Background: Disparities in cancer incidence and mortality rates between regions arise due to differences in socioeconomic conditions and in human development factors. The major purpose of this study was to measure the role of the Human Development Index (HDI) in the pattern of cervical cytological abnormalities (CCAs).
Methods: This was an analytical sectional study involving a review of secondary cervical cytology data collected from women living in the state of Maranhão, Brazil, in 2007-2012 and collected from the Cervical Cancer Information System (Sistema de Informação do Câncer do Colo do Útero - SISCOLO). The cervical screening results were classified according to the Brazilian Classification of Cervical Reporting (Nomenclatura Brasileira para Laudos Cervicais), an adaptation of the Bethesda System. The Municipal Human Development Index (MHDI) was used, which is an adaptation of the global HDI. The association between CCAs and MHDI was evaluated using the chi-squared test and odds ratios (ORs) with 95 % confidence intervals (95 % CI). The significance level used for all tests was 5 %.
Results: We analysed 1,363,689 examinations of women living in the state of Maranhão. CCAs were identified in 2.0 % of smears in municipalities with high MHDI, 2.2 % in those with medium or low MHDI and 4.1 % in those with very low MHDI. In addition, potentially malignant changes and suspected cervical cancer (HSIL+) were 40.0 % more frequent (0.3 %) in municipalities with medium or low MHDI and 3.6 times more frequent (0.8 %) in municipalities with very low MHDI compared to those with high MHDI (0.2 %).
Conclusion: The association between MHDI and the occurrence of CCAs and HSIL+ shows that more developed areas with more effective health services have a lower prevalence of these lesions. To control cervical cancer, it is necessary to reduce social inequality and improve the availability of health services.
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http://dx.doi.org/10.1186/s12905-016-0334-2 | DOI Listing |
J Infect Dis
January 2025
Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland 21218, USA.
Clinical trials that employ human challenge, also known as controlled human infection models (CHIM), have rapidly advanced vaccine development for multiple pathogens, including at least 30 disease models to date. CHIM studies, championed by networks of researchers, regulators, ethicists, technical experts, and other stakeholders, limit exposure of individuals to an investigational product, de-risk product investments, identify correlates of protection, and most importantly provide a prompt readout of vaccine efficacy. While CHIM studies provide multiple advantages, important challenges exist, including strengthening the relevance and comparability of CHIM study results to efficacy trials in endemic areas, particularly in resource-limited settings.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates.
Background: Neuroimaging segmentation is increasingly important for diagnosing and planning treatments for neurological diseases. Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Data and Web Science Group, School of Business Informatics and Mathematics, University of Manneim, Mannheim, Germany.
Background: The rapid evolution of large language models (LLMs), such as Bidirectional Encoder Representations from Transformers (BERT; Google) and GPT (OpenAI), has introduced significant advancements in natural language processing. These models are increasingly integrated into various applications, including mental health support. However, the credibility of LLMs in providing reliable and explainable mental health information and support remains underexplored.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Division of Services and Interventions Research, National Institute of Mental Health, Bethesda, MD, United States.
Background: Although substantial progress has been made in establishing evidence-based psychosocial clinical interventions and implementation strategies for mental health, translating research into practice-particularly in more accessible, community settings-has been slow.
Objective: This protocol outlines the renewal of the National Institute of Mental Health-funded University of Washington Advanced Laboratories for Accelerating the Reach and Impact of Treatments for Youth and Adults with Mental Illness Center, which draws from human-centered design (HCD) and implementation science to improve clinical interventions and implementation strategies. The Center's second round of funding (2023-2028) focuses on using the Discover, Design and Build, and Test (DDBT) framework to address 3 priority clinical intervention and implementation strategy mechanisms (ie, usability, engagement, and appropriateness), which we identified as challenges to implementation and scalability during the first iteration of the center.
Can J Microbiol
January 2025
Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, Quebec, Canada;
Agricultural practices, specifically the use of antibiotics and other biocides, have repercussions on human, animal and plant health. The aim of this study was to evaluate the levels of Enterobacteriaceae and Enterococcus, as antibiotic resistant marker bacteria, in various matrices across the agro-ecosystem of an antibiotic-free swine farm in Quebec (Canada), namely pig feed, feces, manure, agricultural soil, water and sediment from a crossing stream, and soil from nearby forests. Samples were collected in fall 2022, spring and fall 2023 and spring 2024.
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