We present the RespiDisk enabling the fully automated and multiplex point-of-care (POC) detection of (currently) up to 19 respiratory tract infection (RTI) pathogens from a single sample based on reverse transcriptase polymerase chain reaction (RT-PCR). RespiDisk comprises a RTI-specific implementation of the centrifugal microfluidic LabDisk platform and combines new and existing advanced unit operations for liquid control, thereby automating all assay steps only by a spinning frequency and temperature protocol in combination with the use of a permanent magnet for in situ bead handing. The capabilities of the system were demonstrated with 36 tested quality samples mimicking clinical conditions (clinical and/or cultured material suspended in transport medium or synthetic bronchoalveolar lavage (BAL)) from past external quality assessment (EQA) panels covering 13 of the 19 integrated RTI detection assays. In total, 36 samples × 19 assays/sample resulting in 684 assays were performed with the RespiDisk, and its analytical performance was in full agreement with the routine clinical workflow serving as reference. A strong feature of the platform is its universality since its components allow the simultaneous detection of a broad panel of bacteria and viruses in a single run, thereby enabling the differentiation between antibiotic-treatable diseases. Furthermore, the full integration of all necessary biochemical components enables a reduction of the hands-on time from manual to automated sample-to-answer analysis to about 5 min. The study was performed on an air-heated LabDisk Player instrument with a time-to-result of 200 min.
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Sensors (Basel)
January 2025
Phillip M. Drayer Electrical Engineering Department, Lamar University, Beaumont, TX 77705, USA.
Automated ultrasonic testing (AUT) is a critical tool for infrastructure evaluation in industries such as oil and gas, and, while skilled operators manually analyze complex AUT data, artificial intelligence (AI)-based methods show promise for automating interpretation. However, improving the reliability and effectiveness of these methods remains a significant challenge. This study employs the Segment Anything Model (SAM), a vision foundation model, to design an AI-assisted tool for weld defect detection in real-world ultrasonic B-scan images.
View Article and Find Full Text PDFJ Cardiovasc Comput Tomogr
January 2025
Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Diagnostic and Interventional Radiology, University Medical Center of Johannes Gutenberg-University, Mainz, Germany; German Centre for Cardiovascular Research, Mainz, Germany.
Background: This study aimed to determine whether artificial intelligence (AI)-based automated assessment of left atrioventricular coupling index (LACI) can provide incremental value above other traditional risk factors for predicting mortality among patients with severe aortic stenosis (AS) undergoing coronary CT angiography (CCTA) before transcatheter aortic valve replacement (TAVR).
Methods: This retrospective study evaluated patients with severe AS who underwent CCTA examination before TAVR between September 2014 and December 2020. An AI-prototype software fully automatically calculated left atrial and left ventricular end-diastolic volumes and LACI was defined by the ratio between them.
Proc Natl Acad Sci U S A
January 2025
Oncode Institute, Hubrecht Institute-Royal Netherlands Academy of Arts and Science, Utrecht 3584 CT, The Netherlands.
Matrigel/BME, a basement membrane-like preparation, supports long-term growth of epithelial 3D organoids from adult stem cells [T. Sato , , 262-265 (2009); T. Sato , , 1762-1772 (2011)].
View Article and Find Full Text PDFChaos
January 2025
School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.
Stock trend prediction is a significant challenge due to the inherent uncertainty and complexity of stock market time series. In this study, we introduce an innovative dual-branch network model designed to effectively address this challenge. The first branch constructs recurrence plots (RPs) to capture the nonlinear relationships between time points from historical closing price sequences and computes the corresponding recurrence quantifification analysis measures.
View Article and Find Full Text PDFNanomaterials (Basel)
December 2024
Analytical and Testing Center, Northeastern University, Shenyang 110819, China.
High-performance lightweight materials are urgently needed because of energy savings and emission reduction. Here, we design a new steel with a low density of 6.41 g/cm, which is a 20% weight reduction compared to the conventional steel.
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