Transplantation

Exfoliated kidney cells from urine for non-invasive kidney transplant monitoring: A potential opportunity?

Kidney transplantation is usually the optimal treatment option for patients living with kidney failure given its associations with improved survival, quality of life outcomes and a reduction in the personal, economic, and societal burden of long-term dialysis. While advantages of kidney transplantation are recognized, post-transplant complications, such as graft rejection, ischemia-reperfusion inj...

Real-world evaluation of large language models in detecting drug-related problems: A clinical pharmacist-AI concordance study in hematology care.

IntroductionLarge language models (LLMs) offer potential as clinical decision support systems (CDSS) for detecting drug-related problems (DRPs), yet their real-world performance compared to clinical pharmacists (CPs) remains unclear, especially in complex hematology care. We aimed to evaluate the concordance between a clinical pharmacist and three LLMs in identifying DRPs within a Bone Marrow Tran...

Challenging a clinical dogma with multimodal machine learning: a retrospective analysis of transplant mismatched donor selection.

ReFaceX: donor-driven reversible face anonymisation with detached recovery.

Organisations must share facial imagery that remains useful for analysis while protecting identity. Many current methods fail to strike this balance: ...

Advances in the postoperative care of the liver transplant recipient.

PURPOSE OF REVIEW: Survival rates following liver transplantation now exceed 90% at one year. However, the patient group undergoing liver transplantat...

Risk prediction in IgA nephropathy: from conventional models to machine learning, deep learning, and precision nephrology.

IgA nephropathy (IgAN) is the most prevalent primary glomerular disease worldwide and a leading cause of end-stage kidney disease (ESKD). Its clinical...

[Design and synthesis of molecularly imprinted polymers and their applications in medical diagnosis and biocatalysis].

Molecularly imprinted technology （MIT） represents an advanced synthetic strategy that emulates biological recognition mechanisms， such as antigen-anti...

Advances in β-titanium alloys for safer and greener biomedical implants.

In the biomedical field, titanium alloys have long been preferred for orthopedic and dental devices due to their excellent biocompatibility and mechan...

The Rise of Aqueous Selenium-Based Batteries: Challenges, Strategies, and the Path Forward.

Aqueous metal-selenium batteries (AMSeBs) have emerged as promising candidates for safe, cost-effective, and high-energy-density energy storage, yet t...

An annotated dataset of images of Chinese giant salamanders.

The Chinese giant salamander is classified as a Class II protected species in China and is recognized as critically endangered by the International Un...

From Ageing Clocks to Organ Networks: Biological Age-Driven Organ Asynchrony and Inter-organ Interactions Shaping Mortality Risk.

Ageing is a multidimensional and heterogeneous process that progresses asynchronously across organ systems. Advances in multi-omics technologies have ...

Gut microbiota-derived metabolites as immune modulators in aging and age-related chronic inflammatory diseases.

Age-associated dysbiosis, marked by shifts in the composition of gut microbiota and gut microbiota-derived metabolites (GMDMs), is increasingly implic...

Machine Learning Models for Posttransplant Lymphoproliferative Disorder (PTLD) Risk Prediction in Thoracic Transplantation.

Posttransplant lymphoproliferative disorder (PTLD) is the second most common malignancy in thoracic transplant recipients and is associated with poor ...

A machine learning model for predicting 28-day mortality in patients with alcoholic cirrhosis and sepsis: a study based on the MIMIC-IV database.

OBJECTIVE: To develop and validate the best machine learning model for predicting 28-day mortality in septic patients with alcoholic cirrhosis (AC), l...

Machine Learning-Based Pathomics Signature in Predicting MSH2 Expression and Prognosis in Gastric Cancer.

BACKGROUND: Gastric cancer (GC) is one of the most prevalent and lethal gastrointestinal malignancies. MutS homolog 2 (MSH2), a DNA mismatch repair pr...

Deep learning-integrated multilayer thermal gradient sensing platform for real-time blood flow monitoring.

Blood flow monitoring is fundamental for assessing cardiovascular health and identifying vascular complications. Traditional Doppler ultrasound method...

Design and rationale of the artifiCiAl intelligence Model for Evaluating the surgical techniques of caRdiAc surgeons (CAMERA): a cohort study.

INTRODUCTION: Coronary artery bypass grafting (CABG) is a technically demanding procedure where surgical skill directly influences outcomes. Tradition...

Data-driven predictive modeling for massive intraoperative blood loss during living donor liver transplantation: Integrating machine learning techniques.

BACKGROUND: Massive intraoperative bleeding (IBL) in liver transplantation (LT) poses serious risks and strains healthcare resources necessitating bet...

Using human-robot interaction to assess emotion recognition in dialysis patients: A preliminary study.

This cross-sectional observational study examined the relationship between psychological factors and multimodal emotion recognition abilities in patie...

Shear stress optimization and smart control strategies toward AI-integrated tissue culture systems.

Shear stress serves as a key physical stimulus in three-dimensional (3D) cell culture systems, regulating critical physiological processes such as cel...