Nephrology

Immunochromatographic SERS sensor-deep learning combined strategy for intelligent diagnosis of chronic kidney disease.

A combined "immunochromatographic surface-enhanced Raman scattering (SERS) sensor-deep learning" detection strategy is proposed. Specifically, we first prepared an immunochromatographic SERS sensor with excellent surface enhancement capability for the specific recognition of neutrophil gelatinase-associated lipocalin (NGAL) molecules in serum, significantly enhancing the detection sensitivity of t...

Noninvasive prediction of occult pT3a upstaging in localized ccRCC with radiogenomic insights and prognostic relevance.

Occult pathological T3a (pT3a) upstaging in cT1b-T2a clear cell renal cell carcinoma (ccRCC) correlated with poor prognosis and necessitated modifications in surgical planning. However, predicting it preoperatively remains challenging. In this multicenter study involving 1661 patients across five institutions and the KiTS23 dataset, RENALNet, a 3D deep learning framework trained on nephrographic-p...

Study design for an emulated trial of a 2 arm, parallel, stratified, adaptive, RCT of CABG versus PCI in people requiring myocardial revascularization at high risk (High-Risk REVASC).

AIM: This study aims to use routinely collected health data and trial emulation methodology to inform the design of a pragmatic randomized controlled ...

Development of machine learning-driven non-invasive diagnostic models for idiopathic membranous nephropathy in Chinese patients.

BACKGROUND: Idiopathic membranous nephropathy (IMN) is a major cause of nephrotic syndrome and end-stage renal disease, but the gold-standard diagnost...

RenoTrue: A diabetes-specific machine learning model to estimate glomerular filtration rate for people with diabetes.

BACKGROUND: Existing methods for estimating GFR in people with diabetes have shown inaccuracies when compared to mGFR measurements. We developed and v...

Powering the future: advances, challenges, and sustainability of polymer electrolytes in lithium-sulfur batteries.

Lithium-sulfur (Li-S) batteries offer a transformative theoretical energy density (∼2600 Wh kg-1), positioning them as strong candidates for next-gene...

Discovery of an Artificial Intelligence Label Feedback Loop: How the Success of a Clinically Implemented Artificial Intelligence Algorithm Has Created an Unforeseen Challenge to Algorithm Retraining.

BACKGROUND: Artificial intelligence (AI) augmented laboratory tests can improve quality, efficiency, cost-effectiveness, and staff satisfaction. Howev...

Interpretable machine learning reveals phosphorus-to-albumin ratio as a novel predictor of mortality and acute kidney injury in critically ill pancreatitis patients: a multi-center retrospective analysis.

Acute kidney injury (AKI), a common and severe complication of acute pancreatitis (AP), is amenable to early intervention. Phosphorus-to-albumin ratio...

Interpretable Machine Learning for Solid-State Batteries.

Solid-state batteries (SSBs) have emerged as promising candidates for next-generation energy storage systems due to their high energy density and enha...

Multiscale segmentation using hierarchical phase-contrast tomography and deep learning.

Biomedical systems span multiple spatial scales, encompassing tiny functional units to entire organs. Interpreting these systems through image segment...

Bridging machine learning and clinical practice: a multicentre nomogram for 90-day graft failure risk stratification in heart transplantation.

BACKGROUND: Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, base...

Single-cell transcriptomics and machine-learning reveal M1 macrophage-driven progression from minimal change disease to focal segmental glomerulosclerosis.

Minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) are two key nephrotic syndrome types with significant clinical implications...

Validation of a Trained AI Imaging Model for Detecting Diabetic Foot Deformities.

Diabetes is a leading cause of morbidity and mortality, contributing to complications such as cardiovascular disease, kidney failure and lower-limb am...

Integrated network pharmacology and bioinformatics analysis reveals MME as key target of Notoginsenoside R1 in diabetic nephropathy.

BACKGROUND: Diabetic nephropathy (DN) is a major diabetes complication and a primary cause of end-stage renal failure. Notoginsenoside R1 (NGR1) is kn...

Overcoming Resistance in EGFR-Mutant Cancers: A Comprehensive Review of Inhibitor Evolution and SAR-Based Design.

The epidermal growth factor receptor (EGFR) is a key target in cancer therapy, mainly in non-small cell lung cancer (NSCLC). Though, the efficacy of E...

Genomics of kidney volumes: one size does not fit all.

To characterize the genetic basis of chronic kidney disease, genome-wide association studies focused on chronic kidney disease-defining traits that we...

Effects of ABO-Incompatible Blood Transfusion on Immune Response and Rejection After Organ Transplantation.

BACKGROUND: Peri-operative blood transfusion is common during solid-organ transplantation, yet the impact of ABO-incompatible (ABOi) blood exposure on...

Six-axis robotic extrusion of hybrid hydrogels for biomimetic airway model fabrication.

Respiratory diseases remain a major global health burden, motivating the need for improved experimental lung models that capture both anatomical geome...

Development of an interpretable machine learning model for predicting 4-year chronic kidney disease risk in elderly hypertensive patients.

INTRODUCTION: Age and hypertension are key drivers of renal impairment, predisposing older hypertensive adults to faster kidney function decline and h...

C-X-C Motif Chemokine Ligand 3 as a Potential Biomarker for Diagnosis and Prognosis of Diabetic Kidney Disease.

Diabetic kidney disease (DKD) is the primary cause of end-stage renal disease globally, yet reliable biomarkers for its diagnosis and progression asse...