NAC regulates metabolism and cell fate in intestinal stem cells.

Intestinal stem cells (ISCs) face the challenge of integrating metabolic demands with unique regenerative functions. Studies have shown an intricate interplay between metabolism and stem cell capacity; however, it is still not understood how this process is regulated. Combining ribosome profiling and CRISPR screening in intestinal organoids, we identify the nascent polypeptide-associated complex (NAC) as a key mediator of this process.

P-stalk ribosomes act as master regulators of cytokine-mediated processes.

Inflammatory cytokines are pivotal to immune responses. Upon cytokine exposure, cells enter an "alert state" that enhances their visibility to the immune system. Here, we identified an alert-state subpopulation of ribosomes defined by the presence of the P-stalk.

Comparison of early characteristics of multisystemic inflammatory syndrome and Kawasaki disease in children and the course of Kawasaki disease in the pandemic.

Introduction: Multisystemic inflammatory syndrome (MIS-C) is a newly described disease manifestation in children associated with the novel coronavirus SARS-CoV-2 infection and can be easily confused with Kawasaki disease with its clinical and laboratory findings. In this study, the clinical findings, organ involvements, similarities, and differences in laboratory and imaging of the children with MIS-C and KD at the time of admission will be revealed in detail, and the treatment methods and follow-up results will be revealed.

Material And Method: Our study was a single-center study and included pediatric patients who were treated with a diagnosis of MIS-C between March 2020 and July 2023 in the pediatric cardiology, pediatric emergency, pediatric infection, and pediatric intensive care clinics at Celal Bayar University and who were treated with a diagnosis of KD (complete/incomplete) between January 2015 and July 2023.

Enhancing electrochemical detection through machine learning-driven prediction for canine mammary tumor biomarker with green silver nanoparticles.

This study developed an innovative biosensor strategy for the sensitive and selective detection of canine mammary tumor biomarkers, cancer antigen 15-3 (CA 15-3) and mucin 1 (MUC-1), integrating green silver nanoparticles (GAgNPs) with machine learning (ML) algorithms to achieve high diagnostic accuracy and potential for noninvasive early detection. The GAgNPs-enhanced electrochemical biosensor demonstrated selective detection of CA 15-3 in serum and MUC-1 in tissue homogenates, with limits of detection (LODs) of 0.07 and 0.