Experimental study on the lotion for promoting blood circulation and removing blood stasis in pharmacodynamics
Bibliographic record
Abstract
Objective To observe the effects of lotion for promoting blood circulation and removing blood stasis so as to provide experimental evidence for the clinical application. Methods The rat models with acute blood stasis were applied with the lotion for promoting blood circulation and removing blood stasis for prevention,its influence on the whole blood viscosity and plasma viscosity were detected; the rat models with microcirculation dysfunction were applied with the lotion for prevention,and the improvement of microcirculation in auricle were observed; the rat models with pain were applied for prevention with the lotion,and its analgesic effect was observed. Results Compared with the acute blood stasis model group,the whole blood viscosity in the lotion group with the dosage of 0. 32,0. 64 g / m L was reduced significantly( P 0. 05,P 0. 01); compared with the microcirculation dysfunction model group,the microcirculation of auricle in lotion group with the dosage of 0. 40,0. 80 g / m L was improved( P 0. 05); a certain analgesic effect for pain caused by the chemical and heat stimulation was shown in the lotion group with the dosage of 0. 40,0. 80 g / m L( P 0. 05). Conclusion Lotion for promoting blood circulation and removing blood stasis has certain effect in promoting blood circulation and removing blood stasis and also has an analgesic action.
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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 | 0.000 | 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 | 0.001 |
| 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".