Vitamin C and diallyl sulfide as chemosensitizers to cisplatin in treating hepatocellular carcinoma
Bibliographic record
Abstract
Background The resistance to chemotherapy is a major obstacle in the treatment of hepatocellular carcinoma (HCC), necessitating the discovery of additional agents. The use of natural products in this respect is extensively under investigation. Methods Two hundred and ten male albino rats were used, divided into 14 groups. Selected groups were pre-treated with vitamin C (ascorbic acid, AA) and/or diallyl sulphide (DAS). Hepatocellular dysplasia was initiated by a single intra-peritoneal (IP) injection of diethyl nitrosamine (DENA), diabetes was induced by a single IP injection of Streptozotocin (STZ). Other groups were treated with cisplatin (CP) alone or combined with AA and/or DAS for 14 weeks. This work aims to check if naturally occurring materials can help in improving response to CP chemotherapy using ploylol profile as a new index in management of HCC. Results The results revealed that DENA significantly increased relative liver weight, serum ALT, AST and GGT activities, AFP, TNF-α and IL-6 levels, expression of aldose reductase (AR), sorbitol dehydrogenase (SDH) and Bcl2 proteins in the liver with decrease in body weight, expression of Bax protein and Bax/Bcl2 ratio in the liver. These effects were more pronounced in DENA+STZ group. These parameters showed relative correlation to AFP levels in HCC, in response to AA and/or DAS treatment except for SDH. Treatment with CP and/or AA and/or DAS significantly modulated most of these parameters except for SDH which showed no significant change in response to the suggested treatment. Conclusions In conclusion, AA and/or DAS showed apparent chemo-sensitizing, anti-inflammatory, AR inhibitory, apoptotic inducing and anti-diabetic activities, indicating new aspects for use as adjuvant to chemotherapy. Induction of diabetes in hepatocellular dysplasia -bearing rats showed higher resistance to chemotherapy. Ploylol profile is a useful prognostic tool in HCC patients with diabetic interference.
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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".