Ciliary Neurotrophic Factor Suppresses Hypothalamic AMP-Kinase Signaling in Leptin-Resistant Obese Mice
Bibliographic record
Abstract
We examined the actions of a second-generation ciliary neurotrophic factor analog (CNTF(Ax15)) on AMP-activated protein kinase (AMPK), a known regulator of food intake. Unlike leptin CNTF(Ax15) has been shown to reduce food intake in obese rodents and humans. Intraperitoneal injection of CNTF(Ax15) acutely (45 min) reduced hypothalamic AMPKalpha2 activity, AMPKalpha2Thr172 phosphorylation, and acetyl-coenzyme A carboxylase phosphorylation, effects not observed 2 or 6 h after injection. Intracerebroventricular CNTF(Ax15) reduced food intake, increased arcuate nucleus (ARC) signal transducer and activator of transcription 3 phosphorylation, and reduced AMPK signaling but not in the paraventricular nucleus (PVN), posterior hypothalamus, or cortex. To compare the effects of leptin and CNTF(Ax15) in a diet-induced model of obesity, mice were fed a control carbohydrate or high-fat diet (HFD) for 12 wk. Leptin treatment ip reduced food intake in control mice but not in mice fed a HFD. In contrast, ip CNTF markedly reduced food intake in both control and HFD animals. Both leptin and CNTF reduced AMPK activity and acetyl-coenzyme A carboxylase phosphorylation in the ARC and PVN of control-fed mice. A HFD blunted leptin but not CNTF effects on AMPK signaling in the ARC and PVN. In summary, these data demonstrate that CNTF(Ax15) bypasses diet-induced leptin resistance to reduce hypothalamic AMPK activity.
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) | 0.001 | 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 | 0.001 | 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".