Effects of time-of-day on the noradrenaline, adrenaline, cortisol and blood lipidome response to an ice bath.

While the effect of time-of-day (morning versus evening) on hormones, lipids and lipolysis has been studied in relation to meals and exercise, there are no studies that have investigated the effects of time-of-day on ice bath induced hormone and lipidome responses. In this crossover-designed study, a group of six women and six men, 26 ± 5 years old, 176 ± 7 cm tall, weighing 75 ± 10 kg, and a BMI of 23 ± 2 kg/mhad an ice bath (8-12 °C for 5 min) both in the morning and evening on separate days. Absence from intense physical exercise, nutrient intake and meal order was standardized in the 24 h prior the ice baths to account for confounders such as diet or exercise.

Systematic assessment of COVID-19 host genetics using whole genome sequencing data.

Courses of SARS-CoV-2 infections are highly variable, ranging from asymptomatic to lethal COVID-19. Though research has shown that host genetic factors contribute to this variability, cohort-based joint analyses of variants from the entire allelic spectrum in individuals with confirmed SARS-CoV-2 infections are still lacking. Here, we present the results of whole genome sequencing in 1,220 mainly vaccine-naïve individuals with confirmed SARS-CoV-2 infection, including 827 hospitalized COVID-19 cases.

Score matching for differential abundance testing of compositional high-throughput sequencing data.

The class of a-b power interaction models, proposed by Yu et al. (2024), provides a general framework for modeling sparse compositional count data with pairwise feature interactions. This class includes many distributions as special cases and enables zero count handling through power transformations, making it especially suitable for modern high- throughput sequencing data with excess zeros, including single-cell RNA-Seq and amplicon sequencing data.

Bi-allelic variants in DAP3 result in reduced assembly of the mitoribosomal small subunit with altered apoptosis and a Perrault-syndrome-spectrum phenotype.

The mitochondrial ribosome (mitoribosome) synthesizes 13 protein subunits of the oxidative phosphorylation system encoded by the mitochondrial genome. The mitoribosome is composed of 12S rRNA, 16S rRNA, and 82 mitoribosomal proteins encoded by nuclear genes. To date, variants in 12 genes encoding mitoribosomal proteins are associated with rare monogenic disorders and frequently show combined oxidative phosphorylation deficiency.

Missense variants in the TRPM7 α-kinase domain are associated with recurrent pediatric acute liver failure.

Background: Pediatric acute liver failure (PALF) is a rare and life-threatening condition. In up to 50% of PALF cases, the underlying etiology remains unknown during routine clinical testing. This lack of knowledge complicates clinical management and liver transplantation decisions.

An integrated transcriptomic cell atlas of human neural organoids.

Human neural organoids, generated from pluripotent stem cells in vitro, are useful tools to study human brain development, evolution and disease. However, it is unclear which parts of the human brain are covered by existing protocols, and it has been difficult to quantitatively assess organoid variation and fidelity. Here we integrate 36 single-cell transcriptomic datasets spanning 26 protocols into one integrated human neural organoid cell atlas totalling more than 1.

IL-9 sensitizes human T2 cells to proinflammatory IL-18 signals in atopic dermatitis.

Background: T2 cells crucially contribute to the pathogenesis of atopic dermatitis (AD) by secreting high levels of IL-13 and IL-22. Yet the upstream regulators that activate T2 cells in AD skin remain unclear. IL-18 is a putative upstream regulator of T2 cells because it is implicated in AD pathogenesis and has the capacity to activate T cells.

Benchmarking methods for computing local sensitivities in ordinary differential equation models at dynamic and steady states.

Estimating parameters of dynamic models from experimental data is a challenging, and often computationally-demanding task. It requires a large number of model simulations and objective function gradient computations, if gradient-based optimization is used. In many cases, steady-state computation is a part of model simulation, either due to steady-state data or an assumption that the system is at steady state at the initial time point.

BioPathNet: Enhancing Link Prediction in Biomedical Knowledge Graphs through Path Representation Learning.

Understanding complex interactions in biomedical networks is crucial for advancements in biomedicine, but traditional link prediction (LP) methods are limited in capturing this complexity. Representation-based learning techniques improve prediction accuracy by mapping nodes to low-dimensional embeddings, yet they often struggle with interpretability and scalability. We present BioPathNet, a novel graph neural network framework based on the Neural Bellman-Ford Network (NBFNet), addressing these limitations through path-based reasoning for LP in biomedical knowledge graphs.

Biallelic variants in result in reduced assembly of the mitoribosomal small subunit with altered intrinsic and extrinsic apoptosis and a Perrault syndrome-spectrum phenotype.

The mitoribosome synthesizes 13 protein subunits of the oxidative phosphorylation system encoded by the mitochondrial genome. The mitoribosome is composed of 12S rRNA, 16S rRNA and 82 mitoribosomal proteins encoded by nuclear genes. To date, variants in 12 genes encoding mitoribosomal proteins are associated with rare monogenic disorders, and frequently show combined oxidative phosphorylation deficiency.

From computational models of the splicing code to regulatory mechanisms and therapeutic implications.

Since the discovery of RNA splicing and its role in gene expression, researchers have sought a set of rules, an algorithm or a computational model that could predict the splice isoforms, and their frequencies, produced from any transcribed gene in a specific cellular context. Over the past 30 years, these models have evolved from simple position weight matrices to deep-learning models capable of integrating sequence data across vast genomic distances. Most recently, new model architectures are moving the field closer to context-specific alternative splicing predictions, and advances in sequencing technologies are expanding the type of data that can be used to inform and interpret such models.

scooby: Modeling multi-modal genomic profiles from DNA sequence at single-cell resolution.

Understanding how regulatory DNA elements shape gene expression across individual cells is a fundamental challenge in genomics. Joint RNA-seq and epigenomic profiling provides opportunities to build unifying models of gene regulation capturing sequence determinants across steps of gene expression. However, current models, developed primarily for bulk omics data, fail to capture the cellular heterogeneity and dynamic processes revealed by single-cell multi-modal technologies.

Integration of variant annotations using deep set networks boosts rare variant association testing.

Rare genetic variants can have strong effects on phenotypes, yet accounting for rare variants in genetic analyses is statistically challenging due to the limited number of allele carriers and the burden of multiple testing. While rich variant annotations promise to enable well-powered rare variant association tests, methods integrating variant annotations in a data-driven manner are lacking. Here we propose deep rare variant association testing (DeepRVAT), a model based on set neural networks that learns a trait-agnostic gene impairment score from rare variant annotations and phenotypes, enabling both gene discovery and trait prediction.

Epigenetic regulation of cell state by H2AFY governs immunogenicity in high-risk neuroblastoma.

Childhood neuroblastoma with MYCN amplification is classified as high risk and often relapses after intensive treatments. Immune checkpoint blockade therapy against the PD-1/L1 axis shows limited efficacy in patients with neuroblastoma, and the cancer intrinsic immune regulatory network is poorly understood. Here, we leverage genome-wide CRISPR/Cas9 screens and identify H2AFY as a resistance gene to the clinically approved PD-1 blocking antibody nivolumab.

Suppression of ferroptosis by vitamin A or radical-trapping antioxidants is essential for neuronal development.

The development of functional neurons is a complex orchestration of multiple signaling pathways controlling cell proliferation and differentiation. Because the balance of antioxidants is important for neuronal survival and development, we hypothesized that ferroptosis must be suppressed to gain neurons. We find that removal of antioxidants diminishes neuronal development and laminar organization of cortical organoids, which is fully restored when ferroptosis is inhibited by ferrostatin-1 or when neuronal differentiation occurs in the presence of vitamin A.

Lysis of human erythrocytes due to Piezo1-dependent cytosolic calcium overload as a mechanism of circulatory removal.

Hematopoietic stem cells surrender organelles during differentiation, leaving mature red blood cells (RBC) devoid of transcriptional machinery and mitochondria. The resultant absence of cellular repair capacity limits RBC circulatory longevity, and old cells are removed from circulation. The specific age-dependent alterations required for this apparently targeted removal of RBC, however, remain elusive.

Path-based reasoning for biomedical knowledge graphs with BioPathNet.

Understanding complex interactions in biomedical networks is crucial for advancements in biomedicine, but traditional link prediction (LP) methods are limited in capturing this complexity. Representation-based learning techniques improve prediction accuracy by mapping nodes to low-dimensional embeddings, yet they often struggle with interpretability and scalability. We present BioPathNet, a novel graph neural network framework based on the Neural Bellman-Ford Network (NBFNet), addressing these limitations through path-based reasoning for LP in biomedical knowledge graphs.

Differential Analysis of Protein-DNA Binding Using ChIP-Seq Data.

Chromatin immunoprecipitation in combination with next-generation sequencing (ChIP-Seq) allows probing of protein-DNA binding in a rapid and genome-wide fashion. Herein we describe the required steps to preprocess ChIP-Seq data and to analyze the differential binding of proteins to DNA for perturbation experiments. In these experiments, different conditions are compared to find the underlying biological mechanisms caused by the stimulus or treatment.

An Integrated Transcriptomics and Genomics Approach Detects an X/Autosome Translocation in a Female with Duchenne Muscular Dystrophy.

Duchenne and Becker muscular dystrophies, caused by pathogenic variants in , are the most common inherited neuromuscular conditions in childhood. These diseases follow an X-linked recessive inheritance pattern, and mainly males are affected. The most prevalent pathogenic variants in the gene are copy number variants (CNVs), and most patients achieve their genetic diagnosis through Multiplex Ligation-dependent Probe Amplification (MLPA) or exome sequencing.