Transcriptional Regulation of Oxytocin Receptor by Interleukin-1β and Interleukin-6
Bibliographic record
Abstract
The up-regulation of oxytocin (OT) receptors in late pregnancy results principally from increased synthesis of messenger RNA. The 5'-flanking region of the human OT receptor gene contains several putative binding sites for nuclear factor-interleukin-6 (NF-IL6), also known as CAAT/enhancer binding protein-beta. This trans-acting factor modulates the expression of genes involved in acute inflammatory responses. Proinflammatory cytokines, such as IL-1beta or IL-6, have been implicated as mediators in both preterm and term labor, particularly in association with intrauterine infection. We hypothesized that IL-1beta and IL-6 induce OT receptor gene expression in human myometrial cells, and this is mediated by NF-IL6 and cognate response elements in the 5'-flanking region of the OT receptor gene. Contrary to the hypothesis, both IL-1beta and IL-6 treatment resulted in a significant decrease in OT receptor messenger RNA measured by ribonuclease protection analysis. Using electrophoretic mobility shift assay, we have shown that NF-IL6 is present at low levels that appear to be increased after treatment with either IL-1beta or IL-6. Using deletion analysis and functional transfection studies in HeLa cells, we demonstrated that the OT receptor gene promoter displays constitutive basal activity and is negatively regulated by both IL-1beta and IL-6. This suppressive ability of IL-1beta and IL-6 depends on the -1203/-722 region of the OT receptor promoter, which contains binding sites for NF-IL6, acute phase response element, and NF-kappaB. Our findings suggest a role for IL-1beta and IL-6 in the transcriptional regulation of the human OT receptor gene.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".