Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009932 | PMC |
| http://dx.doi.org/10.1093/jamia/ocv066 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Probing the mechanism of peptidoglycan amidase activation by FtsEX-EnvC.
mBio
September 2025
School of Life Sciences, University of Warwick, Coventry, United Kingdom.
The FtsEX-EnvC-AmiA/B system is a key component of the cell division machinery that directs breakage of the peptidoglycan layer during separation of daughter cells. Structural and mechanistic studies have shown that ATP binding by FtsEX in the cytoplasm drives periplasmic conformational changes in EnvC, which lead to the binding and activation of peptidoglycan amidases such as AmiA and AmiB. The FtsEX-EnvC amidase system is highly regulated to prevent cell lysis with at least two separate layers of autoinhibition that must be relieved to initiate peptidoglycan hydrolysis during division.
View Article and Find Full Text PDFA novel peptidoglycan deacetylase modulates daughter cell separation in E. coli.
PLoS Genet
September 2025
Centre for Bacterial Cell Biology, Biosciences Institute, Newcastle University, Newcastle upon Tyne, United Kingdom.
Peptidoglycan hydrolases facilitate bacterial cell wall growth by creating space for insertion of new material and allowing physical separation of daughter cells. In Escherichia coli, three peptidoglycan amidases, AmiA, AmiB and AmiC, cleave septal peptidoglycan during cell division. The LytM-domain proteins EnvC, NlpD and ActS activate these amidases either from inside the cell or the outer membrane: EnvC binds to the cytoplasmic membrane-anchored divisome components FtsEX, while NlpD and ActS are outer membrane-anchored lipoproteins.
View Article and Find Full Text PDFThe Effect of Ambient Artificial Intelligence Scribes on Trainee Documentation Burden.
Appl Clin Inform
August 2025
Department of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, Connecticut, United States.
Ambient artificial intelligence scribes have become widespread commercial products in the era of generative artificial intelligence. While studies have examined the effect of these tools on the experience of attending physicians, little evidence is available regarding their use by resident physician trainees.To assess trainee experience with an ambient artificial intelligence scribe using measures of usability, acceptability, and documentation burden.
View Article and Find Full Text PDFEnhancing Disease Detection in Radiology Reports Through Fine-tuning Lightweight LLM on Weak Labels.
AMIA Jt Summits Transl Sci Proc
June 2025
Department of Population Health Sciences, Weill Cornell Medicine, New York.
Despite significant progress in applying large language models (LLMs) to the medical domain, several limitations still prevent them from practical applications. Among these are the constraints on model size and the lack of cohort-specific labeled datasets. In this work, we investigated the potential of improving a lightweight LLM, such as Llama 3.
View Article and Find Full Text PDFAutomatically Identifying Event Reports of Workplace Violence and Communication Failures using Large Language Models.
AMIA Jt Summits Transl Sci Proc
June 2025
University of Pennsylvania, Philadelphia, PA.
Safety event reporting forms a cornerstone of identifying and mitigating risks to patient and staff safety. However, variabilities in reporting and limited resources to analyze and classify event reports delay healthcare organizations' ability to rapidly identify safety event trends and to improve workplace safety. We demonstrated how large language models can classify safety event report narratives as workplace violence (F1: 0.
View Article and Find Full Text PDF