Corticosteroid-binding globulin levels in North American sciurids: implications for the flying squirrel stress axis
Bibliographic record
Abstract
Corticosteroid-binding globulin (CBG) helps to regulate tissue bioavailability of circulating glucocorticoids (GCs), and in most vertebrates, ≥80%–90% of GCs bind to this protein. New World flying squirrels have higher plasma total cortisol levels (the primary corticosteroid in sciurids) than most vertebrates. Recent research suggests that flying squirrels have either low amounts of CBG or CBG molecules that have a low binding affinity for cortisol, as this taxon appears to exhibit very low proportions of cortisol bound to CBG. To test whether CBG levels have been adjusted over evolutionary time, we assessed the levels of this protein in the plasma of northern (Glaucomys sabrinus (Shaw, 1801)) and southern (Glaucomys volans (Linnaeus, 1758)) flying squirrels using immunoblotting, and compared the relative levels among three phylogenetically related species of sciurids. We also compared the pattern of CBG levels with cortisol levels for the same individuals. Flying squirrels had higher cortisol levels than the other species, but similar levels of CBG to their closest relatives (tree squirrels). We conclude that CBG levels in flying squirrels have not been adjusted over evolutionary time, and thus, the uncoupling of CBG levels from cortisol concentrations may represent an evolutionary modification in the lineage leading to New World flying squirrels.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".