Cultured hypothalamic neurons are resistant to inflammation and insulin resistance induced by saturated fatty acids
Bibliographic record
Abstract
Hypothalamic inflammation induced by high-fat feeding causes insulin and leptin resistance and contributes to the pathogenesis of obesity. Since in vitro exposure to saturated fatty acids causes inflammation and insulin resistance in many cultured cell types, we determined how cultured hypothalamic neurons respond to this stimulus. Two murine hypothalamic neuronal cell cultures, N43/5 and GT1–7, were exposed to escalating concentrations of saturated fatty acids for up to 24 h. Harvested cells were evaluated for activation of inflammation by gene expression and protein content. Insulin-treated cells were evaluated for induction of markers of insulin receptor signaling (p-IRS, p-Akt). In both hypothalamic cell lines, inflammation was induced by prototypical inflammatory mediators LPS and TNFα, as judged by induction of IκBα (3- to 5-fold) and IL-6 (3- to 7-fold) mRNA and p-IκBα protein, and TNFα pretreatment reduced insulin-mediated p-Akt activation by 30% ( P < 0.05). By comparison, neither mixed saturated fatty acid (100, 250, or 500 μM for ≤6 h) nor palmitate exposure alone (200 μM for ≤24 h) caused inflammatory activation or insulin resistance in cultured hypothalamic neurons, whereas they did in control muscle and endothelial cell lines. Despite the lack of evidence of inflammatory signaling, saturated fatty acid exposure in cultured hypothalamic neurons causes endoplasmic reticulum stress, induces mitogen-activated protein kinase, and causes apoptotic cell death with prolonged exposure. We conclude that saturated fatty acid exposure does not induce inflammatory signaling or insulin resistance in cultured hypothalamic neurons. Therefore, hypothalamic neuronal inflammation in the setting of DIO may involve an indirect mechanism mediated by saturated fatty acids on nonneuronal cells.
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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 | 0.001 |
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".