Hemophilia

From In Silico De Novo Generation to In Vitro Functional Validation: Discovery of Multifunctional Antithrombotic Peptides from Food-Derived Proteins via a Hybrid LSTM-GCN and Molecular Simulation Pipeline.

Cardiovascular thromboses bring heavy global health burdens, while traditional screening of food-derived antithrombotic peptides is inefficient. This work built an integrated pipeline integrating de novo peptide generation, hybrid LSTM-GCN deep learning, and molecular simulations, screening 15,000 sequences to obtain lead peptide FPGGIP. It had a binding affinity of -6.4 kcal/mol and a stable thro...

Hydrogen sulfide ameliorates cognitive dysfunction in diabetic encephalopathy by activating PI3K/AKT/GSK-3β signaling to attenuate tau hyperphosphorylation and necroptosis.

Diabetic encephalopathy (DE) is a serious complication of diabetes mellitus characterized by progressive cognitive dysfunction; but its underlying mechanisms remain incompletely understood. Tau hyperphosphorylation and necroptosis are key pathological events in neurodegenerative diseases, but their roles in DE and the capacity of hydrogen sulfide (H2S) to regulate these processes have not been inv...

Laboratory Medicine in Immune Checkpoint Inhibitor-Induced Autoimmune Disorders: Baseline Assessment, Diagnostic Algorithms, Monitoring, and Predictive Biomarkers.

Immune checkpoint inhibitors (ICIs) have substantially improved clinical outcomes across multiple malignancies, but they can disrupt self-tolerance an...

Targeting WEE1 kinase: an integrated machine learning-cheminformatics framework for ultra-large-scale virtual screening and novel inhibitor discovery.

WEE1 kinase, a critical regulator of the G2/M checkpoint, represents a validated therapeutic target in tumors harboring defects in DNA damage response...

AI-driven dual-task prediction model for co-stratifying efficacy and toxicity in NSCLC immunotherapy.

While effective against non-small cell lung cancer (NSCLC), PD-1 inhibitors can induce immune-related adverse events (irAEs), occurring in up to 15.2%...

Discovery of a potent TDP1 inhibitor through machine learning-driven predictive modeling combined with structure-based virtual screening and experimental validation.

Tyrosyl-DNA phosphodiesterase I (TDP1) repairs topoisomerase I (TOP1)-mediated DNA damage and is a promising anticancer target, particularly in combin...

Deep learning-assisted virtual screening of a large chemical library for selective GSK3β inhibitors.

Glycogen synthase kinase-3β (GSK3β) is a serine/threonine kinase involved in neurodegenerative, neuropsychiatric, and oncological disorders. The devel...

Machine Learning Models Integrating CYP2C19 Genotypes for Long-Term Risk Prediction and Personalized Antiplatelet Therapy Selection in Myocardial Infarction.

Machine learning (ML) models integrating genetic and clinical data show promise for personalizing antiplatelet therapy after myocardial infarction (MI...

Identification of novel PKR inhibitory chemotypes via integrated molecular modelling and machine learning.

Interferon-inducible RNA-dependent protein kinase (PKR) is an emerging therapeutic target involved in cancer, neurodegeneration, and inflammatory diso...

A Bayesian Survival Model to Support the Selection of the Best Hematopoietic Stem Cell Donor.

The selection of a donor for allogeneic hematopoietic stem cell transplantation (HSCT) is a complex, multifactorial process requiring the balance of t...

Real-world analysis of depression-related adverse events associated with the adsorbed anthrax vaccine: integrating pharmacovigilance signals, machine learning risk prediction, and transcriptomic mechanisms.

BACKGROUND: Anthrax remains a life-threatening zoonotic disease in resource-limited settings. Adsorbed anthrax vaccine (AVA, BioThrax) is the only Uni...

A clinical-radiomics model based on MRI sub-regions of gluteus maximus for recurrence prediction in high-grade serous ovarian cancer.

PURPOSE: To evaluate the predictive value of MRI sub-regional radiomics of the gluteus maximus for recurrence in high-grade serous ovarian cancer (HGS...

An integrated deep learning and molecular dynamics pipeline for the discovery of novel CDK8 inhibitors against acute myeloid leukaemia.

Cyclin-dependent kinase 8 (CDK8) has emerged as a promising therapeutic target for acute myeloid leukaemia (AML). We developed an integrated computati...

Advanced imaging in systemic sclerosis: distinguishing activity from damage across organ systems.

PURPOSE OF REVIEW: A central challenge in systemic sclerosis (SSc) is the inability to distinguish active, potentially reversible disease, from damage...

Clinical Research on Microecological Landscape for Infection Risk Stratification in Newly Diagnosed Patients with Hematological Conditions.

INTRODUCTION: Infection is a common and potentially fatal complication during the treatment of hematological diseases, particularly in the context of ...

Uncovering the molecular landscape of young-onset diffuse gastric cancer: A relieff-based feature selection analysis on RNA-Seq data.

BACKGROUND: Diffuse Gastric Cancer (DGC) is an aggressive subtype with a poor prognosis and a lack of specific biomarkers, representing a critical unm...

Artificial Intelligence based identification of druggability of essential hypothetical proteins in Plasmodium falciparum.

Malaria, caused by Plasmodium falciparum is a deadly disease and remains a global health concern. With the emergence of resistance to artemisinin; it ...

Radiomics Model Predicts Efficacy of First-Line CDK4/6 Inhibitor Combined with Endocrine Therapy in HR+/HER2- Advanced Breast Cancer.

INTRODUCTION: The combination of CDK4/6 inhibitors and endocrine therapy is the first-line standard regimen for advanced HR⁺/HER₂⁻ breast cancer. Howe...

Integrative multi-omics reveals a prognostic and therapeutic landscape of synthetic lethality-associated signatures in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) exhibits considerable heterogeneity and therapeutic resistance. Here, we integrated single-cell RNA sequencing, spatial tra...

Signal Detection and Temporal Analysis of Aromatase Inhibitor-Associated Hepatotoxicity: A Pharmacovigilance Study Integrating Bayesian Belief-Propagation Network and Frequentist Metrics.

BACKGROUND: This study assessed the real-world hepatotoxicity of third-generation aromatase inhibitors (AIs) for breast cancer using pharmacovigilance...