miRNAs As Emerging Regulators of Oligodendrocyte Development and Differentiation
Bibliographic record
Abstract
Chronic demyelination is a hallmark of neurological disorders such as multiple sclerosis (MS) and several leukodystrophies. In the central nervous system (CNS), remyelination is a regenerative process that is often inadequate during these pathological states. In the MS context, in situ evidence suggests that remyelination is mediated by populations of oligodendrocyte progenitor cells (OPCs) that proliferate, migrate, and differentiate into mature, myelin-producing oligodendrocytes at sites of demyelinated lesions. The molecular programming of OPCs into mature oligodendrocytes is governed by a myriad of complex intracellular signaling pathways that modulate this process. Recent research has demonstrated the importance of specific and short non-coding RNAs, known as microRNAs (miRNAs), in regulating OPC differentiation and remyelination. Fortunately, it may be possible to take advantage of numerous developmental studies (both human and rodent) that have previously characterized miRNA expression profiles from the early neural progenitor cell to the late myelin-producing oligodendrocyte. Here we review much of the work to date and discuss the impact of miRNAs on OPC and oligodendrocyte biology. Additionally, we consider the potential for miRNA-mediated therapy in the context of remyelination and brain repair.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".