Palmitate Attenuates Insulin Signaling and Induces Endoplasmic Reticulum Stress and Apoptosis in Hypothalamic Neurons: Rescue of Resistance and Apoptosis through Adenosine 5′ Monophosphate-Activated Protein Kinase Activation
Bibliographic record
Abstract
Hypothalamic insulin signaling is essential to the maintenance of glucose and energy homeostasis. During pathological states, such as obesity and type 2 diabetes mellitus, insulin signaling is impaired. One key mechanism involved in the development of insulin resistance is lipotoxicity, through increased circulating saturated fatty acids. Although many studies have begun to determine the underlying mechanisms of lipotoxicity in peripheral tissues, little is known about the effects of excess lipids in the brain. We used a hypothalamic, neuronal cell model, mHypoE-44, to understand how the highly prevalent nonesterified fatty acid, palmitate, affects neuronal insulin signaling. Through Western blot analysis, we discerned that prolonged exposure to palmitate impairs insulin activation, as assessed by phosphorylation of Akt. We investigated the role of endoplasmic reticulum (ER) stress, which is known to promote cellular insulin resistance and apoptosis in peripheral tissues. Palmitate treatment induced ER stress through a c-Jun N-terminal kinase (JNK)-dependent pathway because a selective JNK inhibitor blocked palmitate activation of the ER stress pathways eIF2 alpha and X-box binding protein-1. Interestingly, JNK inhibition did not prevent the palmitate-mediated cleaved caspase-3 increase, an apoptotic marker, or insulin signaling attenuation. However, pretreatment with the AMP kinase activator, aminoimidazole carboxamide ribonucleotide, blocked JNK phosphorylation and importantly prevented caspase-3 cleavage and restored insulin signaling during short-term exposure to palmitate. Thus, activation of AMP kinase prevents the deleterious effects of palmitate on hypothalamic neurons by inhibiting the onset of insulin resistance and apoptosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".