Summary of the first Brazilian Symposium on Human Biometeorology.

This brief background highlights Brazil as a 'climate-health hotspot', i.e. a country where climate affects local populations negatively through multiple pathways (Di Napoli et al.

A first approach to human biometeorology research in Brazil: a systematic review and meta-analysis.

This systematic review aims to give an overview of the diversity of research areas related to human biometeorology in Brazil. The main focus of this paper addresses research trends, represented by published papers with national and international authorship, main contributions and shortcomings, as well as challenges and prospects of research in this area of study. An extensive literature search was conducted in the Scopus, Web of Science, and Science Direct databases so as to identify relevant publication output up to July 2021 related to the research area.

Lesion Volume Quantification Using Two Convolutional Neural Networks in MRIs of Multiple Sclerosis Patients.

Background: Multiple sclerosis (MS) is a neurologic disease of the central nervous system which affects almost three million people worldwide. MS is characterized by a demyelination process that leads to brain lesions, allowing these affected areas to be visualized with magnetic resonance imaging (MRI). Deep learning techniques, especially computational algorithms based on convolutional neural networks (CNNs), have become a frequently used algorithm that performs feature self-learning and enables segmentation of structures in the image useful for quantitative analysis of MRIs, including quantitative analysis of MS.

A preliminary study of the concentration of metallic elements in the blood of patients with multiple sclerosis as measured by ICP-MS.

It is estimated that multiple sclerosis (MS) affects 35,000 Brazilians and 2.5 million individuals worldwide. Many studies have suggested a possible role of metallic elements in the etiology of MS, but their concentration in the blood of MS patients is nonetheless little investigated in Brazil.

Valuation of the human thermal discomfort index for the five Brazilian regions in the period of El Niño-Southern Oscillation (ENSO).

Brazil is an extensive country with five administrative regions that have different climates, mainly due to their geographic locations. The El Niño-Southern Oscillation influences the regime of temperature and precipitation of the Brazilian regions, which can directly affect the thermal discomfort of the population. The objective of this study was to evaluate the human thermal discomfort index (HDI) in the five regions of Brazil for El Niño, La Niña, and neutral years from 1979 to 2017, as well as the influence of the degree of intensity of the Pacific Ocean anomaly in the thermal conditions of the Brazilian regions.

Evaluation of metal removal efficiency and its influence in the physicochemical parameters at two sewage treatment plants.

In sewage treatment plants, physicochemical parameters are highly controlled since treated sewage can be returned to water bodies or reused. In addition, pollutants such as heavy metals also deserve attention due to their potential toxicity. In general, these characteristics of sewage and treated water are evaluated independently, with the support of Brazilian legislation that does not require a routine for the analysis of metals as frequent as for the physicochemical parameters.