Machine learning-assisted nanozyme nanosensor for instantaneous quantitative analysis of antitubercular drugs
Chendi Qin, Xuehong Min, Linjian Fang, Xiaoqing Yang, Xian Zhao, Yixin Xiao, Yansong Yang, Xiaoqing Yi, Liyu Zheng, Jinyan Chen, Leiying Zhang, Man Zhou · 2026
Read Machine learning-assisted nanozyme nanosensor for instantaneous quantitative analysis of antitubercular drugs by Chendi Qin, Xuehong Min, Linjian Fang, Xiaoqing Yang, Xian Zhao, Yixin Xiao, Yansong Yang, Xiaoqing Yi, Liyu Zheng, Jinyan Chen, Leiying Zhang, Man Zhou (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/PMC13576141.txt.
Description
Chendi Qin leads a 2026 study building a quick sensor for a key tuberculosis drug, isoniazid. Knowing a patient's drug level helps set the dose and cut side effects, yet lab testing is slow. Their sensor uses a nanozyme, a nanomaterial that acts like an enzyme, whose colour reaction fades as drug levels rise.
Two readouts were built: a bench instrument and a smartphone method that reads colour values from photos. The bench method measured levels from 1 to 30 micromolar units, the phone method from 3 to 30 in the same units. Spiked samples of tablets and rat serum recovered close to the true amounts. Among three learning models, a convolutional network read phone photos best and stayed accurate under room light. The authors pitch the platform for routine drug monitoring.
Catalog record
| CREATOR | Chendi Qin, Xuehong Min, Linjian Fang, Xiaoqing Yang, Xian Zhao, Yixin Xiao, Yansong Yang, Xiaoqing Yi, Liyu Zheng, Jinyan Chen, Leiying Zhang, Man Zhou |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 50413 |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |