Soft Hydrogel Actuator for Fast Machine-Learning-Assisted Bacteria Detection

• DOI: 10.1021/acsami.1c22470
• Publication Date: 2022-01-26T17:44:05Z
• Authors: Filipp V. Lavrentev; Igor S. Rumyantsev; Artemii S. Ivanov; Vladimir V. Shilo...; Olga Yu. Orlova; Konstantin G. Nik...; Daria V. Andreeva; Ekaterina V. Skorb
• Keywords: Machine Learning; 0301 basic medicine; 03 medical and health sciences; Bacillus coagulans; Alloys; Streptococcus thermophilus; Gallium; Hydrogels; Electrochemical Techniques; Indium; Density Functional Theory

We demonstrate that our bio-electrochemical platform facilitates the reduction of detection time from 3-day period existing tests to 15 min. Machine learning and robotized bioanalytical platforms require principles such as hydrogel-based actuators for fast easy analysis bioactive analytes. Bacteria are fragile environmentally sensitive microorganisms a special environment support their lifecycles during analytical tests. Here, we develop based on soft hydrogel/eutectic gallium-indium alloy interface Streptococcus thermophilus Bacillus coagulans bacteria in various mediums. The device is capable bacteria' viability time. Current-voltage data used multilayer perceptron algorithm training. model detecting bacterial concentrations 104 108 cfu/mL range culture medium or dairy products with high accuracy (94%). Such biodetection extremely important food agriculture industries biomedical environmental science.