Palmitate alters <scp>miR</scp>‐2137 and <scp>miR</scp>‐503‐5p to induce orexigenic <i>Npy</i> in hypothalamic neuronal cell models: Rescue by oleate and docosahexaenoic acid
Bibliographic record
Abstract
MicroRNAs (miRNAs) are short noncoding RNA implicated in the pathogenesis of obesity. One cause of obesity is excess exposure to the saturated fatty acid palmitate that can alter miRNA levels in the periphery. Palmitate also promotes obesity by acting on the hypothalamus, the central coordinator of energy homeostasis, to dysregulate hypothalamic feeding neuropeptides and induce ER stress and inflammatory signaling. We hypothesized that palmitate would alter hypothalamic miRNAs that control genes involved in energy homeostasis thereby contributing to the obesity-promoting effects of palmitate. We found that palmitate upregulated 20 miRNAs and downregulated six miRNAs in the orexigenic NPY/AgRP-expressing mHypoE-46 cell line. We focused on delineating the roles of miR-2137 and miR-503-5p, as they were strongly up- and downregulated by palmitate, respectively. Overexpression of miR-2137 increased Npy mRNA levels and downregulated Esr1 levels, while increasing C/ebpβ and Atf3 mRNA. Inhibiting miR-2137 had the opposite effect, except on Npy, which was unchanged. The most downregulated miRNA by palmitate, miR-503-5p, negatively regulated Npy mRNA levels. Exposure to the unsaturated fatty acids oleate or docosahexaenoic acid completely or partially blocked the effects of palmitate on miR-2137 and miR-503-5p as well as Npy, Agrp, Esr1, C/ebpβ and Atf3. MicroRNAs may therefore contribute to palmitate actions in dysregulating NPY/AgRP neurons. Effectively combating the deleterious effects of palmitate is crucial to help prevent or reduce the impact of obesity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".