Quantification of Urinary Sex Steroids in the Big Brown Bat (<i>Eptesicus fuscus</i>)
Bibliographic record
Abstract
Bats (order Chiroptera) are the second largest group of mammals, diverging ~52.5 million years ago. Many species exhibit an unusual reproductive cycle and extreme longevity without reproductive senescence, yet steroid profiles exist for few bats. Big brown bats (Eptesicus fuscus) are temperate insectivores found throughout North America. They mate promiscuously in fall, store sperm during winter hibernation, and have delayed ovulation and fertilization in spring. Here, we report the first urinary steroid profile in bats by quantifying 17β-estradiol (E2) in captive male and female E. fuscus across their reproductive cycle. Male bats had higher urinary E2 levels than females, and adults had higher levels than yearlings following creatinine adjustment for hydration. In nonpregnant females, several seasonal differences in creatinine-adjusted and unadjusted urinary E2 levels were observed. Urinary E2 was higher in males than females in winter for both conditions and in autumn for creatinine-adjusted levels. We quantified progesterone (P4) in a subset of females. In nonpregnant females, urinary P4 was constant across seasons except for unadjusted levels, which were highest in the summer. In pregnant females, urinary E2 and P4 levels peaked beginning ~20 d before parturition, with both steroids returning to baseline in the following weeks. Knowing how urinary steroid levels fluctuate with age and sex and across the annual season is key to understanding reproductive cycling in bats. Our research furthers the potential for bats as a model for medical reproductive research. Moreover, it complements previous studies on the potential role of steroids in primer pheromonal effects in bats.
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) | 0.000 | 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 | 0.000 |
| 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".