Thermomechanical properties of bat and human red blood cells—Implications for hibernation
Bibliographic record
Abstract
Hibernation is a widespread and highly efficient mechanism to save energy in mammals. However, one major challenge of hibernation is maintaining blood circulation at low body temperatures, which strongly depends on the viscoelastic properties of red blood cells (RBCs). Here, we examined at physiologically relevant timescales the thermomechanical properties of hundreds of thousands of individual RBCs from the hibernating common noctule bat ( Nyctalus noctula ), the nonhibernating Egyptian fruit bat ( Rousettus aegyptiacus ), and humans ( Homo sapiens ). We exposed RBCs to temperatures encountered during normothermia and hibernation and found a significant increase in elasticity and viscosity with decreasing temperatures. Our data demonstrate that temperature adjustment of RBCs is mainly driven by membrane properties and not the cytosol while viscous dissipation in the membrane of both bat species exceeds the one in humans by a factor of 15. Finally, our results show that RBCs from both bat species reveal a transition to a more viscous-like state when temperature decreases. This process on a minute timescale has an effect size that is comparable with fluctuations in RBC viscoelasticity over the course of the year, implying that environmental factors, such as diets, have a lower impact on the capability of RBCs to respond to different temperatures than general physical properties of the cell membrane. In summary, our findings suggest membrane viscoelasticity as a promising target for identifying mechanisms that could be manipulated to ensure blood circulation at low body temperatures in humans, which may be one first step toward safe synthetic torpor in medicine and space flight.
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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) | 0.000 | 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".