Transplantation

A novel model (SED-GNDE) integrating graph neural differential equations with selective electrodialysis process for nutrient prediction from synthetic wastewater.

Selective electrodialysis (SED) is a promising method for recovering nutrient ions, such as phosphate, ammonium, sulfate and potassium, from wastewater. However, nutrient recovery by SED is an intricate process governed by multi-dimensional parameters, including wastewater characteristics, membrane properties and operating conditions, making the recovery process complex and challenging to predict....

Microfluidic-electrochemical sweat patches for athletes: monitoring lactate, electrolytes, and hydration status.

Wearable biochemical sensing is shifting sports physiology from intermittent laboratory sampling toward continuous, in situ readouts during training and competition. This review analyzes skin conformal systems that integrate capillary driven fluid routing, flexible sensor arrays, and wireless readout to capture dynamic changes in eccrine secretions relevant to performance management. We compare mi...

AneuSI: A software tool to isolate a region of interest in cerebral aneurysms from full geometrical models.

BACKGROUND AND OBJECTIVE: Modeling cerebral aneurysms using patient-specific geometries demands significant computational resources, particularly when...

Integrative network toxicology, multiomics, and machine learning elucidate zearalenone-induced developmental toxicity mechanisms in zebrafish (Danio rerio).

Zearalenone (ZEN) is a naturally occurring environmental contaminant that is produced by fungi. Developing animals are particularly sensitive to ZEN, ...

IL4Rα blockade inhibits proliferation of malignant lymphocytes and the immunosuppressive tumor microenvironment of mycosis fungoides.

BACKGROUND: Limited therapeutic options are available for patients with advanced-stage mycosis fungoides (MF), and the 5-year survival rate is 25%. Du...

Roles and applications of artificial intelligence in fetal and placental MRI: a literature review.

BACKGROUND: Artificial intelligence (AI) has been increasingly integrated with fetal and placental magnetic resonance imaging (MRI) to enhance the det...

Predicting heterosexual reactions to coming out in China.

For many Chinese sexual minority men, coming out-disclosing their sexual orientation-is stressful because of concerns about how heterosexual recipient...

Impact on Cost and Expert Time of Data-Efficient Deep Learning for Medical Image Segmentation.

Purpose To develop and systematically evaluate an iterative training approach, termed the expert-guided annotation loop, for efficient reference stand...

Segmenting Older Adults by Their Acceptance of Digital Health Care Devices: Cross-Sectional Study Using the Augmented Technology Acceptance Model and K-Means Clustering.

BACKGROUND: Population aging has become a critical global challenge, with South Korea entering a super-aged society and facing rapidly increasing heal...

Human donor liver viability evaluation with polarization-sensitive optical coherence tomography.

Human liver transplantation is constrained by a critical shortage of viable donor livers. In response to this shortage, marginal livers from extended ...

Topology-Aware Segmentation for Tubular Structure in 3D Microscopy.

High-resolution 3D microscopy has become a foundational tool in biomedical research by reconstructing vascular and neural networks from subcellular to...

Molecular characteristics and modifications of glioblastoma affecting the efficacy of immunotherapy.

Glioblastoma is a highly aggressive brain tumor characterized by complex genetic, molecular, and epigenetic features that present significant challeng...

Inflammation-mediated diabetes-liver disease cross-organ crosstalk: From molecular mechanisms to precision therapeutic strategies.

The rising global prevalence of diabetes mellitus and its liver complications presents a significant public health challenge. Inflammation-driven cros...

An immunological panacea for cancer-related cachexia.

Cancer cachexia, responsible for up to 30% of cancer deaths, has transitioned conceptually from a mere nutritional deficit into a highly coordinated, ...

Zero-shot design of drug-binding proteins via neural iterative selection-expansion.

The design of proteins that bind to small molecules has been challenging because it requires simultaneous optimization of the protein sequence, protei...

Development of a precise saliva-based epigenetic clock using a six-CpG-marker panel.

Saliva, a frequently encountered biological specimen in forensic investigations, has great potential to provide critical leads if the donor's age can ...

Multimodal machine learning and deep graph neural networks for the prediction of molecular inhibitory activity and disease associations.

Effectively integrating a variety of biological and chemical data sources is essential for the acceleration of drug discovery and precision diagnostic...

Multimodal deep learning using pre-transplant CT images predicts cardiovascular events after liver transplantation.

Human organ-on-a-chip technology as a catalyst for drug discovery.

The pharmaceutical industry currently faces a critical attrition crisis, with approximately 90% of drug candidates failing during clinical translation...

Overcoming cellular secretion bottlenecks: advanced secretion engineering and molecular tailoring for next-generation microbial α-amylases with enhanced industrial performance.

α-amylases are indispensable industrial biocatalysts, yet their recombinant production faces significant biochemical and cellular bottlenecks. Recent ...