Characterization of a pancreatic islet cell tumor in a polar bear (<i>Ursus maritimus</i>)
Bibliographic record
Abstract
Herein, we report a 25-year-old male polar bear suffering from a pancreatic islet cell tumor. The aim of this report is to present a case of this rare tumor in a captive polar bear. The implication of potential risk factors such as high carbohydrate diet or the presence of amyloid fibril deposits was assessed. Necropsy examination revealed several other changes, including nodules observed in the liver, spleen, pancreas, intestine, and thyroid glands that were submitted for histopathologic analysis. Interestingly, the multiple neoplastic nodules were unrelated and included a pancreatic islet cell tumor. Immunohistochemistry of the pancreas confirmed the presence of insulin and islet amyloid polypeptide (IAPP) within the pancreatic islet cells. The IAPP gene was extracted from the paraffin-embedded liver tissue and sequenced. IAPP cDNA from the polar bear exhibits some differences as compared to the sequence published for several other species. Different factors responsible for neoplasms in bears such as diet, infectious agents, and industrial chemical exposure are reviewed. This case report raised several issues that further studies may address by evaluating the prevalence of cancers in captive or wild animals.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".