Transplantation

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 organ scales, thereby facilitating quantitative analysis of tissue microenvironments, disease progression, and early pathological changes. However, accurately segmenting tubular structure like microvascular and neurite in 3D microscopy remains chall...

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 challenges for treatment. This review explores recent advances in understanding the molecular and epigenetic landscape of glioblastoma, with particular emphasis on epigenetic modifications such as DNA methylation, histone changes, and N6-methyladenosine regu...

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 ...

A self-orchestrating physics-discovering neural architecture for adaptive and fault-resilient robotic motion control via RPA and digital twins.

To autonomously control a robot's movement in complex and unpredictable environments, adaptive models must be developed that can continuously learn ab...

A deep learning framework for histopathological analysis of pixel-level extracellular matrix variation in standard H&E-stained images.

Artificial intelligence-driven image analysis has enabled significant advances in digital pathology. However, most approaches have focused on cell or ...

A case of artificial intelligence-enhanced diagnostics leading to heart transplantation.

PCT-Anchored Machine Learning for Pre-Culture Identification of Gram-Negative Sepsis in Children: A Four-Site Study.

OBJECTIVE: Procalcitonin (PCT) has moderate accuracy for bacteremia detection but is infrequently used in pediatric emergency departments, partly due ...

Contrastive Machine Learning to Quantify Hypertensive Multiorgan Damage and Identify New Disease Phenotypes: A Multinational Multimodal Study.

BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage increases risk of vascular events...

Performance evaluation of AkidaNet converted to spiking domain for the classification of weeds in cotton fields.

The infestation of weeds in cotton fields poses a serious threat to the production of lint. Weeds are eliminated either by spraying weed kill sprays, ...

Machine Learning-Assisted Discovery of Thermally Activated Delayed Fluorescence Emitters.

This study presents a machine learning (ML)-assisted framework for the discovery and screening of novel TADF emitters. A dataset of 366 known compound...

Stem cell-derived extracellular vesicles for rare diseases: A clinical‑bottleneck‑to‑mechanism framework for translation.

Rare diseases impose a disproportionate clinical burden, and yet therapeutic progress is hindered by small cohorts, biological heterogeneity, and limi...

Engineered Neutrophils in Translational Medicine: Gene Editing, Nanotechnology, and AI-Driven Clinical Breakthroughs.

Engineered neutrophils, modified via advanced biotechnological tools, are emerging as pivotal agents in translational medicine. By integrating gene ed...

Integrative multi-omics analysis and machine learning identify M2 macrophage-induced ferroptosis resistance in glioblastoma.

Glioblastoma (GBM) is characterized by profound intratumoral heterogeneity and an immunosuppressive microenvironment that drive therapeutic resistance...