Expansion of regulatory T cells by CD28 superagonistic antibodies attenuates neurodegeneration in A53T-α-synuclein Parkinson’s disease mice
Bibliographic record
Abstract
Abstract Background Regulatory CD4 + CD25 + FoxP3 + T cells (Treg) are a subgroup of T lymphocytes involved in maintaining immune balance. Disturbance of Treg number and impaired suppressive function of Treg correlate with Parkinson’s disease severity. Superagonistic anti-CD28 monoclonal antibodies (CD28SA) activate Treg and cause their expansion to create an anti-inflammatory environment. Methods Using the AAV1/2-A53T-α-synuclein Parkinson’s disease mouse model that overexpresses the pathogenic human A53T-α-synuclein (hαSyn) variant in dopaminergic neurons of the substantia nigra, we assessed the neuroprotective and disease-modifying efficacy of a single intraperitoneal dose of CD28SA given at an early disease stage. Results CD28SA led to Treg expansion 3 days after delivery in hαSyn Parkinson’s disease mice. At this timepoint, an early pro-inflammation was observed in vehicle-treated hαSyn Parkinson’s disease mice with elevated percentages of CD8 + CD69 + T cells in brain and increased levels of interleukin-2 (IL-2) in the cervical lymph nodes and spleen. These immune responses were suppressed in CD28SA-treated hαSyn Parkinson’s disease mice. Early treatment with CD28SA attenuated dopaminergic neurodegeneration in the SN of hαSyn Parkinson’s disease mice accompanied with reduced brain numbers of activated CD4 + , CD8 + T cells and CD11b + microglia observed at the late disease-stage 10 weeks after AAV injection. In contrast, a later treatment 4 weeks after AAV delivery failed to reduce dopaminergic neurodegeneration. Conclusions Our data indicate that immune modulation by Treg expansion at a timepoint of overt inflammation is effective for treatment of hαSyn Parkinson’s disease mice and suggest that the concept of early immune therapy could pose a disease-modifying option for Parkinson’s disease patients.
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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".