Determination of glucosamine in horse plasma by liquid chromatography tandem mass spectrometry
Bibliographic record
Abstract
Glucosamine is an amino sugar involved in the biosynthesis of glycosylated proteins and lipids. Recently, with increased public interest in natural products medicine, glucosamine has been widely used to treat osteoarthritis, even though demonstrations of its actual efficacy remain relatively unknown. Information related to the pharmcokinetics of glucosamine is sparse. A recent analytical method published used 13C-glucosamine as an internal standard to analyse study samples. The method lacked accuracy owing to an important natural isotopic contribution of glucosamine to 13C-glucosamine ion abundance. This manuscript describes a simple method to quantify glucosamine in horse plasma. Glucosamine was extracted by protein precipitation with acetonotrile containing 0.1% formic acid. The chromatography was performed on a Agilent Hypersil-ODS 100x2.1 mm column with a mobile phase composed of acetonitrile and 0.5% formic acid in water (45:55) at a flow rate of 0.3 mL/min. A linear (1/x) relationship was used to perform the calibration over an analytical range of 10-1000 ng/mL. The inter-batch precision and accuracy ranged from 5.3 to 11.3% and from 87.8 to 107.2% in horse plasma, respectively. The mean endogenous level of glucosamine in horse plasma was 14.4 ng/mL (n=6). This LC-ESI/MS/MS method for the determination of glucosamine in horse plasma provided results within generally accepted criteria used for bioanalytical 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 | 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".