AIMC Topic: Anti-Bacterial Agents

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Chemical Space Exploration and Reinforcement Learning for Discovery of Novel Benzimidazole Hybrid Antibiotics.

Journal of chemical information and modeling
Benzimidazole hybrids are promising antibacterial agents, but the growing problem of antibiotic resistance has led to the necessity of developing novel compounds with enhanced antimicrobial activity. This study utilizes AI methods to generate new ant...

Hospital acquired drug resistant pathogens infections in patients with viral respiratory tract infections: a retrospective study.

BMC infectious diseases
BACKGROUND: Viral respiratory infections (VRTIs) caused by influenza (Flu) and COVID-19 pose significant global health challenges. Clinical outcomes are further exacerbated by infections with hospital acquired drug resistant pathogens (DRPs).

Potential application of Healitide-GP1, a novel antibacterial peptide, in wound healing: in vitro studies.

Scientific reports
Wound healing is a complex process that can be compromised by bacterial infections, leading to delayed healing and an increased risk of complications. The aim of this study was to design and develop a novel antibacterial peptide, Healitide-GP1, which...

Prediction of antibiotic resistance from antibiotic susceptibility testing results from surveillance data using machine learning.

Scientific reports
Antimicrobial resistance is a growing global health threat, and artificial intelligence offers a promising avenue for developing advanced tools to address this challenge. In this study, we applied various machine learning techniques to predict bacter...

Design, characterization, and application of novel antimicrobial peptides against Bacillus cereus.

International journal of food microbiology
Foodborne pathogens such as Bacillus cereus threaten food safety, necessitating novel antimicrobial solutions. Antimicrobial peptides (AMPs) offer broad-spectrum activity and potential applications in food preservation. In this study, we designed a l...

AMPGP: Discovering Highly Effective Antimicrobial Peptides via Deep Learning.

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) have emerged as vital candidates in the fight against antibiotic resistance. The traditional processes for AMP design and discovery are often time-consuming and inefficient. Here, we propose the AMPGP model, which employ...

LC-MS/MS metabolomics unravels the resistant phenotype of carbapenemase-producing Enterobacterales.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: The degree of antimicrobial resistance demonstrated by carbapenemase-producing Enterobacterales (CPE) represents a growing public health challenge. Conventional methods for detecting CPE involve culture-based techniques with lengthy inc...

Bioinspired multifunctional conductive hydrogel based on hydroxypropyl methyl cellulose for flexible sensors.

Carbohydrate polymers
Conductive hydrogels based on hydroxypropyl methyl cellulose (HPMC) show great potential in flexible sensors due to their low price and good biocompatibility. Nevertheless, the design of such conductive hydrogels with superior flexible deformability,...

Applying stacked machine learning models to guide electrochemical oxidation of antibiotics: Key parameter identification and process optimization insights.

Journal of environmental management
The continuous accumulation of antibiotics in the environment has become an increasingly concerned global environmental problem. Electrochemical advanced oxidation processes (EAOPs) have been attracted much attention in antibiotic degradation due to ...

Cross-sectoral synergy governance programme for antimicrobial resistance control in China using a 'One Health' approach: study protocol for a mixed-methods study.

BMJ open
INTRODUCTION: Antimicrobial resistance (AMR) is a critical global public health concern, particularly acute in rural China. Counties, which cover extensive rural regions, face major challenges in AMR governance and thus require priority attention. Ye...