Fatty acid mobilization from adipose tissue is mediated by CD36 posttranslational modifications and intracellular trafficking
Bibliographic record
Abstract
The mechanism controlling long-chain fatty acid (LCFA) mobilization from adipose tissue is not well understood. Here, we investigated how the LCFA transporter CD36 regulates this process. By using tissue-specific KO mouse models, we showed that CD36 in adipocytes and endothelial cells mediated both LCFA deposition into and release from adipose tissue. We demonstrated the role of adipocytic and endothelial CD36 in promoting tumor growth and chemoresistance conferred by adipose tissue-derived LCFAs. We showed that dynamic cysteine S-acylation of CD36 in adipocytes, endothelial cells, and cancer cells mediated intercellular LCFA transport. We demonstrated that lipolysis induction in adipocytes triggered CD36 deacylation and deglycosylation, as well as its dissociation from interacting proteins, prohibitin-1 (PHB) and annexin 2 (ANX2). Our data indicate that lipolysis triggers caveolar endocytosis and translocation of CD36 from the cell membrane to lipid droplets. This study suggests a mechanism for both outside-in and inside-out cellular LCFA transport regulated by CD36 S-acylation and its interactions with PHB and ANX2.
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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".