Proteomic analysis of synaptosomal protein expression reveals that cerebral ischemia alters lysosomal Psap processing
Bibliographic record
Abstract
Cerebral ischemia (CI) induces dramatic changes in synaptic structure and function that precedes delayed post-ischemic neuronal death. Here, a proteomic analysis was used to identify the effects of focal CI on synaptosomal protein levels. Contralateral and ipsilateral synaptosomes, prepared from adult mice subjected to 60 min middle cerebral artery occlusion, were isolated following 3, 6 and 20 h of reperfusion. Synaptosomal protein samples (n=3) were labeled using the cleavable ICAT system prior to analysis with nanoLC-MS/MS. Each sample was analyzed by LC-MS to identify differential expressions using InDEPT software and differentially expressed peptides were identified by targeted LC-MS/MS. A total of 62 differentially expressed proteins were identified and Gene Ontology classification (cellular component) indicated that the majority of the proteins were located in the mitochondria and other components consistent with synaptic localization. The observed alterations in synaptic protein levels poorly correlated with gene expression, indicating the involvement of post-transcriptional regulatory mechanisms in determining post-ischemic synaptic protein content. Additionally, immunohistochemistry analysis of prosaposin (Psap) and saposin C (SapC) indicates that CI disrupts Psap processing and glycosphingolipid metabolism. These results demonstrate that the synapse is adversely affected by CI and may play a role in mediating post-ischemic neuronal viability.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".