Bibliographic record
Abstract
Objective: To investigate the effectiveness of tissue specific cytisine deaminase/5-fluorocytosine (CD/5-FC) thermochemotherapy system in treatment of liver metastasis of colon cancer in nude mice. Methods: CEA promoter-regulated recombinant retroviral vector G1CEACDNa was packaged, propagated and purified, and the viral supernatant was harvested. Human colon cancer LoVo cells were injected into the portal veins of 45 nude mice. Two days after the establishment of liver metastasis model, the viral supernatant was intraperitoneally injected into mice (0.2 ml/d, 5 d). The 45 mice were then randomly divided into 3 groups, namely, the control group (injected with sodium), chemotherapy group (pro-drug/5-FC) and thermochemotherapy group (43℃ pro-drug/5-FC). After treated for 21 d, the mice were sacrificed and liver metastasis rate and liver metastasis nodule numbers were observed. Expression of CD gene in liver metastasis tissues was determined by RT-PCR. Pathological changes of liver metastasis tissues were examined by light microscope and electron microscope. Results: The virus titer of G1CEACDNa was 5.6×10^6 CFU/L. CD gene was effectively expressed in the liver metastasis tissues. Liver metastasis rates and number of liver metastasis nodules were significantly lower in the thermochemotherapy group than in the chemotherapy group (13.3% vs 40.0%, [0.20±0.56] vs [0.80±1.01]; all P＜0.05). The tumor cells grew well in the control group, and were greatly inhibited in the thermochemotherapy group compared that in the other two groups. The tumor cells showed different degrees of apoptosis in the thermochemotherapy and chemotherapy groups under electron microscope. Conclusion: The tissue specific CD/5-FC thermochemotherapy system can inhibit the growth of liver metastasis of colon cancer in nude mice.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".