Oxidative dna Damage of Lymphocytes in Peripheral Blood and Ascites in Cancer Patients
Bibliographic record
Abstract
BACKGROUND: Patients with malignant ascites (ma) usually experience poor quality of life, and treatment of this symptom remains a challenge. Oxidative stress, which can cause oxidative damage to dna, plays a pivotal role in carcinogenesis; however, the relationship between oxidative stress and dna damage to tumour-associated lymphocytes (tals) in ma is unclear. METHODS: We measured the total antioxidant capacity (tac) of plasma and ma supernatant in 31 cancer patients with ma, and we used a comet assay to assess dna damage to both peripheral blood mononuclear cells (pbmcs) and tals. Measurements in age- and sex-matched healthy volunteers were used as controls. RESULTS: The tac of plasma was remarkably lower in cancer patients (9.73 ± 1.96 U/mL) than in healthy control subjects (11.31 ± 1.50 U/mL, p < 0.001). The tac of ma supernatant (6.34 ± 1.57 U/mL) was significantly lower than that of plasma in cancer patients (7.42 ± 1.36 U/mL, p < 0.001). The comet percentage of pbmcs was higher in cancer patients (17.26% ± 6.04%) than in healthy control subjects (9.44% ± 4.47%, p < 0.01). In cancer patients, the comet percentage of tals (36.14% ± 17.85%) was significantly higher than that of pbmcs (17.26% ± 6.04%, p < 0.001). In cancer patients with ma, negative correlations were observed between plasma tac and dna damage to pbmcs (r = -0.505, p = 0.004) and between the tac of ma supernatant and the comet percentage of tals (r = -0.588, p = 0.001). CONCLUSIONS: Results indicate the presence of significant oxidative damage to the dna of lymphocytes in peripheral blood and ascites from patients with ma, being especially higher in the cells from ascites. The lower tac of ma supernatant may be related to a higher degree of dna damage to tals. The present study suggests that an oxidant-antioxidant imbalance may be one of the mechanisms leading to the dna damage detected in peripheral blood and local tals in patients with ma, which may provide a novel approach to the treatment of ma.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".