Determination of Metformin in Human Plasma and Urine by High-Performance Liquid Chromatography Using Small Sample Volume and Conventional Octadecyl Silane Column
Bibliographic record
Abstract
PURPOSE: To develop a selective and sensitive high-performance liquid chromatographic method for the determination of metformin in human plasma and urine, using a conventional reverse phase column and low specimen volume. METHODS: Extraction of metformin and ranitidine (as internal standard) from plasma and urine samples (100 µL) was performed with a 1-butanol-hexane (50:50, v/v) mixture under alkaline conditions followed by back-extraction into diluted acetic acid. Chromatography was carried out using a C18 column (250 mm×4.6 mm, 5 μm). A mobile phase consisting of acetonitrile and KH2PO4 (34:66, v/v) and sodium dodecyl sulphate (3 mM) was pumped at an isocratic flow rate of 0.7 mL/min. RESULTS: The calibration curves were linear (>0.995) in the concentration ranges of 10-5000 and 2-2000 μg/mL for metformin in plasma and urine respectively. .The mean absolute recoveries for 100 and 1000 ng/mL metformin in plasma using the present extraction procedure were 93.7 and 88.5%, respectively. The intra- and inter-day coefficients of variation in plasma and urine were <20% at the lowest, and <16% at other concentrations. The percent error values were less than 2% in plasma while it reached ~9% in urine. The lower limits of quantification were 7.8 ng/mL and 1.6 μg/mL of metformin base in plasma and urine respectively. CONCLUSION: The method showed high calibers of sensitivity and selectivity for monitoring therapeutic concentrations of metformin in both plasma and urine based on a 0.1 ml sample size._____________________________________________________________________________________
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".