Rheumatology

Mapping trans-eQTLs at single-cell resolution using Latent Interaction Variational Inference.

Single-cell expression quantitative trait loci (eQTL) studies hold promise for linking genetic variants to changes in gene expression in individual cells, thereby offering deeper insights into the genetic basis of human traits and diseases. Existing methods for mapping cis effects rely on predefined cell types, pseudobulk aggregation, or single-gene association tests, and are thus limited in their...

Late-Stage Generalization Collapse in Grokking: Detecting anti-grokking with Weightwatcher

\emph{Memorization} in neural networks lacks a precise operational definition and is often inferred from the grokking regime, where training accuracy saturates while test accuracy remains very low. We identify a previously unreported third phase of grokking in this training regime: \emph{anti-grokking}, a late-stage collapse of generalization. We revisit two canonical grokking setups: a 3-layer ...

SemBind: Binding Diffusion Watermarks to Semantics Against Black-Box Forgery Attacks

Latent-based watermarks, integrated into the generation process of latent diffusion models (LDMs), simplify detection and attribution of generated ima...

C-RLM: Schema-Enforced Recursive Synthesis for Auditable, Long-Context Clinical Documentation

Clinical decision-making for multi-morbid patients requires synthesizing evidence from lengthy, fragmented records-a task that exposes the limitations...

Predicting Gene Disease Associations in Type 2 Diabetes Using Machine Learning on Single-Cell RNA-Seq Data

Diabetes is a chronic metabolic disorder characterized by elevated blood glucose levels due to impaired insulin production or function. Two main forms...

Pain-regulation circuitry as a predictor of chronic pain phenotypes

Background: Chronic pain is a multidimensional condition in which emotional distress, negative expectations, and functional impairment signal greater ...

An anatomical hotspot for striatal dopamine-acetylcholine interactions during reward and movement

Dopamine (DA) and acetylcholine (ACh) are key neuromodulators that regulate striatal circuits underlying movement and reinforcement learning. Evidence...

Robust and Generalizable Atrial Fibrillation Detection from ECG Using Time-Frequency Fusion and Supervised Contrastive Learning

Atrial fibrillation (AF) is a common cardiac arrhythmia that significantly increases the risk of stroke and heart failure, necessitating reliable and ...

High-dimensional spatial proteomics and novel machine learning pipeline identifies disease specific renal damage states

Lupus nephritis (LuN) and renal allograft rejection (RAR) manifest inflammation and fibrosis that ultimately lead to kidney failure. To quantitatively...

3D reconstruction of spatial transcriptomics with spatial pattern enhanced graph convolutional neural network

Spatially resolved transcriptomics (SRT) is a promising new technology that enables simultaneous analysis of gene expression and spatial information f...

Supervised machine learning and molecular docking modeling to identify potential Anti-Parkinson's agents.

Parkinson's disease is a neurodegenerative condition that affects the brain's neurons, and causes malfunction of nerve cells and their death. A neurot...

Anti-Symmetric Molecular Graph Learning Approach With Residual Adaptive Network Based Fuzzy Inference System for Lethal Dose Forecasting Problem.

In recent times, graph neural networks (GNNs) have become essential tools in molecular graph learning, due to its ability to model intricate structura...

Performance and Practical Considerations of Large and Small Language Models in Clinical Decision Support in Rheumatology

Large language models (LLMs) show promise for supporting clinical decision-making in complex fields such as rheumatology. Our evaluation shows that ...

Multi-Modal Face Anti-Spoofing via Cross-Modal Feature Transitions

Multi-modal face anti-spoofing (FAS) aims to detect genuine human presence by extracting discriminative liveness cues from multiple modalities, such...

RAM-W600: A Multi-Task Wrist Dataset and Benchmark for Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a common autoimmune disease that has been the focus of research in computer-aided diagnosis (CAD) and disease monitorin...

Artificial intelligence in drug discovery: A comprehensive review with a case study on hyperuricemia, gout arthritis, and hyperuricemic nephropathy

This paper systematically reviews recent advances in artificial intelligence (AI), with a particular focus on machine learning (ML), across the enti...

Cells Keep Diverse Company in Diseased Tissues.

Emerging spatial profiling technologies have revolutionized our understanding of how tissue architecture shapes disease progression, yet the contribut...

Advancing T-cell immunotherapy for cellular senescence and disease: Mechanisms, challenges, and clinical prospects.

Cellular senescence is a complex biological process with a dual role in tissue homeostasis and aging-related pathologies. Accumulation of senescent ce...

Specific heat anomalies and local symmetry breaking in (anti-)fluorite materials: A machine learning molecular dynamics study.

Understanding the high-temperature properties of materials with (anti-)fluorite structures is crucial for their application in nuclear reactors. In th...

[Progress in neoadjuvant immunotherapy for locally advanced rectal cancer].

Neoadjuvant chemoradiotherapy (NACRT) is the standard treatment for locally advanced rectal cancer (LARC), yet the pathological complete response (pCR...