COVID-19

Integrated multi-omics and experimental validation for identifying novel biomarkers of acute myocardial infarction.

Acute myocardial infarction (AMI) remains a leading cause of morbidity and mortality, and early diagnosis and personalized therapy are constrained by complex molecular mechanisms. We integrated high-throughput bulk RNA sequencing with weighted gene co-expression network analysis (WGCNA) to prioritize AMI-associated genes, externally validated findings in two independent cohorts, and screened candi...

Uncertainty-Aware Multi-Class Brain Tumor Segmentation Using Bayesian U-Net Variants.

Accurate segmentation of brain tumors in magnetic resonance imaging (MRI) is essential for diagnosis, treatment planning, and surgical guidance. Although deep learning-based segmentation methods have achieved strong performance, their clinical adoption remains limited due to the lack of reliable uncertainty estimation. To address this challenge, we propose an uncertainty-aware framework for multi-...

Unsupervised clustering of clinical and laboratory features of systemic lupus erythematosus: insights from a multicentre cohort.

OBJECTIVE: This study explored the relationship between clinical phenotypes and immuno-molecular features of systemic lupus erythematosus (SLE) using ...

Assessing predictive accuracy of 2D digital templating in fluoroscopy-guided direct anterior approach total hip arthroplasty.

INTRODUCTION: Preoperative 2D digital templating aids surgical planning in total hip arthroplasty (THA). We evaluated template accuracy by comparing p...

Deep learning assessment of nativeness and pairing likelihood for antibody and nanobody design with AbNatiV2.

Most immune-system created antibodies balance good binding and stability with low toxicity and self-reactivity. Quantifying the nativeness of a candid...

Drug repurposing in Alzheimer's disease: Emerging therapeutic strategies and promising candidates.

Alzheimer's disease is a progressive neurodegenerative disorder, and the most common cause of dementia, which causes 60-70 % of cases worldwide, and i...

Lancet2: Improved and accelerated somatic variant calling with joint multi-sample local assembly graphs.

Here, we present Lancet2, an open-source somatic variant caller designed to improve detection of small variants in short-read sequencing data. Lancet2...

Deep learning-enabled scaffolding of spatial arrays of PfCSP epitopes.

Malaria is a leading cause of disease in developing countries. The licensed malaria vaccine RTS,S/AS01 confers partial protection in part due to the e...

Large-scale AI analysis reveals missed opportunities in albuminuria testing and disease-modifying therapy implementation.

BACKGROUND: Albuminuria is a key diagnostic and prognostic biomarker of chronic kidney disease (CKD), associated with adverse cardiovascular and renal...

Predicting public Intensive care unit mortality and hospitalization using Data: An evaluation of Brazil's Largest COVID-19 epidemiological dataset.

OBJECTIVES: To assess the SRAG dataset's potential for modeling COVID-19 mortality and LOS-ICU, identify key data gaps, and support the development of...

Novel deep learning-based optimization framework for the classification of respiratory diseases using lung sound analysis.

Respiratory disease classification using lung sound analysis offers a non-invasive and cost-effective diagnostic alternative to traditional imaging-ba...

Tokenizing loops of antibodies.

The complementarity-determining regions (CDRs) of antibodies are loop structures that are key to their interactions with antigens and are of high impo...

Human Allele Frequency Distributions Contradict Current Narratives of Imminent Danger From Genetically Targeted Bioweapons.

Warnings of pathogens manufactured to target a specific ethnic group, so-called genetic bioweapons, have recently received considerable media attentio...

Integrative multi-omics identifies a diagnostic T cell signature for cutaneous squamous cell carcinoma.

Cutaneous squamous cell carcinoma (cSCC) involves complex immune interactions. This study aimed to identify a T cell-related gene signature to charact...

Simultaneous analysis of miRNA and 16S rDNA by a multiplex droplet digital PCR system for body fluid source identification.

Forensic body fluid identification, crucial for crime scene reconstruction, is often limited by sample scarcity and degradation. Hence, there is growi...

Disposable face masks and PBDEs in aquatic environments: Co-contamination and impacts.

Disposable face masks have emerged as a widespread source of post-COVID contamination in aquatic environments, particularly in coastal and nearshore w...

Performance evaluation of quantum support vector machine for COVID-19 biomarker analysis.

BACKGROUND AND OBJECTIVE: Identifying key biomarkers from multi-omics data is essential for advancing COVID-19 diagnosis and understanding disease mec...

Prediction of post-COVID chronic fatigue syndrome using data mining and machine learning techniques in Isfahan COVID cohort study.

BACKGROUND: Post-COVID Fatigue (PCF) is one of the most common issues people face after recovering from COVID-19. Due to the heterogeneity of clinical...

Next-generation proteomics in medical laboratories: metrologically sound quantitative protein tests vs. innovative and personalized proteome patterns.

In precision medicine protein phenotypes are foreseen that combined with pattern recognition tools exhibit great potential in guaranteeing safe and ac...

Predicting neoadjuvant therapy response in breast cancer from preoperative biopsy via spatial-semantic-differential learning and interpretable clinicopathological-guided fusion.

Predicting pathological complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer remains challenging due to high tumor heterogeneity and ...