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Expression of the Neonatal Fc Receptor FcRn Is Not Required for the Amelioration of Murine ITP by IVIg or a Monoclonal Antibody

2010· article· en· W2556003890 on OpenAlexaff
Andrew R. Crow, Sara J. Suppa, Alan H. Lazarus

Bibliographic record

VenueBlood · 2010
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsCanadian Blood Services
Fundersnot available
KeywordsNeonatal Fc receptorAntibodyImmunologyMonoclonal antibodyImmunoglobulin GReceptorFc receptorImmune systemChemistryAutoantibodyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Abstract Abstract 2529 There are several theories as to the mechanism of intravenous immunoglobulin (IVIg) in the treatment of autoimmune diseases such as immune thrombocytopenia (ITP). One prominent theory involves accelerated pathogenic autoantibody clearance by saturation of the neonatal Fc Receptor (FcRn). FcRn is an IgG receptor, and FcRn within endosomes binds endocytosed IgG and diverts IgG from degradation. In the treatment of ITP, it has been theorized that high concentrations of IVIg saturate FcRn, reducing the ability of the pathogenic anti-platelet antibodies to bind FcRn, increasing their catabolism, and thus rapidly decreasing their serum concentration which results in a decrease in their ability to induce platelet clearance. Mice lacking FcRn have only 20–30% of the level of endogenous IgG as compared with wild-type mice and have an accelerated clearance rate of both endogenous and injected IgG. We have utilized these mice in a murine model of ITP to help understand the role, if any, that FcRn plays in IVIg's therapeutic activity. Both IVIg (2 g/kg body weight) and monoclonal antibodies to CD44 (2 mg/kg body weight; please see submitted abstract ID# 29504, “Amelioration of murine immune thrombocytopenia by CD44 antibodies: a potential therapy for ITP?”) successfully ameliorate murine ITP. To definitively determine if FcRn is required for the acute amelioration of ITP by these two therapeutics, we employed FcRn deficient mice in the murine ITP model. Here, we demonstrate that FcRn deficient mice (B6.129X1-Fcgrttm1Dcr/DcrJ) injected with an anti-platelet antibody exhibit a slightly more profound degree of thrombocytopenia than wild-type mice. FcRn deficient mice treated with IVIg or the anti-CD44 antibody KM114 (at a 3 log fold lower dosage than IVIg) were protected from ITP to the same extent as wild-type mice. FcRn has an absolute requirement for the protein β2 microglobulin (β2M) to be functionally expressed. Specifically, β2M deficient mice do not possess functional FcRn and also show low endogenous IgG levels and increased clearance of IgG. To verify and substantiate the results found with FcRn deficient mice, we next employed β2M deficient mice in the murine ITP model and found that β2M deficient mice (B6.129P2-B2mtm1Unc/J) treated with IVIg or KM114 were also protected from ITP to the same extent as wild-type mice. These data suggest that for both high dose IVIg as well as low dose monoclonal CD44 antibody treatment in an acute ITP model, FcRn expression is dispensable. Disclosures: No relevant conflicts of interest to declare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.026
GPT teacher head0.328
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes1
Has abstractyes

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