A synopsis of knowledge, zoogeography and an online interactive map of Brazilian marine gastrotrichs.
Ontology highlight
ABSTRACT:
SUBMITTER: Campos A
PROVIDER: S-EPMC6802584 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
Publications
A synopsis of knowledge, zoogeography and an online interactive map of Brazilian marine gastrotrichs.
Campos Ariane A Garraffoni André Rinaldo Senna ARS
PeerJ 20191018
Information regarding the records of Brazilian marine gastrotrichs is presented. We systematized and organized the existing information associated with approximately 23 species (belonging to the genera <i>Aspidiophorus</i>, <i>Chaetonotus</i>, <i>Crasiella</i>, <i>Dactylopodola</i>, <i>Dendrodasys</i>, <i>Draculiciteria</i>, <i>Halichaetonotus</i>, <i>Heteroxenotrichula</i>, <i>Kryptodasys</i>, <i>Macrodasys</i>, <i>Pseudostomella</i>, <i>Ptychostomella</i>, <i>Urodasys</i> and <i>Xenotrichula</ ...[more]
Similar Datasets
Project description:Rheumatoid arthritis (RA) is a progressive, inflammatory autoimmune disease of unknown aetiology. The complex mechanism of aetiopathogenesis, progress and chronicity of the disease involves genetic, epigenetic and environmental factors. To understand the molecular mechanisms underlying disease phenotypes, one has to place implicated factors in their functional context. However, integration and organization of such data in a systematic manner remains a challenging task. Molecular maps are widely used in biology to provide a useful and intuitive way of depicting a variety of biological processes and disease mechanisms. Recent large-scale collaborative efforts such as the Disease Maps Project demonstrate the utility of such maps as versatile tools to organize and formalize disease-specific knowledge in a comprehensive way, both human and machine-readable. We present a systematic effort to construct a fully annotated, expert validated, state-of-the-art knowledge base for RA in the form of a molecular map. The RA map illustrates molecular and signalling pathways implicated in the disease. Signal transduction is depicted from receptors to the nucleus using the Systems Biology Graphical Notation (SBGN) standard representation. High-quality manual curation, use of only human-specific studies and focus on small-scale experiments aim to limit false positives in the map. The state-of-the-art molecular map for RA, using information from 353 peer-reviewed scientific publications, comprises 506 species, 446 reactions and 8 phenotypes. The species in the map are classified to 303 proteins, 61 complexes, 106 genes, 106 RNA entities, 2 ions and 7 simple molecules. The RA map is available online at ramap.elixir-luxembourg.org as an open-access knowledge base allowing for easy navigation and search of molecular pathways implicated in the disease. Furthermore, the RA map can serve as a template for omics data visualization.
| S-EPMC7170216 | biostudies-literature
Project description:Online labor markets provide new opportunities for behavioral research, but conducting economic experiments online raises important methodological challenges. This particularly holds for interactive designs. In this paper, we provide a methodological discussion of the similarities and differences between interactive experiments conducted in the laboratory and online. To this end, we conduct a repeated public goods experiment with and without punishment using samples from the laboratory and the online platform Amazon Mechanical Turk. We chose to replicate this experiment because it is long and logistically complex. It therefore provides a good case study for discussing the methodological and practical challenges of online interactive experimentation. We find that basic behavioral patterns of cooperation and punishment in the laboratory are replicable online. The most important challenge of online interactive experiments is participant dropout. We discuss measures for reducing dropout and show that, for our case study, dropouts are exogenous to the experiment. We conclude that data quality for interactive experiments via the Internet is adequate and reliable, making online interactive experimentation a potentially valuable complement to laboratory studies.
| S-EPMC5807491 | biostudies-literature
Project description:BackgroundUnderstanding respiratory physiology and mechanical ventilation is a challenge for healthcare workers, particularly, medical residents. A team of French-speaking experts developed an innovative MOOC incorporating interactive simulation-based videos and serious games aiming at improving knowledge and skills in mechanical ventilation. Our objective was to evaluate the long-term knowledge retention regarding key concepts presented in this MOOC.MethodsFrench residents registered for the MOOC 2020's winter session were invited to participate in a two-step study. The first step consisted in evaluating students' pre-course knowledge of respiratory physiology and mechanical ventilation fusing a 20 five-item multiple choice questions test with a total score ranging from 0 to 100. For the second step, the same students answered the same test (after shuffling the questions) six months after the completion of the course. We assessed the impact of this MOOC on the students' knowledge retention by comparing pre-course and post-course scores.ResultOf the 102 residents who agreed to participate in the study, 80 completed the course and their mean ± SD pre-course score was 76.0 ± 8.0. Fifty-one respondents also completed the second and their post-course score was significantly higher than the baseline one (83.1 ± 7.3 vs. 77.5 ± 7.6, p < 0.001). Scores of the first and second rounds did not differ upon comparing respondents' background specialty or number of years of residency. For the vast majority of individual questions (96%), the success rate was higher at the post-course than at the pre-course assessment.ConclusionAn innovative MOOC incorporating simulation-based videos was effective in teaching medical residents basic mechanical ventilation knowledge and skills, especially in the field of respiratory physiology and ventilatory modes. We observed effective long-term knowledge retention with a higher score at the post-course assessment six months after the completion of the course compared with the pre-course score.
| S-EPMC8635324 | biostudies-literature
Project description:BackgroundCancer cells are characterized by massive dysegulation of physiological cell functions with considerable disruption of transcriptional regulation. Genome-wide transcriptome profiling can be utilized for early detection and molecular classification of cancers. Accurate discrimination of functionally different tumor types may help to guide selection of targeted therapy in translational research. Concise grouping of tumor types in cancer maps according to their molecular profile may further be helpful for the development of new therapeutic modalities or open new avenues for already established therapies.MethodsComplete available human tumor data of the Stanford Microarray Database was downloaded and filtered for relevance, adequacy and reliability. A total of 649 tumor samples from more than 1400 experiments and 58 different tissues were analyzed. Next, a method to score deregulation of KEGG pathway maps in different tumor entities was established, which was then used to convert hundreds of gene expression profiles into corresponding tumor-specific pathway activity profiles. Based on the latter, we defined a measure for functional similarity between tumor entities, which yielded to phylogeny of tumors.ResultsWe provide a comprehensive, easy-to-interpret functional cancer map that characterizes tumor types with respect to their biological and functional behavior. Consistently, multiple pathways commonly associated with tumor progression were revealed as common features in the majority of the tumors. However, several pathways previously not linked to carcinogenesis were identified in multiple cancers suggesting an essential role of these pathways in cancer biology. Among these pathways were 'ECM-receptor interaction', 'Complement and Coagulation cascades', and 'PPAR signaling pathway'.ConclusionThe functional cancer map provides a systematic view on molecular similarities across different cancers by comparing tumors on the level of pathway activity. This work resulted in identification of novel superimposed functional pathways potentially linked to cancer biology. Therefore, our work may serve as a starting point for rationalizing combination of tumor therapeutics as well as for expanding the application of well-established targeted tumor therapies.
| S-EPMC3148554 | biostudies-literature
Project description:This study revises centipede fauna found in Brazilian caves, focusing on troglomorphic taxa and emphasizing conservation status. We present 563 centipede specimens from 274 caves across eleven Brazilian states. Of these, 22 records were derived from existing literature and 252 are newly collected. Specimens represent four orders, ten families, 18 genera, and 47 morphospecies. Together, the cave records represent 21 % of Brazil's centipede fauna. Scolopendromorpha was the most representative order (41 %), followed by Geophilomorpha (26 %), Scutigeromorpha (23 %), and Lithobiomorpha (10 %). Six species were found only in caves, with four considered troglobitic. The distribution of Cryptops iporangensis, the first Brazilian troglobitic centipede species to be discovered, was expanded to other three caves. Cryptops spelaeoraptor and Cryptops iporangensis are two troglobitic species considered Vulnerable and Endangered, respectively, according to the IUCN Red List. Main threats to Brazilian caves are mining, hydroelectric projects, water pollution, and unregulated tourism.
| S-EPMC5904458 | biostudies-literature
Project description:We compiled the records for the genus Salvatoria from Brazilian coastal and oceanic habitats, collected by several projects along the years. Here we present 12 species, eight of which already reported-S. breviarticulata comb. nov., S. clavata, S. euritmica, S. heterocirra, S. limbata, S. longiarticulata comb. nov., S. neapolitana and S. cf. nitidula-with comments regarding the confidence of some of these records. We also describe three new species, S. marielleae n. sp. and Salvatoria nitiduloides n. sp., based on material from Fernando de Noronha and Trindade islands, off the Northeastern Brazilian coast, and S. ypsiloides n. sp., from Fernando de Noronha and also, Campos Basin, off Southeastern Brazilian coast, in depths down to 970 m. Finally, we report a probably undescribed species, Salvatoria sp., represented by only one specimen lacking median antenna, preventing us to proceed with further identification properly. A dichotomous identification key and a comparative table with morphological data of specimens belonging to these species are also provided.
| S-EPMC8099080 | biostudies-literature
Project description:Transcriptome sequencing has opened the field of genomics to a wide variety of researchers, owing to its efficiency, applicability across species and ability to quantify gene expression. The resulting datasets are a rich source of information that can be mined for many years into the future, with each dataset providing a unique angle on a specific context in biology. Maintaining accessibility to this accumulation of data presents quite a challenge for researchers.The primary focus of conventional genomics databases is the storage, navigation and interpretation of sequence data, which is typically classified down to the level of a species or individual. The addition of expression data adds a new dimension to this paradigm - the sampling context. Does gene expression describe different tissues, a temporal distribution or an experimental treatment? These data not only describe an individual, but the biological context surrounding that individual. The structure and utility of a transcriptome database must therefore reflect these attributes. We present an online database which has been designed to maximise the accessibility of crustacean transcriptome data by providing intuitive navigation within and between datasets and instant visualization of gene expression and protein structure.The site is accessible at https://crustybase.org and currently holds 10 datasets from a range of crustacean species. It also allows for upload of novel transcriptome datasets through a simple web interface, allowing the research community to contribute their own data to a pool of shared knowledge.
| S-EPMC7490944 | biostudies-literature
Project description:Knowledge representation has gained in relevance as data from the ubiquitous digitization of behaviors amass and academia and industry seek methods to understand and reason about the information they encode. Success in this pursuit has emerged with data from natural language, where skip-grams and other linear connectionist models of distributed representation have surfaced scrutable relational structures which have also served as artifacts of anthropological interest. Natural language is, however, only a fraction of the big data deluge. Here we show that latent semantic structure can be informed by behavioral data and that domain knowledge can be extracted from this structure through visualization and a novel mapping of the text descriptions of elements onto this behaviorally informed representation. In this study, we use the course enrollment histories of 124,000 students at a public university to learn vector representations of its courses. From these course selection informed representations, a notable 88% of course attribute information was recovered, as well as 40% of course relationships constructed from prior domain knowledge and evaluated by analogy (e.g., Math 1B is to Honors Math 1B as Physics 7B is to Honors Physics 7B). To aid in interpretation of the learned structure, we create a semantic interpolation, translating course vectors to a bag-of-words of their respective catalog descriptions via regression. We find that representations learned from enrollment histories resolved courses to a level of semantic fidelity exceeding that of their catalog descriptions, revealing nuanced content differences between similar courses, as well as accurately describing departments the dataset had no course descriptions for. We end with a discussion of the possible mechanisms by which this semantic structure may be informed and implications for the nascent research and practice of data science.
| S-EPMC7526902 | biostudies-literature
Project description:The Changing Talk intervention improves nursing home staff communication by reducing elderspeak. To facilitate dissemination, interactive online modules were created, maintaining the original content. This article reports on the process of transitioning and the results of pilot testing the modules.Interactive online modules were developed, pilot tested, and the evaluated in comparison to outcomes from the classroom format training.Online participants (N = 9) demonstrated pre to posttest knowledge gain (scores improved from M = 82.4% to M = 91.2%). Rating of a staff-resident interaction showed improved recognition of elderspeak and person-centered communication after training. Online and original participants reported similar intentions to use learned skills and rated the program highly.Evidence-based interventions can be translated from traditional classroom to online format maintaining effects on increasing staff knowledge and intentions to use learned skills in practice. However, the modules should be tested in a larger and more representative sample. J Contin Educ Nurs. 2017;48(7):320-328.
| S-EPMC5492957 | biostudies-literature
Project description:MotivationWhat if you could explain complex chemistry in a simple tree and share that data online with your collaborators? Computational biology often incorporates diverse chemical data to probe a biological question, but the existing tools for chemical data are ill-suited for the very large datasets inherent to bioinformatics. Furthermore, existing visualization methods often require an expert chemist to interpret the patterns. Biologists need an interactive tool for visualizing chemical information in an intuitive, accessible way that facilitates its integration into today's team-based biological research.ResultsChemTreeMap is an interactive, bioinformatics tool designed to explore chemical space and mine the relationships between chemical structure, molecular properties, and biological activity. ChemTreeMap synergistically combines extended connectivity fingerprints and a neighbor-joining algorithm to produce a hierarchical tree with branch lengths proportional to molecular similarity. Compound properties are shown by leaf color, size and outline to yield a user-defined visualization of the tree. Two representative analyses are included to demonstrate ChemTreeMap's capabilities and utility: assessing dataset overlap and mining structure-activity relationships.Availability and implementationThe examples from this paper may be accessed at http://ajing.github.io/ChemTreeMap/ Code for the server and client are available in the Supplementary Information, at the aforementioned github site, and on Docker Hub (https://hub.docker.com) with the nametag ajing/chemtreemap.Contactcarlsonh@umich.eduSupplementary information: Supplementary data are available at Bioinformatics online.
| S-EPMC5181537 | biostudies-literature