QuickProt: A Bioinformatics and Visualization Tool for DIA and PRM Mass Spectrometry-Based Proteomics Datasets.

Mass spectrometry (MS)-based proteomics focuses on identifying and quantifying peptides and proteins in biological samples. Processing of MS-derived raw data, including deconvolution, alignment, and peptide-protein prediction, has been achieved through various software platforms. However, the downstream analysis, including quality control, visualizations, and interpretation of proteomics results, remains cumbersome due to the lack of integrated tools to facilitate the analyses.

Polysubstance use in early adulthood and associated factors in the Republic of Ireland: An analysis of a nationally representative cohort.

Background And Aims: Alcohol and other drug use is common in early adulthood; however, research on contemporary polysubstance use patterns-defined as use of multiple psychoactive substances-and their associated factors is limited. This study aimed to identify groups with differing polysubstance use patterns and to examine associations with individual, family and socio-environmental factors.

Design: This is a cohort study based on data from the Growing Up in Ireland (GUI) study.

Age-Related Changes in the Clinical Picture of Long COVID.

Background: This study evaluated the impact of aging on the frequency and prevalent symptoms of Long COVID, also termed post-acute sequelae of SARS-CoV-2, using a previously developed Long COVID research index (LCRI) of 41 self-reported symptoms in which those with 12 or more points were classified as likely to have Long COVID.

Methods: We analyzed community-dwelling participants ≥ 60 years old (2662 with prior infection, 461 controls) compared to participants 18-59 years (7549 infected, 728 controls) in the Researching COVID to Enhance Recovery adult (RECOVER-Adult) cohort ≥ 135 days post-onset.

Results: Compared to the Age 18-39 group, the adjusted odds of LCRI ≥ 12 were higher for the Age 40-49 group (odds ratio [OR] = 1.

The effect of taxonomic, host-dependent features and sample bias on virus host prediction using machine learning and short sequence k-mers.

Metaviromic studies of potential emerging infection reservoirs led to discovery of many novel viruses. Since metaviromes contain viruses from target host, its food or other sources, fast and robust approaches are needed to predict hosts of unknown viruses based on their genome data. Four machine learning algorithms (random forest, two gradient boosting machines, support vector machine) were used here to predict the hosts of RNA viruses that infect mammals, insects and plants.

Multiomic clocks to predict phenotypic age in mice.

Biological age refers to a person's overall health in aging, as distinct from their chronological age. Diverse measures of biological age, referred to as "clocks", have been developed in recent years and enable risk assessments, and an estimation of the efficacy of longevity interventions in animals and humans. While most clocks are trained to predict chronological age, clocks have been developed to predict more complex composite biological age outcomes, at least in humans.

The coronavirus spike HR2 domain: An obscure player entering the limelight during membrane fusion?

The coronavirus spike protein, the key entity effectuating membrane fusion, cannot exist without membrane-active fragments. In addition to fusion peptides, among such domains are HR1 and HR2. Crucial to the spike's refolding and membrane fusion, they are believed to both interact with each other and bind to the membranes that are merged.

Modelling the effectiveness of Integrated Pest Management strategies for the control of Septoria tritici blotch.

Reducing reliance on pesticides is an important global challenge. With increasing constraints on their use, in recent years there has been a declining trend in pesticide use for arable crops in the UK. But with increasing disease pressures and global demand for food, there is a greater need for effective measures of pest and disease control.

A multivariate cell-based liquid biopsy for lung nodule risk stratification: Analytical validation and early clinical evaluation.

Background: The Indicator Cell Assay Platform (iCAP) is a novel tool for blood-based diagnostics that uses living cells as biosensors to integrate and amplify weak, multivalent disease signals present in patient serum. In the platform, standardized cells are exposed to small volumes of patient serum, and the resulting transcriptomic response is analyzed using machine learning tools to develop disease classifiers.

Methods: We developed a lung cancer-specific iCAP (LC-iCAP) as a rule-out test for the management of indeterminate pulmonary nodules detected by low-dose CT screening.

Placental network differences among obstetric syndromes identified with an integrated multiomics approach.

The placenta is essential for pregnancy, and its dysfunction can harm both mother and fetus. To better understand placental physiology and its disruption in disease, we employ a multiomics approach (transcriptomics, metabolomics, and proteomics) combined with clinical data and histopathology from 321 placentas across conditions: severe fetal growth restriction (FGR), FGR with hypertension (FGR + HDP), severe preeclampsia (PE), and spontaneous preterm delivery (PTD). Cellular deconvolution reveals FGR + HDP placentas have more extravillous trophoblasts than controls (p < 0.

Climate variability amplifies the need for vector-borne disease outbreak preparedness.

In locations that do not currently experience vector-borne disease (VBD) outbreaks but may be at risk under climate change, modeling future climate suitability for transmission is important for outbreak preparedness. Uncertainty in the future climate arises from three sources-differences in emissions scenarios, structural uncertainty across climate models, and internal climate variability (ICV)-but ICV is rarely considered in climate-VBD studies. Here, we demonstrate that ICV is a key source of uncertainty in climate suitability for VBD transmission, even decades into the future.

Complementary Predictors for Asthma Attack Prediction in Children: Salivary Microbiome, Serum Inflammatory Mediators, and Past Attack History.

Background: Early identification of children at risk of asthma attacks is important for optimizing treatment strategies. We aimed to integrate salivary microbiome and serum inflammatory mediator profiles with asthma attacks history to develop a comprehensive predictive model for future attacks.

Methods: This study contained a discovery (SysPharmPediA) and a replication phase (U-BIOPRED).

Manuscript title: Cytokines Associated With Moderate and Severe Adverse Events During a Sporozoite Malaria Vaccine Trial with Controlled Human Malaria Infection.

Ensuring the safety and efficacy of candidate vaccines is critical. Although mechanisms underpinning protective immune responses to malaria vaccines are frequently investigated, immune responses correlating with moderate and severe adverse events are rarely examined. Here, we leverage a malaria vaccine trial with a higher-than-expected adverse event rate and frequent sampling to investigate cytokine profiles associated with adverse events.

Cellular pH homeostasis shapes root system architecture by modulating auxin-mediated developmental responses.

Cell expansion relies on turgor pressure and acidification-dependent loosening of the rigid cell wall. Distinct cell surface-based and intracellular auxin signaling pathways synergistically activate plasma membrane H+-ATPases, acidifying the apoplast, a prerequisite for cell elongation. Unlike in shoots, auxin inhibits cell elongation in roots.

Personalized Clostridioides difficile colonization risk prediction and probiotic therapy assessment in the human gut.

Clostridioides difficile (C. difficile) colonizes up to 40% of community-dwelling adults without causing disease but can eventually lead to infection (C. difficile infection [CDI]).

Taxonomic and Functional Features of Surface to Deep-Sea Prokaryotic Communities in the Eastern North Pacific Ocean.

Biogeochemical cycles in the ocean are strongly influenced by microbial activity, which affects nutrient and organic matter cycling. These processes, influenced by factors such as temperature, salinity, density and inorganic nutrients, drive the vertical stratification of microbial communities, which subsequently influence the chemistry at different depth layers. Sequencing technology has expanded our understanding of oceanic prokaryotic communities' taxonomic and functional potential.

Nasal and systemic immune responses correlate with viral shedding after influenza challenge in people with complex preexisting immunity.

Each year in the United States, ~50% of adults ≥18 years old are vaccinated against influenza viruses, with protective efficacy averaging 40.5% over the past 20 years. To model annual seasonal influenza, a cohort of 74 adults, who were unscreened for preexisting A/H1N1 immunity and half of whom were recently immunized with licensed QIV (mean of 64 days), were challenged with A/H1N1 influenza virus.

Cellular heterogeneity and therapeutic response profiling of human IDH+ glioma stem cell cultures.

Glioblastoma stem cell (GSC) cultures are initiated from glioblastoma (GBM) surgical resection tissue. They can capture and propagate key GBM primary tumor molecular and cellular features. We have deeply characterized four isocitrate dehydrogenase (IDH)-expressing (or IDH+) GSC cultures from unrelated adults to serve as cellular models for the majority of adult primary GBM.

UBR-1 enzyme network regulates glutamate homeostasis to affect organismal behavior and developmental viability.

Johanson-Blizzard Syndrome (JBS) is an autosomal recessive spectrum disorder associated with the UBR-1 ubiquitin ligase that features developmental delay including motor abnormalities. Here, we demonstrate that UBR-1 regulates high-intensity locomotor behavior and developmental viability via both ubiquitin ligase and scaffolding mechanisms. Super-resolution imaging with CRISPR-engineered UBR-1 and genetic results demonstrated that UBR-1 is expressed and functions in the nervous system including in pre-motor interneurons.

Longitudinal big biological data in the AI era.

Generating longitudinal and multi-layered big biological data is crucial for effectively implementing artificial intelligence (AI) and systems biology approaches in characterising whole-body biological functions in health and complex disease states. Big biological data consists of multi-omics, clinical, wearable device, and imaging data, and information on diet, drugs, toxins, and other environmental factors. Given the significant advancements in omics technologies, human metabologenomics, and computational capabilities, several multi-omics studies are underway.

Credible inferences in microbiome research: ensuring rigour, reproducibility and relevance in the era of AI.

The microbiome has critical roles in human health and disease. Advances in high-throughput sequencing and metabolomics have revolutionized our understanding of human gut microbial communities and identified plausible associations with a variety of disorders. However, microbiome research remains constrained by challenges in establishing causality, an over-reliance on correlative studies, and methodological and analytical limitations.

Metagenomic estimation of absolute bacterial biomass in the mammalian gut through host-derived read normalization.

Absolute bacterial biomass estimation in the human gut is crucial for understanding microbiome dynamics and host-microbe interactions. Current methods for quantifying bacterial biomass in stool, such as flow cytometry, quantitative polymerase chain reaction (qPCR), or spike-ins, can be labor-intensive, costly, and confounded by factors like water content, DNA extraction efficiency, PCR inhibitors, and other technical challenges that add bias and noise. We propose a simple, cost-effective approach that circumvents some of these technical challenges: directly estimating bacterial biomass from metagenomes using bacterial-to-host (B:H) read count ratios.

Mitochondrial complex I deficiency induces Alzheimer's disease-like signatures that are reversible by targeted therapy.

Introduction: Mitochondrial dysfunction is implicated in Alzheimer's disease (AD), but whether it drives AD-associated changes is unclear. We assessed transcriptomic alterations in the brains of Ndufs4 mice, a model of mitochondrial complex I (mtCI) deficiency, and evaluated the therapeutic effects of the neuroprotective mtCI inhibitor CP2.

Methods: Cortico-hippocampal tissue from Ndufs4 and wild-type mice was subjected to transcriptomic analysis, followed by cross-species comparisons to human late-onset AD and familial AD mouse datasets.

Applying a Conservation-Based Approach for Predicting Novel Phosphorylation Sites in Eukaryotes and Evaluating Their Functional Relevance.

Protein phosphorylation, a key post-translational modification, is central to cellular signaling and disease pathogenesis. The development of high-throughput proteomics pipelines has led to the discovery of large numbers of phosphorylated protein motifs and sites (phosphosites) across many eukaryotic species. However, the majority of phosphosites are reported from human samples, with most species having a few experimentally confirmed or computationally predicted phosphosites.

A comparative study using Xpert MTB/RIF and culture methods evaluates MassARRAY technology for rapid detection of and drug resistance.

Tuberculosis (TB) remains a major global health threat, with the urgent need for rapid and accurate diagnostic methods to improve control and treatment outcomes. This study evaluates the performance of MassARRAY technology for detecting (MTB) and identifying drug resistance, compared to traditional culture methods and Xpert MTB/RIF. From July 2021 to February 2024, bronchoalveolar lavage fluid (BALF) samples from 289 suspected pulmonary tuberculosis patients at Henan Provincial Chest Hospital, China, were tested using MassARRAY, Xpert MTB/RIF, and conventional culturing techniques.

Concerted changes in Epithelium and Stroma: a multi-scale, multi-omics analysis of progression from Barrett's Esophagus to adenocarcinoma.

Esophageal adenocarcinoma arises from Barrett's esophagus, a metaplastic condition. Multi-omics profiling, integrating single-cell transcriptomics, extracellular matrix proteomics, tissue mechanics and spatial proteomics of the paths of progression from squamous epithelium through metaplasia, dysplasia to adenocarcinoma, in 107 samples from 26 patients in two independent cohorts, defined shared and patient-specific progression characteristics. Metaplastic replacement of epithelial cell composition and architecture was paralleled by changes in stromal cells, extracellular matrix (ECM) and tissue stiffness.