Antibody- and Cell-Mediated Immune Thrombocytopenia Are Differentially Sensitive to Intravenous Gammaglobulin Therapy
Bibliographic record
Abstract
Abstract Immune thrombocytopenic purpura (ITP) is a bleeding disorder characterized by IgG autoantibody-opsonized platelets prematurely being destroyed in the spleen although recent evidence suggests that thrombocytopenia in perhaps as many as 40% of patients with ITP can be mediated by CD8+ T cells. Although several animal models of immune thrombocytopenia have been developed, few are induced by platelet-specific autoimmune mechanisms nor have any demonstrated cell-mediated platelet destruction. We developed a murine model of ITP by first immunizaing GPIIIa (CD61) knockout (KO) mice against wildtype (WT) CD61+ platelet transfusions and subsequently transferring their splenocytes (5×104 cells/transfer) intraperitonealy into irradiated SCID mouse recipients. The SCID mice developed significant bleeding mortality and thrombocytopenia within 2 weeks post-transfer. Lower doses (<104) of immune splenocytes transferred induced thrombocytopenia in the SCID mouse recipients with no mortality. Depletion of lymphocyte subsets in the splenocytes before transfer showed that both CD19+ B cell (antibody)- and CD8+ T cell (cell)-mediated thrombocytopenia existed and that bleeding mortality was particularly associated with antibody-mediated thrombocytopenia. Treatment of the SCID mouse recipients bi-weekly with 2g/kg intravenous gammaglobulins (IVIg) demonstrated that IVIg was beneficial in eliminating bleeding mortality and thrombocytopenia only in the recipients displaying the antibody-mediated form of ITP. Cell-mediated bleeding mortality and thombocytopenia was completely resistant to IVIg therapy. This model suggests a potential reason why some patients with ITP fail IVIg therapy and may aid in the development of new therapeutics for individuals inflicted with cell mediated thrombocytopenia.
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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) | 0.001 | 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".