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Abstract Visceral leishmaniasis (VL) is an urgent public health concern in Brazil. We evaluated the spatiotemporal distribution of VL to better understand the effects of economic activities related to agriculture, livestock, and deforestation on its incidence in the Brazilian Legal Amazon (BLA). The data on newly confirmed cases of VL in Brazilian municipalities from 2007 to 2020 were extracted from the Brazilian Notifiable Diseases Information System (SINAN) and analyzed. The data on agricultural production (planted area in hectares) and livestock (total number of cattle) were obtained from the Brazilian Institute of Geography and Statistics (IBGE), whereas deforestation data (in hectares) were obtained from the Amazon Deforestation Estimation Project (PRODES). SatScan and the local indicators of spatial association (LISA) were used to identify the spatial and temporal patterns of VL and its relationships with economic and environmental variables. The cumulative incidence rate was found to be 4.5 cases per 100,000 inhabitants. Based on the LISA results, areas with a high incidence of VL and deforestation were identified in the states of Roraima, Pará, and Maranhão. Strengthening deforestation monitoring programs and environmental enforcement actions can help implement public policies to control illegal deforestation and mitigate the socio-environmental vulnerability in the BLA. Therefore, areas identified in this study should be prioritized for controlling VL.

Paulo Cruchinho,1 María Dolores López-Franco,2 Manuel Luís Capelas,3 Sofia Almeida,4 Phillippa May Bennett,5– 7 Marcelle Miranda da Silva,1,8 Gisela Teixeira,1 Elisabete Nunes,1 Pedro Lucas,1 Filomena Gaspar1 On Behalf of the Handovers4SafeCare1Nursing Research, Innovation and Development Center (CIDNUR) of Lisbon, Nursing School of Lisbon, Lisboa, Portugal; 2CTS-464 Nursing and Innovation in Healthcare, University of Jaén, Jaén, Spain; 3Universidade Católica Portuguesa, Faculty of Health Sciences and Nursing, Center for Interdisciplinary Research in Health (CIIS), Lisboa, Portugal; 4Universidade Católica Portuguesa, Faculty of Health Sciences and Nursing, Center for Interdisciplinary Research in Health (CIIS), Porto, Portugal; 5Center for English, Translation, and Anglo-Portuguese Studies (CETAPS), Lisboa, Portugal; 6Faculty of Social Sciences and Humanities of the New University of Lisbon, Lisboa, Portugal; 7Faculty of Arts and Humanities of the University of Coimbra, Department of Languages, Literatures and Cultures, Coimbra, Portugal; 8Federal University of Rio de Janeiro, Anna Nery Nursing School, Rio de Janeiro, BrazilCorrespondence: Paulo Cruchinho, Nursing School of Lisbon, Avenida Prof. Egas Moniz, Lisboa, 1600-190, Portugal, Tel +351 217913400, Email pjcruchinho@esel.ptAbstract: Cross-cultural validation of self-reported measurement instruments for research is a long and complex process, which involves specific risks of bias that could affect the research process and results. Furthermore, it requires researchers to have a wide range of technical knowledge about the translation, adaptation and pre-test aspects, their purposes and options, about the different psychometric properties, and the required evidence for their assessment and knowledge about the quantitative data processing and analysis using statistical software. This article aimed: 1) identify all guidelines and recommendations for translation, cross-cultural adaptation, and validation within the healthcare sciences; 2) describe the methodological approaches established in these guidelines for conducting translation, adaptation, and cross-cultural validation; and 3) provide a practical guideline featuring various methodological options for novice researchers involved in translating, adapting, and validating measurement instruments. Forty-two guidelines on translation, adaptation, or cross-cultural validation of measurement instruments were obtained from “CINAHL with Full Text” (via EBSCO) and “MEDLINE with Full Text”. A content analysis was conducted to identify the similarities and differences in the methodological approaches recommended. Bases on these similarities and differences, we proposed an eight-step guideline that includes: a) forward translation; 2) synthesis of translations; 3) back translation; 4) harmonization; 5) pre-testing; 6) field testing; 7) psychometric validation, and 8) analysis of psychometric properties. It is a practical guideline because it provides extensive and comprehensive information on the methodological approaches available to researchers. This is the first methodological literature review carried out in the healthcare sciences regarding the methodological approaches recommended by existing guidelines.Keywords: cross-cultural comparison, decision-making, psychometric properties, research design, validation studies, health services research

Introduction 5-fluorouracil (5-FU) and methotrexate (MTX) are the antineoplastic drugs most commonly used worldwide. Considered cytotoxic, these pharmaceuticals exhibit low specificity, causing damage not only to cancer cells but also to healthy cells in organisms. After being consumed and metabolized, these drugs are excreted through urine and feces, followed by wastewater treatment. However, conventional treatments do not have the capacity to completely remove these substances, risking their introduction into freshwater systems. This could pose a risk to human health even at low concentrations. Aims Thus, the present study aimed to investigate the genotoxicity, cytotoxicity, and mutagenicity of 5-FU and MTX at environmentally relevant concentrations after a long-term exposure, using adult male rats as an experimental model. Methods Male Wistar rats (70 days old) were distributed into 4 groups (n  = 10/group): control, received only vehicle; MTX, received methotrexate at 10ngL−1; 5-FU received 5-fluorouracil at 10ngL−1; and MTX + 5-FU, received a combination of MTX and 5-FU at 10ngL−1 each. The period of exposure was from postnatal day (PND) 70 to PND 160, through drinking water. After that, the animals were euthanized and the samples (liver, testis, femoral bone marrow, and peripheral blood) were obtained. Results Increased DNA fragmentation was observed in the peripheral blood, liver, and testis, altering the parameters of the tail moment and tail intensity in the Comet assay. Besides, the change in the ratio between PCE and NCE indicates bone marrow suppression. Conclusion These findings warn the adverse effects for the general population worldwide chronically exposed to these drugs at trace concentration unintentionally. [ABSTRACT FROM AUTHOR]

A hemiatrofia facial ou síndrome de Parry-Romberg é caracterizada por atrofia progressiva dos tecidos da hemiface, acometendo a pele e o subcutâneo. Suas manifestações clínicas são muito variadas. As estratégias terapêuticas de eleição para o tratamento da síndrome ainda não foram completamente estabelecidas. Os autores descrevem um caso de hemiatrofia facial leve, em que o paciente foi submetido a lipofilling (lipoenxertia autóloga), evoluindo com resultado satisfatório. As alternativas de tratamento, suas vantagens e desvantagens, são amplamente discutidas no estudo, sendo que a lipoenxertia autóloga desponta como excelente opção terapêutica, por sua segurança, baixo custo e reprodutibilidade.

Brazil presents the highest number of lightning-related deaths in the world. This study aimed to identify the key victims' characteristics associated with such fatalities in Brazil and to develop a model that predicts the number of deaths as function of the victims' data. The dataset provided by the Department of Informatics of the Unified Health System in Brazil (DATASUS) was analyzed and machine learning regression techniques were applied. The gradien-boosting regressor (GBR) model was found to be the most effective, achieving a prediction accuracy of 97%. Through the analysis of 34 initial variables, 10 variables were identified as having the greatest influence on the model's outcomes. These variables included race, gender, age group, occupational accidents, education, and location of death. Understanding these characteristics is crucial for implementing targeted prevention and safety strategies in various regions, helping to mitigate the risk of lightning-related deaths worldwide. Additionally, the methodology used in this study can serve as a framework for similar research in different locations, allowing for the identification of important factors specific to each region. By adapting the machine learning regression techniques and incorporating local datasets, researchers can gain valuable insights into the determinants of lightning-related fatalities, enabling the development of effective prevention and safety measures tailored to specific geographical areas. [ABSTRACT FROM AUTHOR]