Serum C-reactive protein concentrations in Nova Scotia Duck Tolling Retrievers with immune-mediated rheumatic disease
Bibliographic record
Abstract
Nova Scotia Duck Tolling Retrievers (NSDTRs) are a dog breed often affected by immune-mediated rheumatic disease (IMRD), a disorder characterised by chronic stiffness and joint pain. Most, but not all, dogs with IMRD, have antinuclear antibodies (ANA), which are also commonly present in the autoimmune disease systemic lupus erythematosus (SLE). The clinical and diagnostic findings of IMRD indicate that it is an SLE-related disorder. C-reactive protein (CRP), an acute phase protein, is a quantitative marker of inflammation for many diseases and is used for diagnosing and monitoring systemic inflammation in both humans and dogs. However, in human SLE, CRP concentrations are often elevated but correlate poorly with disease activity; they can be low in individual patients with active disease. The aim of the study was to investigate CRP in a group of NSDTRs with the SLE-related disorder IMRD. The hypothesis was that CRP concentrations would be increased in dogs with IMRD compared to healthy dogs, but that the increase would be mild. Serum CRP concentrations were measured in 18 IMRD-affected NSDTRs and 19 healthy control NSDTRs using two different canine-specific CRP assays. Dogs with IMRD and ANA had higher CRP concentrations than the control dogs, but the concentrations were below the clinical decision limit for systemic inflammation for most of the IMRD dogs. These results indicate that CRP concentrations were increased in dogs with IMRD and ANA, but the increase was mild, similar to what has been observed in human SLE.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".