Modulation of Estrogen Signaling by the Novel Interaction of Heat Shock Protein 27, a Biomarker for Atherosclerosis, and Estrogen Receptor β
Bibliographic record
Abstract
OBJECTIVE: We sought to discover proteins that associate with estrogen receptor beta (ERbeta) and modulate estrogen signaling. METHODS AND RESULT: Using a yeast 2-hybrid screen, we identified heat shock protein 27 (HSP27) as an ERbeta-associated protein. HSP27 is a recently identified biomarker of atherosclerosis that is secreted at reduced levels from atherosclerotic compared with normal arteries. In vitro protein-binding assays confirmed the specific interaction of HSP27 with ERbeta and not ERalpha. HSP27 expression was absent in coronary arteries with complex atherosclerotic lesions. Interestingly, HSP27 expression was also absent in 60% of coronary arteries from young males and females (27+/-6.5 years) with normal histology or nonobstructive fatty streaks/atheromas. Moreover, the absence of HSP27 in these normal or minimally diseased arteries coincided with the loss of ERbeta expression. Only 35% of arteries showed coexpression of HSP27 and ERbeta. Relative to controls, estradiol-mediated transcription was reduced 20% with overexpression of HSP27 and increased 44% when HSP27 protein levels were reduced with HSP27 siRNA. CONCLUSIONS: HSP27, an ERbeta-associated protein, shows attenuated expression with coronary atherosclerosis and modulates estrogen signaling.
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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".