The epigenome influences gene regulation and phenotypes in response to exposures. Epigenome assessment can determine exposure history aiding in diagnosis. Here we developed and implemented a machine learning algorithm, the exposure signature discove...
Assessing the visual accuracy of two large language models (LLMs) in microbial classification. GPT-4o and Gemini 1.5 Pro were evaluated in distinguishing Gram-positive from Gram-negative bacteria and classifying them as cocci or bacilli using 80 Gra...
Marine antimicrobial peptides (AMPs) represent a promising source for combating infections, especially against antibiotic-resistant pathogens and traditionally challenging infections. However, traditional drug discovery methods face challenges such a...
The ample peptide field is the best source for discovering clinically available novel antimicrobial peptides (AMPs) to address emerging drug resistance. However, discovering novel AMPs is complex and expensive, representing a major challenge. Recent ...
The ESKAPE family, comprising Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp., poses a significant global threat due to their heightened virulence and extensiv...
International journal of antimicrobial agents
39244164
BACKGROUND: The use of matrix-assisted laser desorption/ionisation-time-of-flight mass spectra (MALDI-TOF MS) with machine learning (ML) has been explored for predicting antimicrobial resistance. This study evaluates the effectiveness of MALDI-TOF MS...
Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi
39638747
BACKGROUND: Rapid and accurate identification of bacteria is required in order to develop effective treatment strategies. Traditional culture-based methods are time-consuming, while MALDI-TOF MS is expensive. The Raman spectroscopy, due to its relati...
BACKGROUND: Among no-touch automated disinfection devices, ultraviolet-C (UV-C) radiation has been proven to be one of the most effective against a broad spectrum of micro-organisms causing healthcare-associated infections.
This study aimed to calculate the effect of nanopatterns' peak sharpness, width, and spacing parameters on P. aeruginosa and S. aureus cell walls by artificial neural network and finite element analysis. Elastic and creep deformation models of bacter...
Fast and accurate detection of infectious bacteria in wounds is crucial for effective clinical treatment. However, traditional methods take over 24 h to yield results, which is inadequate for urgent clinical needs. Here, we introduce a deep learning-...