Detecting Network Communities: An Application to Phylogenetic Analysis

This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis

Wildfire, deforestation and health in tropical rainforest areas: a scoping review protocol.

INTRODUCTION: Wildfires and deforestation potentially have direct effects on multiple health outcomes as well as indirect consequences for climate change. Tropical rainforest areas are characterised by high rainfall, humidity and temperature, and they are predominantly found in low-income and middle-income countries. This study aims to synthesise the methods, data and health outcomes reported in scientific papers on wildfires and deforestation in these locations. METHODS AND ANALYSIS: We will carry out a scoping review according to the Joanna Briggs Institute's (JBI) manual for scoping reviews and the framework proposed by Arksey and O'Malley, and Levac et al. The search for articles was performed on 18 August 2023, in 16 electronic databases using Medical Subject Headings terms and adaptations for each database from database inception. The search for local studies will be complemented by the manual search in the list of references of the studies selected to compose this review. We screened studies written in English, French, Portuguese and Spanish. We included quantitative studies assessing any human disease outcome, hospitalisation and vital statistics in regions of tropical rainforest. We exclude qualitative studies and quantitative studies whose outcomes do not cover those of interest. The text screening was done by two independent reviewers. Subsequently, we will tabulate the data by the origin of the data source used, the methods and the main findings on health impacts of the extracted data. The results will provide descriptive statistics, along with visual representations in diagrams and tables, complemented by narrative summaries as detailed in the JBI guidelines. ETHICS AND DISSEMINATION: The study does not require an ethical review as it is meta-research and uses published, deidentified secondary data sources. The submission of results for publication in a peer-reviewed journal and presentation at scientific and policymakers' conferences is expected. STUDY REGISTRATION: Open Science Framework (https://osf.io/pnqc7/)

Modulatory effects of Tabebuia impetiginosa (Lamiales, Bignoniaceae) on doxorubicin-induced somatic mutation and recombination in Drosophila melanogaster

The wing Somatic Mutation and Recombination Test (SMART) in D. melanogaster was used to study genotoxicity of the medicinal plant Tabebuia impetiginosa. Lapachol (naphthoquinone) and β-lapachone (quinone) are the two main chemical constituents of T. impetiginosa. These compounds have several biological properties. They induce apoptosis by generating oxygen-reactive species, thereby inhibiting topoisomerases (I and II) or inducing other enzymes dependent on NAD(P)H:quinone oxidoreductase 1, thus affecting cell cycle checkpoints. The SMART was used in the standard (ST) version, which has normal levels of cytochrome P450 (CYP) enzymes, to check the direct action of this compound, and in the high bioactivation (HB) version, which has a high constitutive level of CYP enzymes, to check for indirect action in three different T. impetiginosa concentrations (10%, 20% or 40% w/w). It was observed that T. impetiginosa alone did not modify the spontaneous frequencies of mutant spots in either cross. The negative results observed prompted us to study this phytotherapeuticum in association with the reference mutagen doxorubicin (DXR). In co-treated series, T. impetiginosa was toxic in both crosses at higher concentration, whereas in the HB cross, it induced a considerable potentiating effect (from ~24.0 to ~95.0%) on DXR genotoxity. Therefore, further research is needed to determine the possible risks associated with the exposure of living organisms to this complex mixture