Impacts of linseed meal and estradiol-17β on cellularity, angiogenic and vasoactive factor mRNA expression, and vascularity of the uterus in ovariectomized ewes
Bibliographic record
Abstract
Ilse, B. R., O'Neil, M. R., Lardy, G. P., Reynolds, L. P. and Vonnahme, K. A. 2012. Impacts of linseed meal and estradiol-17β on cellularity, angiogenic and vasoactive factor mRNA expression, and vascularity of the uterus in ovariectomized ewes. Can. J. Anim. Sci. 92: 297–306. The objective of the current study was to determine the estrogenic potential of the phytoestrogen secoisolariciresinol diglycoside (SDG) found in linseed meal (LSM) on uterine cell proliferation, vascularity, and angiogenic factor mRNA expression. Ovariectomized ewes (n=48) were fed a diet containing 12.5% LSM for 0, 1, 7, or 14 d and implanted with estradiol-17β (E2) for 0, 6, or 24 h before tissue collection. There was an interaction of LSM×E2 on uterine mass (grams; P=0.03; percentage change; P<0.003). Uterine mass increased (P≤0.02) after 24 h of E2 exposure on days 1, 7, and 14 of LSM feeding, with the greatest mass occurring in ewes exposed to E2 for 24 h and 1 d LSM feeding. Regardless of days fed LSM, after 24 h of E2 exposure uterine mass was greatest. The greatest percentage increase in uterine mass occurred in ewes exposed to E2 for 24 h and fed 1 d of LSM. Cell proliferation within the uterine luminal epithelium was greatest (P<0.01) with 24 h of E2 exposure compared with 0 h and 6 h. When expressed as the percentage change in uterine cell proliferation, feeding LSM for 14 d negated these effects. Only length of E2 exposure impacted vascularity with capillary number density at 6 h of E2 exposure being greater (P=0.02) than at 24 h. While mRNA expression of several angiogenic factors was influenced by E2, there was a LSM×E2 interaction (P≤0.03) only on vascular endothelial growth factor receptor 2 and fibroblast growth factor receptor 2C. It appears that growth and angiogenesis of E2 sensitive tissues may be influenced by the duration of LSM feeding.
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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".