Tissue-specific seasonal changes in mitochondrial function of a mammalian hibernator
Bibliographic record
Abstract
; GMGS), cease to feed while reducing metabolic rate and body temperature during winter months, surviving exclusively on endogenous fuels stored before hibernation. We hypothesized that mitochondria, the cellular sites of oxidative metabolism, undergo tissue-specific seasonal adjustments in carbohydrate and fatty acid utilization to facilitate or complement this remarkable phenotype. To address this, we performed high-resolution respirometry of mitochondria isolated from GMGS liver, heart, skeletal muscle, and brown adipose tissue (BAT) sampled during summer (active), fall (prehibernation), and winter (hibernation) seasons using multisubstrate titration protocols. Mitochondrial phospholipid composition was examined as a postulated intrinsic modulator of respiratory function across tissues and seasons. Respirometry revealed seasonal variations in mitochondrial oxidative phosphorylation capacity, substrate utilization, and coupling efficiency that reflected the distinct functions and metabolic demands of the tissues they support. A consistent finding across tissues was a greater influence of fatty acids (palmitoylcarnitine) on respiratory parameters during the prehibernation and hibernation seasons. In particular, fatty acids had a greater suppressive effect on pyruvate-supported oxidative phosphorylation in heart, muscle, and liver mitochondria and enhanced uncoupled respiration in BAT and muscle mitochondria in the colder seasons. Seasonal variations in the mitochondrial membrane composition reflected changes in the supply and utilization of polyunsaturated fatty acids but were generally mild and inconsistent with functional variations. In conclusion, mitochondria respond to seasonal variations in physical activity, temperature, and nutrient availability in a tissue-specific manner that complements circannual shifts in the bioenergetic and thermoregulatory demands of mammalian hibernators.
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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".