Effects of castration on insulin levels and glucose tolerance in the mouse differ from those in man
Bibliographic record
Abstract
BACKGROUND: Plasma insulin concentration is increased in prostate cancer patients during androgen deprivation therapy (ADT) and hyperinsulinemia has been associated with aggressive prostate cancer behavior. To investigate the possible role of castration-induced hyperinsulinemia as a mechanism that may attenuate the beneficial effects of ADT in patients with prostate cancer, a murine model would be useful. We therefore investigated long-term metabolic effects of castration in several mouse models. METHODS: We studied the long-term influence of castration on energy intake, body weight, glucose tolerance, plasma-insulin, plasma insulin-like growth factor-1 (IGF-1), plasma adiponectin, and plasma leptin in C57BL/6, Swiss nu/nu, and CB17 scid mice receiving various diets. In each case, mice were randomized to have either bilateral orchiectomy or a sham operation. RESULTS: Energy intake, body weight, blood glucose levels in glucose tolerance test, plasma insulin, plasma IGF-1, and plasma leptin level in all had a trend to be decreased in castrated as compared to sham operated mice. Plasma adiponectin level was increased in the castrated mice. CONCLUSIONS: The effects of castration on glucose, insulin, and related markers in several mouse models studied does not coincide with clinical observations; further studies in this area will require clinical research and/or the use of alternate models such as the dog.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".