MicroRNA abundance is altered in synaptoneurosomes during prion disease
Bibliographic record
Abstract
Discrepancy in synaptic structural plasticity is one of the earliest manifestations of the neurodegenerative state. In prion diseases, a reduction in synapses and dendritic spine densities is observed during preclinical disease in neurons of the cortex and hippocampus. The underlying molecular mechanisms of these alterations have not been identified but microRNAs (miRNAs), many of which are enriched at the synapse, likely regulate local protein synthesis in rapid response to stressors such as replicating prions. MiRNAs are therefore candidate regulators of these early neurodegenerative changes and may provide clues as to the molecular pathways involved. We therefore determined changes in mature miRNA abundance within synaptoneurosomes isolated from prion-infected, as compared to mock-infected animals, at asymptomatic and symptomatic stages of disease. During preclinical disease, miRNAs that are enriched in neurons including miR-124a-3p, miR-136-5p and miR-376a-3p were elevated. At later stages of disease we found increases in miRNAs that have previously been identified as deregulated in brain tissues of prion infected mice, as well as in Alzheimer's disease (AD) models. These include miR-146a-5p, miR-142-3p, miR-143-3p, miR-145a-5p, miR-451a, miR-let-7b, miR-320 and miR-150-5p. A number of miRNAs also decreased in abundance during clinical disease. These included almost all members of the related miR-200 family (miR-200a-3p, miR-200b-3p, miR-200c-3p, miR-141-3p, and miR-429-3p) and the 182 cluster (miR-182-5p and miR-183-5p).
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".