Correlation between glucocorticoid receptor binding parameters, blood pressure, and body mass index in a healthy human population
Bibliographic record
Abstract
Correlation between the glucocorticoid receptor (GR) number and affinity for the ligand, as well as the relationship between these equilibrium binding parameters and body mass index, blood pressure, and age were examined in peripheral blood mononuclear cells (PBMC) of healthy human subjects. It was found that the only statistically significant correlation was that between the GR number per cell and equilibrium dissociation constant, K(d) (r = 0.84, p < 0.0001). This observation implies the existence of a compensatory mechanism providing for lower GR affinity in individuals that have more receptor sites in circulating mononuclear cells and vice versa. This compensatory phenomenon together with considerable interindividual variation (GR number per cell ranging from 1391 to 15133, CV = 58.62%; and K(d) from 2.5 to 98.6 nM, CV = 80.87%), reflects plasticity of the glucocorticoid system. The results pose the question of whether this compensatory mechanism observed in healthy human subjects persists in pathophysiological states associated with glucocorticoid hormone actions and suggest that tissue sensitivity to glucocorticoids could be better predicted by the sign and magnitude of the correlation between the two receptor equilibrium binding parameters than by each of them separately.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".