The Effect of Glucocorticoids on Canine Lymphocyte Marker Expression and Apoptosis
Bibliographic record
Abstract
BACKGROUND: Glucocorticoids are commonly administered to dogs for the treatment of inflammatory disorders, autoimmunity and cancers such as lymphoma. Despite evidence of clinical efficacy, understanding of the effects of glucocorticoids on cells of the canine immune system is limited. HYPOTHESIS: Glucocorticoids affect the expression of phenotypic markers on canine lymphocytes and induce apoptosis. ANIMALS: Fifteen healthy mixed breed dogs. METHODS: Prospective randomized study. Prednisone was administered orally for 3 days, and cells aspirated from the popliteal lymph node before prednisone administration, and on days 1, 3, 10, 17, 24, and 38, were labeled with antibodies against canine CD3, CD4, CD8alpha, CD18, CD21, CD45, CD45RA, and CD90 molecules, and analyzed by flow cytometry. Additional samples were cultured in media with prednisolone for 24 hours and analyzed by cytometry for marker expression, and by gel electrophoresis for DNA fragmentation. RESULTS: Treatment of dogs with glucocorticoids resulted in reduced (p < or = .05) proportions of CD3 (days 1, 3, 17, and 24), CD4 (days 3 and 10), CD21 (day 1, 3, and 38), CD45RA (day 17) and CD90 (days 1, 10, and 17) expressing lymphocytes, and reduced intensity of CD18 (day 17) and CD45 (day 17 and 24) molecules on nodal lymphocytes. Culture oflymphocytes with prednisolone for 24 hours caused a significant reduction in the expression of all markers (p < or = .05) and DNA fragmentation. CONCLUSIONS AND CLINICAL IMPORTANCE: Glucocorticoids significantly alter the expression of phenotypic markers on canine lymphocytes, and in vitro induce apoptosis. These findings identify potential mechanisms for clinical immunosuppression from glucocorticoid treatment.
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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 | 0.002 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".