MicroRNA-223 protects neurons from degeneration in experimental autoimmune encephalomyelitis
Bibliographic record
Abstract
Multiple sclerosis is a chronic inflammatory, demyelinating, and neurodegenerative disease affecting the brain, spinal cord and optic nerves. Neuronal damage is triggered by various harmful factors that engage diverse signalling cascades in neurons; thus, therapeutic approaches to protect neurons will need to focus on agents that can target multiple biological processes. We have therefore focused our attention on microRNAs: small non-coding RNAs that primarily function as post-transcriptional regulators that target messenger RNAs and repress their translation into proteins. A single microRNA can target many functionally related messenger RNAs making microRNAs powerful epigenetic regulators. Dysregulation of microRNAs has been described in many neurodegenerative diseases including multiple sclerosis. Here, we report that two microRNAs, miR-223-3p and miR-27a-3p, are upregulated in neurons in the experimental autoimmune encephalomyelitis mouse model of CNS inflammation and in grey matter-containing multiple sclerosis lesions. Prior work has shown peripheral blood mononuclear cell conditioned media causes sublethal degeneration of neurons in culture. We find overexpression of miR-27a-3p or miR-223-3p protects dissociated cortical neurons from condition media mediated degeneration. Introduction of miR-223-3p in vivo in mouse retinal ganglion cells protects their axons from degeneration in experimental autoimmune encephalomyelitis. In silico analysis revealed that messenger RNAs involved in glutamate receptor signalling are enriched as miR-27a-3p and miR-223-3p targets. We observe that antagonism of NMDA and AMPA type glutamate receptors protects neurons from condition media dependent degeneration. Our results suggest that miR-223-3p and miR-27a-3p are upregulated in response to inflammation to mediate a compensatory neuroprotective gene expression program that desensitizes neurons to glutamate by targeting messenger RNAs involved in glutamate receptor signalling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".