Ochratoxin A is not detectable in renal and testicular tumours
Bibliographic record
Abstract
INTRODUCTION: Ochratoxin-A (OTA) is one of the most abundant food-contaminating mycotoxins, known for its nephrotoxicity, neurotoxicity, gonadotoxicity, teratogenicity, immunosuppression and carcinogenesis. OTA has been linked to several genitourinary pathologies, including Balkan nephropathy and genitourinary malignancies. We examine OTA levels in serum samples and tumour specimens collected from patients with renal and testicular tumours. METHODS: Frozen samples were obtained from the Ontario Tumour Bank. Serum specimens, along with renal and testicular tumour biopsies, were included in this study. Normal tissue from the negative surgical margins of each tumour served as a control. OTA levels in serum was measured using the enzyme-linked immunosorbent assay (ELISA), while OTA detection in tissue specimens was determined using immunohistochemistry (IHC). RESULTS: We included specimens collected from 56 patients (36 men and 20 women). Histopathology of the 52 renal tumours included 31 (60%) conventional type renal cell carcinomas (RCC), 5 (10%) chromophobe RCC, 5 (10%) papillary RCC, 1 (2%) oncocytoma and 10 (19%) upper tract urothelial carcinoma (UC). The 4 testicular tumours included 1 seminomatous (25%) germ cell tumour and 3 (75%) non-seminomatous germ cell tumours. OTA was detected in the serum of renal tumour patients, with a range from 0.004 to 0.25 ng/mL (mean: 0.07 and median 0.06 ng/mL). There was no OTA signal detected by IHC staining in all tested renal and testicular tumours. CONCLUSIONS: The OTA levels detected in the serum of patients were highly variable and relatively low. No OTA was detected in the tissue samples.
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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) | 0.003 | 0.001 |
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".