Transcriptomic and Lipidomic Analyses Reveal a Novel Antiapoptotic Mechanism of Peptide IRW in the Arteries of Spontaneously Hypertensive Rats through the Reduction of Ceramide Levels and Arachidonic Acid Release
Bibliographic record
Abstract
IRW, an antihypertensive peptide derived from ovotransferrin, has been shown to lower blood pressure in spontaneously hypertensive rats (SHRs) by upregulating angiotensin-converting enzyme 2 (ACE2). ACE2 is cardioprotective and a well-documented inhibitor of apoptosis. This study aims to investigate the anti-apoptotic effects of IRW and its underlying mechanism in SHRs’ vasculature. IRW was orally administered to SHRs at 15 mg/kg body weight. Transcriptomic analysis of mesenteric arteries revealed enrichment of genes involved in apoptosis suppression by IRW; proteins associated with pro-apoptotic effects, including cytosolic cytochrome c, Bax, caspase-3, and caspase-9, as well as cathepsin B and D, were reduced, whereas the X-linked inhibitor of apoptosis was significantly increased. Lipidomic analysis revealed a notable decrease in mesenteric arterial ceramides (0.040 ± 0.0027% of total lipids) after IRW treatment, likely due to the downregulation of sphingomyelinase and the upregulation of ceramidase, two key enzymes, respectively, responsible for the production and degradation of ceramides. This reduction, along with the IRW-mediated inhibition of arachidonic acid release from membrane phospholipids, contributed to reduced apoptosis. While IRW inhibited the metabolism of released arachidonic acid, some anti-apoptotic oxylipins (prostaglandin E 2 and 5-hydroxyeicosatetraenoic acid) were enhanced. These findings highlight IRW’s potential as a modulator of vascular cell survival through multiple antiapoptotic pathways.
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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".