The Effect of Degradation on Biological Activity and Chemical Content of Lom-Am-Ma-Preuk Extract
Bibliographic record
Abstract
Introduction: Lom-Am-Ma-Preuk (LAP) remedy is a herbal remedy in Traditional Thai Medicine scripture and is on the National List of Essential Medicine in Thailand. Many herbal ingredients of LAP have significant inhibitory activity against the production of inflammatory mediators. The aim of this current study was to investigate forced degradation of extracts by heat, moisture, oxidation, and acid hydrolysis. The effects of these degradations were determined by anti-inflammatory activity and chemical content analysis of the LAP extract. The identified chemical markers including eugenol, myristicin, and piperine were compared amongst the remedies. Methods: Antiinflammatory activity was determined by an inhibitory effect on nitric oxide production as assessed through the Griess reaction and content markers were analyzed by high performance liquid chromatography. Results: The forced degradation conditions which the extracts were treated with included oxidation, heat, moisture, and acid which did not affect the production inhibition of nitric oxide when compared with control (IC50 as 29.75, 35.69, 40.50, 48.04, and 40.37 µg/mL, respectively). Eugenol contents in LAP treated with acidic and alkaline treatments were significantly less than control (0.85 ± 0.11, 0.37 ± 0.11, and 2.28 ± 0.11 mg/g extract, respectively). Piperine content in the LAP extract which was treated with oxidation and acid was significantly less than control (24.71 ± 1.02, 25.69 ± 0.96, and 38.48 ± 0.74 mg/g extract, respectively) and myristicin content was not significantly different from controlled content after treatments. Conclusions: Except under alkaline conditions the LAP ethanolic extract is stable under forced degradation conditions in terms of biological properties. Thus, the preparation of a LAP extract should avoid alkaline conditions in the production process. LAP extract is considered to be a potential candidate for further development into a topical product for analgesic relief.
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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) | 0.000 | 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) | 0.002 | 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".