Transplantation

From donor to recipient: Interpretable machine learning refocuses the prediction of post-transplant MASLD.

Advances in Biomaterial-Based Cardiac Organoids Engineering for Modeling Development and Congenital Heart Defects.

Human cardiac organoids have emerged as transformative platforms that bridge the gap between reductionist 2D cultures and poorly predictive animal models. By recapitulating the three-dimensional tissue architecture, multicellular composition, and developmental dynamics of the human heart, these systems enable mechanistic studies of heart development and congenital heart disease. This review survey...

Embryo transfer in dairy herds: a comprehensive review of factors affecting pregnancy success from donor to embryo and recipient.

Embryo transfer (ET) is a fundamental biotechnology in modern dairy production, utilized to maximize the propagation of superior genetics and circumve...

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 t...

Medical students' attitudes toward socioscientific issues in female reproductive anatomy teaching: a cross-sectional study.

OBJECTIVES: This study aimed to assess medical students' attitudes toward integrating socioscientific issues (SSI) into female reproductive anatomy te...

Proteomic and machine learning analysis predicts treatment response signatures in Myasthenia Gravis.

BACKGROUND: Myasthenia gravis (MG) is a prototypical antibody-mediated autoimmune disease with variable treatment responses with a need for biomarkers...

Ultra-Broadband Microwave Absorption and Programmable Multispectral Camouflage Enabled by Neural-Network-Driven Impedance-Gradient Metadevices.

Achieving omnidirectional multispectral compatible camouflage remains a significant challenge due to the pronounced disparities in electromagnetic wav...

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...

A comprehensive landscape of human organ N-glycoproteome.

N-glycosylation, as a common post-translational modification with complex structures, plays key roles in protein folding, cellular recognition and sig...

A donor-recipient ranking model to optimize long-term survival post liver transplant.

Liver transplant (LT) is a life-saving treatment for patients with cirrhosis and/or hepatocellular carcinoma (HCC), but organ shortages and suboptimal...

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...

Non-invasive detection of Oncostatin M and TNF-α in a microphysiological chip with embedded pH tuning capabilities.

The detection of disease biomarkers is crucial in biomedical research, diagnostics and personalized medicine. However, challenges still exist for the ...

Deep Learning-Driven 3D Histopathology Method: A Pipeline for Cellular-Resolution Myocarditis Analysis.

Infiltrative cardiovascular diseases are characterized by complex spatial distributions of abnormal tissue that hinder accurate diagnosis and therapeu...

The gut microbiome in preterm infants: development, dysbiosis, and disease implications.

SUMMARYPreterm infants face a unique trajectory of gut microbiome assembly, shaped by the convergence of physiological immaturity, necessary clinical ...

Drug-induced multisystem syndromes: An overlooked challenge in pharmacovigilance.

BackgroundDrug-Induced Multisystem Syndromes (DIMS) represent a clinically significant yet under-recognized group of delayed immune-mediated adverse d...

AI-planned and robotic-assisted pedicle screw placement improves accuracy and reduces loosening in lumbar fusion for patients with low bone mass: a multicenter study.

OBJECTIVE: This study aimed to evaluate the effectiveness of artificial intelligence (AI)-based pedicle screw trajectory planning combined with roboti...

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...

Rational design of low-risk and high-efficiency β-triketone herbicide alternatives via integrative computational toxicology and NGBoost modeling.

β-Triketone herbicides (bTHs) are widely applied in crops such as maize, rice, and sorghum. However, their efficacy on some gramineous weeds is limite...