Assessment of three variations of the 1,9-dimethylmethylene blue assay for measurement of sulfated glycosaminoglycan concentrations in equine synovial fluid
Bibliographic record
Abstract
OBJECTIVE: To determine whether 3 variations of the 1,9-dimethylmethylene blue (DMMB) assay yield comparable results when measuring sulfated glycosaminoglycan (sGAG) concentrations in equine synovial fluid (SF). SAMPLE POPULATION: 25 samples of SF collected from affected joints of 13 horses and 13 samples of SF collected from nonaffected (control) joints of 4 horses. PROCEDURE: Sulfated glycosaminoglycan concentrations were measured by the direct spectrophotometric (ie, Farndale), microplate, and indirect DMMB assays in samples of SF collected from normal and affected joints and in samples digested with nucleases, papain, and hyaluronidase. RESULTS: All 3 assays reacted similarly to standard solutions of sGAGs and digestion of SF samples with nucleases, papain, and hyaluronidase. Nucleic acids were not important interfering substances, and papain and hyaluronidase could not be used interchangeably to digest SE All 3 assays proved to have satisfactory precision (SD < 10%), but each DMMB assay resulted in significantly different measures of sGAG in equine SF. CONCLUSIONS AND CLINICAL RELEVANCE: Samples of SF should be digested with papain or hyaluronidase prior to measurement via DMMB assay. Researchers currently are unable to compare clinical information when variations of the DMMB assay are used, because each DMMB assay yields substantially different sGAG concentrations in SF. Of the 3 assays examined here, we recommend use of the direct spectrophotometric DMMB assay.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".