Using the K/BxN mouse model of endogenous, chronic, rheumatoid arthritis for the evaluation of potential immunoglobulin-based therapeutic agents, including IVIg and Fc-μTP-L309C, a recombinant IgG1 Fc hexamer
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: High-dose intravenous immunoglobulin (IVIg), and more recently, subcutaneously-delivered Ig (SCIg), are used to treat a variety of autoimmune diseases; however, there are challenges associated with product production, availability, access and efficacy. These challenges have provided incentives to develop a human recombinant Fc as a more potent alternative to IVIg and SCIg for the treatment of autoimmune diseases. Recently, a recombinant human IgG1 Fc hexamer (Fc-μTP-L309C) was shown to be more efficacious than IVIg in a variety of autoimmune mouse models. We have now examined its efficacy compared to IVIg and SCIg in the K/BxN mouse model of endogenous, chronic rheumatoid arthritis (RA). RESULT: Using the serum-transfer K/BxN model and the endogenous autoimmune model, amelioration of the arthritis was achieved. Effective treatment required high and frequent doses of IVIg, SCIg and Fc-μTP-L309C. However, Fc-μTP-L309C was efficacious at 10-fold lower doses that IVIg/SCIg. Also, arthritis could be prevented when Fc-μTP-L309C was given prior to onset of the arthritis in both the endogenous model and in the serum transfer model. CONCLUSIONS: Our results show that Fc-μTP-L309C is a powerful treatment for the prevention and amelioration of severe, chronic arthritis in a true autoimmune mouse model of RA. Thus, the K/BxN endogenous arthritis model should be useful for testing potential therapeutics for RA. Our findings provide rationale for further examination of the treatment efficacy of immunoglobulin-based therapeutics in rheumatoid arthritis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it