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MmuPV1 infection of Tmc6/Ever1 or Tmc8/Ever2 deficient FVB mice as a model of βHPV in typical epidermodysplasia verruciformis.
PLoS Pathog
January 2025
Department of Pathology, Johns Hopkins University, Baltimore, Maryland, United States of America.
Typical epidermodysplasia verruciformis (EV) is a rare, autosomal recessive disorder characterized by an unusual susceptibility to infection with specific skin-trophic types of human papillomavirus, principally betapapillomaviruses, and a propensity for developing malignant skin tumors in sun exposed regions. Its etiology reflects biallelic loss-of-function mutations in TMC6 (EVER1), TMC8 (EVER2) or CIB1. A TMC6-TMC8-CIB1 protein complex in the endoplasmic reticulum is hypothesized to be a restriction factor in keratinocytes for βHPV infection.
View Article and Find Full Text PDFEvaluating a Public Health Assessment and Response Framework: SARS-CoV-2 Spread Under the Controlled Distancing Model of Rio Grande do Sul, Brazil.
Health Secur
January 2025
Ricardo Rohweder, MSc, is a PhD Student, Programa de Pós-Graduação em Genética e Biologia Molecular; Lavinia Schuler-Faccini, PhD, is a Professor, Department of Genética and Programa de Pós-Graduação em Genética e Biologia Molecular; and Gonçalo Ferraz, PhD, is a Professor, Programa de Pós-Graduação em Ecologia and Programa de Pós-Graduação em Genética e Biologia Molecular; all at the Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil. Lavinia Schuler-Faccini is also a Professor, Medical Genetics Service of Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.
In early 2020, to halt the spread of SARS-CoV-2, the state government of Rio Grande do Sul in Brazil established a public health assessment and response framework known as a "controlled distancing model." Using this framework, the government divided the state into 21 regions and evaluated them against a composite index of disease transmission and health service capacity. Regions were assessed using a color-coded scale of flags that was updated on a weekly basis and used to guide the adoption of nonpharmaceutical interventions.
View Article and Find Full Text PDFReflecting on the impact of the COVID pandemic on patient management and its subsequent influence on long-term outcomes: a case-control study in the field of esophago-gastric cancer.
World J Surg Oncol
January 2025
Department of Oesophago-Gastric & Bariatric Surgery, Salford Care Organisation, Northern Care Alliance NHS Foundation Trust, Salford Royal Hospital, Manchester, UK.
Background: The delivery of cancer services changed significantly during the COVID-19 pandemic. This study aimed to describe changes in presentations, assess the change in recommendations by the MDT during the pandemic, and describe the subsequent long-term impact of these changes on survival rates in patients with EG cancer.
Methods: A retrospective cohort study was designed comparing three patient groups of those referred to EG MDT in the same 6-month period pre-pandemic (PP;2019) during the initial phase of the pandemic (P1;2020) and the year after the initial phase (P2;2021).
Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial.
J Med Internet Res
January 2025
Black Dog Institute, University of New South Wales, Sydney, Australia.
Background: With increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment methods are more effective than traditional methods such as newspapers, media, or flyers is inconsistent. Here we present insights from our experience recruiting tertiary education students for a digital mental health artificial intelligence-driven adaptive trial-Vibe Up.
View Article and Find Full Text PDFA twofold perspective on the quality of research publications: The use of ICTs and research activity models.
PLoS One
January 2025
Department of Structural and Molecular Biology, University College London, London, United Kingdom.
Previous studies have highlighted the inherent subjectivity, complexity, and challenges associated with research quality leading to fragmented findings. We identified determinants of research publication quality in terms of research activities and the use of information and communication technologies by employing an interdisciplinary approach. We conducted web-based surveys among academic scientists and applied machine learning techniques to model behaviors during and after the COVID-19 pandemic.
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