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In the coronavirus (CoV) disease 2019 (COVID-19) pandemic, highly selective serological testing is essential to define exposure to severe acute respiratory syndrome CoV 2 (SARS-CoV-2). Many tests have been developed, yet with variable speeds to first results, and are of unknown quality, particularly when considering the prediction of neutralizing capacity. The LIAISON SARS-CoV-2 S1/S2 IgG assay was designed to measure antibodies against the SARS-CoV-2 native S1/S2 proteins in a standardized automated chemiluminescence assay. The clinical and analytical performances of the test were validated in an observational study using residual samples (>1,500) with a positive or negative COVID-19 diagnosis. The LIAISON SARS-CoV-2 S1/S2 IgG assay proved to be highly selective and specific and offered semiquantitative measures of serum or plasma levels of anti-S1/S2 IgG with neutralizing activity. The assay's diagnostic sensitivities were 91.3% and 95.7% at >5 or ≥15 days from diagnosis, respectively, and 100% when assessed against a neutralizing assay. The assay's specificity ranged between 97% and 98.5%. The average imprecision of the assay was a <5% coefficient of variation. Assay performance at 2 different cutoffs was evaluated to optimize predictive values. The automated LIAISON SARS-CoV-2 S1/S2 IgG assay brings efficient, sensitive, specific, and precise serological testing to the laboratory, with the capacity to test large amounts of samples per day; first results are available within 35 min, with a throughput of 170 tests/hour. The semiquantitative results provided by the test also associate with the presence of neutralizing antibodies and may provide a useful tool for the large-scale screening of convalescent-phase plasma for safe therapeutic use.
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http://dx.doi.org/10.1128/JCM.01224-20 | DOI Listing |
Int J Epidemiol
August 2025
Department of Biostatistics and Informatics, University of Colorado, Aurora, CO, United States.
Background: Existing longitudinal cohort study data and associated biospecimen libraries provide abundant opportunities to efficiently examine new hypotheses through retrospective specimen testing. Outcome-dependent sampling (ODS) methods offer a powerful alternative to random sampling when testing all available specimens is not feasible or biospecimen preservation is desired. For repeated binary outcomes, a common ODS approach is to extend the case-control framework to the longitudinal setting.
View Article and Find Full Text PDFDiabetologia
September 2025
Department of Diabetology and Internal Medicine, Medical University of Warsaw, Warsaw, Poland.
This review article, developed by the EASD Global Council, addresses the growing global challenges in diabetes research and care, highlighting the rising prevalence of diabetes, the increasing complexity of its management and the need for a coordinated international response. With regard to research, disparities in funding and infrastructure between high-income countries and low- and middle-income countries (LMICs) are discussed. The under-representation of LMIC populations in clinical trials, challenges in conducting large-scale research projects, and the ethical and legal complexities of artificial intelligence integration are also considered as specific issues.
View Article and Find Full Text PDFDrugs Aging
September 2025
Dalla Lana School of Public Health, University of Toronto, V1 06, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada.
Background And Objectives: Older adults living with dementia are a heterogeneous group, which can make studying optimal medication management challenging. Unsupervised machine learning is a group of computing methods that rely on unlabeled data-that is, where the algorithm itself is discovering patterns without the need for researchers to label the data with a known outcome. These methods may help us to better understand complex prescribing patterns in this population.
View Article and Find Full Text PDFFam Cancer
September 2025
School of Social Policy and Practice, University of Pennsylvania, Philadelphia, USA.
Li-Fraumeni syndrome (LFS) is an early-onset cancer syndrome caused by pathogenic germline TP53 variants. Adolescents and young adults (AYAs) with LFS may have challenges navigating new romantic partnerships given the significant effects of LFS on multiple life domains that also affect partners (e.g.
View Article and Find Full Text PDFSmall
September 2025
School of Chemistry and Chemical Engineering, Guangxi Key Laboratory of AI-Driven Zero-Carbon Technologies, Key Laboratory of New Low-carbon Green Chemical Technology Education Department of Guangxi Zhuang Autonomous Region, Guangxi University, Nanning, 530004, China.
Sarcosine (Sar), a critical potential biomarker for prostate cancer (PCa), is primarily detected via enzyme cascade reactions involving sarcosine oxidase (SOx) and peroxidase. Nevertheless, the intermediate product hydrogen peroxide (HO) tends to diffuse to the bulk solution phase without entering subsequent reaction, leading to suboptimal detection sensitivity and compromised analytical performance. To tackle this challenge, a multilayered sandwich nanozyme cascade sensor (designated as Cu-MOF/Rf@BDC) is proposed through a confinement-mediated HO enrichment strategy.
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