The Protective Effects of Ciji-Hua’ai-Baosheng II Formula on Chemotherapy-Treated H22 Hepatocellular Carcinoma Mouse Model by Promoting Tumor Apoptosis
Bibliographic record
Abstract
Ciji-Hua’ai-Baosheng II Formula (CHB-II-F) is a traditional Chinese medical formula that has been shown in clinical practice to relieve side effects of chemotherapy and improve quality of life for cancer patients. In order to understand the mechanism of its protective effects on chemotherapy, mice with transplanted H22 hepatocellular carcinoma were employed in this study. Ninety-two mice were injected subcutaneously with H22 HCC cell suspension into the right anterior armpit. After mice were treated with 5-fluorine pyrimidine (5-FU), they were divided into six groups as untreated group, 5-FU group, 5-FU plus Yangzheng Xiaoji Capsule group and three groups of 5-FU plus different concentrations of CHB-II-F. Twenty mice were euthanized after 7 days of treatment in untreated and medium concentration of CHB-II-F groups and all other mice were euthanized after 14 days of treatment. Herbal components/metabolites were analyzed by UPLC-MS. Tumors were evaluated by weight and volume, morphology of light and electron microscope, and cell cycle. Apoptosis were examined by apoptotic proteins expression by western blot. Four major components/metabolites were identified from serum of mice treated with CHB-II-F and they are β-Sitosterol, Salvianolic acid, isobavachalcone and bakuchiol. Treatment of CHB-II-F significantly increased body weights of mice and decreased tumor volume compared to untreated group. Moreover, CHB-II-F treatment increased tumor cells in G0-G1 transition instead of in S phase. Furthermore, CHB-II-F treatment increased the expression of pro-apoptotic proteins and decreased the expression anti-apoptotic protein. Therefore, CHB-II-F could improve mice general condition and reduce tumor cell malignancy. Moreover, CHB-II-F regulates apoptosis of tumor cells, which could contribute its protective effect on chemotherapy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".