The subcellular compartmentation of fatty acid transporters is regulated differently by insulin and by AICAR
Bibliographic record
Abstract
Cellular fatty acid uptake is facilitated by a number of fatty acid transporters, FAT/CD36, FABPpm and FATP1. It had been presumed that FABPpm, was confined to the plasma membrane and was not regulated. Here, we demonstrate for the first time that FABPpm and FATP1 are also present in intracellular depots in cardiac myocytes. While we confirmed previous work that insulin and AICAR each induced the translocation of FAT/CD36 from an intracellular depot to the PM, only AICAR, but not insulin, induced the translocation of FABPpm. Moreover, neither insulin nor AICAR induced the translocation of FATP1. Importantly, the increased plasmalemmal content of these LCFA transporters was associated with a concomitant increase in the initial rate of palmitate uptake into cardiac myocytes. Specifically, the insulin-stimulated increase in the rate of palmitate uptake (+60%) paralleled the insulin-stimulated increase in plasmalemmal FAT/CD36 (+34%). Similarly, the greater AICAR-stimulated increase in the rate of palmitate uptake (+90%) paralleled the AICAR-induced increase in both plasmalemmal proteins (FAT/CD36 (+40%)+FABPpm (+36%)). Inhibition of palmitate uptake with the specific FAT/CD36 inhibitor SSO indicated that FABPpm interacts with FAT/CD36 at the plasma membrane to facilitate the uptake of palmitate. In conclusion, (1) there appears to be tissue-specific sensitivity to insulin-induced FATP1 translocation, as it has been shown elsewhere that insulin induces FATP1 translocation in 3T3-L1 adipocytes, and (2) clearly, the subcellular distribution of FABPpm, as well as FAT/CD36, is acutely regulated in cardiac myocytes, although FABPpm and FAT/CD36 do not necessarily respond identically to the same stimuli.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".