Measurement of free glucocorticoids: quantifying corticosteroid-binding globulin binding affinity and its variation within and among mammalian species
Bibliographic record
Abstract
Plasma glucocorticoids (GCs) are commonly used as measures of stress in wildlife. A great deal of evidence indicates that only free GC (GC not bound by the specific binding protein, corticosteroid-binding globulin, CBG) leaves the circulation and exerts biological effects on GC-sensitive tissues. Free hormone concentrations are difficult to measure directly, so researchers estimate free GC using two measures: the binding affinity and the binding capacity in plasma. We provide an inexpensive saturation binding method for calculating the binding affinity (equilibrium dissociation constant, K d) of CBG that can be run without specialized laboratory equipment. Given that other plasma proteins, such as albumin, also bind GCs, the method compensates for this non-specific binding. Separation of bound GC from free GC was achieved with dextran-coated charcoal. The method provides repeatable estimates (12% coefficient of variation in the red squirrel, Tamiasciurus hudsonicus), and there is little evidence of inter-individual variation in K d (range 2.0-7.3 nM for 16 Richardson's ground squirrels, Urocitellus richardsonii). The K d values of 28 mammalian species we assessed were mostly clustered around a median of 4 nM, but five species had values between 13 and 61 nM. This pattern may be distinct from birds, for which published values are more tightly distributed (1.5-5.1 nM). The charcoal separation method provides a reliable and robust method for measuring the K d in a wide range of species. It uses basic laboratory equipment to provide rapid results at very low cost. Given the importance of CBG in regulating the biological activity of GCs, this method is a useful tool for physiological ecologists.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".