Early α-synuclein aggregation decreases corticostriatal glutamate drive and synapse density
Bibliographic record
Abstract
Neuronal inclusions of α-synuclein (α-syn) are pathological hallmarks of Parkinson's disease (PD) and Dementia with Lewy Bodies (DLB). α-Syn pathology accumulates in cortical neurons which project to the striatum. To understand how α-syn pathology affects cortico-striatal synapses at early time points before significant dopamine neuron loss, pre-formed α-syn fibrils (PFF) were injected into the striatum to induce endogenous α-syn aggregation in corticostriatal-projecting neurons. Electrophysiological recordings of striatal spiny projection neurons (SPNs) from acute slices found a significant decrease in evoked corticostriatal glutamate release and corticostriatal synaptic release sites in mice with PFF-induced aggregates compared to monomer injected mice. Expansion microscopy, confocal microscopy and Imaris reconstructions were used to identify VGLUT1 positive presynaptic terminals juxtaposed to Homer1 positive postsynaptic densities, termed synaptic loci. Quantitation of synaptic loci density revealed an early loss of corticostriatal synapses. Immunoblots of the striatum showed reductions in expression of pre-synaptic proteins VGLUT1, VAMP2 and Snap25, in mice with α-syn aggregates compared to controls. Paradoxically, a small percentage of remaining VGLUT1+ synaptic loci positive for pS129-α-syn aggregates showed enlarged volumes compared to nearby synapses without α-syn aggregates. Our combined physiology and high-resolution imaging data point to an early loss of corticostriatal synapses in mice harboring α-synuclein inclusions, which may contribute to impaired basal ganglia circuitry in PD and DLB.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".