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Anti-Bacterial Agents

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Antibacterial and antibiofilm activities of star anise-cinnamon essential oil against multidrug-resistant Thompson.

Frontiers in cellular and infection microbiology
INTRODUCTION: The emergence of foodborne multidrug-resistant (MDR) has attracted considerable global attention. Given that food is the primary transmission route, our study focuses on , a freshwater snail that is commonly consumed as a specialty foo...

GP or ChatGPT? Ability of large language models (LLMs) to support general practitioners when prescribing antibiotics.

The Journal of antimicrobial chemotherapy
INTRODUCTION: Large language models (LLMs) are becoming ubiquitous and widely implemented. LLMs could also be used for diagnosis and treatment. National antibiotic prescribing guidelines are customized and informed by local laboratory data on antimic...

Exploring the role of breastfeeding, antibiotics, and indoor environments in preschool children atopic dermatitis through machine learning and hygiene hypothesis.

Scientific reports
The increasing global incidence of atopic dermatitis (AD) in children, especially in Western industrialized nations, has attracted considerable attention. The hygiene hypothesis, which posits that early pathogen exposure is crucial for immune system ...

Biofilm-mediated infections; novel therapeutic approaches and harnessing artificial intelligence for early detection and treatment of biofilm-associated infections.

Microbial pathogenesis
A biofilm is a group of bacteria that have self-produced a matrix and are grouped together in a dense population. By resisting the host's immune system's phagocytosis process and attacking with anti-microbial chemicals such as reactive oxygen and nit...

SERS-ATB: A comprehensive database server for antibiotic SERS spectral visualization and deep-learning identification.

Environmental pollution (Barking, Essex : 1987)
The rapid and accurate identification of antibiotics in environmental samples is critical for addressing the growing concern of antibiotic pollution, particularly in water sources. Antibiotic contamination poses a significant risk to ecosystems and h...

A clinical data-driven machine learning approach for predicting the effectiveness of piperacillin-tazobactam in treating lower respiratory tract infections.

BMC pulmonary medicine
BACKGROUND: In hospitalized patients, inadequate antibiotic dosage leading to bacterial resistance and increased antimicrobial use intensity due to overexposure to antibiotics are common problems. In the present study, we constructed a machine learni...

BERT-AmPEP60: A BERT-Based Transfer Learning Approach to Predict the Minimum Inhibitory Concentrations of Antimicrobial Peptides for and .

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) are a promising alternative for combating bacterial drug resistance. While current computer prediction models excel at binary classification of AMPs based on sequences, there is a lack of regression methods to accurately...

Strategies in using artificial intelligence to combat antimicrobial resistance.

Recenti progressi in medicina
Infectious diseases caused by pathogens resistant to antimicrobial treatments, defined as antimicrobial resistance (AMR), are a serious global health crisis, considered among the main threats to global public health according to the World Health Orga...

Exploration of Novel Antimicrobial Agents against Foodborne Pathogens via a Deep Learning Approach.

Journal of agricultural and food chemistry
The emergence of antibiotic-resistant bacteria poses a severe threat to food safety and human health, necessitating an urgent search for novel antimicrobial agents that can be applied in the food industry. This study utilizes a deep learning approach...

Exploring the repository of de novo-designed bifunctional antimicrobial peptides through deep learning.

eLife
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...