Bgee in 2024: focus on curated single-cell RNA-seq datasets, and query tools.

Bgee (https://www.bgee.org/) is a database to retrieve and compare gene expression patterns in multiple animal species.

DiffPaSS-high-performance differentiable pairing of protein sequences using soft scores.

Motivation: Identifying interacting partners from two sets of protein sequences has important applications in computational biology. Interacting partners share similarities across species due to their common evolutionary history, and feature correlations in amino acid usage due to the need to maintain complementary interaction interfaces. Thus, the problem of finding interacting pairs can be formulated as searching for a pairing of sequences that maximizes a sequence similarity or a coevolution score.

New developments for the Quest for Orthologs benchmark service.

The Quest for Orthologs (QfO) orthology benchmark service (https://orthology.benchmarkservice.org) hosts a wide range of standardized benchmarks for orthology inference evaluation.

Self-organized patterning of crocodile head scales by compressive folding.

Amniote integumentary appendages constitute a diverse group of micro-organs, including feathers, hair and scales. These structures typically develop as genetically controlled units, the spatial patterning of which emerges from a self-organized chemical Turing system with integrated mechanical feedback. The seemingly purely mechanical patterning of polygonal crocodile head scales provides an exception to this paradigm.

DOME Registry: implementing community-wide recommendations for reporting supervised machine learning in biology.

Supervised machine learning (ML) is used extensively in biology and deserves closer scrutiny. The Data Optimization Model Evaluation (DOME) recommendations aim to enhance the validation and reproducibility of ML research by establishing standards for key aspects such as data handling and processing, optimization, evaluation, and model interpretability. The recommendations help to ensure that key details are reported transparently by providing a structured set of questions.

VILOCA: sequencing quality-aware viral haplotype reconstruction and mutation calling for short-read and long-read data.

RNA viruses exist as large heterogeneous populations within their host. The structure and diversity of virus populations affects disease progression and treatment outcomes. Next-generation sequencing allows detailed viral population analysis, but inferring diversity from error-prone reads is challenging.

Immune digital twins for complex human pathologies: applications, limitations, and challenges.

Digital twins represent a key technology for precision health. Medical digital twins consist of computational models that represent the health state of individual patients over time, enabling optimal therapeutics and forecasting patient prognosis. Many health conditions involve the immune system, so it is crucial to include its key features when designing medical digital twins.

Practical Recommendations for Navigating Digital Tools in Hospitals: Qualitative Interview Study.

Background: The digitalization of health care organizations is an integral part of a clinician's daily life, making it vital for health care professionals (HCPs) to understand and effectively use digital tools in hospital settings. However, clinicians often express a lack of preparedness for their digital work environments. Particularly, new clinical end users, encompassing medical and nursing students, seasoned professionals transitioning to new health care environments, and experienced practitioners encountering new health care technologies, face critically intense learning periods, often with a lack of adequate time for learning digital tools, resulting in difficulties in integrating and adopting these digital tools into clinical practice.

Fibroblastic reticular cells generate protective intratumoral T cell environments in lung cancer.

Stringent control of T cell activity in the tumor microenvironment is essential for the generation of protective antitumor immunity. However, the identity, differentiation, and functions of the cells that create critical fibroblastic niches promoting tumor-infiltrating T cells remain elusive. Here, we show that CCL19-expressing fibroblastic reticular cells (FRCs) generate interconnected T cell environments (TEs) in human non-small cell lung cancer, including tertiary lymphoid structures and T cell tracks.

Profiling of insulin-resistant kidney models and human biopsies reveals common and cell-type-specific mechanisms underpinning Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is the leading cause of end stage kidney failure worldwide, of which cellular insulin resistance is a major driver. Here, we study key human kidney cell types implicated in DKD (podocytes, glomerular endothelial, mesangial and proximal tubular cells) in insulin sensitive and resistant conditions, and perform simultaneous transcriptomics and proteomics for integrated analysis. Our data is further compared with bulk- and single-cell transcriptomic kidney biopsy data from early- and advanced-stage DKD patient cohorts.

Machine learning for precision diagnostics of autoimmunity.

Early and accurate diagnosis is crucial to prevent disease development and define therapeutic strategies. Due to predominantly unspecific symptoms, diagnosis of autoimmune diseases (AID) is notoriously challenging. Clinical decision support systems (CDSS) are a promising method with the potential to enhance and expedite precise diagnostics by physicians.

IL-21/IL-21R signaling renders acute myeloid leukemia stem cells more susceptible to cytarabine treatment and CAR T cell therapy.

Self-renewal programs in leukemia stem cells (LSCs) predict poor prognosis in patients with acute myeloid leukemia (AML). We identify CD4 T cell-derived interleukin (IL)-21 as an important negative regulator of self-renewal of LSCs. IL-21/IL-21R signaling favors asymmetric cell division and differentiation in LSCs through the activation of p38-MAPK signaling, resulting in reduced LSC numbers and significantly prolonged survival in murine AML models.

The molecular toll pathway repertoire in anopheline mosquitoes.

Innate immunity in mosquitoes has received much attention due to its potential impact on vector competence for vector-borne disease pathogens, including malaria parasites. The nuclear factor (NF)-κB-dependent Toll pathway is a major regulator of innate immunity in insects. In mosquitoes, this pathway controls transcription of the majority of the known canonical humoral immune effectors, mediates anti-bacterial, anti-fungal and anti-viral immune responses, and contributes to malaria parasite killing.

Enhancing data standards to advance translation in spinal cord injury.

Data standards are available for spinal cord injury (SCI). The International SCI Data Sets were created in 2002 and there are currently 27 freely available. In 2014 the National Institute of Neurological Disorders and Stroke developed clinical common data elements to promote clinical data sharing in SCI.

Single-cell RNA-sequencing of BK polyomavirus replication in primary human renal proximal tubular epithelial cells identifies specific transcriptome signatures and a novel mitochondrial stress pattern.

BK polyomavirus (BKPyV) contributes to premature renal failure in 10%-20% of kidney transplant recipients. Current treatment relies on reducing immunosuppression to regain BKPyV-specific immune control. Subsequently, declining allograft function may result from persisting viral cytopathology, BKPyV-specific immune reconstitution, or alloimmunity/rejection, all being poorly distinguishable by current histological or molecular approaches.

Association of Urinary Epidermal Growth Factor, Fatty Acid-Binding Protein 3, and Vascular Cell Adhesion Molecule 1 Levels with the Progression of Early Diabetic Kidney Disease.

Introduction: Diabetic kidney disease (DKD) is a common cause of chronic kidney disease with around 25-40% of patients with diabetes being affected. The course of DKD is variable, and estimated glomerular filtration rate (eGFR) and albuminuria, the currently used clinical markers, are not able to accurately predict the individual disease trajectory, in particular in early stages of the disease. The aim of this study was to assess the association of urine levels of selected protein biomarkers with the progression of DKD at an early stage of disease.

ENKIE: a package for predicting enzyme kinetic parameter values and their uncertainties.

Motivation: Relating metabolite and enzyme abundances to metabolic fluxes requires reaction kinetics, core elements of dynamic and enzyme cost models. However, kinetic parameters have been measured only for a fraction of all known enzymes, and the reliability of the available values is unknown.

Results: The ENzyme KInetics Estimator (ENKIE) uses Bayesian Multilevel Models to predict value and uncertainty of KM and kcat parameters.