Intracerebroventricular infusion of monoclonal antibody or its derived Fab fragment against misfolded forms of SOD1 mutant delays mortality in a mouse model of ALS
Bibliographic record
Abstract
The finding of a secretion pathway and toxicity for mutant superoxide dismutase 1 (SOD1) raised up the possibility of using immunization approaches to reduce or neutralize the burden of toxic SOD1 species in the nervous system. Here we tested a passive immunization approach based on intracerebroventricular infusion in G93A-SOD1 mice of monoclonal antibodies specific to misfolded forms of SOD1 (mSOD1). We tested two monoclonal antibodies that bind distinct epitopes in mSOD1 and that do not bind to intact wild-type (WT) SOD1. One antibody succeeded in reducing the level of mSOD1 by 23% in the spinal cord and in prolonging the lifespan of G93A-SOD1 mice in proportion to the duration of treatment. However, another monoclonal antibody binding to a different SOD1 epitope failed to confer protection indicating that not all anti-SOD1 antibodies might be suitable for immunotherapy. Interestingly, the variable Fab fragment of an anti-SOD1 antibody was sufficient to confer some protection in G93A-SOD1 mice. The partial dispensability of Fc region should offer some advantages for development of immunotherapy with antibodies of smaller molecular size and low immunogenicity. From these results, we propose that passive immunization strategies should be considered as potential avenues for treatment of familial amyotrophic lateral sclerosis caused by SOD1 mutations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".