Examination of EROD Activity and Fibronectin Levels in Lake Whitefish as Biomarkers of Neoplasia
Bibliographic record
Abstract
The study of tumors in fish has been hampered by the lack of suitable bioindicators especially because the ultimate diagnosis is not achieved until the fish are dead or killed. The present study was undertaken to develop simple, reliable and minimally invasive procedures to detect neoplasms in lake whitefish (Coregonus clupeaformis) and investigate their applicability as fish tumor biomarkers. Ethoxyresorufin-o-deethylase (EROD) assays have been widely used as an indicator of the activity of cytochrome P450-1A1, an isozyme located in a variety of tissues and in measurable amounts in the liver of many vertebrates. A fluorometric protocol using very small sized samples such as those from biopsies was used to measure EROD activity. Although no direct correlation could be made between EROD activity and liver tumor occurrence, EROD activity was significantly higher in livers with high melanomacrophage aggregates (P<0.001). Fibronectin (Fn) is a plasma and cellular protein that can be conveniently measured from biological fluids and has been used as tumor biomonitor in humans. Changes in Fn within serum and tissue samples of whitefish were monitored. Mean Fn levels in serum samples (n=65) was 2.03% of total serum proteins. Among the serologically evaluated fish, three had hepatic neoplasia as diagnosed by histological means. Fn levels in two of these were reduced at 1.89 and 1.22% of total serum proteins, however, no statistical correlations could be made with such small sample size, and further analysis is in progress.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 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".