Heart Transplantation

Sustainable nanofiltration of industrial wastewater using waste-derived-graphene oxide-modified polyamide membranes: machine learning toward a smart portable water treatment unit.

Industrial wastewater treatment poses significant challenges because effluents vary in composition, containing dissolved salts, organic contaminants, and heavy metals. Nanofiltration (NF), employing thin-film composite (TFC) membranes, offers an energy-efficient separation platform capable of rejecting multivalent ions, organics, and dissolved metals. Here, graphene oxide (GO) was synthesized from...

Machine Learning and Molecular Modeling Reveal HDAC6 as a Key Target of Tanshinone IIA in Multiple Myeloma.

Multiple myeloma (MM) is a malignant blood cancer marked by severe bone destruction and immune microenvironment disruption. Yet relapse and drug resistance remain major clinical challenges. Tanshinone IIA (TIIA) exhibits potent antitumor activity, but its molecular targets and mechanisms in MM remain unclear. Here, we systematically elucidate TIIA's pharmacological mechanisms in MM using network p...

Machine learning identifies ac4C-related prognostic signature and TUBA1C as therapeutic target in COAD.

To explore the role of N4-acetylcytidine (ac4C)-related genes (acRGs) in colon adenocarcinoma (COAD) and identify reliable prognostic biomarkers and p...

Targeting GLUTs in Cancer: Mechanisms, Combination Strategies, and Translational Challenges.

Cancer cells exhibit metabolic reprogramming, most notably the Warburg effect, which underscores their heightened dependency on glucose uptake facilit...

Machine learning models for early detection of urinary tract infections in kidney transplant patients.

BACKGROUND: Renal transplantation is the preferred treatment for end-stage chronic kidney disease but requires lifelong immunosuppression, increasing ...

Peptide Therapeutics for Solid Tumors: Functional Classes, AI-Enhanced Discovery and Clinical Advances.

Solid tumors, the most prevalent form of malignancy, pose therapeutic challenges distinct from hematologic malignancies due to their complex biology, ...

Composite learning based finite time nonsingular terminal sliding mode path tracking control for intelligent vehicles.

This paper addresses the path tracking control problem for intelligent vehicles subject to parametric uncertainties, unmodeled dynamics, and external ...

Artificial Intelligence in Xenotransplantation: A Prioritized Roadmap for Early Clinical Translation, Opportunities and Challenges.

Xenotransplantation represents a potential solution to the persistent global organ shortage, yet its clinical application remains stalled by complex i...

Integrated multi-omics and functional analyses reveal a GDCA-TGR5-mediated immunometabolic signature in anorexia nervosa.

BACKGROUND: Anorexia nervosa (AN) is frequently accompanied by metabolic disturbances and immune dysregulation, yet its peripheral molecular mechanism...

Development and internal validation of an interpretable machine learning model for predicting vancomycin-induced nephrotoxicity in hospitalized children.

INTRODUCTION: Vancomycin is widely used for severe Gram‑positive infections in children, but vancomycin‑induced nephrotoxicity (VIN) limits its safe a...

Development and validation of a multidimensional machine learning model for predicting delayed graft function in deceased donor kidney transplantation.

PURPOSE: Delayed graft function (DGF) remains a significant complication following deceased donor kidney transplantation. This study aimed to develop ...

Integrative single-cell and machine-learning analysis identifies LGALS1 as a macrophage-associated diagnostic and prognostic biomarker in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is characterized by marked heterogeneity and an immunosuppressive microenvironment in which tumor-associate...

Integrative single-cell sequencing and machine learning analyses identify chronic inflammation and cancer-associated fibroblast subsets as drivers of adverse outcomes in ovarian cancer.

BACKGROUND: Ovarian cancer remains the deadliest gynecological malignancy, with neoadjuvant chemotherapy (NACT) often leaving residual fibroblast-enri...

NeutroChem Fusion: an uncertainty-aware source diagnosis framework for mining impacted waters in West Africa.

Mining impacted waters in West Africa are mixed chemical systems in which mining-derived Hg-Pb-Cd signals, geogenic As-Fe-Mn mobilisation, acid mine d...

Revisiting clinical scoring tools for the diagnosis of thrombotic thrombocytopenic purpura (TTP).

Thrombotic thrombocytopenic purpura (TTP) is a rare, life-threatening hematologic emergency that leads to increased complexities and mortality due to ...

Deep learning-driven rare-event sampling reveals an Ala7/D-Ala8 conformational hinge governing amphiphilic switching in cyclosporine A.

Passive membrane permeability of N-methylated macrocyclic peptides remains poorly understood because high-energy conformational intermediates are rare...

CLDN18.2 antibody design with protein language models: A deep learning optimization framework.

CLDN18.2 is a promising tumor-specific antigen; however, the development of therapeutic antibodies against it is challenged by the need for simultaneo...

Machine learning of sunitinib resistance genes reveals that SP5 regulates angiogenesis and sunitinib resistance in RCC via the VEGFA/AKT axis.

BACKGROUND: Sunitinib resistance remains a major clinical challenge in renal cell carcinoma, and the underlying molecular mechanisms are incompletely ...

Unclassifiable Invasive Pulmonary Aspergillosis in the Intensive Care Unit: Insights From a Multicenter, Retrospective Cohort Study in France (2022-2024).

BACKGROUND: Suspected invasive pulmonary aspergillosis (IPA) is increasingly treated in intensive care, including in patients without classical immuno...

Nanotechnology-based immunotherapy: integrating Artificial Intelligence (AI) with current strategies in combating brain cancer disease.

Brain cancer is one of the most challenging malignancies and a major contributor to worldwide morbidity and mortality. Glioblastoma, the most aggressi...