Vasodilatory effects and underlying mechanisms of the ethyl acetate extracts from <i>Gastrodia elata</i>
Bibliographic record
Abstract
The objective of this study was to assess the ethyl acetate extracts of Gastrodia elata Blume (GEB) on vascular tone and the mechanisms involved. GEB was extracted with 95% EtOH followed by a further extraction with ethyl acetate. The effects of GEB and its ingredients on the isometric tensions of the aortic rings from rats were measured. The ethyl acetate extract of GEB induced a vasodilatory effect on rat aorta, which was partially dependent on endothelium. Four chemical compounds isolated from GEB were identified as 3,4-dihydroxybenzaldehyde (DB), 4-hydroxybenzaldehyde (HB), 4-methoxybenzyl alcohol (MA), and 4,4′-dihydroxydiphenyl methane (DM), respectively. All of these compounds induced vasodilatations, which were dependent on the endothelium to different degrees. After pretreatment with Nω-nitro-l-arginine methyl ester, indomethacin, or methylene blue, the vasodilatations induced by DB, HB, and MA were significantly decreased. In addition, the contractions of the rat aortic rings due to Ca2+ influx and intracellular Ca2+ release were also inhibited by DM. Furthermore, the administration of DB significantly enhanced the productions of nitric oxide (NO) and the activities of the endothelial NO synthase in aorta and in endothelial cells. Thus, GEB may play an important role in the amelioration of hypertension by modulating vascular tones.
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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) | 0.001 | 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".