Itaconate transporter SLC13A3 impairs tumor immunity via endowing ferroptosis resistance.

Immune checkpoint blockade (ICB) triggers tumor ferroptosis. However, most patients are unresponsive to ICB. Tumors might evade ferroptosis in the tumor microenvironment (TME).

Adding Highly Variable Genes to Spatially Variable Genes Can Improve Cell Type Clustering Performance in Spatial Transcriptomics Data.

Spatial transcriptomics has allowed researchers to analyze transcriptome data in its tissue sample's spatial context. Various methods have been developed for detecting spatially variable genes (SV genes), whose gene expression over the tissue space shows strong spatial autocorrelation. Such genes are often used to define clusters in cells or spots downstream.

Beyond the Spectrum: Subtype-Specific Molecular Insights into Autism Spectrum Disorder Via Multimodal Data Integration.

Some toddlers with autism spectrum disorder (ASD) have mild social symptoms and developmental improvement in skills, but for others, symptoms and abilities are moderately or even severely affected. Those with profound autism have the most severe social, language, and cognitive symptoms and are at the greatest risk of having a poor developmental outcome. The little that is known about the underlying biology of this important profound autism subtype, points clearly to embryonic dysregulation of proliferation, differentiation and neurogenesis.

Landscape of Differentiation Potentials as a "Hallmark" in Oral-derived MSCs.

Background: Mesenchymal stem cells (MSCs) offer clinical promise for use in cell therapy approaches for regenerative medicine. A therapeutic challenge is that MSCs from different tissues are phenotypically and functionally distinct. Therefore, this study aims to molecularly characterize oral-derived MSCs by defining one of the three hallmarks of MSCs, differentiation potential, to discern their true molecular identities.

Five-Feature Models to Predict Preeclampsia Onset Time From Electronic Health Record Data: Development and Validation Study.

Background:  Preeclampsia is a potentially fatal complication during pregnancy, characterized by high blood pressure and the presence of excessive proteins in the urine. Due to its complexity, the prediction of preeclampsia onset is often difficult and inaccurate.

Objective:  This study aimed to create quantitative models to predict the onset gestational age of preeclampsia using electronic health records.