Centrally Administered Insulin-Like Growth Factor II Fails to Alter Pulsatile Growth Hormone Secretion or Food Intake
Bibliographic record
Abstract
Insulin-like growth factor II (IGF-II) peptide, mRNA, and receptors are widely distributed in the central nervous system, yet the physiological role of IGF-II in brain remains largely unknown. In the present study, we examined the in vivo effects of central administration of recombinant human IGF-II on pulsatile GH secretion and food intake. The IGF-II preparation used was shown to stimulate 3H-thymidine incorporation in MG-63 human osteosarcoma cells in vitro. Free-moving adult male rats bearing chronic intracerebroventricular (icv) and intracardiac venous cannulae were icv administered 10 microliters of either IGF-II (in doses of 300 ng and 1 microgram) or the vehicle solution, and blood samples were obtained every 15 min for 6 h. Vehicle-injected control animals exhibited the typical pulsatile pattern of GH secretion with most peak GH values greater than 100 ng/ml and trough levels less than 1.2 ng/ml. Central administration of IGF-II, at both doses, failed to alter the spontaneous 6-hour GH secretory profile; there were no significant differences in either GH peak amplitude, GH trough level, GH interpeak interval, or mean 6-hour plasma GH level, compared to vehicle-injected controls. There was also no effect of icv administered IGF-II on mean plasma glucose or insulin levels. Compared to vehicle-injected control rats, the icv injection of IGF-II (at doses of 300 ng and 1 microgram) did not significantly alter 24-h food intake or body weight gain in normal feeding rats.(ABSTRACT TRUNCATED AT 250 WORDS)
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".