Development of Beta-Amyloid-Specific CAR-Tregs for the Treatment of Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disease that remains uncured. Its pathogenesis is characterized by the formation of β-amyloid (Aβ) plaques. The use of antigen-specific regulatory T cells (Tregs) through adoptive transfer has shown promise for the treatment of many inflammatory diseases, although the effectiveness of polyspecific Tregs is limited. Obtaining a sufficient number of antigen-specific Tregs from patients remains challenging. AIMS AND METHODS: To address this problem, we used an antibody-like single-chain variable fragment from a phage library and subsequently generated a chimeric antigen receptor (CAR) targeting β-amyloid. RESULTS: The β-amyloid-specific CARs obtained were stimulated by both recombinant and membrane-bound Aβ isolated from the murine brain. The generated CAR-Tregs showed a normal Treg phenotype, were antigen-specific activatable, and had suppressive capacity. CONCLUSION: This study highlights the potential of CAR technology to generate antigen-specific Tregs and presents novel approaches for developing functional CARs.
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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) | 0.000 | 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 | 0.001 |
| 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".