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Record W2764327865 · doi:10.1002/etc.4000

Integrated in silico and in vivo approaches to investigate effects of BDE-99 mediated by the nuclear receptors on developing zebrafish

2017· article· en· W2764327865 on OpenAlexaff
Li Zhang, Yaru Jin, Zhihua Han, Hongling Liu, Laihao Shi, Xiaoxue Hua, Jon A. Doering, Song Tang, John P. Giesy, Hongxia Yu

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsUniversity of Saskatchewan
FundersNational Natural Science Foundation of China
KeywordsIn silicoZebrafishIn vivoComputational biologyReceptorBiologyCell biologyChemistryGeneticsGene

Abstract

fetched live from OpenAlex

Abstract One of the most abundant polybrominated diphenyl ethers (PBDEs) is 2,2′,4,4′,5-pentabromodiphenyl ether (BDE-99), which persists and potentially bioaccumulates in aquatic wildlife. Previous studies in mammals have shown that BDE-99 affects development and disrupts certain endocrine functions through signaling pathways mediated by nuclear receptors. However, fewer studies have investigated the potential of BDE-99 to interact with nuclear receptors in aquatic vertebrates such as fish. In the present study, interactions between BDE-99 and nuclear receptors were investigated by in silico and in vivo approaches. This PBDE was able to dock into the ligand-binding domain of zebrafish aryl hydrocarbon receptor 2 (AhR2) and pregnane X receptor (PXR). It had a significant effect on the transcriptional profiles of genes associated with AhR or PXR. Based on the developed cytoscape of all zebrafish genes, it was also inferred that AhR and PXR could interact via cross-talk. In addition, both the in silico and in vivo approaches found that BDE-99 affected peroxisome proliferator–activated receptor alpha (PPARα), glucocorticoid receptor, and thyroid receptor. Collectively, our results demonstrate for the first time detailed in silico evidence that BDE-99 can bind to and interact with zebrafish AhR and PXR. These findings can be used to elaborate the molecular mechanism of BDE-99 and guide more objective environmental risk assessments. Environ Toxicol Chem 2018;37:780–787. © 2017 SETAC Abstract BDE-99 was drawn by ChemBioDraw (ChemBioOffice 2008, CambridgeSoft, Corp., USA). In the part of “in silico investigations”, the picture of NRs and the interaction between BDE-99 and z-AhR2, z-PXR were generated and captured in PyMol (Version 0.99, open source), and the plot of RMSDs was generated by Origin 8 (OriginLab Corp, Northampton, MA, USA). The pictures of “in vivo investigations” were taken in the State Key Laboratory of Pollution Control and Resource Reuse at School of the Environment of Nanjing University. The panoramic map of signaling pathways was integrated within Cytoscape software v3.1.1 (Cytoscape consortium, San Diego, CA, USA). Morphology effects on embryos/larvae were taken by an inverted stereomicroscope in the State Key Laboratory of Pollution Control and Resource Reuse at School of the Environment of Nanjing University. All pictures were either drawn or taken by the authors of this study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.199
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2017
Admission routes1
Has abstractyes

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