Glutathione Stability in Whole Blood: Effects of Various Deproteinizing Acids
Bibliographic record
Abstract
High-performance liquid chromatography separation of reduced and oxidized glutathione (GSH and GSSG) in biologic samples using electrochemical detection offers the convenience of both simultaneous quantitation and simple sample preparation. Rapid acidification is required to prevent GSH autooxidation, GSH and GSSG degradation, and precipitate proteins that interfere with analysis. Currently, little consistency exists in the literature regarding acid selection or the feasibility of sample storage before analysis. The purpose of this work was to examine the effects of perchloric (PCA), trichloroacetic (TCA), metaphosphoric (MPA), and 5-sulfosalicylic (SSA) acids on the short-term stability of GSH and GSSG measurements in whole blood. Samples were collected from adult volunteers and treated with multiple concentrations of each acid. The samples were analyzed immediately and aliquots were stored at -80 degrees C for up to 28 days. The suitability of each acid was assessed by percentage change of GSH and GSSG from baseline, efficiency of protein removal, and alteration of chromatogram characteristics. In general, increasing the acid concentration improved sample stability. Nevertheless, SSA did not achieve acceptable sample stability at any concentration tested. MPA was found to leave substantial amounts of protein in the samples, and TCA may interfere with the peaks of interest. Based on these results, a final concentration of 15% PCA is suggested for analysis of glutathione in whole blood. Although immediate sample preparation is preferred, 15% PCA can maintain sample integrity for 4 weeks after storage at -80 degrees C.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".