A novel synaptopathy‐defective synaptic vesicle protein trafficking in the mutant CHMP2B mouse model of frontotemporal dementia
Bibliographic record
Abstract
Mutations in the ESCRT-III subunit CHMP2B cause frontotemporal dementia (FTD) and lead to impaired endolysosomal trafficking and lysosomal storage pathology in neurons. We investigated the effect of mutant CHMP2B on synaptic pathology, as ESCRT function was recently implicated in the degradation of synaptic vesicle (SV) proteins. We report here that expression of C-terminally truncated mutant CHMP2B results in a novel synaptopathy. This unique synaptic pathology is characterised by selective retention of presynaptic SV trafficking proteins in aged mutant CHMP2B transgenic mice, despite significant loss of postsynaptic proteins. Furthermore, ultrastructural analysis of primary cortical cultures from transgenic CHMP2B mice revealed a significant increase in the number of presynaptic endosomes, while neurons expressing mutant CHMP2B display defective SV recycling and alterations to functional SV pools. Therefore, we reveal how mutations in CHMP2B affect specific presynaptic proteins and SV recycling, identifying CHMP2B FTD as a novel synaptopathy. This novel synaptopathic mechanism of impaired SV physiology may be a key early event in multiple forms of FTD, since proteins that mediate the most common genetic forms of FTD all localise at the presynapse.
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 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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".