Molecular Basis of MC1R Activation: Mutation-Induced Alterations in Structural Dynamics.

The MC1R protein is a receptor found in melanocytes that plays a role in melanin synthesis. Mutations in this protein can impact hair color, skin tone, tanning ability, and increase the risk of skin cancer. The MC1R protein is activated by the alpha-melanocyte-stimulating hormone (α-MSH).

Exploring bacterial diversity and antimicrobial resistance gene on a southern Brazilian swine farm.

The bacterial composition of and the circulation of antimicrobial resistance genes (ARGs) in waste from Brazilian swine farms are still poorly understood. Considering that antimicrobial resistance (AMR) is one of the main threats to human, animal, and environmental health, the need to accurately assess the load of ARGs released into the environment is urgent. Therefore, this study aimed to characterize the microbiota in a swine farm in southern Brazil and the resistome in swine farm wastewater treated in a series of waste stabilization ponds (WSPs).

Sodium propionate oral supplementation ameliorates depressive-like behavior through gut microbiome and histone 3 epigenetic regulation.

Major depressive disorder (MDD) is a global health concern, affecting over 250 million individuals worldwide. In recent years, the gut-brain axis has emerged as a promising field for understanding the pathophysiology of MDD. Microbial metabolites, such as short-chain fatty acids (SCFAs)-acetate, butyrate, and propionate-, have gained attention for their potential to influence epigenetic modifications within the host brain.

Assessment of esterase conformational dynamics in response to poly(ethylene terephthalate) binding.

The pervasive presence of plastic in the environment has reached a concerning scale, being identified in many ecosystems. Bioremediation is the cheapest and most eco-friendly alternative to remove this polymer from affected areas. Recent work described that a novel cold-active esterase enzyme extracted from the bacteria could promiscuously degrade PET.

The MAPSTROKE project: A computational strategy to improve access to acute stroke care.

Background: Global access to acute stroke treatment is variable worldwide, with notable gaps in low and middle-income countries (LMIC), especially in rural areas. Ensuring a standardized method for pinpointing the existing regional coverage and proposing potential sites for new stroke centers is essential to change this scenario.

Aims: To create and apply computational strategies (CSs) to determine optimal locations for new acute stroke centers (ASCs), with a pilot application in nine Latin American regions/countries.

MC1R and age heteroclassification of face phenotypes in the Rio Grande do Sul population.

Background: Forensic DNA phenotyping (FDP) consists of the use of methodologies for predicting externally visible characteristics (EVCs) from the genetic material of biological samples found in crime scenes and has proven to be a promising tool in aiding human identification in police activities. Currently, methods based on multiplex assays and statistical models of prediction of EVCs related to hair, skin, and iris pigmentation using panels of SNP and INDEL biomarkers have already been developed and validated by the forensic scientific community. As well as traces of pigmentation, an individual's perceived age (PA) can also be considered an EVC and its estimation in unknown individuals can be useful for the progress of investigations.

Functional response of microbial communities in lab-controlled oil-contaminated marine sediment.

Crude oil contamination is one of the biggest problems in modern society. As oil enters into contact with the environment, especially if the point of contact is a body of water, it begins a weathering process by mixing and spreading. This is dangerous to local living organisms' communities and can impact diversity.

The nucleotide excision repair proteins through the lens of molecular dynamics simulations.

Mutations that affect the proteins responsible for the nucleotide excision repair (NER) pathway can lead to diseases such as xeroderma pigmentosum, trichothiodystrophy, Cockayne syndrome, and Cerebro-oculo-facio-skeletal syndrome. Hence, understanding their molecular behavior is needed to elucidate these diseases' phenotypes and how the NER pathway is organized and coordinated. Molecular dynamics techniques enable the study of different protein conformations, adaptable to any research question, shedding light on the dynamics of biomolecules.

NIAS-Server 2.0: A versatile complementary tool for structural biology studies.

Increasing the repertoire of available complementary tools to advance the knowledge of protein structures is fundamental for structural biology. The Neighbors Influence of Amino Acids and Secondary Structures (NIAS) is a server that analyzes a protein's conformational preferences of amino acids. NIAS is based on the Angle Probability List, representing the normalized frequency of empirical conformational preferences, such as torsion angles, of different amino acid pairs and their corresponding secondary structure information, as available in the Protein Data Bank.

Meta-analyses of host metagenomes from colorectal cancer patients reveal strong relationship between colorectal cancer-associated species.

Colorectal cancer (CRC) is one of the most common types of cancer, with many studies associating its development with changes in the gut microbiota. Recent developments in sequencing technologies and subsequent meta-analyses of gut metagenome provided a better understanding of species related to CRC tumorigenesis. Still, the importance of high-importance taxonomic singletons ( species highly associated with a given condition but observed only in the minority of datasets) and the species interactions and co-occurrence across cohorts need further exploration.

Transcriptomic Analysis of Long Non-Coding RNA during Infection.

is one of the most commonly found species in fungal infections. Due to its clinical importance, molecular aspects of the host immune defense against the fungus are of interest to biomedical sciences. Long non-coding RNAs (lncRNAs) have been investigated in different pathologies and gained widespread attention regarding their role as gene regulators.

Ancestry resolution of South Brazilians by forensic 165 ancestry-informative SNPs panel.

Forensic DNA phenotyping (FDP) includes biogeographic ancestry (BGA) inference and externally visible characteristics (EVCs) prediction directly from an evidential DNA sample as alternatives to provide valuable intelligence when conventional DNA profiling fails to achieve identification. In this context, the application of Massively Parallel Sequencing (MPS) methodologies, which enables simultaneous typing of multiple samples and hundreds of forensic markers, has been gradually implemented in forensic genetic casework. The Precision ID Ancestry Panel (Thermo Fisher Scientific, Waltham, USA) is a forensic multiplex assay consisting of 165 autosomal SNPs designed to provide biogeographic ancestry information.

Interdisciplinary Overview of Lipopeptide and Protein-Containing Biosurfactants.

Biosurfactants are amphipathic molecules capable of lowering interfacial and superficial tensions. Produced by living organisms, these compounds act the same as chemical surfactants but with a series of improvements, the most notable being biodegradability. Biosurfactants have a wide diversity of categories.

The Drosophila melanogaster ACE2 ortholog genes are differently expressed in obesity/diabetes and aging models: Implications for COVID-19 pathology.

The Spike glycoprotein of SARS-CoV-2, the virus responsible for coronavirus disease 2019, binds to its ACE2 receptor for internalization in the host cells. Elderly individuals or those with subjacent disorders, such as obesity and diabetes, are more susceptible to COVID-19 severity. Additionally, several SARS-CoV-2 variants appear to enhance the Spike-ACE2 interaction, which increases transmissibility and death.

Gene Expression Variation Analysis (GEVA): A new R package to evaluate variations in differential expression in multiple biological conditions.

Nowadays, there are thousands of publicly available gene expression datasets which can be analyzed in silico using specialized software or the R programming language. However, transcriptomic studies consider experimental conditions individually, giving one independent result per comparison. Here we describe the Gene Expression Variation Analysis (GEVA), a new R package that accepts multiple differential expression analysis results as input and performs multiple statistical steps, such as weighted summarization, quantiles partition, and clustering to find genes whose differential expression varied less across all experiments.

Feature selection reveal peripheral blood parameter's changes between COVID-19 infections patients from Brazil and Ecuador.

The investigation of conventional complete blood-count (CBC) data for classifying the SARS-CoV-2 infection status became a topic of interest, particularly as a complementary laboratory tool in developing and third-world countries that financially struggled to test their population. Although hematological parameters in COVID-19-affected individuals from Asian and USA populations are available, there are no descriptions of comparative analyses of CBC findings between COVID-19 positive and negative cases from Latin American countries. In this sense, machine learning techniques have been employed to examine CBC data and aid in screening patients suspected of SARS-CoV-2 infection.

Genetic and molecular Omp25 analyses from worldwide Brucella canis strains: Possible mutational influences in protein function.

Brucella canis is responsible for canine brucellosis, a neglected zoonotic disease. The omp25 gene has been described as an important marker for Brucella intra-species differentiation, in addition to the ability to interact with the host immune system. Therefore, this study investigated the omp25 sequence from B.

Comparison of machine learning techniques to handle imbalanced COVID-19 CBC datasets.

The Coronavirus pandemic caused by the novel SARS-CoV-2 has significantly impacted human health and the economy, especially in countries struggling with financial resources for medical testing and treatment, such as Brazil's case, the third most affected country by the pandemic. In this scenario, machine learning techniques have been heavily employed to analyze different types of medical data, and aid decision making, offering a low-cost alternative. Due to the urgency to fight the pandemic, a massive amount of works are applying machine learning approaches to clinical data, including complete blood count (CBC) tests, which are among the most widely available medical tests.

Modifying the catalytic preference of alpha-amylase toward n-alkanes for bioremediation purposes using in silico strategies.

Since the beginning of oil exploration, whole ecosystems have been affected by accidents and bad practices involving petroleum compounds. In this sense, bioremediation stands out as the cheapest and most eco-friendly alternatives to reverse the damage done in oil-impacted areas. However, more efforts must be made to engineer enzymes that could be used in the bioremediation process.

Evaluation of drug repositioning by molecular docking of pharmaceutical resources available in the Brazilian healthcare system against SARS-CoV-2.

In 2020 SARS-CoV-2 reached pandemic status, reaching Brazil in mid-February. As of now, no specific drugs for treating the disease are available. In this work, the possibility of interaction between SARS-CoV-2 viral proteins (open and closed spike protein, isolate spike protein RBD, NSP 10, NSP 16, main protease, and RdRp polymerase) and multiple molecules is addressed through the repositioning of drugs available for the treatment of other diseases that are approved by the FDA and covered by SUS, the Brazilian Public Health System.

Multi-Approach Bioinformatics Analysis of Curated Omics Data Provides a Gene Expression Panorama for Multiple Cancer Types.

Studies describing the expression patterns and biomarkers for the tumoral process increase in number every year. The availability of new datasets, although essential, also creates a confusing landscape where common or critical mechanisms are obscured amidst the divergent and heterogeneous nature of such results. In this work, we manually curated the Gene Expression Omnibus using rigorous filtering criteria to select the most homogeneous and highest quality microarray and RNA-seq datasets from multiple types of cancer.

Hemogram data as a tool for decision-making in COVID-19 management: applications to resource scarcity scenarios.

Background: COVID-19 pandemics has challenged emergency response systems worldwide, with widespread reports of essential services breakdown and collapse of health care structure. A critical element involves essential workforce management since current protocols recommend release from duty for symptomatic individuals, including essential personnel. Testing capacity is also problematic in several countries, where diagnosis demand outnumbers available local testing capacity.

ConfID: an analytical method for conformational characterization of small molecules using molecular dynamics trajectories.

Motivation: The conformational space of small molecules can be vast and difficult to assess. Molecular dynamics (MD) simulations of free ligands in solution have been applied to predict conformational populations, but their characterization is often based on clustering algorithms or manual efforts.

Results: Here, we introduce ConfID, an analytical tool for conformational characterization of small molecules using MD trajectories.