Improved mouse models for the study of treatment modalities for immune‐mediated platelet destruction
Bibliographic record
Abstract
BACKGROUND: We found when using a mouse model of immune thrombocytopenia (ITP) that platelet (PLT) nadir could not be maintained in the face of daily PLT antibody, making interpretation of treatment modalities difficult. This finding was documented to be at least in part due to increased thrombopoiesis as a result of a compensated thrombocytolytic state. Thus, it was important to develop an improved mouse model of human ITP so as to maintain PLT nadir over time. STUDY DESIGN AND METHODS: To maintain PLT nadir, we have developed two mouse models. One model uses single-dose sublethal total body gamma irradiation (TBI) in combination with daily low-dose PLT antibody administration while the second model uses escalation of the dose of PLT antibody over time. Both models maintain PLT nadir and allow for the study of treatment modalities without interference by marrow compensation. RESULTS: Surprisingly, intravenous immune globulin (IVIG) shows no efficacy when using the TBI combination model but works well using the dose-escalation mouse model. In contrast, anti-TER-119 shows efficacy using either mouse model. Our results indicate that the mechanism of action of IVIG requires a functional marrow and/or involves a radiosensitive regulatory cell. However, IVIG works using the dose-escalation model without TBI and the increase in PLT counts correlates directly with reticulated PLTs suggesting that the IVIG mechanism involves effects on megakaryopoiesis/thrombopoiesis. CONCLUSIONS: These mouse models should be useful for investigators wishing to maintain PLT nadir over prolonged periods of time for the study of mechanism and efficacy of various treatments for 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".