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During an epidemic, individual test results form the basis of epidemiological indicators such as case numbers or incidence. Therefore, the accuracy of measures derived from these indicators depends on the reliability of individual results. In the COVID-19 pandemic, monitoring and evaluating the performance of the unprecedented number of testing facilities in operation, and novel testing systems in use, was urgently needed. External quality assessment (EQA) schemes are unique sources of data reporting on testing performance, and their providers are recognised contacts and support for test facilities (for technical-analytical topics) and health authorities (for planning the monitoring of infection diagnostics). To identify information provided by SARS-CoV-2 genome detection EQA schemes that is relevant for public health microbiology, we reviewed the current literature published in PubMed between January, 2020, and July, 2022. We derived recommendations for EQA providers and their schemes for best practices to monitor pathogen-detection performance in future epidemics. We also showed laboratories, test facilities, and health authorities the information and benefits they can derive from EQA data, and from the non-EQA services of their providers.
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http://dx.doi.org/10.1016/S2666-5247(23)00072-1 | DOI Listing |
MAGMA
September 2025
Department of Medical Imaging, (766), Radboud University Medical Center, Geert Grooteplein 10Radboudumc, P.O. Box 9101, 6500 HB, Nijmegen, the Netherlands.
Objective: To improve B field homogeneity in prostate MR imaging and spectroscopy using a custom-designed 16-channel external local shim coil array.
Methods: In vivo prostate imaging was performed in seven healthy volunteers (mean age: 40.7 years) without bowel preparation.
J Cancer Res Clin Oncol
September 2025
Department of Radiology, Guizhou Provincial People's Hospital, No. 83 East Zhongshan Road, Guiyang, 550002, Guizhou, China.
Purpose: Targeted therapy with lenvatinib is a preferred option for advanced hepatocellular carcinoma, however, predicting its efficacy remains challenging. This study aimed to build a nomogram integrating clinicoradiological indicators and radiomics features to predict the response to lenvatinib in patients with hepatocellular carcinoma.
Methods: This study included 211 patients with hepatocellular carcinoma from two centers, who were allocated into the training (107 patients), internal test (46 patients) and external test set(58 patients).
Light Sci Appl
September 2025
Department of Electrical, Electronic, and Communication Engineering, Faculty of Science and Engineering, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo, 112-8551, Japan.
While non-destructive in-line monitoring at manufacturing sites is essential for safe distribution cycles of pharmaceuticals, efforts are still insufficient to develop analytical systems for detailed dynamic visualisation of foreign substances and material composition in target pills. Although spectroscopies, expected towards pharma testing, have faced technical challenges in in-line setups for bulky equipment housing, this work demonstrates compact dynamic photo-monitoring systems by selectively extracting informative irradiation-wavelengths from comprehensive optical references of target pills. This work develops a non-destructive in-line dynamic inspection system for pharma agent pills with carbon nanotube (CNT) photo-thermoelectric imagers and the associated ultrabroadband sub-terahertz (THz)-infrared (IR) multi-wavelength monitoring.
View Article and Find Full Text PDFPediatrics
September 2025
School of Nursing, Yale University, Orange, Connecticut.
Objective: Feeling prepared for a child's end of life (EOL) may help to alleviate parents' psychological symptoms following their child's death from cancer. However, most parents report feeling unprepared, and data on how parents define feeling prepared for their child's EOL remain limited. In this study, we explored how parents define "preparing" for a child's EOL and identified barriers and facilitators to feeling prepared.
View Article and Find Full Text PDFProg Cardiovasc Dis
September 2025
Department of Cardiology, University of Texas Health Science Center, San Antonio, TX, USA.
Background: Cardiopulmonary resuscitation (CPR) is a vital intervention for managing cardiac arrest; however, enhancing survival rates remains a significant challenge. Recent advancements highlight the importance of integrating artificial intelligence (AI) to overcome existing limitations in prediction, intervention, and post-resuscitation care.
Methods: A thorough review of contemporary literature regarding AI applications in CPR was undertaken, explicitly examining its role in the early prediction of cardiac arrest, optimization of CPR quality, and enhancement of post-arrest outcomes.