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Record W3156454816

The Role of Modified Fc Fragments in Treating Autoimmune Diseases: A Potential Replacement for Intravenous Immunoglobulin

2020· dissertation· en· W3156454816 on OpenAlexfundno aff
Bonnie J.B. Lewis

Bibliographic record

VenueTSpace · 2020
Typedissertation
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsnot available
FundersHealth CanadaCanadian Blood ServicesAustralian GovernmentGovernment of CanadaCSL Behring
KeywordsAntibodyIntravenous ImmunoglobulinsMedicineImmunologyFragment crystallizable region
DOInot available

Abstract

fetched live from OpenAlex

High-dose (1-2 g/kg) intravenous immunoglobulin (IVIg), and more recently, subcutaneously delivered immunoglobulin (SCIg), are used to treat a variety of autoimmune diseases; however, there are challenges associated with product production and availability. These challenges have provided incentives to develop a human recombinant fragment crystallizable region (Fc) as a more potent alternative to IVIg and SCIg for the treatment of autoimmune diseases where its mechanism has been suggested to be Fc-dependent. Various Fc multimers have been produced that show enhanced efficacy compared to IVIg for amelioration of disease in animal models, such as primary immune thrombocytopenia (ITP) and rheumatoid arthritis (RA). Recently, a recombinant human immunoglobulin (Ig) G1 Fc hexamer entitled Fc-µTP-L309C was produced by CSL Behring by fusing the 18 amino acid (aa) IgM tailpiece to the C-terminus of a variant human IgG1 Fc with a point mutation at position 309. To better understand whether Fc-µTP-L309C is good replacement therapy for IVIg/SCIg, I first examined its efficacy in a mouse model of ITP. I demonstrated that Fc-µTP-L309C is more efficacious than SCIg at ameliorating ITP and at blocking Fc gamma receptor (FcγR)-mediated phagocytosis. With the limited amount of studies performed on the therapeutic efficacy of IVIg/SCIg in RA, I decided to investigate the efficacy of IVIg and SCIg in the K/BxN serum transfer model and in the endogenous K/BxN model of RA and compare it to that of Fc-µTP-L309C. Again, I showed that Fc-µTP-L309C is more efficacious than SCIg at ameliorating RA in the K/BxN mouse models. Furthermore, I showed that Fc-µTP-L309C affected both the innate and the adaptive immune system in the K/BxN endogenous model of RA. Fc-µTP-L309C decreased auto-antibody (Ab) production by B cells and the subsequent deposition of auto-Abs on the articular cartilage. Fc-µTP-L309C also increased transforming growth factor beta (TGF-β) and forkhead box P3 (FoxP3)+ T regulatory cells (Tregs) in the joints of K/BxN mice. Fc-µTP-L309C also blocked FcγRIII on neutrophils and prevented interleukin-1 beta (IL-1β) release from neutrophils. Thus, Fc-µTP-L309C serves as a potential replacement for IVIg for Ab mediated autoimmune diseases and its mechanism is likely multifactorial and different depending on the disease.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.014
GPT teacher head0.339
Teacher spread0.325 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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
Published2020
Admission routes1
Has abstractyes

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