Congenital Zika virus infection impacts on male mouse offspring's reproductive biology.

In brief: Congenital ZIKV infection promotes alarming effects on male offspring's reproductive biology. This study showed the presence of the ZIKV antigen in the testis parenchyma, decreased testosterone levels, and sperm abnormalities in male offspring born to infected mothers. Abstract: Infection with ZIKV during pregnancy is associated with fetal developmental problems. Although neurological issues are being explored more in experimental studies, limited research has focused on the reproductive health consequences for offspring born to infected mothers. In this context, this study aimed to assess the impact of ZIKV infection during pregnancy on the testes and sperm of adult male offspring. Female mice were intraperitoneally inoculated with a Brazil strain of ZIKV during the 5.5th day of embryonic gestation. The offspring were evaluated 12 weeks after birth to analyze cellular and molecular changes in the testes and sperm. A novel approach combining variable-angle spectroscopic ellipsometry and machine learning modeling was also introduced for sperm sample analysis. The study revealed the presence of ZIKV protein in the testis parenchyma of adult male offspring born to infected mothers. It was shown that the testes exhibited altered steroidogenesis and inflammatory mediators, in addition to significant issues with spermiogenesis that resulted in sperm with DNA fragmentation, head defects, and protamination failure. Additionally, sperm dielectric properties and artificial intelligence showed potential for rapid identification and classification of sperm samples from infected mice. These findings provide crucial insights into the reproductive risks for men born from ZIKV-infected pregnant women.

New, fast, and precise method of COVID-19 detection in nasopharyngeal and tracheal aspirate samples combining optical spectroscopy and machine learning.

Fast, precise, and low-cost diagnostic testing to identify persons infected with SARS-CoV-2 virus is pivotal to control the global pandemic of COVID-19 that began in late 2019. The gold standard method of diagnostic recommended is the RT-qPCR test. However, this method is not universally available, and is time-consuming and requires specialized personnel, as well as sophisticated laboratories. Currently, machine learning is a useful predictive tool for biomedical applications, being able to classify data from diverse nature. Relying on the artificial intelligence learning process, spectroscopic data from nasopharyngeal swab and tracheal aspirate samples can be used to leverage characteristic patterns and nuances in healthy and infected body fluids, which allows to identify infection regardless of symptoms or any other clinical or laboratorial tests. Hence, when new measurements are performed on samples of unknown status and the corresponding data is submitted to such an algorithm, it will be possible to predict whether the source individual is infected or not. This work presents a new methodology for rapid and precise label-free diagnosing of SARS-CoV-2 infection in clinical samples, which combines spectroscopic data acquisition and analysis via artificial intelligence algorithms. Our results show an accuracy of 85% for detection of SARS-CoV-2 in nasopharyngeal swab samples collected from asymptomatic patients or with mild symptoms, as well as an accuracy of 97% in tracheal aspirate samples collected from critically ill COVID-19 patients under mechanical ventilation. Moreover, the acquisition and processing of the information is fast, simple, and cheaper than traditional approaches, suggesting this methodology as a promising tool for biomedical diagnosis vis-à-vis the emerging and re-emerging viral SARS-CoV-2 variant threats in the future.

Contribuições da saúde bucal para o acompanhamento de gestantes na estratégia saúde da família

O presente estudo objetiva descrever as principais alterações bucais que acometem as mulheres no ciclo gravídico-puerperal e apresentar propostas de intervenções a serem realizadas pela equipe de saúde bucal na Estratégia Saúde da Família (ESF), por meio de revisão narrativa. O atendimento preconizado pela ESF conta com atividades de prevenção e promoção de saúde, além de ações curativas e de reabilitação dirigidas à população adscrita. Diante das necessidades em saúde da população, destaca-se o ciclo gravídico-puerperal, composto por características peculiares que resultam em vulnerabilidades para as condições de saúde da mulher. O acompanhamento a gestantes e puérperas é considerado prioritário para as equipes de saúde na ESF, através da assistência Pré-Natal. O cuidado Pré-Natal é habitualmente realizado por médicos e enfermeiros, na rotina de trabalho da ESF, com importante atuação dos agentes comunitários de saúde (ACS) na captação e no acompanhamento domiciliar das gestantes. Por outro lado, o acompanhamento de gestantes por cirurgiões-dentistas é reduzido e não padronizado na ESF. Essa realidade converge ao problema identificado pelo Diagnóstico Situacional de Saúde da ESF Nova Holanda de Divinópolis/MG, em 2009. Além de pautar-se em características da formação profissional do cirurgião dentista, com pouca ênfase na saúde pública, bem como no processo de trabalho da saúde bucal ainda focado no aspecto curativo; há ainda, a não procura de gestantes por atendimento odontológico relacionada a mitos e tabus quanto a possíveis prejuízos para a gestação ao se tratar os dentes. O trabalho mostrou a importância da atuação da equipe de saúde bucal no acompanhamento às gestantes e puérperas na ESF confrontando com tímida atuação nesse sentido. Sendo descritas as repercussões bucais mais comuns na gravidez/puerpério, propostas foram apresentadas para condução do cuidado odontológico da gestante e puérpera.