Paving the way for precise diagnostics of antimicrobial resistant bacteria
2022
Hao Wang | Chenhao Jia | Chenhao Jia | Hongzhao Li | Hongzhao Li | Rui Yin | Jiang Chen | Yan Li | Yan Li | Yan Li | Min Yue | Min Yue | Min Yue | Min Yue
The antimicrobial resistance (AMR) crisis from bacterial pathogens is frequently emerging and rapidly disseminated during the sustained antimicrobial exposure in human-dominated communities, posing a compelling threat as one of the biggest challenges in humans. The frequent incidences of some common but untreatable infections unfold the public health catastrophe that antimicrobial-resistant pathogens have outpaced the available countermeasures, now explicitly amplified during the COVID-19 pandemic. Nowadays, biotechnology and machine learning advancements help create more fundamental knowledge of distinct spatiotemporal dynamics in AMR bacterial adaptation and evolutionary processes. Integrated with reliable diagnostic tools and powerful analytic approaches, a collaborative and systematic surveillance platform with high accuracy and predictability should be established and implemented, which is not just for an effective controlling strategy on AMR but also for protecting the longevity of valuable antimicrobials currently and in the future.
Show more [+] Less [-]Bibliographic information
This bibliographic record has been provided by Directory of Open Access Journals