Palmitate‐mediated induction of neuropeptide Y expression occurs through intracellular metabolites and not direct exposure to proinflammatory cytokines
Bibliographic record
Abstract
A contributing factor to the development of obesity is the consumption of a diet high in saturated fatty acids, such as palmitate. These fats induce hypothalamic neuroinflammation, which dysregulates neuronal function and induces orexigenic neuropeptide Y (Npy) to promote food intake. An inflammatory cytokine array identified multiple candidates that could mediate palmitate-induced up-regulation of Npy mRNA levels. Of these, visfatin or nicotinamide phosphoribosyltransferase (NAMPT), macrophage migratory inhibitory factor (MIF), and IL-17F were chosen for further study. Direct treatment of the neuropeptide Y/agouti-related peptide (NPY/AgRP)-expressing mHypoE-46 neuronal cell line with the aforementioned cytokines demonstrated that visfatin could directly induce Npy mRNA expression. Preventing the intracellular metabolism of palmitate through long-chain acyl-CoA synthetase (ACSL) inhibition was sufficient to block the palmitate-mediated increase in Npy gene expression. Furthermore, thin-layer chromatography revealed that in neurons, palmitate is readily incorporated into ceramides and defined species of phospholipids. Exogenous C16 ceramide, dipalmitoyl-phosphatidylcholine, and dipalmitoyl-phosphatidylethanolamine were sufficient to significantly induce Npy expression. This study suggests that the intracellular metabolism of palmitate and elevation of metabolites, including ceramide and phospholipids, are responsible for the palmitate-mediated induction of the potent orexigen Npy. Furthermore, this suggests that the regulation of Npy expression is less reliant on inflammatory cytokines per se than palmitate metabolites in a model of NPY/AgRP neurons. These lipid species likely induce detrimental downstream cellular signaling events ultimately causing an increase in feeding, resulting in an overweight phenotype and/or obesity.
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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".