Faculty Opinions recommendation of Agents blocking the nuclear factor-kappaB pathway are effective inhibitors of endometriosis in an in vivo experimental model.
Bibliographic record
Abstract
BACKGROUND: In vitro studies suggest that the transcription factor nuclear factor-kappa B (NF-kappaB) is implicated in the transduction of proinflammatory signals in endometriosis. The aim of this study was to investigate the involvement of NF-kappaB and the processes regulated by NF-kappaB in the initial development of endometriotic lesionsin vivo.METHODS: Endometriosis was induced in nude mice by intraperitoneal injection of fluorescent-labeled menstrual endometrium. Two NF-kappaB inhibitors (BAY 11-7085 and SN-50) were injected intraperitoneally on days 0, 2 and 4 after endometriosis induction, and endometriotic lesions were recovered on day 5. Number, mass, fluorimetry and surface (morphometry) of endometriotic lesions were quantified. NF-kappaB activation, intercellular adhesion molecule (ICAM)-1 expression, cell proliferation and apoptosis were evaluated by immunohistochemical analyses and the TUNEL method.RESULTS: Both NF-kappaB inhibitors induced a significant reduction in lesion development compared to control mice. NF-kappaB activation and ICAM-1 expression of endometriotic lesions were significantly reduced in treated mice, and cell proliferation was significantly reduced in BAY 11-7085-treated mice. Both inhibitors produced a significant increase in apoptosis of endometriotic lesions, as assessed by active caspase-3 immunostaining and the TUNEL method.CONCLUSION: This study demonstrates, for the first time, that the NF-kappaB pathway is implicated in the development of endometriotic lesions in vivo and that NF-kappaB inhibition reduces ICAM-1 expression and cell proliferation, but increases apoptosis of endometriotic lesions, diminishing the initial development of endometriosis in an animal model. PMID: 18025832
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.212 | 0.101 |
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".