Comparison of rosmarinic acid content in commercial tinctures produced from fresh and dried lemon balm (Melissa officinalis)
Bibliographic record
Abstract
PURPOSE: To measure the rosmarinic acid content of eight commercial tinctures derived from fresh (n= 5) and dried (n=3) Melissa officinalis herb. METHODS: Rosmarinic acid and the internal standard (esculin) were purchased from Aldrich Chemical Co. The column used was a Luna C18, 5 um (150 x 4.6 mm I.D., Phenomenex) maintained at ambient room temperature. The HPLC system consisted of a Shimadzu SCL-6B controller, Shimadzu LC-6A pumps, Shimadzu SPD-6A UV single wavelength spectrophotometric detector set to 320 nm and Shimadzu SIL-6B autosampler. Gradient elution of the samples and standard were performed using ammonium formate (0.02 M; pH 6.25 at 27 oC; eluent A) and methanol (eluent B). The gradient elution initial conditions were 2% of eluent B with linear gradient to 60% at 30 min, followed by linear gradient to 90% of eluent B at 31 min, this proportion being maintained for 4 min. The column was then returned to the initial condition at 36 min and maintained until the end of the run at 43 min. The flow rate was 1 mL/min. The assay was validated for sensitivity, accuracy and reproducibility. RESULTS: The content of rosmarinic acid in commercial tinctures was significantly higher in the tinctures made from dried plant material (2.96 - 22.18 mg/mL) compared to fresh plant tinctures (</= 0.92 mg/mL). CONCLUSION: These results have implications both for the manufacturers of commercial tinctures and also for herbal practitioners in the choice of tinctures for treating Herpes simplex infection.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".