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Machine Learning-Enhanced Bacteria Detection Using a Fluorescent Sensor Array with Functionalized Graphene Quantum Dots.
ACS Appl Mater Interfaces
January 2025
Hefei University of Technology, Hefei, 230009, China.
Pathogenic bacteria are the source of many serious health problems, such as foodborne diseases and hospital infections. Timely and accurate detection of these pathogens is of vital significance for disease prevention, control of epidemic spread, and protection of public health security. Rapid identification of pathogenic bacteria has become a research focus in recent years.
View Article and Find Full Text PDFInfluence of agarose in semi-IPN hydrogels for sustained Polymyxin B release.
Colloids Surf B Biointerfaces
December 2024
Laboratory of Bio & Nano Materials, Drug Delivery and Controlled Release, Department of Microbiology, Faculty of Health Sciences, University of Talca, Talca, Chile. Electronic address:
Hydrogels (HGs) are 3-D polymeric networks with high water content, making them appropriate for biomedical applications such as drug delivery systems. This study examines the impact of agarose in semi-interpenetrating polymer networks (Semi-IPNs) based on poly(acrylic acid) (p(AA)), N, N' Methylenebis(acrylamide) (MBA) and agarose (AGA) on the sustained release of Polymyxin B (PolB). Agarose incorporation improved the mechanical strength, swelling behavior and drug retention capacity of the HG.
View Article and Find Full Text PDFAntimicrobial resistance (AMR) poses a critical global health threat, underscoring the urgent need for innovative antibiotic discovery strategies. While recent advances in peptide design have yielded numerous antimicrobial agents, optimizing these molecules experimentally remains challenging due to unpredictable and resource-intensive trial-and-error approaches. Here, we introduce APEX Generative Optimization (APEX ), a generative artificial intelligence (AI) framework that integrates a transformer-based variational autoencoder with Bayesian optimization to design and optimize antimicrobial peptides.
View Article and Find Full Text PDFDiscovery of antibiotics in the archaeome using deep learning.
bioRxiv
November 2024
Machine Biology Group, Departments of Psychiatry and Microbiology, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
Antimicrobial resistance (AMR) is one of the greatest threats facing humanity, making the need for new antibiotics more critical than ever. While most antibiotics have traditionally been derived from bacteria and fungi, archaea-a distinct and underexplored domain of life-offer a largely untapped reservoir for antibiotic discovery. In this study, we leveraged deep learning to systematically explore the archaeome, uncovering promising new candidates for combating AMR.
View Article and Find Full Text PDFDesign, synthesis, and bioactivity investigation of novel cyclic lipopeptide antibiotics targeting top-priority multidrug-resistant gram-negative bacteria.
Eur J Med Chem
December 2024
Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100050, China; State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100050, China. Electronic address:
Article Synopsis
- Polymyxins are critical for treating multidrug-resistant gram-negative bacteria, but their use is limited by kidney toxicity, prompting the need for a safer derivative.
- Researchers synthesized 25 polymyxin derivatives, focusing on modifying hydrophobicity and positive charge, ultimately identifying compound 12 with enhanced antibacterial efficacy and reduced nephrotoxicity.
- Compound 12 not only maintained strong activity against both sensitive and resistant bacteria but also improved treatment outcomes when combined with rifampicin, disrupting bacterial cell membranes effectively.
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