The QKI-6 RNA Binding Protein Regulates Actin-interacting Protein-1 mRNA Stability during Oligodendrocyte Differentiation
Bibliographic record
Abstract
The quaking viable (qk(v)) mice represent an animal model of dysmyelination. The absence of expression of the QKI-6 and QKI-7 cytoplasmic isoforms in oligodendrocytes (OLs) during CNS myelination causes the qk(v) mouse phenotype. The QKI RNA-binding proteins are known to regulate RNA metabolism of cell cycle proteins and myelin components in OLs; however, little is known of their role in reorganizing the cytoskeleton or process outgrowth during OL maturation and differentiation. Here, we identify the actin-interacting protein (AIP)-1 mRNA as a target of QKI-6 by using two-dimensional differential gel electrophoresis. The AIP-1 mRNA contains a consensus QKI response element within its 3'-untranslated region that, when bound by QKI-6, decreases the half-life of the AIP-1 mRNA. Although the expression of QKI-6 is known to increase during OL differentiation and CNS myelination, we show that this increase is paralleled with a corresponding decrease in AIP-1 expression in rat brains. Furthermore, qk(v)/qk(v) mice that lack QKI-6 and QKI-7 within its OLs had an increased level of AIP-1 in OLs. Moreover, primary rat OL precursors harboring an AIP-1 small interfering RNA display defects in OL process outgrowth. Our findings suggest that the QKI RNA-binding proteins regulate OL differentiation by modulating the expression of AIP-1.
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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".