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Prostaglandin E <sub>2</sub> (PGE <sub>2</sub> ) function in pregnancy – New perspectives for the putatively pro‐quiescent downstream target RGS2

2018· article· en· W3176269412 on OpenAlexaffabout
Daniela Urrego, Stephen Wood, Robert Newton, Donna M. Slater

Bibliographic record

VenueThe FASEB Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicPreterm Birth and Chorioamnionitis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsG protein-coupled receptorMyometriumRGS2Downregulation and upregulationGq alpha subunitCell biologyOxytocin receptorProstaglandinInternal medicineContractilityReceptorEndocrinologyProstaglandin E2 receptorSignal transductionRegulator of G protein signalingFunction (biology)BiologyG proteinUterusGeneMedicineGeneticsGTPase-activating proteinAgonist

Abstract

fetched live from OpenAlex

Background The prostaglandin pathway plays an important, but complex, role in human labour. Targeting this pathway to treat preterm labour is not wholly effective nor fully safe. Developing superior clinical approaches requires further understanding of the mechanisms that govern myometrial function in labour. While PGE 2 is implicated as a pro‐labour mediator, we have previously shown that it can also promote myometrial smooth muscle (MSM) relaxation. Some of these pro‐quiescent effects may result from PGE 2 ‐mediated upregulation of gene expression. Among the genes highly induced by PGE 2 is the regulator of G‐protein signalling 2 (RGS2), which has been shown to selectively turn‐off, G αq ‐coupled, G‐protein coupled receptor (GPCR) signaling. In pregnancy, G αq ‐coupled GPCRs in the MSM, such as the oxytocin receptor, activate uterine contractions in labour in a calcium‐dependent manner. We hypothesize that in the uterus RGS2 can regulate the G αq ‐coupled GPCR signals, that promote contractility giving rise to active labour. By attenuating these signaling pathways, we anticipate that RGS2 promotes quiescence of the uterus and may represent a novel mechanism by which PGE 2 regulates uterine function in pregnancy and labour. This mechanism may be clinically relevant in the management of labour. Objective To investigate the effect of PGE 2 on RGS2 expression, and examine possible roles for RGS2 in attenuating G αq ‐coupled GPCR contractile functions in primary human MSM cells. Methods Primary myometrial smooth muscle cells were isolated from myometrial biopsies from term (37–40 weeks of gestation), non‐labour caesarean section deliveries. Cultured cells were treated with PGE 2 (1 μM) to study effects on RGS2 mRNA and protein expression. The effect of RGS2 on calcium flux stimulated by oxytocin (100 nM) or histamine (1 μM) treatment was studied as a measure of contractility, using a Fluo‐4 calcium assay. Results were analyzed using a one‐way ANOVA (Bonferroni post‐hoc ). Results In MSM cells PGE 2 treatment increased RGS2 mRNA and protein expression. PGE 2 treatment of MSM cells also significantly attenuated G αq ‐coupled GPCR‐stimulated calcium flux response to subsequent treatment with maximally effective concentrations of either oxytocin or histamine. This effect was mimicked by adenoviral overexpression of RGS2, supporting the hypothesis that repression of contraction can be caused by RGS2. Knockdown of PGE2‐induced RGS2 with siRNA in MSM cells is underway to confirm whether RGS2 is indeed responsible for the attenuation of histamine and oxytocin calcium signals that is observed in cells pre‐treated with PGE 2. Conclusion These findings support a pro‐quiescent role of PGE 2 , in part by the protective function of RGS2 attenuating some G αq ‐protein coupled receptor contractile signals. Further investigation is underway to establish to what extent the other aspects of G αq ‐protein coupled receptor signaling that contribute to labour may also be attenuated by RGS2 signals. Support or Funding Information This work is supported by the Canadian Institues for Health Research (CIHR), and DU is funded by an Alberta Innovates Health Solutions (AIHS) MD‐PhD Studentship. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

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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 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 score0.196
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.255
Teacher spread0.236 · 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.

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".

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Citations0
Published2018
Admission routes2
Has abstractyes

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