Urine Metabolite Analysis Offers Potential Early Diagnosis of Ovarian and Breast Cancers
Bibliographic record
Abstract
PURPOSE: Metabolomics is a new, rapidly expanding field dedicated to the global study of metabolites in biological systems. In this article metabolomics is applied to find urinary biomarkers for breast and ovarian cancer. EXPERIMENTAL DESIGN: Urine samples were collected from early- and late-stage breast and ovarian cancer patients during presurgical examinations and randomly from females with no known cancer. After quantitatively measuring a set of metabolites using nuclear magnetic resonance spectroscopy, both univariate and multivariate statistical analyses were employed to determine significant differences. RESULTS: Metabolic phenotypes of breast and ovarian cancers in comparison with normal urine and with each other revealed significance at Bonferroni-corrected significance levels resulting in unique metabolite patterns for breast and ovarian cancer. Intermediates of the tricarboxylic acid cycle and metabolites relating to energy metabolism, amino acids, and gut microbial metabolism were perturbed. CONCLUSIONS: The results presented here illustrate that urinary metabolomics may be useful for detecting early-stage breast and ovarian cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".