Effect of Zhenqi Fuzheng Decoction on Immune Function of Patients with Nasopharyngeal Carcinoma Radiotherapy
Bibliographic record
Abstract
Objective:To observe the effect of Zhenqi Fuzheng Decoction on immune function of patients with nasopharyngeal carcinoma radiotherapy.Method:60 cases of nasopharyngeal carcinoma were randomly divided into study group and control group, each group had 30 cases. The control group carried out a simple three-dimensional conformal radiotherapy, The study group carried three-dimensional conformal radiotherapy and took Astragalus, Ligustrum lucidum mainly taking health care prescription decoction at first day, a daily agent, until the end of radiotherapy. Two groups were observed before and after treatment in patients with peripheral blood CD3, CD4, CD8, CD4/CD8 and NK lymphocyte data changes. Result:the study group as compared with before treatment, CD3, CD4, CD4/CD8 and NK cells were decreased, CD8 increased slightly, but the difference was not statistically significant(P0.05); the control group compared with before treatment, CD3, CD4, CD4/CD8 and NK cells decreased significantly, CD8 increased significantly, the difference was statistically significant(P0.05); the study group in comparison to the control group after treatment, CD3, CD4, NK cells decreased significantly(P0.05),CD8 increased significantly(P0.01).Conclusion:Astragalus, Ligustri Lucidi decoction has the function of health care to improve mainly radiotherapy in patients with nasopharyngeal carcinoma cell immune function, there is of great significance for the maintenance of the follow-up treatment.
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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".