Brain‐Targeted Liposomes Loaded with Monoclonal Antibodies Reduce Alpha‐Synuclein Aggregation and Improve Behavioral Symptoms in Parkinson's Disease
Bibliographic record
Abstract
Monoclonal antibodies (mAbs) hold promise in treating Parkinson's disease (PD), although poor delivery to the brain hinders their therapeutic application. In the current study, it is demonstrated that brain-targeted liposomes (BTL) enhance the delivery of mAbs across the blood-brain-barrier (BBB) and into neurons, thereby allowing the intracellular and extracellular treatment of the PD brain. BTL are decorated with transferrin to improve brain targeting through overexpressed transferrin-receptors on the BBB during PD. BTL are loaded with SynO4, a mAb that inhibits alpha-synuclein (AS) aggregation, a pathological hallmark of PD. It is shown that 100-nm BTL cross human BBB models intact and are taken up by primary neurons. Within neurons, SynO4 is released from the nanoparticles and bound to its target, thereby reducing AS aggregation, and enhancing neuronal viability. In vivo, intravenous BTL administration results in a sevenfold increase in mAbs in brain cells, decreasing AS aggregation and neuroinflammation. Treatment with BTL also improve behavioral motor function and learning ability in mice, with a favorable safety profile. Accordingly, targeted nanotechnologies offer a valuable platform for drug delivery to treat brain neurodegeneration.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".