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Background: Fetal growth restriction (FGR) is a leading risk factor for stillbirth, yet the diagnosis of FGR confers considerable prognostic uncertainty, as most infants with FGR do not experience any morbidity. Our objective was to use data from a large, deeply phenotyped observational obstetric cohort to develop a probabilistic graphical model (PGM), a type of "explainable artificial intelligence (AI)", as a potential framework to better understand how interrelated variables contribute to perinatal morbidity risk in FGR.

Methods: Using data from 9,558 pregnancies delivered at ≥ 20 weeks with available outcome data, we derived and validated a PGM using randomly selected sub-cohorts of 80% (n = 7645) and 20% (n = 1,912), respectively, to discriminate cases of FGR resulting in composite perinatal morbidity from those that did not.

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Objective: To analyze trends of syphilis during pregnancy and congenital syphilis, based on reported cases in São Paulo, Brazil, from 2011 to 2023.

Methods: Ecological time series study, based on data from Notifiable Health Conditions Information System records. The Prais-Winsten method was used to verify trends.

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Background: To develop an effective vaccine against Plasmodium vivax, the most widely dispersed human malaria parasite, it is critical to understand how coinfections with other pathogens could impact malaria-specific immune response. A recent conceptual study proposed that Epstein-Barr virus (EBV), a highly prevalent human herpesvirus that establishes lifelong persistent infection, may influence P. vivax antibody responses.

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Background: Tuberculosis is one of the leading causes of death from infectious diseases in the world, with approximately 25% of the global population having latent tuberculosis infection. Secondhand smoke exposure has been recognised as a significant risk factor in the development of active Tuberculosis in individuals with latent tuberculosis infection.

Study Design And Methods: This study used the Systematic Literature Review method based on PRISMA guidelines.

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Hand, foot and mouth disease (HFMD) is a major public health issue in Hubei Province; however, research on the direct and indirect effects of factors affecting HFMD is limited. This study employed structural equation modeling (SEM) and geographically weighted regression (GWR) to investigate the various impacts and spatial variations in the factors influencing the HFMD epidemic in Hubei Province from 2016 to 2018. The results indicated that (1) with respect to the direct effects, the number of primary school students had the greatest positive direct effect on the number of HFMD cases, with a coefficient of 0.

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