Transplantation

Deep learning unlocks sequence-divergent synthetic promoters to empower Streptomyces natural product engineering.

Streptomyces are renowned for their unparalleled capacity to produce bioactive natural products, making them prime candidates for industrial antibiotic manufacturing. However, Streptomyces lags behind E. coli and yeast in genetic tool development, as its promoters often constrained by narrow strength ranges, poor availability, and minimal diversity, hindering advanced synthetic biology application...

Automated dicentric scoring system in Singapore nuclear research and safety initiative.

The dicentric chromosome assay (DCA) serves as the gold standard for quantifying ionising radiation exposure in individuals. However, the conventional manual scoring method for DCA is both time-consuming and mentally demanding. Consequently, numerous research groups and commercial entities are actively pursuing the integration of artificial intelligence to automate this process. In this study, we ...

Advances in immune checkpoint inhibitor therapy for microsatellite instability-high (MSI-H) and mismatch repair-deficient (dMMR) colorectal cancer: Insights from the tumor immune microenvironment.

This review systematically analyzes the relationship between the immune microenvironment characteristics of microsatellite instability-high (MSI-H) or...

Δ-Machine learning toward CCSD accuracy for homohalogenated borane-phosphine adducts: screening low-energy structures from DFT and MP2 libraries.

Accurate formation energies for weak boron-phosphorus Lewis adducts are challenging because low-order correlation and density-functional methods can m...

Artificial Intelligence in Kidney Transplant Pathology: Current Evidence, Limitations, and Relevance to the Banff Framework.

The Banff Classification, established in 1991, provides a global standard for diagnosing and grading kidney transplant pathology, evolving through reg...

Full-Body AI Agent: A Perspective on Multi-Scale Collaborative AI for Systemic Biology and Precision Medicine.

Artificial intelligence (AI) is increasingly applied to biomedical research, but most current systems remain limited to specific tasks, data types, or...

Cancer immunotherapy: mechanisms, clinical applications, resistance and future directions.

Cancer immunotherapy has revolutionised oncology by utilising immune-mediated mechanisms to achieve durable anti-tumour responses and long-term clinic...

Immersive spatial computing in neurosurgery.

PURPOSE: Immersive spatial computing technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), are increasingly ap...

Machine Learning Model Predicts Clinical Adverse Events of Small Molecule Kinase Inhibitors in Cancer Patients Using On-/Off-Target Engagement and Tissue Selectivity.

Adverse events (AEs) of small molecule kinase inhibitors (SMKIs) at therapeutic doses in cancer patients are largely unpredictable in phase I-III stud...

Quantifying and Interpreting Solvation Power of Cyclic Carbonate by Chemical Calculation and Machine Learning.

Ion dynamics in carbonate electrolytes are fundamentally governed by the solvation power of cyclic solvents, a property whose quantification remains e...

Emerging applications of traditional and generative artificial intelligence in Liver Transplantation.

Artificial intelligence (AI) has emerged as a transformative force in liver transplantation (LT), spanning patient selection, donor-recipient matching...

Microplastics and the Endocrine-Metabolic Interface: Novel Diagnostic Tools Targeting Thyroid-Adipose Axis.

Microplastics (MPs) have been identified as major environmental contaminants that can affect organisms directly and act as carriers of particles and c...

T-cell-mediated immunity to influenza A (H2N3): implications for caccine efficacy and cross-subtype protection.

Influenza A viruses pose a significant pandemic threat, with H2N3 in particular representing a subtype of particular concern due to limited population...

Comparative analysis of AI and human radiographer performance in radiographic image assessments: A pilot study using a large language model to simulate radiographer decision-making.

INTRODUCTION/BACKGROUND: To determine whether a prompting-based, interpretable artificial intelligence (AI) system, specifically a large language mode...

Frailty and Fitness in Older Adults With Acute Myeloid Leukemia: From Chronological Age to Multiparametric Assessment.

Acute Myeloid Leukemia predominantly affects older adults, who often present with comorbidities, functional impairment, and frailty, limiting eligibil...

Explainable machine learning-guided integrated multiomics analysis reveals macrophage-driven immune suppression in breast cancer.

Despite thorough characterizations of cellular compositions within the breast tumor microenvironment (TME), their implications for disease progression...

Exploring multi-feedstock biodiesel-hydrogen synergies for enhanced diesel engine performance using hybrid AI techniques.

In recent years of crude oil shortage and price rise, biodiesel has emerged as a new-age sustainable fuel, owing to its positives mainly providing low...

Artificial Intelligence-based predictive models for adverse blood donor reactions: a systematic review of immediate and delayed events and clinical data approaches.

BACKGROUND: A significant challenge in blood donation is the occurrence of adverse donor reactions (ADRs) and their subsequent negative impact on the ...

Machine learning prediction of dual absorber lead-free perovskite solar cells for boosting PCE.

Curtailing the toxicity level of perovskites is a considerable obstacle resisting the wide-scale commercialization of perovskite solar cells (PSCs). T...

Bridging discovery and clinical science: A framework for advancing atherosclerosis research using innovative models.

Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of death, with substantial residual risk persisting despite current lipid-lowering, ...