The development of a multitarget ultrasensitive immunoassay is significant to fields such as medical research, clinical diagnosis, and food safety inspection. In this study, an artificial intelligence (AI)-assisted programmable-particle-decoding technique (APT)-based digital immunoassay system was developed to perform multitarget ultrasensitive detection. Multitarget was encoded by programmable polystyrene (PS) microspheres with different characteristics (particle size and number), and subsequent visible signals were recorded under an optical microscope after the immune reaction. The resultant images were further analyzed using a customized, AI-based computer vision technique to decode the intrinsic properties of polystyrene microspheres and to reveal the types and concentrations of targets. Our strategy has successfully detected multiple inflammatory markers in clinical serum and antibiotics with a broad detection range from pg/mL to μg/mL without extra signal amplification and conversion. An AI-based digital immunoassay system exhibits great potential to be used for the next generation of multitarget detection in disease screening for candidate patients.
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http://dx.doi.org/10.1021/acs.analchem.2c04703 | DOI Listing |
Menopause
January 2025
From the Department of Obstetrics, Gynecology and Reproduction, Dexeus University Hospital, Barcelona, Spain.
Objective: To examine the association between serum thyroid-stimulating hormone (TSH) levels with handgrip strength (HGS) and dynapenia in euthyroid postmenopausal women.
Methods: This was an exploratory cross-sectional study among 385 participants from the Department of Obstetrics, Gynecology, and Reproduction of the Dexeus Women's University Hospital, Barcelona, Spain. Age, age at menopause, adiposity, alcohol consumption, body mass index (BMI), and smoking status were recorded.
Food Chem X
January 2025
State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, China.
Here, we report a SERS based VFA using PNC as a sensing substrate for highly sensitive multiplex mycotoxins detection. The PNC was fabricated by filtration-based self-assembled monodisperse SiO NPs on a filter membrane as a template, and the obtained PNC had an ordered complementary inverse opal structure. In parallel, three kinds of Raman dyes encoding Au@Ag, Au@Ag and Au@Ag SERS nanotags were synthesized for the detection of OTA, AFB1 and ZON.
View Article and Find Full Text PDFAnal Chem
January 2025
Department of Laboratory Medicine, Clinical Laboratory Medicine Research Center of West China Hospital, Med+X Center for Manufacturing, Department of Rheumatology & Immunology, National Clinical Research Center for Geriatrics, Department of Gynecology of West China Tianfu Hospital, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
Homogeneous analysis techniques offer several advantages as alternatives to heterogeneous immunoassays, such as simplicity and rapidity. In this study, a visual homogeneous immunoassay without a labeling process was developed based on target-induced steric hindrance to regulate competitive recognition mechanism. Specifically, as the analyte concentration varies, the change of microenvironment based on steric hindrance could affect the recognition of Cu by signal probes.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department Hamm 1, Hamm-Lippstadt University of Applied Science, 59063 Hamm, Germany.
An obstacle for many microfluidic developments is the fabrication of its structures, which is often complex, time-consuming, and expensive. Additive manufacturing can help to reduce these barriers. This study investigated whether the results of a microfluidic assay for the detection of the promyelocytic leukemia (PML)-retinoic acid receptor α (RARα) fusion protein (PML::RARA), and thus for the differential diagnosis of acute promyelocytic leukemia (APL), could be transferred from borosilicate glass microfluidic structures to additively manufactured fluidics.
View Article and Find Full Text PDFAnal Chem
January 2025
The School of Information Sciences and Technology, Northwest University, Xi'an 710127, P.R.China.
Digital fluorescence immunoassay (DFI) based on random dispersion magnetic beads (MBs) is one of the powerful methods for ultrasensitive determination of protein biomarkers. However, in the DFI, improving the limit of detection (LOD) is challenging since the ratio of signal-to-background and the speed of manual counting beads are low. Herein, we developed a deep-learning network (ATTBeadNet) by utilizing a new hybrid attention mechanism within a UNet3+ framework for accurately and fast counting the MBs and proposed a DFI using CdS quantum dots (QDs) with narrow peak and optical stability as reported at first time.
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