Changes in systemic oxidative stress correlate to chemoresistance and poor prognosis features in women with breast cancer
Bibliographic record
Abstract
Objectives Breast cancer is a malignant neoplasm that affects women worldwide, and cytotoxic chemotherapy remains a primary treatment modality. In breast cancer, many women experience therapeutic failure and unfavorable clinical outcomes due to mechanisms related to chemoresistance acquisition, which may include oxidative stress . In this study, we investigated the systemic oxidative stress profile of women diagnosed with chemoresistant breast cancer and evaluated the correlation of this profile with clinicopathological features. Methods The oxidative stress levels were determined based on lipid peroxidation and nitric oxide metabolite (NOx) measurements. Chemoresistance was determined based on the Response Evaluation Criteria in Solid Tumors guidelines, and patients were categorized as responsive (complete response) or chemoresistant (partial or no response). Results Reduced lipid peroxide levels were observed independent of the pattern of chemotherapy response, without NOx variation. The type of drug schedule did not interfere with oxidative stress levels in the responsive patients. However, lipid peroxide levels were reduced in patients in the chemoresistant group receiving the combination of adryamicin + ciclofosfamide + Taxol . Additionally, lipid peroxidation strongly correlated with high histological grade and obesity in chemoresistant patients, while NOx correlated with disease stage, risk of death and recurrence, and menopausal status. Conclusion These findings highlight lipid peroxidation and NOx concentrations as putative markers of chemotherapy response in human breast cancer patients.
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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 | 0.000 | 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".