Reduction of αSYN Pathology in a Mouse Model of PD Using a Brain-Penetrating Bispecific Antibody
Bibliographic record
Abstract
Immunotherapy targeting aggregated alpha-synuclein (αSYN) is a promising approach for the treatment of Parkinson's disease. However, brain penetration of antibodies is hampered by their large size. Here, RmAbSynO2-scFv8D3, a modified bispecific antibody that targets aggregated αSYN and binds to the transferrin receptor for facilitated brain uptake, was investigated to treat αSYN pathology in transgenic mice. Ex vivo analyses of the blood and brain distribution of RmAbSynO2-scFv8D3 and the unmodified variant RmAbSynO2, as well as in vivo analyses with microdialysis and PET, confirmed fast and efficient brain uptake of the bispecific format. In addition, intravenous administration was shown to be superior to intraperitoneal injections in terms of brain uptake and distribution. Next, aged female αSYN transgenic mice (L61) were administered either RmAbSynO2-scFv8D3, RmAbSynO2, or PBS intravenously three times over five days. Levels of TBS-T soluble aggregated αSYN in the brain following treatment with RmAbSynO2-scFv8D3 were decreased in the cortex and midbrain compared to RmAbSynO2 or PBS controls. Taken together, our results indicate that facilitated brain uptake of αSYN antibodies can improve treatment of αSYN pathology.
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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 | 0.001 |
| 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) | 0.002 | 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".