Nasopharyngeal carcinoma (NPC) is prevalent in Southern China and Southeast Asia, and autoantibody signatures may improve early detection of NPC. In this study, serum levels of autoantibodies against a panel of six tumor-associated antigens (p53, NY-ESO-1, MMP-7, Hsp70, Prx VI, and Bmi-1) and Epstein-Barr virus capsid antigen-IgA (VCA-IgA) were tested by enzyme-linked immunosorbent assay in a training set (220 NPC patients and 150 controls) and validated in a validation set (90 NPC patients and 68 controls). We used receiver-operating characteristics (ROC) to calculate diagnostic accuracy. ROC curves showed that use of these 6 autoantibody assays provided an area under curve (AUC) of 0.855 [95% confidence interval (CI), 0.818-0.892], 68.2% sensitivity, and 90.0% specificity in the training set and an AUC of 0.873 (95% CI, 0.821-0.925), 62.2% sensitivity, and 91.2% specificity in the validation set. Moreover, the autoantibody panel maintained diagnostic accuracy for VCA-IgA-negative NPC patients [0.854 (0.809-0.899), 67.8%, and 90.0% in the training set; 0.879 (0.815-0.942), 67.4%, and 91.2% in the validation set]. Importantly, combination of the autoantibody panel and VCA-IgA improved diagnostic accuracy for NPC versus controls compared with the autoantibody panel alone [0.911 (0.881-0.940), 81.4%, and 90.0% in the training set; 0.919 (0.878-0.959), 78.9%, and 91.2% in the validation set), as well as for early-stage NPC (0.944 (0.894-0.994), 87.9%, and 94.0% in the training set; 0.922 (0.808-1.000), 80.0%, and 92.6% in the validation set]. These results reveal autoantibody signatures in an optimized panel that could improve the identification of VCA-IgA-negative NPC patients, may aid screening and diagnosis of NPC, especially when combined with VCA-IgA.
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http://dx.doi.org/10.1158/1940-6207.CAPR-14-0397 | DOI Listing |
Optom Vis Sci
January 2025
Johnson & Johnson MedTech (Vision), Irvine, California.
Significance: Optimal meibography utilization and interpretation are hindered due to poor lid presentation, blurry images, or image artifacts and the challenges of applying clinical grading scales. These results, using the largest image dataset analyzed to date, demonstrate development of algorithms that provide standardized, real-time inference that addresses all of these limitations.
Purpose: This study aimed to develop and validate an algorithmic pipeline to automate and standardize meibomian gland absence assessment and interpretation.
PLoS One
January 2025
Division of Emergency Medicine, University of Cape Town, Cape Town, South Africa.
To validate Palestine's previously derived emergency department quality standards (EDQS) using an e-Delphi survey. A two-round e-Delphi survey validated the EDQS, developed in an earlier study through a literature review and consensus-building among Palestinian emergency medicine and healthcare quality experts. The study purposively sampled 53 emergency department and healthcare quality experts with over 5 years of experience.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
Department of Pathology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Human epidermal growth factor receptor 2 (HER2) positive gastric cancer (GC) shows a robust response to the combined therapy based HER2-targeted therapy. The application of these therapies is highly dependent on the evaluation of tumor HER2 status. However, there are many risks and challenges in HER2 assessment in GC.
View Article and Find Full Text PDFJ Magn Reson Imaging
January 2025
Department of Radiology, Ålesund Hospital, Møre og Romsdal Hospital Trust, Ålesund, Norway.
Background: Deep learning-based segmentation of brain metastases relies on large amounts of fully annotated data by domain experts. Semi-supervised learning offers potential efficient methods to improve model performance without excessive annotation burden.
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Adv Sci (Weinh)
January 2025
Hunan Joint International Research Center for Carbon Dioxide Resource Utilization, School of Physics, Central South University, Changsha, Hunan, 410083, P. R. China.
Perfluorinated compounds (PFCs) are emerging environmental pollutants characterized by their extreme stability and resistance to degradation. Among them, tetrafluoromethane (CF) is the simplest and most abundant PFC in the atmosphere. However, the highest C─F bond energy and its highly symmetrical structure make it particularly challenging to decompose.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!