Monitoring of fasting blood sugar (FBS) is a critical component in the diagnosis and management of diabetes, one of the most widespread chronic diseases globally. Microwave sensing-particularly through microstrip-based sensors-has recently gained att...
Circulating tumor cells (CTCs) are promising biomarkers for cancer diagnosis, while detecting CTCs in clinical samples is still challenging due to the scarcity and heterogeneity of CTCs. Herein, a triple-mode sensing platform based on an antifouling ...
Fully wearable devices are crucial for real-time health monitoring, but existing devices often lack stable power, on-site signal processing, and multimodal sensing. To overcome these limitations, we introduce the first self-powered and fully wearable...
The addition sensing device of sweat to wearable biostress sensors would eliminate the need for using multiple gadgets for healthcare analysis. Due to the distinct package fashion of sensor interface for biostress and biomolecule, achieving permeabil...
Staphylococcal enterotoxin B (SEB) holds critical importance in disease diagnosis, food safety, and public health due to its high toxicity and potent pathogenicity. Traditional immunoassay methods for detecting SEB often exhibit insufficient accuracy...
Real-time monitoring of plant stress signaling molecules is crucial for early disease diagnosis and prevention. However, existing methods are often invasive and lack sensitivity, rendering them inadequate for continuous monitoring of subtle plant str...
The increasing demand for point-of-care detection of low-concentration cancer biomarkers has necessitated the development of innovative nanozyme-based sensing technologies. Here, a smartphone-integrated platform is presented that utilizes artificial ...
The RAS/ERK pathway plays a central role in diagnosis and therapy for many cancers. ERK activity is highly dynamic within individual cells and drives cell proliferation, metabolism, and other processes through effector proteins including c-Myc, c-Fos...
Continuous monitoring of glucose levels is important for diabetes management and prevention. While traditional glucose monitoring methods are often invasive and expensive, recent approaches using machine learning (ML) models have explored non-invasiv...
Conventional point-of-care testing (POCT) has limitations in sensitivity with high risks of missed detection or false positive, which restrains its applications for routine outpatient care analysis and early clinical diagnosis. By merits of the cutti...
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