Lupus

Dataset of manually curated peptides against arthropod-borne viruses.

Anti-arboviral peptides are biomolecules capable of interfering with key stages of the arboviral lifecycle. We present a dataset compiling 270 peptides composed of standard amino acids with reported activity against arboviruses, along with their lengths, sequences, target specificities, peptide entry mechanisms, and interaction mechanisms. The dataset was structured to support the training of mach...

From pathogenesis to precision medicine in systemic lupus erythematosus: Emerging biomarkers and targeted interventions.

Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disease characterized by immune dysregulation, autoantibody production, and chronic inflammation, which can potentially damage almost any organ. The estimated worldwide prevalence of SLE ranges from 5 to 7 million, and it is associated with significant morbidity, premature death, and significant global disparities in terms of sex...

Predicting Molecular Laser Properties from First-Principles Using Machine Learning-Based Nuclear Ensemble Approach Spectra.

The accurate prediction of absorption and emission spectra of molecular compounds using quantum mechanical (QM) methods is essential for understanding...

An interpretable machine learning tool for rheumatoid arthritis screening: integrating novel cellular morphological parameters with routine blood count indices.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease that can cause significant disability. Early detection is vital for improving ou...

Free water in the hippocampal cingulum as a Radiomic biomarker for Identifying inflammatory neuropsychiatric Lupus: A cross-sectional case-control study.

PURPOSE: Neuropsychiatric systemic lupus erythematosus (NPSLE) is a serious manifestation of systemic lupus erythematosus (SLE), yet its neuroimaging ...

The multi-target cardiac protection mechanism of butylphthalide and AI-driven precision medicine: From molecular basis to clinical translation.

Butylphthalide (NBP) is a lipophilic small-molecule drug characterized by its multi-target and multi-pathway regulatory properties. Initially employed...

A machine-learning-based tool for stroke risk prediction in blunt cerebrovascular injury: development and preliminary evaluation.

PURPOSE: Stroke risk correlates with the Biffl grading system in blunt cerebrovascular injury (BCVI). Although anti-thrombotic therapy is the mainstay...

Quinoa bioester application shifts human skin proteome toward molecular profiles associated with younger age.

Skin aging involves complex molecular changes that current strategies struggle to reverse. Here, we developed a machine learning approach using Suppor...

Occlusion-activated autonomous piezoelectric implants for adaptive prevention of peri-implantitis.

More than one-third of the global population suffers from dental defects, with osseointegrated implants being the gold-standard intervention; yet, the...

Valorization of turkey cruor through peptic hydrolysis: peptidomic and machine learning approaches for the identification of antimicrobial peptides.

The slaughterhouse blood remains an underexploited by-product with promising potential for producing natural antimicrobial agents. This study investig...

Fine-grained and multi-pattern anti-nuclear antibody recognition: A new dataset and framework.

Indirect immunofluorescence (IIF) staining imaging on human epithelial cell (HEp-2) is a standard technique for anti-nuclear antibodies (ANA) screenin...

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 ...

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...

Antimicrobial peptides in malaria and tuberculosis management: a systematic review of emerging evidence.

AMPs (Antimicrobial peptides) are small molecules that are crucial components of biological activities, viz wound healing, angiogenesis, antimicrobial...

A novel predictive model for evaluating thrombus regression in postpartum venous thromboembolism patients.

INTRODUCTION: Antithrombotic evaluation of postpartum venous thromboembolism (VTE) after anticoagulant therapy is challenging because of the lack of h...

Significance of tumor infiltrating granulocytes and neutrophil extracellular traps in colorectal cancer.

BACKGROUND: Neutrophils are the most abundant granulocytes in the tumor microenvironment and exert both pro- and anti-cancer effects. Activated neutro...

HCCaging: a liver physiological aging-related biomarker for hepatocellular carcinoma diagnosis based on transcriptome data.

Aging is a fundamental biological process that influences cancer development in a context-dependent manner; however, how aging-related programs manife...

Integrated bioinformatics reveals tubulointerstitial immune microenvironment signatures and machine learning-driven prognostication of clinical treatment response in lupus nephritis.

Lupus nephritis (LN) represents the most severe renal manifestation of systemic lupus erythematosus (SLE), contributing to significant morbidity. Whil...

Mechanistic Topology of Notopterygium incisum Essential Oil against Rheumatoid Arthritis: Machine Learning-Guided CASP1 Screening and Nanoemulsion Evaluation.

OBJECTIVE: To elucidate the anti-rheumatoid arthritis (RA) mechanisms of Notopterygium incisum essential oil (NIEO) using an integrated strategy combi...

Long term evolutions of hard exudates after anti-VEGF therapy for diabetic macular oedema.

PURPOSE: To evaluate longitudinal change in hard exudate (HEs) volume over 5-years following anti-VEGF treatment for diabetic macular oedema (DMO). ME...