Ciliary Neural Trophic Factor: Mimicking Leptin’s Effects in Skeletal Muscle?
Bibliographic record
Abstract
There is a clear association between obesity and the development of insulin resistance; however, the mechanisms underlying this relationship are unclear. In both humans and rodents, there is a strong correlation between abnormal fatty acid (FA) metabolism and the development of insulin resistance in skeletal muscle, the largest tissue by mass regulated by insulin. In addition to being a major sink for circulating glucose, skeletal muscle takes up significant quantities of plasma FA, for either energy production or storage. The accumulation of im triacylglycerol (TAG) (1, 2) as well as an impaired capacity to oxidize FA (3) are correlated to the presence of insulin resistance. However, elevated TAG stores may only be a marker of dysfunctional FA metabolism, and accumulation of more reactive lipid species, such as diacylglycerol (DAG) and ceramide, is likely to be responsible for the impaired insulin signaling. Interestingly, and perhaps somewhat surprisingly, the elevation of circulating lipids need not be present chronically to induce insulin resistance. Infusion of a lipid emulsion for several hours in humans results in increases in muscle DAG content (4) and the acute development of insulin resistance (5, 6).
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".