Retrieving biodiversity data from multiple sources: making secondary data standardised and accessible.

Biodiversity data, particularly species occurrence and abundance, are indispensable for testing empirical hypothesis in natural sciences. However, datasets built for research programmes do not often meet FAIR (findable, accessible, interoperable and reusable) principles, which raises questions about data quality, accuracy and availability. The 21 century has markedly been a new era for data science and analytics and every effort to aggregate, standardise, filter and share biodiversity data from multiple sources have become increasingly necessary.

Late Quaternary hydroclimate and vegetation changes in an upland lake in southeastern Amazonia.

An integrated approach considering facies, isotopic, and palynological analyses of lake sediments from the Serra Norte de Carajás, southeastern Amazonia, is presented in this work to refine paleoclimate and paleohydrological changes based on upland lake sediments during the late Quaternary. The sediments have a fining-upward deposition cycle typical of upland swamps/lakes. The origin of organic matter is autochthonous mainly related to C3 terrestrial plants, macrophytes and algae.

The quest for the reliability of machine learning models in binary classification on tabular data.

In this paper we explore the reliability of contexts of machine learning (ML) models. There are several evaluation procedures commonly used to validate a model (precision, F1 Score and others); However, these procedures are not linked to the evaluation of learning itself, but only to the number of correct answers presented by the model. This characteristic makes it impossible to assess whether a model was able to learn through elements that make sense of the context in which it is inserted.

"Bunch of acai berries sign": a new radiological sign in patients with CNS involvement in Chagas disease.

Chagas disease is an infection caused by Trypanosoma cruzi, a parasite endemic in Latin America. Acute involvement of the CNS by Chagas has been considered rare, but presumed reactivation of chronic disease in immunosuppressed patients has been the subject of recent reports. Our objective is to describe the clinical and imaging characteristics of four patients with Chagas disease and CNS involvement, and the patients had to have available MRI and a diagnosis confirmed by biopsy.

Draft Genome Sequence of the Novel, Moderately Thermophilic, Iron- and Sulfur-Oxidizing Firmicute Strain Y002, Isolated from an Extremely Acidic Geothermal Environment.

We report the draft genome sequence of the Firmicute strain Y002, a facultatively anaerobic, acidophilic bacterium that catalyzes the dissimilatory oxidation of iron and sulfur and the reduction of ferric iron. Analysis of the genome (2.9 Mb; G+C content, 46 mol%) provided insights into its ability to grow in extremely acidic geothermal environments.

PipeCoV: a pipeline for SARS-CoV-2 genome assembly, annotation and variant identification.

Motivation: Since the identification of the novel coronavirus (SARS-CoV-2), the scientific community has made a huge effort to understand the virus biology and to develop vaccines. Next-generation sequencing strategies have been successful in understanding the evolution of infectious diseases as well as facilitating the development of molecular diagnostics and treatments. Thousands of genomes are being generated weekly to understand the genetic characteristics of this virus.

New plastomes of eight Ipomoea species and four putative hybrids from Eastern Amazon.

Ipomoea is a large pantropical genus globally distributed, which importance goes beyond the economic value as food resources or ornamental crops. This highly diverse genus has been the focus of a great number of studies, enriching the plant genomics knowledge, and challenging the plant evolution models. In the Carajás mountain range, located in Eastern Amazon, the savannah-like ferruginous ecosystem known as canga harbors highly specialized plant and animal populations, and Ipomoea is substantially representative in such restrictive habitat.

Unraveling the plant diversity of the Amazonian through DNA barcoding.

The of the Serra dos Carajás, in Eastern Amazon, is home to a unique open plant community, harboring several endemic and rare species. Although a complete flora survey has been recently published, scarce to no genetic information is available for most plant species of the ironstone outcrops of the Serra dos Carajás. In this scenario, DNA barcoding appears as a fast and effective approach to assess the genetic diversity of the Serra dos Carajás flora, considering the growing need for robust biodiversity conservation planning in such an area with industrial mining activities.

Conservation implications of genetic structure in the narrowest endemic quillwort from the Eastern Amazon.

The quillwort is a critically endangered species occurring in a single lake in Serra dos Carajás, Eastern Amazon. Low genetic diversity and small effective population sizes ( ) are expected for narrow endemic species (NES). Conservation biology studies centered in a single species show some limitations, but they are still useful considering the limited time and resources available for protection of species at risk of extinction.

geneRFinder: gene finding in distinct metagenomic data complexities.

Background: Microbes perform a fundamental economic, social, and environmental role in our society. Metagenomics makes it possible to investigate microbes in their natural environments (the complex communities) and their interactions. The way they act is usually estimated by looking at the functions they play in those environments and their responsibility is measured by their genes.

Combining genotype, phenotype, and environmental data to delineate site-adjusted provenance strategies for ecological restoration.

Despite the importance of climate-adjusted provenancing to mitigate the effects of environmental change, climatic considerations alone are insufficient when restoring highly degraded sites. Here we propose a comprehensive landscape genomic approach to assist the restoration of moderately disturbed and highly degraded sites. To illustrate it we employ genomic data sets comprising thousands of single nucleotide polymorphisms from two plant species suitable for the restoration of iron-rich Amazonian Savannas.

On the utilization of deep and ensemble learning to detect milk adulteration.

Background: Fraudulent milk adulteration is a dangerous practice in the dairy industry that is harmful to consumers since milk is one of the most consumed food products. Milk quality can be assessed by Fourier Transformed Infrared Spectroscopy (FTIR), a simple and fast method for obtaining its compositional information. The spectral data produced by this technique can be explored using machine learning methods, such as neural networks and decision trees, in order to create models that represent the characteristics of pure and adulterated milk samples.

Landscape genomics to the rescue of a tropical bee threatened by habitat loss and climate change.

Habitat degradation and climate change are currently threatening wild pollinators, compromising their ability to provide pollination services to wild and cultivated plants. Landscape genomics offers powerful tools to assess the influence of landscape modifications on genetic diversity and functional connectivity, and to identify adaptations to local environmental conditions that could facilitate future bee survival. Here, we assessed range-wide patterns of genetic structure, genetic diversity, gene flow, and local adaptation in the stingless bee a tropical pollinator of key biological and economic importance inhabiting one of the driest and hottest regions of South America.

A metagenomic survey of soil microbial communities along a rehabilitation chronosequence after iron ore mining.

Microorganisms are useful environmental indicators, able to deliver essential insights to processes regarding mine land rehabilitation. To compare microbial communities from a chronosequence of mine land rehabilitation to pre-disturbance levels from references sites covered by native vegetation, we sampled non-rehabilitated, rehabilitating and reference study sites from the Urucum Massif, Southwestern Brazil. From each study site, three composed soil samples were collected for chemical, physical, and metagenomics analysis.

Influence of water quality on diversity and composition of fungal communities in a tropical river.

Freshwater fungi are key decomposers of organic material and play important roles in nutrient cycling, bio-remediation and ecosystem functioning. Although aquatic fungal communities respond to pollution, few studies have quantitatively assessed the effect of freshwater contamination on fungal diversity and composition; and knowledge is scarcer for tropical systems. Here we help fill this knowledge gap by studying a heavily-contaminated South American river spanning a biodiversity hotspot.

Machine learning meets genome assembly.

Motivation: With the recent advances in DNA sequencing technologies, the study of the genetic composition of living organisms has become more accessible for researchers. Several advances have been achieved because of it, especially in the health sciences. However, many challenges which emerge from the complexity of sequencing projects remain unsolved.

PIPEBAR and OverlapPER: tools for a fast and accurate DNA barcoding analysis and paired-end assembly.

Background: Taxonomic identification of plants and insects is a hard process that demands expert taxonomists and time, and it's often difficult to distinguish on morphology only. DNA barcodes allow a rapid species discovery and identification and have been widely used for taxonomic identification by targeting known gene regions that permit to discriminate these species. DNA barcode sequence analysis is usually carried out with processes and tools that still demand a high interaction with the user or researcher.

Quillworts from the Amazon: A multidisciplinary populational study on Isoetes serracarajensis and Isoetes cangae.

Isoetes are ancient quillworts members of the only genus of the order Isoetales. The genus is slow evolving but is resilient, and widespread worldwide. Two recently described species occur in the Eastern Brazilian Amazon, Isoetes serracarajensis and Isoetes cangae.

Landscape Genomic Conservation Assessment of a Narrow-Endemic and a Widespread Morning Glory From Amazonian Savannas.

Although genetic diversity ultimately determines the ability of organisms to adapt to environmental changes, conservation assessments like the widely used International Union for Conservation of Nature (IUCN) Red List Criteria do not explicitly consider genetic information. Including a genetic dimension into the IUCN Red List Criteria would greatly enhance conservation efforts, because the demographic parameters traditionally considered are poor predictors of the evolutionary resilience of natural populations to global change. Here we perform the first genomic assessment of genetic diversity, gene flow, and patterns of local adaptation in tropical plant species belonging to different IUCN Red List Categories.

New chimeric RNAs in acute myeloid leukemia.

High-throughput next generation sequencing (NGS) technologies enable the detection of biomarkers used for tumor classification, disease monitoring and cancer therapy. Whole-transcriptome analysis using RNA-seq is important, not only as a means of understanding the mechanisms responsible for complex diseases but also to efficiently identify novel genes/exons, splice isoforms, RNA editing, allele-specific mutations, differential gene expression and fusion-transcripts or chimeric RNA (chRNA). We used Crac, a tool that uses genomic locations and local coverage to classify biological events and directly infer splice and chimeric junctions within a single read.

Differential accumulation of proteins in oil palms affected by fatal yellowing disease.

There is still no consensus on the true origin of fatal yellowing, one of the most important diseases affecting oil palm (Elaeis guineensis Jacq.) plantations. This study involved two-dimensional liquid chromatography coupled with tandem mass spectrometry (2D-UPLC-MSE) analyses to identify changes in protein profiles of oil palms affected by FY disease.

On the evaluation of the fidelity of supervised classifiers in the prediction of chimeric RNAs.

Background: High-throughput sequencing technology and bioinformatics have identified chimeric RNAs (chRNAs), raising the possibility of chRNAs expressing particularly in diseases can be used as potential biomarkers in both diagnosis and prognosis.

Results: The task of discriminating true chRNAs from the false ones poses an interesting Machine Learning (ML) challenge. First of all, the sequencing data may contain false reads due to technical artifacts and during the analysis process, bioinformatics tools may generate false positives due to methodological biases.

Tally: a scoring tool for boundary determination between repetitive and non-repetitive protein sequences.

Motivation: Tandem Repeats (TRs) are abundant in proteins, having a variety of fundamental functions. In many cases, evolution has blurred their repetitive patterns. This leads to the problem of distinguishing between sequences that contain highly imperfect TRs, and the sequences without TRs.

A visual-analytics system for railway safety management.

The working environment of railways is challenging and complex and often involves high-risk operations. These operations affect both the company staff and inhabitants of the towns and cities alongside the railway lines. To reduce the employees' and public's exposure to risk, railway companies adopt strategies involving trained safety personnel, advanced forms of technology, and special work processes.