Vascular endothelial growth factor: a blood biomarker in canine idiopathic pulmonary fibrosis.
Bibliographic record
Abstract
Canine idiopathic pulmonary fibrosis (CIPF) is a progressive interstitial lung disease that mainly occurs in the West Highland white terrier (WHWT) breed. CIPF diagnosis is challenging. Identification of measurable markers of fibrosis might be helpful in this circumstance. VEGF is an angiogenic regulator involved in a variety of physiological and pathological processes. The aims of the present study were (1) to investigate the potential role of VEGF as a peripheral blood biomarker in CIPF; and (2) to investigate possible breed-related differences in basal VEGF concentration, that might explain the high predisposition of the WHWT breed for CIPF. Therefore, VEGF was determined by ELISA in the serum of 14 WHWT with CIPF, 18 healthy WHWT, and 85 healthy dogs of other breeds, including : 14 Scottish terrier (ST), 16 Jack Russell terrier (JRT), 15 Maltese, 14 King Charles Spaniel (KCS), 12 Labrador Retriever (LR) and 14 Malinois Belgian Shepherd. Eight CIPF WHWT (57%) have serum VEGF concentrations above the kit detection limit (39.1 pg/ml) compared to 1 WHWT (0.05%) in the group of healthy dogs (P=0.001). Concerning inter-breed differences in healthy dogs, most values obtained were below the kit detection limit with only 3 KCS (21%), 3 JRT (19%), 3 LR (25%) and 1 ST (7%) having VEGF serum levels above 39.1 pg/ml (P=0.147). Results of the present study show that (1) VEGF might be an interesting blood biomarker for CIPF; (2) canine VEGF Quantikine Elisa kit is not appropriate for measurement of serum VEGF levels in healthy canine populations.
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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 | 0.001 | 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) | 0.001 | 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".