AIMC Topic: Anti-Bacterial Agents

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Performance and hypothetical clinical impact of an mNGS-based machine learning model for antimicrobial susceptibility prediction of five ESKAPEE bacteria.

Microbiology spectrum
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...

Investigating long-term risk of aortic aneurysm and dissection from fluoroquinolones and the key contributing factors using machine learning methods.

Scientific reports
The connection between fluoroquinolones and severe heart conditions, such as aortic aneurysm (AA) and aortic dissection (AD), has been acknowledged, but the full extent of long-term risks remains uncertain. Addressing this knowledge deficit, a retros...

Barriers to the widespread adoption of diagnostic artificial intelligence for preventing antimicrobial resistance.

Scientific reports
Currently, antimicrobial resistance (AMR) poses a major public health challenge. The emergence of AMR, which significantly threatens public health, is primarily due to the overuse of antimicrobial agents. This study explored the possibility that the ...

Machine learning predicts selectivity of green synthesized iron nanoparticles toward typical contaminants: critical factors in synthesis conditions, material properties, and reaction process.

Environmental research
Green synthesized iron nanoparticles (FeNPs) have gained popularity in contaminant removal due to their low cost and environmentally friendly properties. However, a gap remains in understanding how synthesis conditions (SC), material properties (MP),...

Micro- and Nano-Bots for Infection Control.

Advanced materials (Deerfield Beach, Fla.)
Medical micro- and nano-bots (MMBs and MNBs) have attracted a lot of attention owing to their precise motion for accessing difficult-to-reach areas in the body. These emerging tools offer the promise of non-invasive diagnostics and therapeutics for a...

Therapeutic effect and concomitant toxicity of hydrargyrum chloratum compositum on chronic difficult-to-heal wounds in rats.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: Hydrargyrum chloratum compositum(Hcc) is a traditional Chinese medicine for external use, with the efficacy of 'transforming corrosion and pulling out toxins, removing corrosion and regenerating muscles'. The main comp...

Pre-trained molecular representations enable antimicrobial discovery.

Nature communications
The rise in antimicrobial resistance poses a worldwide threat, reducing the efficacy of common antibiotics. Determining the antimicrobial activity of new chemical compounds through experimental methods remains time-consuming and costly. While compoun...

Antimicrobial resistance: Linking molecular mechanisms to public health impact.

SLAS discovery : advancing life sciences R & D
BACKGROUND: Antimicrobial resistance (AMR) develops into a worldwide health emergency through genetic and biochemical adaptations which enable microorganisms to resist antimicrobial treatment. β-lactamases (blaNDM, blaKPC) and efflux pumps (MexAB-Opr...

Febrile neutropenia management in high-risk neutropenic patients: a narrative review on antibiotic prophylaxis and empirical treatment.

Expert review of anti-infective therapy
INTRODUCTION: Although febrile neutropenia (FN) remains a major cause of morbidity and mortality in patients with hematologic malignancies and hematopoietic stem cell transplant (HSCT) recipients, the increasing prevalence of antimicrobial resistance...

Machine learning approach for dosage individualization of azithromycin in children with community-acquired pneumonia.

British journal of clinical pharmacology
AIMS: The uncertainty about the efficacy and safety of currently used azithromycin dosing regimens in children warrants individualized therapy. The area under the plasma concentration-time curve over 24 h (AUC) of azithromycin correlates best with it...