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Record W4308825587 · doi:10.1093/toxsci/kfac120

TCDD alters essential transcriptional regulators of osteogenic differentiation in multipotent mesenchymal stem cells

2022· article· en· W4308825587 on OpenAlexaff
AtLee T. D. Watson, Aldo Carmona Baez, Dereje D. Jima, David M. Reif, Jun Ding, Reade B. Roberts, Seth W. Kullman

Bibliographic record

VenueToxicological Sciences · 2022
Typearticle
Languageen
FieldNeuroscience
TopicNuclear Receptors and Signaling
Canadian institutionsMcGill University Health Centre
FundersNational Institute of Environmental Health Sciences
KeywordsCell biologyMesenchymal stem cellOsteoblastWnt signaling pathwayCellular differentiationTranscriptomeChemistryExtracellular matrixTranscription factorStem cellBiologyRUNX2Gene expressionSignal transductionIn vitroBiochemistryGene

Abstract

fetched live from OpenAlex

Differentiation of multipotent mesenchymal stem cells (MSCs) into bone-forming osteoblasts requires strict coordination of transcriptional pathways. Aryl hydrocarbon receptor ligands, such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), have been shown to alter osteoblast differentiation in vitro and bone formation in multiple developmental in vivo models. The goal of the present study was to establish a global transcriptomic landscape during early, intermediate, and apical stages of osteogenic differentiation in vitro in response to TCDD exposure. Human bone-derived mesenchymal stem cells (hBMSCs) were cultured in growth media (GM), osteogenic differentiation media (ODM), or ODM containing 10 nM TCDD (ODM + TCDD), thus enabling a comparison of the transcriptomic profiles of undifferentiated, differentiated, and differentiated-TCDD-exposed hBMSCs, respectively. In this test system, exposure to TCDD attenuated the differentiation of hBMSCs into osteoblasts as evidenced by reduced alkaline phosphatase activity and mineralization. At various timepoints, we observed altered expression of genes that play a role in the Wnt, fibroblast growth factor, bone morphogenetic protein/transforming growth factor beta developmental pathways, as well as pathways related to extracellular matrix organization and deposition. Reconstruction of gene regulatory networks with the interactive dynamic regulatory event miner (iDREM) analysis revealed modulation of transcription factors (TFs) including POLR3G, NR4A1, RDBP, GTF2B, POU2F2, and ZEB1, which may putatively influence osteoblast differentiation and the requisite deposition and mineralization of bone extracellular matrix. We demonstrate that the combination of RNA-Seq data in conjunction with the iDREM regulatory model captures the transcriptional dynamics underlying MSC differentiation under different conditions in vitro. Model predictions are consistent with existing knowledge and provide a new tool to identify novel pathways and TFs that may facilitate a better understanding of the osteoblast differentiation process, perturbation by exogenous agents, and potential intervention strategies targeting those specific pathways.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.021
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.050
GPT teacher head0.263
Teacher spread0.213 · 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 teacher head, not a consensus.

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

Citations7
Published2022
Admission routes1
Has abstractyes

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