AIMC Topic: Acinetobacter baumannii
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Discovery of CYP1A1 Inhibitors for Host-Directed Therapy against Sepsis.
Journal of medicinal chemistry
May 29, 2025
Bacterial sepsis remains a leading cause of death globally, exacerbated by the rise of multidrug resistance (MDR). Host-directed therapy (HDT) has emerged as a promising nonantibiotic approach to combat infections; thus, multiple HDT targets have bee...
Performance and hypothetical clinical impact of an mNGS-based machine learning model for antimicrobial susceptibility prediction of five ESKAPEE bacteria.
Microbiology spectrum
Apr 17, 2025
UNLABELLED: Antimicrobial resistance is an escalating global health crisis, underscoring the urgent need for timely and targeted therapies to ensure effective clinical treatment. We developed a machine learning model based on metagenomic next-generat...
Exploring the repository of de novo-designed bifunctional antimicrobial peptides through deep learning.
eLife
Mar 13, 2025
Antimicrobial peptides (AMPs) are attractive candidates to combat antibiotic resistance for their capability to target biomembranes and restrict a wide range of pathogens. It is a daunting challenge to discover novel AMPs due to their sparse distribu...
Artificial intelligence using a latent diffusion model enables the generation of diverse and potent antimicrobial peptides.
Science advances
Feb 5, 2025
Artificial intelligence holds great promise for the design of antimicrobial peptides (AMPs); however, current models face limitations in generating AMPs with sufficient novelty and diversity, and they are rarely applied to the generation of antifunga...
Essential Oils as Antimicrobials against : Experimental and Literature Data to Definite Predictive Quantitative Composition-Activity Relationship Models Using Machine Learning Algorithms.
Journal of chemical information and modeling
Jan 22, 2025
Essential oils (EOs) exhibit a broad spectrum of biological activities; however, their clinical application is hindered by challenges, such as variability in chemical composition and chemical/physical instability. A critical limitation is the lack of...
Explainable deep learning and virtual evolution identifies antimicrobial peptides with activity against multidrug-resistant human pathogens.
Nature microbiology
Jan 17, 2025
Artificial intelligence (AI) is a promising approach to identify new antimicrobial compounds in diverse microbial species. Here we developed an AI-based, explainable deep learning model, EvoGradient, that predicts the potency of antimicrobial peptide...
Ensemble learning based on bi-directional gated recurrent unit and convolutional neural network with word embedding module for bioactive peptide prediction.
Food chemistry
Dec 12, 2024
Bioactive peptides, as small protein fragments, are essential mediators of diverse physiological activities, such as antimicrobial, anti-inflammatory, anticancer, antioxidant, and immunomodulatory functions. Despite their substantial potential in pha...
A machine-learning model for prediction of Acinetobacter baumannii hospital acquired infection.
PloS one
Dec 5, 2024
BACKGROUND: Acinetobacter baumanni infection is a leading cause of morbidity and mortality in the Intensive Care Unit (ICU). Early recognition of patients at risk for infection allows early proper treatment and is associated with improved outcomes. T...
High-content imaging and deep learning-driven detection of infectious bacteria in wounds.
Bioprocess and biosystems engineering
Dec 2, 2024
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-...
Identification of Staphylococcus aureus, Enterococcus faecium, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii from Raman spectra by Artificial Intelligent Raman Detection and Identification System (AIRDIS) with machine learning.
Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi
Nov 29, 2024
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...
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