ELAVL1 regulates alternative splicing of eIF4E transporter to promote postnatal angiogenesis
Bibliographic record
Abstract
Posttranscriptional RNA regulation is important in determining the plasticity of cellular phenotypes. However, mechanisms of how RNA binding proteins (RBPs) influence cellular behavior are poorly understood. We show here that the RBP embryonic lethal abnormal vision like 1 (ELAVL1, also know as HuR) regulates the alternative splicing of eukaryotic translation initiation factor 4E nuclear import factor 1 (Eif4enif1), which encodes an eukaryotic translation initiation factor 4E transporter (4E-T) protein and suppresses the expression of capped mRNAs. In the absence of ELAVL1, skipping of exon 11 of Eif4enif1 forms the stable, short isoform, 4E-Ts. This alternative splicing event results in the formation of RNA processing bodies (PBs), enhanced turnover of angiogenic mRNAs, and suppressed sprouting behavior of vascular endothelial cells. Further, endothelial-specific Elavl1 knockout mice exhibited reduced revascularization after hind limb ischemia and tumor angiogenesis in oncogene-induced mammary cancer, resulting in attenuated blood flow and tumor growth, respectively. ELAVL1-regulated alternative splicing of Eif4enif1 leading to enhanced formation of PB and mRNA turnover constitutes a novel posttranscriptional mechanism critical for pathological angiogenesis.
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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".