Effect of whole peptidoglycan of bifidobacterium on proliferation and apoptosis in experimental gastric cancer
Bibliographic record
Abstract
OBJECTIVE:To explore the effects of whole peptidoglycan(WPG)from bifidobacterium on proliferation and apoptosis in experimental gastric cancer in vivo.METHODS:Thirty nude mice subcutaneously transplanted with MKN-45 human gastric cancer cells were administered with different doses of WPG and 5-FU by intraperitoneal injection when the tumors were palpable.The weights of the tumors and inhibitory rates were observed.TUNEL staining was used to detect the apoptosis of transplanted tumor cells.The immunohistochemical staining was used to detect the expression of bcl-2,bax and proliferating cell nuclear antigen(PCNA)in the transplanted tumor.RESULTS:The growth rates of the tumors in vivo were obviously slower when intragastric administration of WPG,and the tumor weights were significantly lower than those in the NS group when the study was over,P0.01.But not significantly different from 5-FU group,P0.05.The apoptosis indexes in the three WPG groups and 5-FU group were significantly higher than that in the normal saline group,P0.01.The immunohistochemical staining showed that the expression rate of bcl-2 protein and proliferating cell nuclear antigen were significantly lowed down in the WPG group compared with the normal saline group(P0.05),while the expression of apoptosis-inducing protein and bax was just the opposite.It was greatly up-regulated by WPG,P0.01.CONCLUSIONS:The whole peptidoglycan of bifidobacterium exerts an inhibiting effect on the growth of human gastric cancer in nude mice.The possible antitumor mechanisms are to decrease the proliferating activity of tumor cells or the expression of bcl-2 gene and increase the expression of bax gene,which can induce the apoptosis of the tumor cells.
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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 | 0.000 |
| 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".