Concentration of Lipocalin Region of Collagen XXVII Alpha 1 in the Serum of Dogs with Hemangiosarcoma
Bibliographic record
Abstract
BACKGROUND: Hemangiosarcoma (HSA) is a common malignancy of dogs with characteristic early, aggressive metastasis. Diagnosis of HSA is challenging because of lack of sensitive and specific diagnostic tests. HYPOTHESIS: Specific proteins that are increased in serum of dogs with HSA might represent useful biomarkers of the disease. ANIMALS: Thirty-four dogs with HSA and 42 healthy dogs from the Ontario Veterinary College Teaching Hospital. METHODS: This case-control study compared serum proteins in dogs with HSA and healthy dogs. Proteins were separated by 2-dimensional difference gel electrophoresis and identified by liquid chromatography and tandem mass spectrometry. RESULTS: Western blot analysis showed that serum collagen XXVII peptide concentration in serum of dogs with large metastatic HSA burdens (1,488, 231-3,754 DU; median, minimum-maximum); was, on average, 9.5-fold higher than in healthy dogs (156; 46-2,101 DU). While concentrations for dogs with osteosarcomas (678; 124-3,251 DU), lymphomas (423; 92-2,777 DU), carcinomas (1,022; 177-3,448 DU), and inflammatory disease were also increased, values were consistently lower than those for HSA. Receiver operating characteristic curves revealed an estimated area under the curve of 83% for HSA cases whereas areas for other neoplastic and nonneoplastic diseases were nondiscriminatory. Serum collagen XXVII peptide concentration before splenectomy (1,350; 1,156-1,929 DU) was reduced after tumor removal (529; 452-562 DU) and chemotherapy but increased in 2 dogs with tumor recurrence (511-945 DU; 493-650 DU). CONCLUSIONS AND CLINICAL IMPORTANCE: Collagen XXVII peptide might be useful for diagnosis and monitoring of advanced HSA.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".