Modulatory effects of estrogen in two murine models of experimental colitis
Bibliographic record
Abstract
The association between oral contraceptives or pregnancy and inflammatory bowel disease is unclear. We investigated whether 17beta-estradiol modulates intestinal inflammation in two models of colitis. Female mice were treated with 17beta-estradiol alone or with tamoxifen, tamoxifen alone, 17 alpha-estradiol, or placebo. Dinitrobenzene sulfonic acid (DNB)- or dextran sodium sulfate (DSS)-induced colitis were assessed macroscopically, histologically, and by myeloperoxidase (MPO) activity. Malondialdehyde and mRNA levels of intercellular adhesion molecule-1 (ICAM-1), interferon-gamma (IFN-gamma), and interleukin-13 (IL-13) were determined. In DNB colitis, 17beta-estradiol alone, but not 17beta-estradiol plus tamoxifen, or 17 alpha-estradiol reduced macroscopic and histological scores, MPO activity and malondialdehyde levels. 17beta-Estradiol also decreased the expression of ICAM-1, IFN-gamma, and IL-13 mRNA levels compared with placebo. In contrast, 17beta-Estradiol increased the macroscopic and histological scores compared with placebo in mice with DSS colitis. These results demonstrate anti-inflammatory and proinflammatory effects of 17beta-estradiol in two different models of experimental colitis. The net modulatory effect most likely reflects a combination of estrogen receptor-mediated effects and antioxidant activity and may explain, in part, conflicting results from clinical trials.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".