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Existing genetic classification systems for porcine reproductive and respiratory syndrome virus type 2 (PRRSV-2), such as restriction fragment length polymorphisms and sub-lineages, are unreliable indicators of close genetic relatedness or lack sufficient resolution for epidemiological monitoring routinely conducted by veterinarians. Here, we outline a fine-scale classification system for PRRSV-2 genetic variants in the United States. Based on >25,000 U.S. open reading frame 5 (ORF5) sequences, sub-lineages were divided into genetic variants using a clustering algorithm. Through classifying new sequences every 3 months and systematically identifying new variants across 8 years, we demonstrated that prospective implementation of the variant classification system produced robust, reproducible results across time and can dynamically accommodate new genetic diversity arising from virus evolution. From 2015 to 2023, 118 variants were identified, with ~48 active variants per year, of which 26 were common (detected >50 times). Mean within-variant genetic distance was 2.4% (max: 4.8%). The mean distance to the closest related variant was 4.9%. A routinely updated webtool (https://stemma.shinyapps.io/PRRSLoom-variants/) was developed and is publicly available for end users to assign newly generated sequences to a variant ID. This classification system relies on U.S. sequences from 2015 onward; further efforts are required to extend this system to older or international sequences. Finally, we demonstrate how variant classification can better discriminate between previous and new strains on a farm, determine possible sources of new introductions into a farm/system, and track emerging variants regionally. Adoption of this classification system will enhance PRRSV-2 epidemiological monitoring, research, and communication, and improve industry responses to emerging genetic variants.IMPORTANCEThe development and implementation of a fine-scale classification system for PRRSV-2 genetic variants represent a significant advancement for monitoring PRRSV-2 occurrence in the swine industry. Based on systematically applied criteria for variant identification using national-scale sequence data, this system addresses the shortcomings of existing classification methods by offering higher resolution and adaptability to capture emerging variants. This system provides a stable and reproducible method for classifying PRRSV-2 variants, facilitated by a freely available and regularly updated webtool for use by veterinarians and diagnostic labs. Although currently based on U.S. PRRSV-2 ORF5 sequences, this system can be expanded to include sequences from other countries, paving the way for a standardized global classification system. By enabling accurate and improved discrimination of PRRSV-2 genetic variants, this classification system significantly enhances the ability to monitor, research, and respond to PRRSV-2 outbreaks, ultimately supporting better management and control strategies in the swine industry.
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http://dx.doi.org/10.1128/msphere.00709-24 | DOI Listing |
Subst Abuse Treat Prev Policy
September 2025
Centre for Interdisciplinary Addiction Research (ZIS), Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf (UKE), Martinistraße 52, 20246, Hamburg, Germany.
Background: Alcohol use disorder (AUD) is conceptualized as a dimensional phenomenon in the DSM-5, but electronic health records (EHRs) rely on binary AUD definitions according to the ICD-10. The present study classifies AUD severity levels using EHR data and tests whether increasing AUD severity levels are linked with increased comorbidity.
Methods: Billing data from two German statutory health insurance companies in Hamburg included n = 21,954 adults diagnosed with alcohol-specific conditions between 2017 and 2021.
BMC Oral Health
September 2025
Oral and Maxillofacial Radiology Department, Cairo university, Cairo, Egypt.
Aim: The purpose of this study was to assess the accuracy of a customized deep learning model based on CNN and U-Net for detecting and segmenting the second mesiobuccal canal (MB2) of maxillary first molar teeth on cone beam computed tomography (CBCT) scans.
Methodology: CBCT scans of 37 patients were imported into 3D slicer software to crop and segment the canals of the mesiobuccal (MB) root of the maxillary first molar. The annotated data were divided into two groups: 80% for training and validation and 20% for testing.
Crit Care
September 2025
Department of Pediatrics I, University Hospital Essen, University of Duisburg-Essen, Hufelandstr, 55, Essen, 45239, Germany.
Background: Gender disparities persist in medical research. This study assessed gender representation trends in first and senior authorships in the five highest-ranked critical care journals (by impact factor) over a 20-year period.
Methods: We analyzed author gender distribution from 2005 to 2024.
Lipids Health Dis
September 2025
Department of Gastroenterology, Weifang People's Hospital, The First Affiliated Hospital of Shandong Second Medical University, 151 Guangwen Street, Weifang, Shandong, 261000, China.
Background: Current scoring systems for hypertriglyceridaemia-induced acute pancreatitis (HTG-AP) severity are few and lack reliability. The present work focused on screening predicting factors for HTG-SAP, then constructing and validating the visualization model of HTG-AP severity by combining relevant metabolic indexes.
Methods: Between January 2020 and December 2024, retrospective clinical information for HTG-AP inpatients from Weifang People's Hospital was examined.
BMC Psychiatry
September 2025
Department of Cognitive Neuroscience, Faculty of Biology, Bielefeld University, Bielefeld, Germany.
Obsessive-compulsive disorder (OCD) is a chronic and disabling condition affecting approximately 3.5% of the global population, with diagnosis on average delayed by 7.1 years or often confounded with other psychiatric disorders.
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