Torpor expression is associated with differential spermatogenesis in hibernating eastern chipmunks
Bibliographic record
Abstract
Hibernators suppress physiological processes when expressing torpor, yet little is known about the effects of torpor on male reproductive physiology. Studies of hibernating mammals suggest that deep torpor negatively impacts spermatogenesis and that transitions between torpor and euthermic arousals increase cellular oxidative stress, with potentially damaging effects on sperm. Here, we hypothesize that variation in torpor expression affects the reproductive readiness of hibernators by impacting their sperm production. To test this, we examined the relationship between torpor expression and spermatogenesis in captive eastern chipmunks ( Tamias striatus). We determined torpor depth with temperature data loggers and assessed its relationship with spermatogenesis by examining spermatogenic progression, cell division, sperm counts, sperm maturity, and DNA damage. We show that deep hibernators (high levels of torpor) largely halted spermatogenesis in late hibernation in comparison with shallow hibernators (low levels of torpor), where ongoing spermatogenesis was observed. Despite these differences in spermatogenic state during hibernation, spermatogenic progression, sperm numbers, and maturity did not differ in spring, potentially reflecting similar degrees of reproductive readiness. Interestingly, shallow hibernators exhibited higher rates of DNA damage in spermatogenic cells during hibernation, with this trend reversing in spring. Our results thus indicate that once heterothermy is terminated, deep hibernators resume spermatogenesis but are characterized by higher rates of DNA damage in spermatogenic cells at the seasonal stage when spring mating commences. Therefore, our study confirmed posthibernation recovery of sperm production but also a potential impact of deep torpor expression during winter on DNA damage in spring.
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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 | 0.000 | 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 | 0.000 |
| 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".