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Surface-enhanced Raman scattering (SERS) technology, as an important analytical tool, has been widely applied in the field of chemical and biomedical sensing. Automated testing is often combined with biochemical analysis technologies to shorten the detection time and minimize human error. The present SERS substrates for sample detection are time-consuming and subject to high human error, which are not conducive to the combination of SERS and automated testing. Here, a novel honeycomb-inspired SERS microarray is designed for large-area automated testing of urease in saliva samples to shorten the detection time and minimize human error. The honeycomb-inspired SERS microarray is decorated with hexagonal microwells and a homogeneous distribution of silver nanostars. Compared with the other four common SERS substrates, the optimal honeycomb-inspired SERS microarray exhibits the best SERS performance. The RSD of 100 SERS spectra continuously collected from saliva samples is 6.56%, and the time of one detection is reduced from 5 min to 10 s. There is a noteworthy linear relationship with a of 0.982 between SERS intensity and urease concentration, indicating the quantitative detection capability of the urease activity in saliva samples. The honeycomb-inspired SERS microarray, combined with automated testing, provides a new way in which SERS technology can be widely used in biomedical applications.
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http://dx.doi.org/10.1021/acssensors.4c00006 | DOI Listing |
Prev Oncol Epidemiol
May 2025
Implenomics, Dover, DE, USA.
Introduction: We identified potential approaches to address barriers to colorectal cancer (CRC) screening in rural communities of award recipients from the Centers for Disease Control and Prevention's Colorectal Cancer Control Program (CRCCP).
Methods: Nine program managers and directors discussed approaches to address barriers to CRC screening. The programs served areas with rural communities and tribal reservations.
Patterns (N Y)
July 2025
Sandia National Laboratories, Albuquerque, NM, USA.
Pyomo is an open-source optimization modeling software that has undergone significant evolution since its inception in 2008. Pyomo has evolved to enhance flexibility, solver integration, and community engagement. Modern collaborative tools for open-source software have facilitated the development of new Pyomo functionality and improved our development process through automated testing and performance-tracking pipelines.
View Article and Find Full Text PDFJ Appl Clin Med Phys
September 2025
Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Department of Oncology, Shanghai Clinical Research Center for Radiation Oncology, Shanghai Key Laboratory of Radiation Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
Purpose: This study aims to assess percentage of automated AIO plans that met clinical treatment standards of radiotherapy plans generated by the fully automated All-in-one (AIO) process.
Methods: The study involved 117 rectal cancer patients who underwent AIO treatment. Fully automated regions of interest (ROI) and treatment plans were developed without manual intervention, comparing them to manually generated plans used in clinical practice.
AJNR Am J Neuroradiol
September 2025
From the Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America (J.S.S., B.M., S.H., A.H., J.S.), and Department of Aerospace Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India (H.S.).
Background And Purpose: The choroid of the eye is a rare site for metastatic tumor spread, and as small lesions on the periphery of brain MRI studies, these choroidal metastases are often missed. To improve their detection, we aimed to use artificial intelligence to distinguish between brain MRI scans containing normal orbits and choroidal metastases.
Materials And Methods: We present a novel hierarchical deep learning framework for sequential cropping and classification on brain MRI images to detect choroidal metastases.
J Korean Med Sci
September 2025
Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea.
Background: Neuropsychological assessments are critical to cognitive care, but are time-consuming and often of variable quality. Automated tools, such as ReadSmart4U, improve report quality and consistency while meeting the growing demand for cognitive assessments.
Methods: This retrospective cross-sectional study analysed 150 neuropsychological assessments stratified by cognitive diagnosis (normal cognition, mild cognitive impairment and Alzheimer's disease) from the Clinical Data Warehouse of a university-affiliated referral hospital (2010-2020).