Regulation of leptin secretion from white adipocytes by free fatty acids
Bibliographic record
Abstract
Norepinephrine stimulates lipolysis and concurrently inhibits insulin-stimulated leptin secretion from white adipocytes. To assess whether there is a cause-effect relationship between these two metabolic events, the effects of fatty acids were investigated in isolated rat adipocytes incubated in buffer containing low (0.1%) and high (4%) albumin concentrations. Palmitic acid (1 mM) mimicked the inhibitory effects of norepinephrine (1 microM) on insulin (10 nM)-stimulated leptin secretion, but only at low albumin concentrations. Studies investigating the effects of the chain length of saturated fatty acids [from butyric (C4) to stearic (C18) acids] revealed that only fatty acids with a chain length superior or equal to eight carbons effectively inhibited insulin-stimulated leptin secretion. Long-chain mono- and polyunsaturated fatty acids constitutively present in adipocyte triglyceride stores (oleic, linoleic, gamma-linolenic, palmitoleic, eicosapentanoic, and docosahexanoic acids) also completely suppressed leptin secretion. Saturated and unsaturated fatty acids inhibited insulin-stimulated leptin secretion with the same potency and without any significant effect on basal secretion. On the other hand, inhibitors of mitochondrial fatty acid oxidation (palmoxirate, 2-bromopalmitate, 2-bromocaproate) attenuated the stimulatory effects of insulin on leptin release without reversing the effects of fatty acids or norepinephrine, suggesting that fatty acids do not need to be oxidized by the mitochondria to inhibit leptin release. These results demonstrate that long-chain fatty acids mimic the effects of norepinephrine on leptin secretion and suggest that they may play a regulatory role as messengers between stimulation of lipolysis by norepinephrine and inhibition of leptin secretion.
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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".