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Drug Resistance, Microbial

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Temporal variation and sharing of antibiotic resistance genes between water and wild fish gut in a peri-urban river.

Journal of environmental sciences (China)
Antibiotic resistance genes (ARGs) as emergence contaminations have spread widely in the water environment. Wild fish may be recipients and communicators of ARGs in the water environment, however, the distribution and transmission of ARGs in the wild...

AI-based mobile application to fight antibiotic resistance.

Nature communications
Antimicrobial resistance is a major global health threat and its development is promoted by antibiotic misuse. While disk diffusion antibiotic susceptibility testing (AST, also called antibiogram) is broadly used to test for antibiotic resistance in ...

HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes.

Microbiome
BACKGROUND: The spread of antibiotic resistance has become one of the most urgent threats to global health, which is estimated to cause 700,000 deaths each year globally. Its surrogates, antibiotic resistance genes (ARGs), are highly transmittable be...

Prediction of antibiotic-resistance genes occurrence at a recreational beach with deep learning models.

Water research
Antibiotic resistance genes (ARGs) have been reported to threaten the public health of beachgoers worldwide. Although ARG monitoring and beach guidelines are necessary, substantial efforts are required for ARG sampling and analysis. Accordingly, in t...

Combining genetic algorithm with machine learning strategies for designing potent antimicrobial peptides.

BMC bioinformatics
BACKGROUND: Current methods in machine learning provide approaches for solving challenging, multiple constraint design problems. While deep learning and related neural networking methods have state-of-the-art performance, their vulnerability in decis...

Using computers to ESKAPE the antibiotic resistance crisis.

Drug discovery today
Since the discovery of penicillin, the development and use of antibiotics have promoted safe and effective control of bacterial infections. However, the number of antibiotic-resistance cases has been ever increasing over time. Thus, the drug discover...

Identification of antibiotic resistance and virulence-encoding factors in Klebsiella pneumoniae by Raman spectroscopy and deep learning.

Microbial biotechnology
Klebsiella pneumoniae has become the number one bacterial pathogen that causes high mortality in clinical settings worldwide. Clinical K. pneumoniae strains with carbapenem resistance and/or hypervirulent phenotypes cause higher mortality comparing w...

Prediction of antimicrobial peptides toxicity based on their physico-chemical properties using machine learning techniques.

BMC bioinformatics
BACKGROUND: Antimicrobial peptides are promising tools to fight against ever-growing antibiotic resistance. However, despite many advantages, their toxicity to mammalian cells is a critical obstacle in clinical application and needs to be addressed.

Automated extraction of genes associated with antibiotic resistance from the biomedical literature.

Database : the journal of biological databases and curation
The detection of bacterial antibiotic resistance phenotypes is important when carrying out clinical decisions for patient treatment. Conventional phenotypic testing involves culturing bacteria which requires a significant amount of time and work. Who...

Direct antimicrobial resistance prediction from clinical MALDI-TOF mass spectra using machine learning.

Nature medicine
Early use of effective antimicrobial treatments is critical for the outcome of infections and the prevention of treatment resistance. Antimicrobial resistance testing enables the selection of optimal antibiotic treatments, but current culture-based t...