Effect of needle puncture and electro-acupuncture on mucociliary clearance in anesthetized quails
Bibliographic record
Abstract
BACKGROUND: Acupuncture therapy for obstructive respiratory diseases has been effectively used in clinical practice and the acupuncture points or acupoints of Zhongfu and Tiantu are commonly-used acupoints to treat patients with the diseases. Since the impaired mucociliary clearance is among the most important features of airway inflammation in most obstructive respiratory diseases, the effect of needle puncture and electro-acupuncture at the specific acupoints on tracheal mucociliary clearance was investigated in anesthetized quails. METHODS: Mucociliary transport velocity on tracheal mucosa was measured through observing the optimal pathway, and fucose and protein contents in tracheal lavages were determined with biochemical methods. In the therapeutic group, needle puncture or electro-acupuncture stimulation to the acupoints was applied without or with constant current output in 2 mA and at frequency of 100 Hz for 60 minutes. In the sham group, electro-acupuncture stimulation to Liangmen was applied. RESULTS: Our present experiments demonstrated that the electro-acupuncture stimulation to Zhongfu and Tiantu significantly increased tracheal mucociliary transport velocity and decreased the content of protein in the tracheal lavage, compared with the control group. Moreover, either needle puncture or electro-acupuncture stimulation to Zhongfu and Tiantu significantly reverted the human neutrophil elastase-induced decrease in tracheal mucociliary transport velocity and human neutrophil elastase -induced increase in the contents of fucose and protein in the tracheal lavage, compared with the control group. CONCLUSION: These results suggest that either needle puncture or electro-acupuncture stimulation to the effective acupoints significantly improves both airway mucociliary clearance and the airway surface liquid and that the improvements maybe ascribed to both the special function of the points and the substantial stimulation of electricity.
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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".