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This study synthesizes zinc oxide nanoparticles using Flemingia macrophylla extract and demonstrates their anti-diabetic and anti-inflammatory effects in Drosophila melanogaster.

This study investigates CYP1A2's role in metabolizing organophosphorus compounds and finds it selectively degrades thions and is inhibited by OP compounds, suggesting its potential as a bioscavenger.

This study tracks the development of human autoantibodies against interferons over time, revealing their maturation, specificity, and synergistic effects in blocking IFN signaling.

This paper introduces a method using femtosecond laser trenching to speed up cryo-electron tomography lamella preparation by reducing milling time and damage.

AGVarPred is a gradient-boosted classifier that improves pathogenicity prediction of germline variants by integrating AlphaGenome features, outperforming existing models across SNVs and indels.

Open-source Python package parses Axion spk files directly and matches NeuralMetric Tool outputs, then reveals burst and network burst hyperexcitability, without synchrony change, in LGI2-knockdown human iPSC neurons.

The paper introduces RiboCouple, a method that links RNA backbone geometry to sequence design using learned interaction topologies, improving refolding validity in RNA structure prediction.

This study examines how panitumumab affects the proteome of EGFRvIII glioblastoma cells and their extracellular vesicles, showing reduced EGFRvIII on EVs and changes in extracellular matrix proteins.

The paper identifies novel extracellular and intercellular γ-tubulin structures in mouse oocytes and embryos, revealing their role in early developmental processes.

This paper evaluates the feasibility of re-identifying individuals using polygenic predictions and finds that real-world effectiveness is limited due to low priors and poor sensitivity for sensitive genotypes.

The paper introduces a framework to analyze network topology in focal epilepsy using resting-state fMRI, identifying two axes that reveal distinct topological phenotypes and their clinical associations.

ScienceRSI improves scientific AI through recursive self-improvement by transferring capabilities across model scales, achieving top performance on multiple benchmarks.

This study uses live imaging in zebrafish to show that cone outer segments are removed in small, successive particles at the cone-RPE interface without extracellular accumulation.

This study integrates a large scRNA-seq dataset of CTCL to identify molecular subtypes and microenvironmental changes with clinical relevance.

This paper develops a Bayesian framework to integrate multiple converging pathways in adverse outcome pathways, demonstrating improved predictive performance for liver steatosis.

The paper benchmarks clustering strategies for patient-specific gene regulatory networks across 9,778 cancer samples, finding that standard deviation-based feature selection with k-means performs best.

The paper identifies an altORF-encoded microprotein, GndA, that facilitates stress-dependent relocalization of its primary ORF partner, Gnd, in E. coli during heat shock.

This paper develops a real-time deep learning workflow for non-invasive high-magnification imaging of C. elegans, enabling stable imaging across magnifications without immobilization.

This study shows that autoantibodies against GABAB receptors cause presynaptic pathology leading to cognitive decline and memory impairment.