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Cryptococcus is a family of strongly infectious pathogens that results in a wide variety of symptoms, particularly threatening the patients undergoing the immune‐deficiency or medical treatment. Rapidly identifying Cryptococcus subtypes and accurately quantifying their contents remain urgent needs for infection control and timely therapy. However, traditional detection techniques heavily rely on expensive, specialized instruments, significantly compromising their applicability for large‐scale population screening. In this work, we report a portable microwell array chip platform integrated with a deep learning‐based image recognition program, which enables rapid, precise quantification of the specific subtypes of Cryptococcus. The platform features four zones of microwell arrays preloaded with the subtype‐targeted CRISPR–Cas12a system that avoid dependence on slow, instrumental‐mediated target amplification, achieving rapid (10 min), high specificity for identifying the sequence of Cryptococcus. The deep learning‐based image recognition program utilizing segment anything model (SAM) significantly enhances automation and accuracy in identifying target concentrations, which eventually achieves ultra‐low limit of detection (0.5 pM) by personal smartphones. This platform can be further customized to adapt to various scenarios in clinical settings. [ABSTRACT FROM AUTHOR]

Fast and accurate detection of Cryptococcus and precise differentiation of its subtypes is of great significance in protecting people from cryptococcal disease and preventing its spread in populations. However, traditional Cryptococcus identification and detection techniques still face significant challenges in achieving high analysis speed as well as high sensitivity. In this work, we report an electric microfluidic biochip. Compared to conventional methods that take several hours or even a day, this chip can detect Cryptococcus within 20 min, and achieve its maximum detection limit within 1 h, with the ability to differentiate between the Cryptococcus neoformans (NEO) and rare Cryptococcus gattii (GAT) efficiently, which accounts for nearly 100%. This device integrated two functional zones of an electroporation lysis (EL) zone for rapid cell lysis (<30 s) and an electrochemical detection (ED) zone for sensitive analysis of the released nucleic acids. The EL zone adopted a design of microelectrode arrays, which obtains a large electric field intensity at the constriction of the microchannel, addressing the safety concerns associated with high-voltage lysis. The device enables a limit of detection (LOD) of 60 pg/mL for NEO and 100 pg/mL for GAT through the modification of nanocomposites and specific probes. In terms of the detection time and sensitivity, the integrated microfluidic biochip demonstrates broad potential in Cryptococcus diagnosis and disease prevention. [ABSTRACT FROM AUTHOR]

Precise quantification of low-dose ionizing radiation is of great significance in protecting people from damage caused by clinical radiotherapy or environmental radiation. Traditional techniques for detecting radiation, however, remain extreme challenges to achieve high sensitivity and speed in quantifying radiation dosage. In this work, we report a Cas13a-Microdroplet platform that enables sensitive detection of ultra-low doses of radiation (0.5 Gy vs. 1 Gy traditional) within 1 h. The micro-platform adopts an ideal, specific radiation-sensitive marker, m6A on NCOA4 gene (NCOA4-m6A) that was first reported in our recent work. Microfluidics of the platform generate uniform microdroplets that encapsulate a CRISPR/Cas13a detection system and NCOA4-m6A target from the whole RNA extraction, achieving 10-fold enhancement in sensitivity and significantly reduced limit of detection (LOD). Systematic mouse models and clinical patient samples demonstrated its superior sensitivity and LOD (0.5 Gy) than traditional qPCR, which show wide potentials in radiation tracking and damage protection. [ABSTRACT FROM AUTHOR]