Predictive modeling of gestational weight gain: a machine learning multiclass classification study.

Background: Gestational weight gain (GWG) is a critical factor influencing maternal and fetal health. Excessive or insufficient GWG can lead to various complications, including gestational diabetes, hypertension, cesarean delivery, low birth weight, and preterm birth. This study aims to develop and evaluate machine learning models to predict GWG categories: below, within, or above recommended guidelines.

Assessment of immune responses to a Comirnaty® booster following CoronaVac® vaccination in healthcare workers.

Background: The immunological response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and immunisation is variable.

Objectives: To describe the humoral immune response by correlating IgA and IgG antibodies with NAbs titration following CoronaVac® immunisation and an mRNA (Comirnaty®) booster among healthcare workers (HCWs) and to compare the cytokine and interleukin profiles between HCWs vaccinated with CoronaVac and coronavirus disease 2019 (COVID-19) infected patients.

Methods: Samples from 133 HCWs collected at 20 (T1) and 90 (T2) days after CoronaVac immunisation and 15 (T3) days after a booster dose with the Comirnaty vaccine were analysed for IgA and IgG EIA and neutralisation assay.

Potential involvement of beta-lactamase homologous proteins in resistance to beta-lactam antibiotics in gram-negative bacteria of the ESKAPEE group.

Enzymatic degradation mediated by beta-lactamases constitutes one of the primary mechanisms of resistance to beta-lactam antibiotics in gram-negative bacteria. This enzyme family comprises four molecular classes, categorized into serine beta-lactamases (Classes A, C, and D) and zinc-dependent metallo-beta-lactamases (Class B). Gram-negative bacteria producing beta-lactamase are of significant concern, particularly due to their prevalence in nosocomial infections.

Diagnosis of fasciolosis antibodies in Brazilian cattle through ELISA employing both native and recombinant antigens.

Unlabelled: Bovine fasciolosis is a parasitic disease with a global reach. Coprological based on egg detection in fecal samples and liver inspection to evaluate the presence of the parasite is currently the gold standard for diagnosing chronic fasciolosis in cattle. However, these techniques are labor-intensive and ineffective during the acute phase of the disease.

Alternative polyadenylation and dynamic 3' UTR length is associated with polysome recruitment throughout the cardiomyogenic differentiation of hESCs.

Alternative polyadenylation (APA) increases transcript diversity through the generation of isoforms with varying 3' untranslated region (3' UTR) lengths. As the 3' UTR harbors regulatory element target sites, such as miRNAs or RNA-binding proteins, changes in this region can impact post-transcriptional regulation and translation. Moreover, the APA landscape can change based on the cell type, cell state, or condition.

[Access to neonatal healthcare services: analysis of displacement networks between municipalities in the State of Paraná, Brazil].

This study aimed to characterize hospitalizations of residents in Paraná State, Brazil, that occurred during the neonatal period in a municipality different from their place of residence from 2008 to 2019, and to describe displacement networks for the first and last biennium of the series, corresponding to periods before and after initiatives to regionalize health services in the state. Admissions of children aged from 0 to 27 days were obtained from the Hospital Information System of the Brazilian National Unified Health System (SIH-SUS) database. For each biennium and health region, the proportion of admissions that occurred outside the municipality of residence, the weighted average distance traveled, and indicators of health and service provision were calculated.

Clusters of Pregnant Women with Severe Acute Respiratory Syndrome Due to COVID-19: An Unsupervised Learning Approach.

COVID-19 has been widely explored in relation to its symptoms, outcomes, and risk profiles for the severe form of the disease. Our aim was to identify clusters of pregnant and postpartum women with severe acute respiratory syndrome (SARS) due to COVID-19 by analyzing data available in the Influenza Epidemiological Surveillance Information System of Brazil (SIVEP-Gripe) between March 2020 and August 2021. The study's population comprised 16,409 women aged between 10 and 49 years old.

Selecting Genetic Variants and Interactions Associated with Amyotrophic Lateral Sclerosis: A Group LASSO Approach.

Amyotrophic lateral sclerosis (ALS) is a multi-system neurodegenerative disease that affects both upper and lower motor neurons, resulting from a combination of genetic, environmental, and lifestyle factors. Usually, the association between single-nucleotide polymorphisms (SNPs) and this disease is tested individually, which leads to the testing of multiple hypotheses. In addition, this classical approach does not support the detection of interaction-dependent SNPs.

Antigenicity and adhesiveness of a Plasmodium vivax VIR-E protein from Brazilian isolates.

Background: Plasmodium vivax, the major cause of malaria in Latin America, has a large subtelomeric multigene family called vir. In the P. vivax genome, about 20% of its sequences are vir genes.

Proteogenomics Reveals Orthologous Alternatively Spliced Proteoforms in the Same Human and Mouse Brain Regions with Differential Abundance in an Alzheimer's Disease Mouse Model.

Alternative splicing (AS) may increase the number of proteoforms produced by a gene. Alzheimer's disease (AD) is a neurodegenerative disease with well-characterized AS proteoforms. In this study, we used a proteogenomics strategy to build a customized protein sequence database and identify orthologous AS proteoforms between humans and mice on publicly available shotgun proteomics (MS/MS) data of the corpus callosum (CC) and olfactory bulb (OB).

Dysregulation of Transcription Factor Networks Unveils Different Pathways in Human Papillomavirus 16-Positive Squamous Cell Carcinoma and Adenocarcinoma of the Uterine Cervix.

Squamous cell carcinoma (SCC) and adenocarcinoma (ADC) are the most common histological types of cervical cancer (CC). The worse prognosis of ADC cases highlights the need for better molecular characterization regarding differences between these CC types. RNA-Seq analysis of seven SCC and three ADC human papillomavirus 16-positive samples and the comparison with public data from non-tumoral human papillomavirus-negative cervical tissue samples revealed pathways exclusive to each histological type, such as the epithelial maintenance in SCC and the maturity-onset diabetes of the young (MODY) pathway in ADC.

Cause-specific mortality prediction in older residents of São Paulo, Brazil: a machine learning approach.

Background: Populational ageing has been increasing in a remarkable rate in developing countries. In this scenario, preventive strategies could help to decrease the burden of higher demands for healthcare services. Machine learning algorithms have been increasingly applied for identifying priority candidates for preventive actions, presenting a better predictive performance than traditional parsimonious models.

Rosettes integrity protects Plasmodium vivax of being phagocytized.

Plasmodium vivax is the most prevalent cause of malaria outside of Africa. P. vivax biology and pathogenesis are still poorly understood.

Plasmodium vivax AMA1: Implications of distinct haplotypes for immune response.

In Brazil, Plasmodium vivax infection accounts for around 80% of malaria cases. This infection has a substantial impact on the productivity of the local population as the course of the disease is usually prolonged and the development of acquired immunity in endemic areas takes several years. The recent emergence of drug-resistant strains has intensified research on alternative control methods such as vaccines.

Prospective association between burnout and road traffic accidents in teachers.

We investigated whether burnout (emotional exhaustion, depersonalization and reduced professional efficacy) is a risk factor for traffic accidents. A prospective cohort study was conducted with 509 school teachers. The teachers were interviewed in 2012-2013, and the Maslach Burnout Inventory was applied.

Assessing the impact of a doctor in remote areas of Brazil.

Objectives: The More Doctors Program (MDP) is an ongoing Brazilian policy that aims to improve healthcare by providing physicians to the most vulnerable municipalities. We aimed to measure the impact of MDP in mortality and infant mortality rate, the proportion of live births with low weight, prenatal appointments, childbirths at first and fifth min Apgar, public health investment and immunization in Brazil.

Methods: Municipal health indicators were collected before and after the intervention (2012 and 2015).

Blurred lines: racial misclassification in death certificates in Brazil.

Objectives: To analyze the agreement between self-reported race and race reported on death certificates for older (≥ 60 years) residents of São Paulo, Brazil (from 2000 to 2016) and to estimate weights to correct mortality data by race.

Methods: We used data from the Health, Well-Being and Aging Study (SABE) and from Brazil's Mortality Information System. Misclassification was identified by comparing individual self-reported race with the corresponding race on the death certificate (n = 1012).

Machine learning to predict 30-day quality-adjusted survival in critically ill patients with cancer.

Purpose: To develop and compare the predictive performance of machine-learning algorithms to estimate the risk of quality-adjusted life year (QALY) lower than or equal to 30 days (30-day QALY).

Material And Methods: Six machine-learning algorithms were applied to predict 30-day QALY for 777 patients admitted in a prospective cohort study conducted in Intensive Care Units (ICUs) of two public Brazilian hospitals specialized in cancer care. The predictors were 37 characteristics collected at ICU admission.

Using the Maternity Safety Thermometer to estimate harm-free care in Southeast Brazil: A hospital-based cohort.

Background: High rates of unnecessary cesareans and interventions in vaginal births contribute to stagnant maternal and neonatal mortality rates in Brazil. We used the Maternity Safety Thermometer (MST) to assess the prevalence of harm during maternity care.

Methods: This secondary analysis of the "Birth in Brazil" survey included a representative sample of 10 155 women who gave birth in public and private hospitals in southeastern Brazil.

[Machine learning for predictive analyses in health: an example of an application to predict death in the elderly in São Paulo, Brazil].

This study aims to present the stages related to the use of machine learning algorithms for predictive analyses in health. An application was performed in a database of elderly residents in the city of São Paulo, Brazil, who participated in the Health, Well-Being, and Aging Study (SABE) (n = 2,808). The outcome variable was the occurrence of death within five years of the elder's entry into the study (n = 423), and the predictors were 37 variables related to the elder's demographic, socioeconomic, and health profile.

Job strain among teachers: associations with occupational factors according to social support.

This study aimed to ascertain the occupational factors associated with job strain among elementary school teachers and whether the associations varied according to social support. This was a cross-sectional study with 842 teachers from the state school system of a municipality in southern Brazil. Occupational information was obtained by means of interviews.

Factors associated with preterm birth: from logistic regression to structural equation modeling.

This study proposed the application of structural equation modeling (SEM) to investigate variables associated with preterm birth based on a theoretical model analyzed previously by hierarchical logistic regression. The data came from a population-based case-control observational study of hospital births to mothers residing in Londrina, Paraná State, Brazil (June 2006 to March 2007). For the SEM, the study considered the association between socioeconomic characteristics and psychosocial aspects pertaining to reproductive history, work and physical activity, complications during the pregnancy, and fetal characteristics.

Overachieving Municipalities in Public Health: A Machine-learning Approach.

Background: Identifying successful public health ideas and practices is a difficult challenge towing to the presence of complex baseline characteristics that can affect health outcomes. We propose the use of machine learning algorithms to predict life expectancy at birth, and then compare health-related characteristics of the under- and overachievers (i.e.