Simultaneous determination of urinary cortisol, cortisone and corticosterone in parachutists, depressed patients and healthy controls in view of biomedical and pharmacokinetic studies
Bibliographic record
Abstract
A rapid and sensitive reversed-phase liquid chromatographic method (RP-LC) with UV detection has been developed for the determination of free cortisol, cortisone and corticosterone in human urine. The assay was performed after a solid-phase extraction procedure (SPE) with dexamethasone as the internal standard. Chromatographic separation was carried out on a Nucleosil 100 C(18) analytical column using a mixture of acetonitrile and water (30 : 70, v/v) as a mobile phase at a flow-rate of 1 mL min(-1). Spectrophotometric detection was performed at 240 nm. The method has been validated for accuracy, precision, selectivity, linearity, recovery and stability. The absolute recoveries of glucocorticoids were above 94.6%. The limits of detection (LOD) and quantification (LOQ) were 0.5 and 2 ng mL(-1), respectively, for all analytes. Linearity was confirmed in the range of 2-300 ng mL(-1) with a correlation coefficient greater than 0.9997 for all steroid hormones. The proposed method was sensitive, robust and specific allowing reliable quantification of steroid hormones. This method was successfully applied for determination of three endogenous glucocorticoid levels in human urine. The studies were performed on 20 sedentary healthy volunteers in comparison to two socially diversified groups, namely 10 parachutists before and after jump and 10 patients with depression. Pharmacokinetic studies performed on these groups indicated that urinary free cortisol and cortisol-to-cortisone ratios can be treated as biomarkers of stress and depressive disorders.
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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) | 0.001 | 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".