Stem Cell Research

Personalised approach to hypertension treatment: Rationale and design of the HYPERMARKER randomised trial

Background and Objective: Blood pressure treatment response is variable in individual patients, and the choice of medical therapy is often dependent on clinician experience. Treatment choices can be personalised by patient empowerment, metabolomic profiles and augmented by machine learning, but robust evaluation is lacking on how these can be combined to enhance clinical effectiveness. The HYPERMA...

GRAVITY: Dynamic gene regulatory network-enhanced RNA velocity modeling for trajectory inference and biological discovery

RNA velocity techniques have emerged as efficient tools for unraveling the complex trajectories of cell development and differentiation. However, most of existing RNA velocity approaches are constrained by estimating transcriptional parameters for each gene in isolation and neglects the regulatory relationships among genes, which limits the ability to jointly resolve the dynamic rewiring of gene r...

Graph neural network-based prediction of direct reprogramming factors using gene regulatory networks with microRNA-mediated regulation

Direct reprogramming (DR) converts somatic cells directly into target cell types while bypassing an intermediate pluripotent state, such as induced pl...

Machine Learning Identifies Distinct Treg-Mediated Remodeling in HFpEF Hearts Treated with Neonatal Mesenchymal Stem Cells and Their Secretome

Background: Heart failure with preserved ejection fraction (HFpEF) remains a major therapeutic challenge due to its complex pathophysiology and pronou...

Machine learning-based image analysis of Parkinson's disease iPS-derived neurons predicts genotype and reveals mitochondria-lysosome abnormalities

Mitochondrial and lysosomal dysfunction are central features of Parkinson's disease (PD) across major genetic forms including PRKN, SNCA, and LRRK2. W...

An Advanced Humanized Systemic Lupus Erythematosus Model Enables Parallel Profiling of B Cell-Targeted Therapies

B cell-targeted therapies represent a transformative frontier for systemic lupus erythematosus (SLE) intervention, yet clinical recommendation of spec...

Expected Return Causes Outcome-Level Mode Collapse in Reinforcement Learning and How to Fix It with Inverse Probability Scaling

Many reinforcement learning (RL) problems admit multiple terminal solutions of comparable quality, where the goal is not to identify a single optimum ...

Single-Cell Raman Profiling Enables Rapid Precision Phage Therapy Against Multidrug-Resistant Hypervirulent Klebsiella pneumoniae

Multidrug-resistant hypervirulent Klebsiella pneumoniae (MDR-hvKP) poses a severe global health threat. Phage therapy is a promising alternative, but ...

Machine Learning Driven 'Therapy Calculator' for Self-Managed Digital Speech-Language Therapy for Individuals with Post-stroke Aphasia

Individuals with post-stroke aphasia live with long-term disabilities, yet they do not know whether they will improve their communication and cognitiv...

Retrospective multi-cohort validation of a real-world transcriptomics-guided machine learning model for treatment response prediction in breast cancer

Selection of systemic therapy for breast cancer remains largely empirical, particularly for chemotherapy, due to the lack of robust biomarkers that pr...

Peripheral blood profiles reflecting progenitor lineage balance predict treatment response in chronic myeloid leukemia

Early achievement of deep remission improves patients' outcome in chronic myeloid leukemia (CML) treatment, highlighting the need for predictive indic...

Normal Breast Tissue (NBT)-Classifiers: Advancing Compartment Classification in Normal Breast Histology

Background: Cancer research emphasises early detection, yet quantitative methods for analysing normal tissue remain limited. Hematoxylin and eosin (H&...

Deep learning-guided design of cell type-specific AAV promoters

Precise cell type targeting is critical for both clinical and experimental applications of adeno-associated viral (AAV) vectors, yet engineering vecto...

Proceedings of the Association for Pathology Informatics Bootcamp 2023: Ethics, equity, and regulations.

The Pathology Informatics Bootcamp is held annually at the Pathology Informatics Summit and provides pathology trainees with knowledge about both core...

Real-Time Dose-Guided Radiation Therapy.

Dramatic strides have been made in real-time adaptive radiation therapy, where treating single tumors as dynamic but rigid bodies has demonstrated a h...

GloBIAS: strengthening the foundations of BioImage Analysis

There is a global need for BioImage Analysis (BIA) as advances in life sciences increasingly rely on cutting-edge imaging systems that have dramatic...

ABCD: A Simulation Method for Accelerating Conversational Agents With Applications in Aphasia Therapy.

PURPOSE: Development of aphasia therapies is limited by clinician shortages, patient recruitment challenges, and funding constraints. To address these...

Ethics by Design: A Lifecycle Framework for Trustworthy AI in Medical Imaging From Transparent Data Governance to Clinically Validated Deployment

The integration of artificial intelligence (AI) in medical imaging raises crucial ethical concerns at every stage of its development, from data coll...

A Practical SAFE-AI Framework for Small and Medium-Sized Enterprises Developing Medical Artificial Intelligence Ethics Policies

Artificial intelligence (AI) offers incredible possibilities for patient care, but raises significant ethical issues, such as the potential for bias...

Climate change and health: the next challenge of ethical AI.

Artificial intelligence (AI) is one of the world's most resource-intensive digital technologies, but the environmental impact of AI on health remains ...