Neuronal microRNA regulation in Experimental Autoimmune Encephalomyelitis
Bibliographic record
Abstract
Multiple sclerosis (MS) is an autoimmune, neurodegenerative disease but the molecular mechanisms underlying neurodegenerative aspects of the disease are poorly understood. microRNAs (miRNAs) are powerful regulators of gene expression that regulate numerous mRNAs simultaneously and can thus regulate programs of gene expression. Here, we describe miRNA expression in neurons captured from mice subjected to experimental autoimmune encephalomyelitis (EAE), a model of central nervous system (CNS) inflammation. Lumbar motor neurons and retinal neurons were laser captured from EAE mice and miRNA expression was assessed by next-generation sequencing and validated by qPCR. We describe 14 miRNAs that are differentially regulated in both neuronal subtypes and determine putative mRNA targets though in silico analysis. Several upregulated neuronal miRNAs are predicted to target pathways that could mediate repair and regeneration during EAE. This work identifies miRNAs that are affected by inflammation and suggests novel candidates that may be targeted to improve neuroprotection in the context of pathological inflammation.
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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".