A monoclonal antibody against synthetic Aβ dimer assemblies neutralizes brain‐derived synaptic plasticity‐disrupting Aβ
Bibliographic record
Abstract
Diverse lines of evidence indicate that pre-fibrillar, diffusible assemblies of the amyloid β-protein (Aβ) play an important role in Alzheimer's disease pathogenesis. Although the precise molecular identity of these soluble toxins remains unsettled, recent experiments suggest that sodium dodecyl sulfate (SDS)-stable Aβ dimers may be the basic building blocks of Alzheimer's disease-associated synaptotoxic assemblies and as such present an attractive target for therapeutic intervention. In the absence of sufficient amounts of highly pure cerebral Aβ dimers, we have used synthetic disulfide cross-linked dimers (free of Aβ monomer or fibrils) to generate conformation-specific monoclonal antibodies. These dimers aggregate to form kinetically trapped protofibrils, but do not readily form fibrils. We identified two antibodies, 3C6 and 4B5, which preferentially bind assemblies formed from covalent Aβ dimers, but do not bind to Aβ monomer, amyloid precursor protein, or aggregates formed by other amyloidogenic proteins. Monoclonal antibody 3C6, but not an IgM isotype-matched control antibody, ameliorated the plasticity-disrupting effects of Aβ extracted from the aqueous phase of Alzheimer's disease brain, thus suggesting that 3C6 targets pathogenically relevant Aβ assemblies. These data prove the usefulness of covalent dimers and their assemblies as immunogens and recommend further investigation of the therapeutic and diagnostic utility of monoclonal antibodies raised to such assemblies.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".