The Mechanism of Rh-Immune Globulin Prophylaxis Involves Significant Increases in the Immunosuppressive Cytokines TGFβ and PGE2.
Bibliographic record
Abstract
Abstract For more than 40 years, hemolytic disease of the newborn (HDN) caused by anti-Rh(D) antibody produced by a pregnant mother to her Rh(D)+ baby has been prevented by Rh(D)-immune globulin prophylaxis. Surprisingly, although a number of theories have been proposed, the mechanism of action of this immunosuppressive treatment remains completely unknown (Kumpel BM, Immunol Lett.2002;82:67–73). One potential mechanism of action is the production of one or several strongly immunosuppressive cytokines capable of blocking a primary immune response. Thus, to begin to unravel the possible mechanism(s) of the immunosuppression induced by administration of Rh(D)-immune globulin, we have examined production of a number of immunomodulatory cytokines following administration of Rh(D)-immune globulin. After informed consent, we measured levels of 17 different cytokines pre- and 48 hours post-administration of 300 μg of anti-Rh(D)(WinRhoSDF) in 10 healthy women candidates for Rh(D)-immune globulin prophylaxis. We used platelet-poor plasma from citrated whole blood and quantitative ELISA having the most sensitive detection limits. We observed no striking changes in levels of the cytokines IL-1 sRII, IL-12 p40, IL-16, or MCP-1. Levels of IL-4, IL-5, IL-10, IL-13, IL-17, MIP-1α, GM-CSF, TNFβ, and IFNγ remained below detection levels both pre- and post-testing. However, IL-1ra levels showed a slight to moderate decrease in 7 of 10 women after Rh(D)-immune globulin administration. In contrast, levels of TGFβ-1 increased, >1.3-fold in 7 of 10 women and >2-fold in 4 of 10 women. In one instance, the increase in TGFβ-1 (42, 855 pg/mL) was >5-fold and this woman also had a significant increase in TGFβ-2 (352 pg/mL). In addition to TGFβ, 4 of 10 women had increases of >1.5-fold in PGE2. Statistical analyses using ANOVA, paired Student’s t-test, and Wilcoxon signed-rank, for the combined results of all 10 women receiving Rh(D)-immune globulin indicated that only TGFβ and PGE2 were significantly elevated post administration of Rh(D)-immune globulin. These results indicate that Rh(D)-immune prophylaxis can induce high levels of the strongly immunosuppressive cytokines TGFβ and PGE2. Both of these molecules have been shown to induce profound immunosuppression including prevention of primary immune responses (Ludviksson BR, et al., Eur J Immunol.2000;30:2101–2111; Zhou H, Lamont SJ, Int J Fertil.1986;31:305–310). Our findings represent the first clear evidence for a mechanism of action of Rh(D)-immune prophylaxis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".