A Growth Hormone-Releasing Peptide Promotes Mitochondrial Biogenesis and a Fat Burning-Like Phenotype through Scavenger Receptor CD36 in White Adipocytes
Bibliographic record
Abstract
Whereas the uptake of oxidized lipoproteins by scavenger receptor CD36 in macrophages has been associated with foam cell formation and atherogenesis, little is known about the role of CD36 in regulating lipid metabolism in adipocytes. Here we report that treatment of 3T3-L1 adipocytes with hexarelin, a GH-releasing peptide that interacts with CD36, resulted in a depletion of intracellular lipid content with no significant change in CD36 expression. Microarray analysis revealed an increased pattern in several genes involved in fatty acid mobilization toward the mitochondrial oxidative phosphorylation process in response to hexarelin. Interestingly, many of these up-regulated genes are known targets of peroxisomal proliferator-activated receptor (PPAR)-gamma, such as FATP, CPT-1, and F(1)-ATPase, suggesting that adipocyte response to hexarelin may involve PPARgamma activation. Expression studies also indicate an increase in thermogenic markers PPARgamma coactivator 1alpha and uncoupling protein-1, which are normally expressed in brown adipocytes. Electron microscopy of hexarelin-treated 3T3-L1 adipocytes showed an intense and highly organized cristae formation that spans the entire width of mitochondria, compared with untreated cells, and cytochrome c oxidase activity was enhanced by hexarelin, two features characteristic of highly oxidative tissues. A similar mitochondrial phenotype was detected in epididymal white fat of mice treated with hexarelin, along with an increased expression of thermogenic markers that was lost in treated CD36-null mice, suggesting that the ability of hexarelin to promote a brown fat-like phenotype also occurs in vivo and is dependent on CD36. These results provide a potential role for CD36 to impact the overall metabolic activity of fat usage and mitochondrial biogenesis in adipocytes.
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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 | 0.001 |
| 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".