<scp>T</scp>he roles of extracellular vesicle micro<scp>RNA</scp>s in the central nervous system
Bibliographic record
Abstract
MicroRNAs (miRNAs) are small, highly conserved non-coding RNA molecules that post-transcriptionally regulate protein expression and most biological processes. Mature miRNAs are recruited to the RNA-induced silencing complex (RISC) and target mRNAs via complementary base-pairing, thus resulting in translational inhibition and/or transcript degradation. Here, we present evidence implicating miRNAs within extracellular vesicles (EVs), including microvesicles and exosomes, as mediators of central nervous system (CNS) development, homeostasis, and injury. EVs are extracellular vesicles that are secreted by all cells and represent a novel method of intercellular communication. In glial cells, the transfer of miRNAs via EVs can alter the function of recipient cells and significantly impacts cellular mechanisms involved in both injury and repair. This review discusses the value of information to be gained by studying miRNAs within EVs in the context of CNS diseases and their potential use in the development of novel disease biomarkers and therapeutic strategies.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".