Circulating and Urinary Adrenal Corticosterone, Progesterone, and Estradiol in Response to Acute Stress in Female Mice (Mus musculus)
Bibliographic record
Abstract
In studies of stress, it can be difficult to obtain blood rapidly enough to avoid confounding steroid measures. Noninvasive urinary steroid measures may provide an alternative insofar as they reflect systemic steroids. In Experiment 1, we profiled urinary corticosterone, progesterone, and estradiol in ovariectomized female mice following 1 h on an elevated platform. This increased urinary corticosterone for 3 h and progesterone for 4 h. In Experiment 2, blood and urine samples were obtained at 0-6 h following stressor offset. Females showed increased serum corticosterone and progesterone immediately after stressor offset. Urinary corticosterone was increased at both 0 and 2 h post-stress, while an increase in progesterone 2-6 h after stressor offset was not significant. Estradiol was not influenced by this mild stressor. In Experiment 3, mice were exposed to a more severe 1 h stressor, a rat across a wire-mesh grid. In serum, both corticosterone and progesterone were elevated immediately after stressor offset and returned to baseline within 2 h. In urine, this severe stressor elevated corticosterone immediately and 2 h after stressor offset, and in progesterone 2 h after stressor offset. Estradiol in serum was not dynamic, but it was significantly elevated in urine 4 h after stressor offset. Urinary measures generally reflected systemic measures; however, with a different time course resulting in a longer return to baseline. We suggest that the relative value of serum or urinary steroid measures in mice depends upon the experimental design, and that estradiol may only respond when the stressor is severe.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".