Impact of body mass index on the circulating levels of nitric oxide metabolites in clinicopathological features from women with breast cancer
Bibliographic record
Abstract
Abstract To investigate the clinical meaning of systemic nitric oxide metabolites (NOx) by comparing eutrophic and overweight/obese patients with breast cancer, considering clinical factors determinant of disease prognosis. A total of 61 women diagnosed with breast cancer were included in the study. NOx estimative was performed on plasma samples using the cadmium–copper‐Griess method. It was then categorized according to the age at diagnosis, body mass index, menopausal status, tumor histological features, molecular subtype lymph nodal invasion, and emboli presence, considering p ≤ 0.05 as significant. A significant augment was observed in NOx levels from overweight patients carrying Luminal B tumors concerning the Luminal B eutrophic ones. There was a considerable reduction in NOx levels in eutrophic postmenopausal patients compared to the overweight postmenopausal ones. Patients bearing tumor sizes between 2 and 5 cm in the eutrophic group had lower levels of NOx, concerning the overweight patients carrying tumors of the same size interval. Circulating NOx levels change significantly according to the trophic‐adipose status of breast cancer patients, and it is further affected by prognostic factors related to poor disease prognosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".