Anti‐D (WinRho SD<sup>™</sup>) treatment of children with chronic autoimmune thrombocytopenic purpura stimulates transient cytokine/chemokine production
Bibliographic record
Abstract
Intravenous anti-D is often used in the treatment of autoimmune thrombocytopenic purpura (AITP), but little is known about its mechanisms of action. To investigate anti-D's potential in vivo mechanism(s) of action, a small group (N = 7) of children with chronic AITP was studied. The children initially received either 25 or 50 microg/kg of WinRho-SD in a four-cycle cross-over trial, and peripheral blood samples from the first and third cycles were assessed for cytokine levels at pre-treatment, 3 hr, 1 day, and 8 days post-treatment. Results showed that platelet counts significantly increased in all the children by day 8 post-treatment. Analysis of serum by ELISA showed that there was a significant but transient rise in both pro- and anti-inflammatory cytokine/chemokine levels (e.g., IL1RA, IL6, GM-CSF, MCP-1 alpha, TNF-alpha and MCP-1) by 3 hr post-treatment in both cycles which returned to baseline levels by 8 days post-treatment. These results suggest that anti-D administration may initially activate the RES in the form of cytokine/chemokine secretion, which is subsequently followed by an increase in platelet counts. It is possible that the induced cytokine/chemokine storm may have an effect on several physiological processes such as those mediating either adverse effects or potentially RES phagocytic activity.
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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 | 0.000 |
| 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".