Mechanisms of Action and Relative Efficacy of Glucocorticosteroid Treatment in Ameliorating Immune Thrombocytopenia Induced by Anti-platelet GPIbα Versus GPIIbIIIa Immune Responses
Bibliographic record
Abstract
Immune thrombocytopenia (ITP) is an autoimmune disorder, mediated mainly by autoantibodies against platelet glycoprotein GPIIbIIIa and GPIbα resulting in enhanced platelet destruction. Decreased platelet production and cellular immunity also contribute to ITP. GPIIbIIIa and GPIbα are distinct platelet receptors. Previous studies suggested that anti-GPIbα (versus anti-GPIIbIIIa)-mediated ITP is less responsive to IVIG therapy. However, little information is available whether antibody specificities also dictate efficacy of Glucocorticosteroids (GC), which are the first-line ITP treatment. Here, I first induced ITP in mice by passive administration of anti-GPIbα or anti-GPIIbIIIa antibodies. Results suggest GCs were more effective at amelioration of anti-GPIIbIIIa-mediated thrombocytopenia. I repeated this observation in an active ITP model, in which splenocytes from wild-type platelet immunized GPIbα-/- or GPIIIa-/- mice were engrafted into wild-type mice, which developed ITP. Thus, I established new murine models of ITP for GC therapy and demonstrated that anti-GPIbα-mediated thrombocytopenia may be less responsive to GC therapy.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".