Effect of Vasopressin and Naloxone Alone and in Combination on Cortisol Secretion after Dexamethasone Pretreatment
Bibliographic record
Abstract
In order to further examine the possible role of endogenous opioid peptides and vasopressin in the phenomenon of dexamethasone nonsuppression, we studied the effect of naloxone, vasopressin, and vasopressin-naloxone combination on cortisol secretion following dexamethasone pretreatment. Nine healthy males were given 1 mg dexamethasone at 23.00 h. The following day starting at 12.30 h and at 90-min intervals they received intravenously naloxone (0.2 mg/kg), arginine vasopressin 3 units, or the two drugs combined. The order of drug administration was counterbalanced using a Latin square design. Blood samples were drawn at 15-min intervals, and plasma aliquots were assayed for cortisol and dexamethasone. Naloxone failed to induce an escape from dexamethasone suppression. Four of the 9 subjects responded with an escape from dexamethasone suppression in response to vasopressin alone. The observed variability in response to vasopressin was unrelated to dexamethasone plasma levels but was associated with a decrease in systolic blood pressure. Peak cortisol levels were lowest in response to naloxone and highest in response to vasopressin. There was no evidence of an increased cortisol response to the coadministration of naloxone with vasopressin compared to vasopressin alone. These results fail to implicate an opioidergic mechanism in the pathophysiology of dexamethasone nonsuppression.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 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".