Navigating in vitro bioactivity data by investigating available resources using model compounds.
Ontology highlight
ABSTRACT:
SUBMITTER: Ilmjarv S
PROVIDER: S-EPMC6488657 | biostudies-literature | 2019 Apr
REPOSITORIES: biostudies-literature
Publications
Navigating in vitro bioactivity data by investigating available resources using model compounds.
Ilmjärv Sten S Augsburger Fiona F Bolleman Jerven Tjalling JT Liechti Robin R Bridge Alan James AJ Sandström Jenny J Jaquet Vincent V Xenarios Ioannis I Krause Karl-Heinz KH
Scientific data 20190429 1
Similar Datasets
Project description:Animal testing alone cannot practically evaluate the health hazard posed by tens of thousands of environmental chemicals. Computational approaches making use of high-throughput experimental data may provide more efficient means to predict chemical toxicity. Here, we use a supervised machine learning strategy to systematically investigate the relative importance of study type, machine learning algorithm, and type of descriptor on predicting in vivo repeat-dose toxicity at the organ-level. A total of 985 compounds were represented using chemical structural descriptors, ToxPrint chemotype descriptors, and bioactivity descriptors from ToxCast in vitro high-throughput screening assays. Using ToxRefDB, a total of 35 target organ outcomes were identified that contained at least 100 chemicals (50 positive and 50 negative). Supervised machine learning was performed using Naïve Bayes, k-nearest neighbor, random forest, classification and regression trees, and support vector classification approaches. Model performance was assessed based on F1 scores using 5-fold cross-validation with balanced bootstrap replicates. Fixed effects modeling showed the variance in F1 scores was explained mostly by target organ outcome, followed by descriptor type, machine learning algorithm, and interactions between these three factors. A combination of bioactivity and chemical structure or chemotype descriptors were the most predictive. Model performance improved with more chemicals (up to a maximum of 24%), and these gains were correlated (ρ = 0.92) with the number of chemicals. Overall, the results demonstrate that a combination of bioactivity and chemical descriptors can accurately predict a range of target organ toxicity outcomes in repeat-dose studies, but specific experimental and methodologic improvements may increase predictivity.
| S-EPMC6172960 | biostudies-literature
Project description:Marine ecosystems are in decline. New transformational changes in governance are urgently required to cope with overfishing, pollution, global changes, and other drivers of degradation. Here we explore social, political, and ecological aspects of a transformation in governance of Chile's coastal marine resources, from 1980 to today. Critical elements in the initial preparatory phase of the transformation were (i) recognition of the depletion of resource stocks, (ii) scientific knowledge on the ecology and resilience of targeted species and their role in ecosystem dynamics, and (iii) demonstration-scale experimental trials, building on smaller-scale scientific experiments, which identified new management pathways. The trials improved cooperation among scientists and fishers, integrating knowledge and establishing trust. Political turbulence and resource stock collapse provided a window of opportunity that triggered the transformation, supported by new enabling legislation. Essential elements to navigate this transformation were the ability to network knowledge from the local level to influence the decision-making processes at the national level, and a preexisting social network of fishers that provided political leverage through a national confederation of artisanal fishing collectives. The resultant governance scheme includes a revolutionary national system of marine tenure that allocates user rights and responsibilities to fisher collectives. Although fine tuning is necessary to build resilience of this new regime, this transformation has improved the sustainability of the interconnected social-ecological system. Our analysis of how this transformation unfolded provides insights into how the Chilean system could be further developed and identifies generalized pathways for improved governance of marine resources around the world.
| S-EPMC2947917 | biostudies-other
Project description:Methods to assess environmental exposure to hazardous chemicals have primarily focused on quantification of individual chemicals, although chemicals often occur in mixtures, presenting challenges to the traditional risk characterization framework. Sampling sites in a defined geographic region provide an opportunity to characterize chemical contaminants, with spatial interpolation as a tool to provide estimates for non-sampled sites. At the same time, the use of in vitro bioactivity measurements has been shown to be informative for rapid risk-based decisions. In this study, we measured in vitro bioactivity in 39 surface soil samples collected immediately after flooding associated with Hurricane Harvey in Texas in a residential area known to be inundated with polycyclic aromatic hydrocarbon (PAH) contaminants. Bioactivity data were from a number of functional and toxicity assays in 5 human cell types, such as induced pluripotent stem cell-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, as well as human umbilical vein endothelial cells. Data on concentrations of PAH in these samples were also available and the combination of data sources offered a unique opportunity to assess the joint spatial variation of PAH components and bioactivity. We found significant evidence of spatial correlation of a subset of PAH contaminants and of cell-based phenotypes. In addition, we show that the cell-based bioactivity data can be used to predict environmental concentrations for several PAH contaminants, as well as overall PAH summaries and cancer risk. This study's impact lies in its demonstration that cell-based profiling can be used for rapid hazard screening of environmental samples by anchoring the bioassays to concentrations of PAH. This work sets the stage for identification of the areas of concern and direct quantitative risk characterization based on bioactivity data, thereby providing an important supplement to traditional individual chemical analyses by shedding light on constituents that may be missed from targeted chemical monitoring.
| S-EPMC7797768 | biostudies-literature
Project description:IntroductionThe field of metabolomics has expanded greatly over the past two decades, both as an experimental science with applications in many areas, as well as in regards to data standards and bioinformatics software tools. The diversity of experimental designs and instrumental technologies used for metabolomics has led to the need for distinct data analysis methods and the development of many software tools.ObjectivesTo compile a comprehensive list of the most widely used freely available software and tools that are used primarily in metabolomics.MethodsThe most widely used tools were selected for inclusion in the review by either ≥ 50 citations on Web of Science (as of 08/09/16) or the use of the tool being reported in the recent Metabolomics Society survey. Tools were then categorised by the type of instrumental data (i.e. LC-MS, GC-MS or NMR) and the functionality (i.e. pre- and post-processing, statistical analysis, workflow and other functions) they are designed for.ResultsA comprehensive list of the most used tools was compiled. Each tool is discussed within the context of its application domain and in relation to comparable tools of the same domain. An extended list including additional tools is available at https://github.com/RASpicer/MetabolomicsTools which is classified and searchable via a simple controlled vocabulary.ConclusionThis review presents the most widely used tools for metabolomics analysis, categorised based on their main functionality. As future work, we suggest a direct comparison of tools' abilities to perform specific data analysis tasks e.g. peak picking.
| S-EPMC5550549 | biostudies-literature
Project description:Recently, there has been a move encouraged by many stakeholders towards generating big, open data in many areas of research. One area where big, open data is particularly valuable is in research relating to complex heterogeneous disorders such as Autism Spectrum Disorder (ASD). The inconsistencies of findings and the great heterogeneity of ASD necessitate the use of big and open data to tackle important challenges such as understanding and defining the heterogeneity and potential subtypes of ASD. To this end, a number of initiatives have been established that aim to develop big and/or open data resources for autism research. In order to provide a useful data reference for autism researchers, a systematic search for ASD data resources was conducted using the Scopus database, the Google search engine, and the pages on 'recommended repositories' by key journals, and the findings were translated into a comprehensive list focused on ASD data. The aim of this review is to systematically search for all available ASD data resources providing the following data types: phenotypic, neuroimaging, human brain connectivity matrices, human brain statistical maps, biospecimens, and ASD participant recruitment. A total of 33 resources were found containing different types of data from varying numbers of participants. Description of the data available from each data resource, and links to each resource is provided. Moreover, key implications are addressed and underrepresented areas of data are identified.
| S-EPMC5237363 | biostudies-literature
Project description:BackgroundUnited States data protection laws vary depending on the data type and its context. Data projects involving social determinants of health often concern different data protection laws, making them difficult to navigate.ObjectiveWe systematically aggregated and assessed useful online resources to help navigate the data-sharing landscape.MethodsWe included publicly available resources that discussed legal data-sharing issues with some health relevance and published between 2010 and 2019. We conducted an iterative search with a common string pattern using a general-purpose search engine that targeted 24 different sectors identified by Data Across Sectors for Health. We scored each online resource for its depth of legal and data-sharing discussions and value for addressing legal barriers.ResultsOut of 3710 total search hits, 2721 unique URLs were reviewed for scope, 322 received full-text review, and 154 were selected for final coding. Legal agreements, consent, and agency guidance were the most widely covered legal topics, with HIPAA (The Health Insurance Portability and Accountability Act), Family Educational Rights and Privacy Act (FERPA), Title 42 of the Code of Federal Regulations Part 2 being the top 3 federal laws discussed. Clinical health care was the most prominent sector with a mention in 73 resources.ConclusionsThis is the first systematic study of publicly available resources on legal data-sharing issues. We found existing gaps where resources covering certain laws or applications may be needed. The volume of resources we found is an indicator that real and perceived legal issues are a substantial barrier to efforts in leveraging data from different sectors to promote health.
| S-EPMC9490527 | biostudies-literature
Project description:Biological control is emerging as a feasible alternative to chemical pesticides in agriculture. Measuring the microbial biocontrol agent (mBCA) populations in the environment is essential for an accurate environmental and health risk assessment and for optimizing the usage of an mBCA-based plant protection product. We hereby show a workflow to obtain a large number of qPCR markers suitable for robust strain-specific quantification. The workflow starts from whole genome sequencing data and consists of four stages: (i) identifying the strain-specific sequences, (ii) designing specific primer/probe sets for qPCR, and (iii) empirically verifying the performance of the assays. The first two stages involve exclusively computer work, but they are intended for researchers with little or no bioinformatic background: Only a knowledge of the BLAST suite tools and work with spreadsheets are required; a familiarity with the Galaxy environment and next-generation sequencing concepts are strongly advised. All bioinformatic work can be implemented using publicly available resources and a regular desktop computer (no matter the operating system) connected to the Internet. The workflow was tested with five bacterial strains from four different genera under development as mBCAs and yielded thousands of candidate markers and a triplex qPCR assay for each candidate mBCA. The qPCR assays were successfully tested in soils of different natures, water from different sources, and with samples from different plant tissues. The mBCA detection limits and population dynamics in the different matrices are similar to those in qPCR assays designed by other means. In summary, a new accessible, cost-effective, and robust workflow to obtain a large number of strain-specific qPCR markers is presented.
| S-EPMC7077341 | biostudies-literature
Project description:Internationally, there are thousands of existing and newly introduced chemicals in commerce, highlighting the ongoing importance of innovative approaches to identify emerging chemicals of concern. For many chemicals, there is a paucity of hazard and exposure data. Thus, there is a crucial need for efficient and robust approaches to address data gaps and support risk-based prioritization. Several studies have demonstrated the utility of in vitro bioactivity data from the ToxCast program in deriving points of departure (PODs). ToxCast contains data for nearly 1,400 endpoints per chemical, and the bioactivity concentrations, indicative of potential adverse outcomes, can be converted to human-equivalent PODs using high-throughput toxicokinetics (HTTK) modeling. However, data gaps need to be addressed for broader application: the limited chemical space of HTTK and quantitative high-throughput screening data. Here we explore the applicability of in silico models to address these data needs. Specifically, we used ADMET predictor for HTTK predictions and a generalized read-across approach to predict ToxCast bioactivity potency. We applied these models to profile 5,801 chemicals on Canada’s Domestic Substances List (DSL). To evaluate the approach’s performance, bioactivity PODs were compared with in vivo results from the EPA Toxicity Values database for 1,042 DSL chemicals. Comparisons demonstrated that the bioactivity PODs, based on ToxCast data or read-across, were conservative for 95% of the chemicals. Comparing bioactivity PODs to human exposure estimates supports the identification of chemicals of potential interest for further work. The bioactivity workflow shows promise as a powerful screening tool to support effective triaging of chemical inventories.
| S-EPMC8973434 | biostudies-literature
Project description:The international tax treaty system is a highly integrated and complex network. In this system, many multinational enterprises (MNEs) explore ways of reducing taxes by choosing optimal detour routes. Treaty abuse by these MNEs causes significant loss of tax revenues for many countries, but there is no systematic way of regulating their actions. However, it may be helpful to find a way of detecting the optimal routes by which MNEs avoid taxes and observe the effects of this behavior. In this paper, we investigate the international tax treaty network system of foreign investment channels based on real data and introduce a novel measure of tax-routing centrality and other centralities via network analysis. Our analysis of tax routing in a multiplex network reveals not only various tax-minimizing routes and their rates, but also new paths which cannot be found by navigating a single network layer. In addition, we identify strongly connected components of the multiplex tax treaty system with minimal tax shopping routes; more than 80 countries are included in this system. This means that there are far more pathways to be observed than can be detected on any given individual single layer. We provide a unified framework for analyzing the international tax treaty system and observing the effects of tax avoidance by MNEs.
| S-EPMC8396775 | biostudies-literature
Project description:BackgroundSince the classic Hopkins and Groom druggable genome review in 2002, there have been a number of publications updating both the hypothetical and successful human drug target statistics. However, listings of research targets that define the area between these two extremes are sparse because of the challenges of collating published information at the necessary scale. We have addressed this by interrogating databases, populated by expert curation, of bioactivity data extracted from patents and journal papers over the last 30 years.ResultsFrom a subset of just over 27,000 documents we have extracted a set of compound-to-target relationships for biochemical in vitro binding-type assay data for 1,736 human proteins and 1,654 gene identifiers. These are linked to 1,671,951 compound records derived from 823,179 unique chemical structures. The distribution showed a compounds-per-target average of 964 with a maximum of 42,869 (Factor Xa). The list includes non-targets, failed targets and cross-screening targets. The top-278 most actively pursued targets cover 90% of the compounds. We further investigated target ranking by determining the number of molecular frameworks and scaffolds. These were compared to the compound counts as alternative measures of chemical diversity on a per-target basis.ConclusionsThe compounds-per-protein listing generated in this work (provided as a supplementary file) represents the major proportion of the human drug target landscape defined by published data. We supplemented the simple ranking by the number of compounds assayed with additional rankings by molecular topology. These showed significant differences and provide complementary assessments of chemical tractability.
| S-EPMC3118229 | biostudies-literature