Determination of Aloin A, Aloin B, and Aloe-Emodin in Raw Materials and Finished Products Using HPLC Multilaboratory Validation Study, AOAC 2016.09, Final Action
Bibliographic record
Abstract
BACKGROUND: A multilaboratory validation study was performed on AOAC Official Method 2016.09, for final action. Eight different laboratories throughout the world participated in the study and tested the same set of six different laboratory samples of raw materials (commercial) and formulated products (commercial), and all the laboratories successfully generated results within the acceptance criteria. OBJECTIVE: The intention of the study was to evaluate specificity, precision (variation), linearity/range, system suitability, LOD, and LOQ by multiple laboratories to satisfy the requirement for moving Official Method 2016.09 to final action status. Accuracy and ruggedness were already validated in earlier work through single-laboratory validation, and it was not necessary to include these validation parameters in the multilaboratory validation study. METHODS: Laboratory samples containing Aloe vera were sent out to participating laboratories. Each laboratory followed Official Method 2016.09 (First Action) to analyze the content of aloin A, aloin B, and aloe-emodin using HPLC. The results generated by each laboratory were collected and evaluated. RESULTS: The specificity results show that blank and matrix chromatograms do not contain major interfering peaks at the retention time of aloin A, aloin B, and aloe-emodin. The precision (variation) results of duplicated preparations are not more than 0.05 parts per million (ppm) different. The linearity/range results from six standards (10 parts per billion [ppb], 20 ppb, 40 ppb, 80 ppb, 160 ppb, and 500 ppb) have correlation coefficient (R) values of ≥0.999. The system suitability results meet the acceptance criteria to show the instrument validity. The LOD results show that the S/N ratios of the 10 ppb standards for all three components are about 3. The LOQ results show that the S/N ratios of 20 ppb standards for all three components are about 10. CONCLUSION: The parameters (specificity, precision [variation], linearity/range, system suitability, LOD, and LOQ) have been validated and show that the test method is suitable for its intended use. HIGHLIGHTS: The test method has been successfully validated by eight different laboratories around the world (United States, United Kingdom, Germany, and Canada). Each of the laboratories is managed independently by a site laboratory management team. This multilaboratory study has validated Official Method 2016.09 (First Action) and the method is fit for its intended purpose.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 teacher head, 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".