Possible common central pathway for resistin and insulin in regulating food intake
Bibliographic record
Abstract
AIM: Adipose tissue has been the object of intense research in the field of obesity and diabetes diseases in the last decade. Examination of adipocyte-secreted peptides led to the identification of a unique polypeptide, resistin (RSTN), which has been suggested as a link between obesity and diabetes. RSTN plays a clearly documented role in blocking insulin (INS)-induced hypoglycaemia. As brain injection of INS affects feeding behaviour, we studied the possible interaction between INS and RSTN in food-deprived rats, measuring effects on food intake. In addition, we examined how RSTN might affect neuropeptide Y (NPY)-induced feeding, as studies have shown that rat RSTN can interfere with the NPY system. METHODS: Overnight food-deprived rats were injected into the third brain ventricle (3V) with either INS (10 or 20 mUI), RSTN (0.1-0.4 nmol/rat), or saline before access to food. Another group of rats was injected into the 3V with RSTN alone, NPY alone or RSTN plus NPY. Their food intake and body weight were measured. RESULTS: Our results confirm the hypophagic effect of RSTN on food deprivation-induced food intake, and more importantly, show that RSTN neither potentiates nor blocks the effects of INS on food intake, but does reduce the hyperphagic effect of NPY. CONCLUSION: The observation that RSTN does not modify feeding INS-induced hypophagia, but does influence NPY-induced feeding, points to the possibility that RSTN may be involved in control of food intake through an NPY-ergic mechanism as INS.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".