Synaptic Organizers in Alzheimer’s Disease: A Classification Based on Amyloid-β Sensitivity
Bibliographic record
Abstract
Synaptic pathology is one of the major hallmarks observed from the early stage of Alzheimer's disease (AD), leading to cognitive and memory impairment characteristic of AD patients. Synaptic connectivity and specificity are regulated by multiple trans-bindings between pre- and post-synaptic organizers, the complex of which exerts synaptogenic activity. Neurexins (NRXs) and Leukocyte common antigen-related receptor protein tyrosine phosphatases (LAR-RPTPs) are the major presynaptic organizers promoting synaptogenesis through their distinct binding to a wide array of postsynaptic organizers. Recent studies have shown that amyloid-β oligomers (AβOs), a major detrimental molecule in AD, interact with NRXs and neuroligin-1, an NRX-binding postsynaptic organizer, to cause synaptic impairment. On the other hand, LAR-RPTPs and their postsynaptic binding partners have no interaction with AβOs, and their synaptogenic activity is maintained even in the presence of AβOs. Here, we review the current evidence regarding the involvement of synaptic organizers in AD, with a focus on Aβ synaptic pathology, to propose a new classification where NRX-based and LAR-RPTP-based synaptic organizing complexes are classified into Aβ-sensitive and Aβ-insensitive synaptic organizers, respectively. We further discuss how their different Aβ sensitivity is involved in Aβ vulnerability and tolerance of synapses for exploring potential therapeutic approaches for AD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".