RP-HPLC Method for Simultaneous Quantification of Withanolides in <i>Withania somnifera</i>
Bibliographic record
Abstract
Background: Withanolides are the primary bioactive components of Withania somnifera (L.) Dunal. Among them, withanolide A, and 12-deoxy-withastramonolide are the herb’s most physiologically active ingredients. The steroidal lactones are isomers, which makes them difficult to separate. Aim: In the current research, a simple, precise, accurate, and decent RP-HPLC method has been developed, optimised and validated for simultaneous quantification and separation. Methods: Resolution was conducted on Gemini, Phenominex C18 (250mm X 4.6mm, 5 μ) column at 40oC utilising binary mobile phases of acetonitrile and ammonium acetate (10 mM) in gradient mode with 1.0 mL/min flow rate and observed at 230 nm. The total run time was twenty-five minutes. The procedure complied with ICH guidelines, covering the limit of detection, specificity, linearity, quantification, precision, accuracy, and robustness. Results: The standard curves of both relevant analytes displayed a linear pattern with regression values > 0.999 in the 1–10 μg/mL range. For both herbal markers, 1 μg/mL was the lowest limit of quantification. The method’s accuracy was 100.38-100.93 % and 99.13-100.75 % for with withanolide A, and 12-deoxy-withastramonolide respectively. The precision of within and between days was found in the tolerable limit of >2% for both herbal markers. Conclusion: The suggested method worked well for simultaneously analyzing the extracted samples and identifying withanolides.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".