Hypothalamic α7 nicotinic acetylcholine receptor (α7nAChR) is downregulated by TNFα‐induced Let‐7 overexpression driven by fatty acids
Bibliographic record
Abstract
The α7nAChR is crucial to the anti-inflammatory reflex, and to the expression of neuropeptides that control food intake, but its expression can be decreased by environmental factors. We aimed to investigate whether microRNA modulation could be an underlying mechanism in the α7nAchR downregulation in mouse hypothalamus following a short-term exposure to an obesogenic diet. Bioinformatic analysis revealed Let-7 microRNAs as candidates to regulate Chrna7, which was confirmed by the luciferase assay. Mice exposed to an obesogenic diet for 3 days had increased Let-7a and decreased α7nAChR levels, accompanied by hypothalamic fatty acids and TNFα content. Hypothalamic neuronal cells exposed to fatty acids presented higher Let-7a and TNFα levels and lower Chrna7 expression, but when the cells were pre-treated with TLR4 inhibitor, Let-7a, TNFα, and Chrna7 were rescued to normal levels. Thus, the fatty acids overload trigger TNFα-induced Let-7 overexpression in hypothalamic neuronal cells, which negatively regulates α7nAChR, an event that can be related to hyperphagia and obesity predisposition in mice.
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 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 | 0.000 |
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".