Similarities in acute phase protein response during hibernation in black bears and major depression in humans: a response to underlying metabolic depression?
Bibliographic record
Abstract
This study investigated the effects of hibernation with mild hypothermia and the stress of captivity on levels of six acute-phase proteins (APPs) in serial samples of serum from 11 wild and 6 captive black bears (Ursus ameri canus Pallas, 1780) during active and hibernating states. We hypothesize that during hibernation with mild hypothermia, bears would show an APP response similar to that observed in major depression. Enzyme-linked immuno absorbent assay was used to measure alpha2-macroglobulin and C-reactive protein, and a nephelometer to measure alpha1-antitrypsin, hapto globin, ceruloplasmin, and transferrin. Levels of all other proteins except ceruloplasmin were significantly elevated during hibernation in both wild and captive bears at the p < 0.05 to p < 0.001 level. Alpha2-macroglobulin and C-reactive-protein levels were increased in captive versus wild bears in both active and hibernating states at the p < 0.01 to p < 0.0001 level. During hibernation with mild hypothermia, black bears do not show immunosuppression, but show an increased APP response similar to that in patients with major depression. This APP response is explained as an adaptive response to the underlying metabolic depression in both conditions. Metabolic depression in hibernating bears is suggested as a natural model for research to explain the neurobiology of depression.
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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) | 0.000 | 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".