Atheroprotective and atheroregressive potential of azapeptide derivatives of GHRP-6 as selective CD36 ligands in apolipoprotein E-deficient mice
Bibliographic record
Abstract
Background and aimsScavenger receptor class B member 3, also known as cluster of differentiation-36 (CD36) receptor, is involved in the uptake and accumulation of modified lipoprotein in macrophages, driving atherosclerosis progression. Azapeptide analogs of growth hormone-releasing peptide-6 (GHRP-6) have been developed as selective CD36 ligands and evaluated for their anti-atherosclerotic properties in apoe−/− mice.MethodsFrom 4 to 19 weeks of age, male apoe−/− mice were fed a high fat high cholesterol (HFHC) diet, then switched to normal chow and treated daily with 300 nmol/kg of MPE-001 ([aza-Tyr4]-GHRP-6) or MPE-003 ([aza-(N,N-diallylaminobut-2-ynyl)Gly4]-GHRP-6) for 9 weeks. In another protocol, mice were fed a HFHC diet throughout the study.ResultsAzapeptides decreased lesion progression in the aortic arch and reduced aortic sinus lesion areas below pre-existing lesions levels in apoe−/− mice which were switched to chow diet. In mice fed a HFHC throughout the study, azapeptides reduced lesion progression in the aortic vessel and sinus. The anti-atherosclerotic effect of azapeptides was associated with a reduced ratio of iNOS+/CD206+ macrophages within lesions, and lowered plasma inflammatory cytokine levels. Monocytes from azapeptide-treated mice showed altered mitochondrial oxygen consumption rates, consistent with an M2-like phenotype. These effects were dependent on CD36, and not observed in apoe−/−cd36−/− mice.ConclusionsAzapeptides MPE-001 and MPE-003 diminished aortic lesion progression and reduced, below pre-existing levels, lesions in the aortic sinus of atherosclerotic mice. A relative increase of M2-like macrophages was observed in lesions, associated with reduced systemic inflammation. Development of CD36-selective azapeptide ligands merits consideration for treating atherosclerotic disease.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".