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- Mansouri, Kamel, et al.
(författare)
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CoMPARA : Collaborative Modeling Project for Androgen Receptor Activity
- 2020
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Ingår i: Journal of Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 128:2, s. 1-17
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling.OBJECTIVES: In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP).METHODS: The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast (TM) metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast (TM)/Tox21 HTS in vitro assays.RESULTS: The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set.DISCUSSION: The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of similar to 875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment.
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| 2. |
- Stephan, Astrid, et al.
(författare)
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Barriers and facilitators to the access to and use of formal dementia care : findings of a focus group study with people with dementia, informal carers and health and social care professionals in eight European countries
- 2018
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Ingår i: BMC Geriatrics. - : BioMed Central. - 1471-2318. ; 18:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: People with dementia and informal carers often access formal care late in the process of dementia. The barriers and facilitators to service use from the perspectives of different stakeholders involved are not well understood. Thus, we aimed to explore the barriers and facilitators of access to and utilisation of formal care from the perspectives of people with dementia, their informal carers and health and social care professionals.METHOD: Focus groups with people with dementia, informal carers and professionals were conducted in eight European countries. Recruitment targeted people with dementia, informal carers with experience of formal care and professionals involved in providing (access to) formal care. Qualitative content analysis using open coding was used on a national level. Cross-national synthesis was based on the translated national reports.RESULTS: Overall, 55 focus groups with 261 participants were conducted, involving 51 people with dementia, 96 informal carers and 114 professionals. Sixteen categories describing barriers and facilitators were identified, referring to three global themes: Aspects related to 1) individuals involved, 2) the system or 3) overarching aspects. The attitudes and beliefs of people with dementia and their carers may have a major impact, and they often serve as barriers. Formal care was perceived as a threat to the individual independence of people with dementia and was thus avoided as long as possible. A healthcare professional serving as a constant key contact person could be an essential facilitator to overcome these barriers. Contact should be initiated proactively, as early as possible, and a trusting and consistent relationship needs to be established. Beyond that, the findings largely confirm former research and show that barriers to accessing and using formal care still exist across Europe despite a number of national and European initiatives.CONCLUSION: Further investigations are needed to elaborate how the concept of a key contact person could be integrated with existing case management approaches and how the independence and autonomy of people with dementia can be strengthened when formal care needs to be accessed and used. These may be meaningful facilitators regarding enhanced access to formal care for people with dementia and their families.
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| 4. |
- Mansouri, Kamel, et al.
(författare)
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CERAPP : Collaborative Estrogen Receptor Activity Prediction Project
- 2016
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Ingår i: Journal of Environmental Health Perspectives. - : Environmental Health Perspectives. - 0091-6765 .- 1552-9924. ; 124:7, s. 1023-1033
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Humans are exposed to thousands of man-made chemicals in the environment. Some chemicals mimic natural endocrine hormones and, thus, have the potential to be endocrine disruptors. Most of these chemicals have never been tested for their ability to interact with the estrogen receptor (ER). Risk assessors need tools to prioritize chemicals for evaluation in costly in vivo tests, for instance, within the U.S. EPA Endocrine Disruptor Screening Program. OBJECTIVES: We describe a large-scale modeling project called CERAPP (Collaborative Estrogen Receptor Activity Prediction Project) and demonstrate the efficacy of using predictive computational models trained on high-throughput screening data to evaluate thousands of chemicals for ER-related activity and prioritize them for further testing. METHODS: CERAPP combined multiple models developed in collaboration with 17 groups in the United States and Europe to predict ER activity of a common set of 32,464 chemical structures. Quantitative structure-activity relationship models and docking approaches were employed, mostly using a common training set of 1,677 chemical structures provided by the U.S. EPA, to build a total of 40 categorical and 8 continuous models for binding, agonist, and antagonist ER activity. All predictions were evaluated on a set of 7,522 chemicals curated from the literature. To overcome the limitations of single models, a consensus was built by weighting models on scores based on their evaluated accuracies. RESULTS: Individual model scores ranged from 0.69 to 0.85, showing high prediction reliabilities. Out of the 32,464 chemicals, the consensus model predicted 4,001 chemicals (12.3%) as high priority actives and 6,742 potential actives (20.8%) to be considered for further testing.CONCLUSION: This project demonstrated the possibility to screen large libraries of chemicals using a consensus of different in silico approaches. This concept will be applied in future projects related to other end points.
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