Expression of small heat shock-related protein 20 (HSP20) in rat myometrium is markedly decreased during late pregnancy and labour
Bibliographic record
Abstract
The underlying mechanisms regulating uterine contractions during labour are still poorly understood. Heat shock protein 20 (HSP20) is known to be present at high levels in smooth muscle and implicated in muscle relaxation, but HSP20 expression in the myometrium is completely undetermined. Since HSP20 has been implicated in smooth muscle relaxation, we hypothesized that HSP20 would be highly expressed in the rat myometrium during early and mid-pregnancy when the myometrium is relatively quiescent. Northern blot analysis particularly demonstrated that HSP20 mRNA detection was significantly decreased from day (d) 22 of pregnancy to 1-day post-partum (PP) compared with d6 (P < 0.05). HSP20 mRNA detection was also significantly decreased from d22 to d23 of gestation compared with non-pregnant (NP) samples. Immunoblot analysis showed that detection of HSP20 was significantly decreased at d23 compared with d12 and d15 (P < 0.05). HSP20 detection also significantly decreased at PP compared with d15 (P < 0.05). Immunofluorescence analysis demonstrated that after d15, plasma membrane-associated localization of HSP20 decreased markedly in both circular and longitudinal muscle layers. In addition, HSP20 was detectable near cell membranes at much higher levels in the longitudinal muscle layer of progesterone-treated pregnant rats (delayed labour) at all gestational time points examined, compared with controls. Our results demonstrate that HSP20 mRNA and protein are highly expressed during early and mid-pregnancy and then the expression markedly decreases during late pregnancy and labour. The observed patterns of HSP20 expression are consistent with a potential role for HSP20 in facilitating myometrium quiescence during early and mid-pregnancy.
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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".