Results 81 to 90 of about 640,924 (242)
The ER's continuous tubular network is maintained by ER‐shaping proteins whose mutation or dysregulation contributes to neurodegenerative diseases. Here, we show that ER morphology sets the speed of Ca2+ store replenishment between firing events. Disrupting ER continuity slows intra‐ER Ca2+ redistribution from extracellular refill (SOCE) sites, driving
Valentina Davi +13 more
wiley +1 more source
Protein complexes like KIBRA‐PKMζ are crucial for maintaining memories, forming month‐long protein traces in memory‐tagged neurons, but conventional RNA‐seq analysis fails to detect their transcript changes, leaving memory molecules undetected in the shadows of abundantly‐expressed genes.
Jiyeon Han +10 more
wiley +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Nucleation Kinetics Reveals a Distinct Biological Function Space of Biomolecular Condensates
This study utilizes microfluidics to quantify the nucleation rates of dense liquid phases within dilute solutions and of the reverse process, in which dilute voids nucleate inside condensates. The interfacial tension is identified as the key determinant of both processes.
Leif‐Thore Deck +5 more
wiley +1 more source
This study outlines the developmental pipeline of a multiplexed nanozyme‐based lateral flow immunoassay for the purpose of ovarian germ cell tumor detection. It demonstrates the application of a design of experiments optimization approach for nanozyme probe conjugate development.
Aida Abdelwahed +10 more
wiley +1 more source
Cross‐Modal Denoising and Integration of Spatial Multi‐Omics Data with CANDIES
In this paper, we introduce CANDIES, which leverages a conditional diffusion model and contrastive learning to effectively denoise and integrate spatial multi‐omics data. We conduct extensive evaluations on diverse synthetic and real datasets, CANDIES shows superior performance on various downstream tasks, including denoising, spatial domain ...
Ye Liu +5 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Laterally spreading tumors (LSTs) are precancerous colorectal lesions characterized by a flat morphology. This study reveals a mechanochemical pathway through which a soft matrix microenvironment diminishes spatial constraints in intestinal adenomas. This process promotes deficiencies in tight junction proteins, mediated by the mechanoreceptor ADORA2B ...
Jiamin Zhong +21 more
wiley +1 more source
The impact of the mathematical adversity quotient on preparatory students' mathematics learning engagement: moderated mediation effect analysis. [PDF]
Liu J, Sun Y, Li Y.
europepmc +1 more source
Accurate prediction of early recurrence in pancreatic ductal adenocarcinoma is vital for optimizing treatment. A novel, integrated radiomics‐pathology machine learning model successfully forecasts recurrence risks by analyzing preoperative CT images and computational pathology.
Sihang Cheng +17 more
wiley +1 more source

