SorCS1 inhibits amyloid-β binding to neurexin and rescues amyloid-β–induced synaptic pathology
Bibliographic record
Abstract
Amyloid-β oligomers (AβOs), toxic peptide aggregates found in Alzheimer's disease, cause synapse pathology. AβOs interact with neurexins (NRXs), key synaptic organizers, and this interaction dampens normal trafficking and function of NRXs. Axonal trafficking of NRX is in part regulated by its interaction with SorCS1, a protein sorting receptor, but the impact of SorCS1 regulation of NRXs in Aβ pathology was previously unstudied. Here, we show competition between the SorCS1 ectodomain and AβOs for β-NRX binding and rescue effects of the SorCS1b isoform on AβO-induced synaptic pathology. Like AβOs, the SorCS1 ectodomain binds to NRX1β through the histidine-rich domain of NRX1β, and the SorCS1 ectodomain and AβOs compete for NRX1β binding. In cultured hippocampal neurons, SorCS1b colocalizes with NRX1β on the axon surface, and axonal expression of SorCS1b rescues AβO-induced impairment of NRX-mediated presynaptic organization and presynaptic vesicle recycling and AβO-induced structural defects in excitatory synapses. Thus, our data suggest a role for SorCS1 in the rescue of AβO-induced NRX dysfunction and synaptic pathology, providing the basis for a novel potential therapeutic strategy for Alzheimer's disease.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.001 |
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 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".