Modulation of miR-145 in a mouse model of multiple sclerosis: A promising approach to attenuate inflammation and degeneration
Bibliographic record
Abstract
Multiple sclerosis (MS) is a progressive inflammatory disease of the central nervous system (CNS) marked by myelin loss, which impairs nerve function. Current therapies fail to halt disease progression or prevent myelin and axonal degeneration. In this study, we explored the impact of miR-145 loss in a murine model of experimental autoimmune encephalomyelitis (EAE), which mimics MS pathology. Loss of miR-145 reduced clinical severity and significantly decreased immune cell infiltration in the lumbar spinal cord during both the onset and chronic stages of the disease. Additionally, miR-145 loss altered the expression of key inflammatory genes and modulated astrocytic activity throughout EAE. Of significant interest, acute treatment with an antisense oligonucleotide (ASO) targeting miR-145 decreased miR-145 levels and led to reduced disease severity, decreased immune cell infiltration, and an increase in regulatory T cells in EAE mice. Moreover, miR-145 deficiency mitigated axon and myelin degeneration. Our findings suggest that ASOs targeting miR-145 may offer a promising therapeutic strategy, addressing both inflammatory and degenerative components of MS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".