Minimum Minutes Machine-Learning Microfluidic Microbe Monitoring Method (M7).

Abstract: Rapid detection and identification of airborne bacteria are critical for safeguarding human health, yet current technologies remain inadequate. To address this gap, we developed a multifunctional biochip that synergistically integrated a heptagonal micropillar array with a silver nanostructure–polydopamine–co–chitosan (AgNS@PDA–co–CS) composite gel to achieve highly efficient sampling, capture, enrichment, and in situ SERS detection of airborne bacteria. The integrated micropillar array increased the capture efficiency of S. aureus in aerosols from 11.4% (with a flat chip) to 86.3%, owing to its high specific surface area and its ability to generate chaotic vortices that promote bacterial impaction. Subsequent functionalization with the AgNS@PDA–co–CS gel improved the capture efficiency further to >99.9%, due to the synergistic effect of the gel’s adhesive properties and the abundant capture sites provided by the nanostructure, which collectively ensure robust bacterial retention. The incorporated AgNS also served as SERS-active sites, enabling direct identification of captured S. aureus at concentrations as low as 105 CFU m−3 after 20 min of sampling. Furthermore, the platform successfully distinguished among three common bacterial species—S. aureus, E. coli, and Bacillus cereus—based on their SERS spectral profiles combined with principal component analysis (PCA). This work presents a synergistic strategy for simultaneous bacterial sampling, capture, enrichment, and detection, offering a promising platform for rapid airborne pathogen monitoring.

TL;DR: High-throughput virus infection detection based on light diffraction fingerprints for disease control.

TL;DR: This study presents a multi-scale approach to organoid construction, evaluation, and application, integrating micro-scale and macro-scale strategies, four-dimensional evaluation, and triple-point application to advance organoid research and biomedical applications, leveraging AI for optimization and translation.

TL;DR: Nanoplasmonic single-tumoroid microarray for real-time secretion analysis enables label-free monitoring of tumoroid behavior and drug response.

TL;DR: In this article, the authors discuss current evidence regarding the transmission of respiratory viruses by aerosols-how they are generated, transported, and deposited, as well as the factors affecting the relative contributions of droplet-spray deposition versus aerosol inhalation as modes of transmission.

TL;DR: Air and surfaces in hospital rooms of COVID-19 patients are sampled, SARS-CoV-2 RNA is detected in air samples of two of three tested airborne infection isolation rooms, and surface contamination is found in 66.7% of tested rooms during the first week of illness and 20% beyond the first month of illness.

TL;DR: An amendment to this paper has been published and can be accessed via a link at the top of the paper.

TL;DR: In this article, an electrochemical biosensor based on isothermal rolling circle amplification (RCA) was used to detect SARS-CoV-2 in clinical samples, with a 100% concordance result with qRT-PCR, with complete correlation between the biosensor current signals and quantitation cycle (Cq) values.