The interaction of estrogen and CSE/H<sub>2</sub>S pathway in the development of atherosclerosis
Bibliographic record
Abstract
Both estrogen and hydrogen sulfide (H2S) have been shown to inhibit the development of atherosclerosis. We previously reported that cystathionine γ-lyase knockout (CSE-KO) male mice develop atherosclerosis earlier than male wild-type (WT) mice. The present study investigated the interaction of CSE/H2S pathway and estrogen on the development of atherosclerosis in female mice. Plasma estrogen levels were significantly lower in female CSE-KO mice than in female WT mice. NaHS treatment had no effect on plasma estrogen levels in both WT and CSE-KO female mice. After CSE-KO and WT female mice were fed with atherogenic diet for 12 wk, plasma lipid levels were significantly increased and triglyceride levels decreased compared with those of control diet-fed mice. Atherogenic diet induced more atherosclerotic lesion, oxidative stress, intracellular adhesion molecule-1 (ICAM-1), and NF-κB in CSE-KO mice than in WT mice. Estrogen treatment of atherogenic diet-fed WT mice attenuated hypercholesterolemia, oxidative stress, ICAM-1 expression, and NF-κB in WT mice but not in atherogenic diet-fed CSE-KO mice. Furthermore, H2S production in both the liver and vascular tissues was enhanced by estrogen in WT mice but not in CSE-KO mice. It is concluded that the antiatherosclerotic effect of estrogen is mediated by CSE-generated H2S. This study provides new insights into the interaction of H2S and estrogen signaling pathways on the regulation of cardiovascular functions. NEW & NOTEWORTHY Female cystathionine γ-lyase (CSE)-knockout mice have significantly lower plasma estrogen levels and more severe early atherosclerotic lesion than female wild-type mice. H2S production in liver and vascular tissues is enhanced by estrogen via its stimulatory effect on CSE activity. The antiatherosclerotic effect of estrogen is mediated by CSE-generated H2S.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".