Circadian Rhythm and Response to an Acute Stressor of Urinary Corticosterone, Testosterone, and Creatinine in Adult Male Mice
Bibliographic record
Abstract
In small laboratory species, steroid measures can be obtained more frequently and less invasively from urine than blood. Insofar as urinary levels reflect systemic levels, they could provide advantages particularly for measurement of glucocorticoids, whose blood levels react rapidly to handling and stress. In Experiment 1, urinary samples were collected from male mice every second hour over a 14:10 h light:dark cycle. Samples were analyzed via enzyme immunoassay for corticosterone, testosterone, and creatinine. Corticosterone had peak concentrations 1 h after light offset and a trough 1 h after light onset. Testosterone showed peak concentrations 5-7 h after light onset and lowest concentrations during the dark phase of the cycle. Creatinine showed some variation over the light-dark cycle, but steroid measures showed similar trends with and without adjustment for creatinine. In Experiment 2, mice were stressed via an injection at times close to the determined peak and trough levels of corticosterone. In urinary samples taken 90 min after injection, corticosterone was significantly higher in injected animals at both times relative to levels in control animals, but testosterone was unaffected by injection stress. In Experiment 3, serum and urine samples were collected from mice every sixth hour across the diurnal cycle. Corticosterone peaked in urine and serum immediately after light offset, and urinary measures predicted those in serum. These data indicate that urinary corticosterone reflects systemic levels in mice, document circadian variation in urinary testosterone, and indicate that circadian variation in creatinine is minimal, but potentially relevant in stressed animals.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".