Lymphocyte immunophenotype in dogs with immune-mediated hematologic disease
Bibliographic record
Abstract
Immune-mediated hematologic diseases (IMHD) including immune-mediated hemolytic anemia (IMHA) and immune thrombocytopenia (ITP) can cause severe disease in dogs. The underlying immune system abnormalities associated with these conditions is not known. The hypotheses of this study were that dogs with IMHD would have increased frequencies of CD4+ and CD8 + lymphocytes, decreased frequencies and numbers of T regulatory cells, and increased frequencies of interleukin (IL)-17 + lymphocytes. Fifteen dogs with newly diagnosed IMHA or ITP and 15 healthy control dogs were recruited for this prospective study. Flow cytometry was used to enumerate CD4 + lymphocytes, CD8 + lymphocytes, T regulatory (CD4 + CD25 + Foxp3+) cells, and lymphocytes secreting IL-17 in dogs with IMHD at diagnosis, then 2 and 4 days after starting immunosuppressive treatment. Median proportion of CD4+ (Day 0: 3.4%, Day 2: 3.3%) and CD8+ (Day 0: 1%, Day 2: 0.6%) cells was lower in dogs with IMHD compared to control dogs (CD4 + 22.8%, CD8 + : 13.6%; P < 0.0001 for each). Additionally, T regulatory cells were reduced in IMHD dogs at Day 0 (0.2% versus 0.6% of total lymphocytes, P = 0.0025). Dogs with IMHD had a higher proportion of lymphocytes positive for IL-17 at Day 2 (1.3%) compared to control dogs (0.4%, P = 0.0024). Dogs with IMHD have immune system alterations at diagnosis and during early treatment characterized by a deficiency in T regulatory cells and an increase in IL-17 + lymphocyte. These changes might contribute to the pathogenesis of IMHA and ITP.
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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) | 0.001 | 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".