar progenitor cell renewal and prevent severe pulmonary fibrosis in mice

Successful recovery from lung injury requires the repair and regeneration of alveolar epithelial cells to restore the integrity of gas-exchanging regions within the lung and preserve organ function. Improper regeneration of the alveolar epithelium is often associated with severe pulmonary fibrosis, the latter of which involves the recruitment and activation of fibroblasts, as well as matrix accumulation. Type 2 alveolar epithelial cells (AEC2s) are stem cells in the adult lung that contribute to the lung repair process. The mechanisms that regulate AEC2 renewal are incompletely understood. We provide evidence that expression of the innate immune receptor Toll-like receptor 4 (TLR4) and the extracellular matrix glycosaminoglycan hyaluronan (HA) on AEC2s are important for AEC2 renewal, repair of lung injury and limiting the extent of fibrosis. Either deletion of TLR4 or HA synthase 2 in surfactant-protein-C-positive AEC2s leads to impaired renewal capacity, severe fibrosis and mortality. Furthermore, AEC2s from patients with severe pulmonary fibrosis have reduced cell surface HA and impaired renewal capacity, suggesting that HA and TLR4 are key contributors to lung stem cell renewal and that severe pulmonary fibrosis is the result of distal epithelial stem cell failure

Single-Cell Deconvolution of Fibroblast Heterogeneity in Mouse Pulmonary Fibrosis

Summary: Fibroblast heterogeneity has long been recognized in mouse and human lungs, homeostasis, and disease states. However, there is no common consensus on fibroblast subtypes, lineages, biological properties, signaling, and plasticity, which severely hampers our understanding of the mechanisms of fibrosis. To comprehensively classify fibroblast populations in the lung using an unbiased approach, single-cell RNA sequencing was performed with mesenchymal preparations from either uninjured or bleomycin-treated mouse lungs. Single-cell transcriptome analyses classified and defined six mesenchymal cell types in normal lung and seven in fibrotic lung. Furthermore, delineation of their differentiation trajectory was achieved by a machine learning method. This collection of single-cell transcriptomes and the distinct classification of fibroblast subsets provide a new resource for understanding the fibroblast landscape and the roles of fibroblasts in fibrotic diseases. : Xie et al. have analyzed mesenchymal cell subpopulations at single-cell resolution and have demonstrated known subtypes and a newly emerging subtype during pulmonary fibrosis in mouse lung. Keywords: single-cell RNA-seq, fibroblast, lung mesenchymal cells, fibrosi