Amelioration of Murine Passive Immune Thrombocytopenia by IVIg and a Therapeutic Monoclonal CD44 Antibody Does Not Require the Myd88 Signaling Pathway
Bibliographic record
Abstract
Immune thrombocytopenia (ITP) is an autoimmune bleeding disorder characterized by a low platelet count and the production of anti-platelet antibodies. The majority of ITP patients have antibodies to platelet integrin α(IIb)β₃ (GPIIbIIIa) which can direct platelet phagocytosis by macrophages. One effective treatment for patients with ITP is intravenous immunoglobulin (IVIg) which rapidly reverses thrombocytopenia. The exact mechanism of IVIg action in human patients is unclear, although in mouse models of passive ITP, IVIg can rapidly increase platelet counts in the absence of adaptive immunity. Another antibody therapeutic that can similarly increase platelet counts independent of adaptive immunity are CD44 antibodies. Toll-like receptors (TLRs) are pattern recognition receptors which play a central role in helping direct the innate immune system. Dendritic cells, which are notable for their expression of TLRs, have been directly implicated in IVIg function as an initiator cell, while CD44 can associate with TLR2 and TLR4. We therefore questioned whether IVIg, or the therapeutic CD44 antibody KM114, mediate their ameliorative effects in a manner dependent upon normal TLR function. Here, we demonstrate that the TLR4 agonist LPS does not inhibit IVIg or KM114 amelioration of antibody-induced thrombocytopenia, and that these therapeutics do not ameliorate LPS-induced thrombocytopenia. IVIg was able to significantly ameliorate murine ITP in C3H/HeJ mice which have defective TLR4. All known murine TLRs except TLR3 utilize the Myd88 adapter protein to drive TLR signaling. Employing Myd88 deficient mice, we found that both IVIg and KM114 ameliorate murine ITP in Myd88 deficient mice to the same extent as normal mice. Thus both IVIg and anti-CD44 antibody can mediate their ameliorative effects in murine passive ITP independent of the Myd88 signaling pathway. These data help shed light on the mechanism of action of IVIg and KM114 in the amelioration of murine 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) | 0.001 | 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 | 0.001 | 0.002 |
| 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".