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Are Putative Beta-Lactamases Posing a Potential Future Threat?
Summary
Researchers propose a reproducible early warning framework for identifying putative beta-lactamase enzymes that could contribute to future antibiotic resistance. The framework uses motif analysis and mobility context to prioritize candidates and complements existing antimicrobial resistance surveillance systems. The study aligns with a One Health approach that integrates monitoring across human, animal, and environmental reservoirs.
We propose a reproducible, bias-aware, early warning framework that prioritizes candidates based on motif integrity and mobility context. The framework complements existing surveillance (GLASS/EARS-Net) and aligns with a One Health approach integrating human, animal, and environmental reservoirs. Identity thresholds and IPM are used for inclusion and contextual prioritization, rather than as proof of function or mobility; AI-based predictions serve as hypothesis-generating tools. Experimental studies will be essential to confirm enzymatic activity, mobility, and clinical relevance.
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