Heart Transplantation

Mechanism-Based Multitarget Modeling for Pathway-Level Prediction of PI3K/Akt Signaling Perturbation Induced by Liquid Crystal Monomers.

Liquid crystal monomers (LCMs) are emerging contaminants whose system-level toxicity mechanisms remain poorly understood. Here, we developed a pathway-centric multitarget framework to characterize coordinated toxicological perturbations at the signaling network level. KEGG enrichment identified the PI3K/Akt pathway as a key mechanistic axis, and a minimal set of 19 proteins covering upstream recep...

Machine learning model based on clinical and imaging features for predicting fungal infections in children with leukemia.

BACKGROUND: Due to immunosuppression, mucosal barrier injury, and prolonged neutropenia resulting from both the disease and chemotherapy, along with the frequent use of broad-spectrum antibiotics and glucocorticoids, children with leukemia are at a high risk of invasive fungal disease (IFD). The present study aimed to develop an effective machine learning model to predict fungal infections in chil...

Explainable machine learning on resting-state magnetoencephalography power spectra reveals neural alterations in knee osteoarthritis.

This study aimed to investigate abnormal patterns of resting-state magnetoencephalography (MEG) power spectra in patients with knee osteoarthritis (KO...

Transcriptomic profiling identifies immunotherapy-responsive phenotypes in microsatellite-stable metastatic colorectal cancer.

Conventional immune checkpoint inhibitors (ICIs) remain largely ineffective in microsatellite-stable metastatic colorectal cancer (MSS mCRC), where lo...

Dissecting PCD-driven molecular landscapes in AML: a multi-omic framework for prognostication and therapeutic targeting.

Acute myeloid leukemia (AML) remains a molecularly heterogeneous malignancy with poor prognosis, necessitating robust biomarkers for risk stratificati...

Multi-omics analysis identifies GINS1 as a prognostic biomarker in lung adenocarcinoma, linked to macrophage polarization and tumor cell survival.

This study aimed to identify essential genes driving lung adenocarcinoma (LUAD) progression by integrating CRISPR-Cas9 dependency data from the Cancer...

Machine learning-based identification of basement membrane-related signature to predict recurrence and immunotherapy benefit in bladder cancer.

The basement membrane (BM) plays a critical role in regulating bladder cancer (BC) progression. However, a BM-related signature for predicting BC recu...

A myeloid immunosuppressive phenotype defines primary refractoriness to atezolizumab Plus bevacizumab in hepatocellular caarcinoma.

BACKGROUND: Despite improved outcomes with atezolizumab plus bevacizumab (A+B) in hepatocellular carcinoma (HCC), primary refractoriness (PRef), chara...

RRBP1 promotes osimertinib resistance by activating fatty acid oxidation-dependent metabolic and immune reprogramming in EGFR-Mutant lung adenocarcinoma.

Osimertinib is a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor that improves clinical outcomes in patients with E...

Infections in Burn Patients: Pathophysiology, Prevention, and Contemporary Therapeutic Strategies in the Era of Antimicrobial Resistance.

Burn injuries are associated with significant morbidity and mortality, largely driven by infectious complications. Disruption of the skin barrier, sys...

A Dataset of Microelectrode Recordings from Deep Brain Stimulation Procedures.

Precise intraoperative localisation of subcortical brain structures remains a critical challenge in deep brain stimulation, yet openly available micro...

Targeting colorectal cancer stem-like cells: Overcoming therapeutic resistance and reprogramming the immunosuppressive niche.

Colorectal cancer stem-like cells (CRC-SCs) represent a tumor subpopulation with enhanced tumor-initiating capacity and have been implicated in metast...

Machine Learning-Guided Predictive Modeling and Optimization of Polyamide-Based Thin-Film Nanocomposite Reverse Osmosis Membranes.

The growing scarcity of global freshwater resources, coupled with steady advancements in seawater desalination technology, has made the development of...

A Machine Learning-Assisted Framework for Performance Prediction and Optimization of Graphene Oxide Nanofiltration Membranes.

Graphene oxide (GO) holds considerable promise for nanofiltration applications, owing to its distinctive two-dimensional layered architecture and tuna...

Integrating Molecular Pathology, Tumor Microenvironment, and Novel Therapies to Overcome Resistance in Glioblastoma.

Glioblastoma multiforme (GBM) represents the most aggressive primary brain tumor in adults, characterized by significant heterogeneity, rapid progress...

Recommendations for disclosure of artificial intelligence in scientific writing and publishing: a regional anesthesia and pain medicine modified Delphi study.

INTRODUCTION: The use of artificial intelligence (AI) in the scientific process is advancing at a remarkable speed, thanks to continued innovations in...

How Following Medical Artificial Intelligence Advice Can Mitigate Malpractice Liability: Cross-National Insights from a Randomized Trial.

Artificial intelligence (AI) increasingly influences clinical decision-making, yet its recommendations may diverge from standard care. Although malpra...

Quality assessment of radiographs through AI-driven feedback: A randomized comparative study on radiographer response in lateral knee radiographs.

INTRODUCTION: High-quality radiographic positioning is essential for accurate diagnosis in knee imaging. Although artificial intelligence (AI) can ass...

Immune cell delivery platforms for tumor therapy: From empirical approaches to AI-integrated frameworks.

The heterogeneity and immunosuppressive characteristics of the tumor microenvironment present significant challenges to traditional treatment strategi...

Nanomedicine in precision treatment of gastric cancer: current clinical landscape.

Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, with therapeutic efficacy often hindered by late-stage diagnosis, c...