Conservation of RET proto-oncogene splicing variants and implications for RET isoform function
Bibliographic record
Abstract
The RET proto-oncogene encodes a receptor tyrosine kinase required for development of the kidney and neural crest-derived cell types. Alternative splicing of the 3' exons of human RET results in three protein isoforms with distinct C-termini: RET9, RET51, and RET43. These RET isoforms show differential binding to downstream adapter molecules, suggesting they may have distinct signaling functions. We have characterized Ret 3' sequences in mouse and investigated alternative splicing of this region. We found that the organization of Ret 3' sequences is very similar to human RET. The mouse locus also has alternatively spliced C-terminal coding regions, and the sequences corresponding to RET9 and RET51 are highly conserved in both position and sequence with the human locus. Further, we compared the predicted C-terminal amino acids of RET9 and RET51 in seven vertebrate species, and found that they are well conserved. We have identified sequence encoding a putative ret43 isoform in mouse, however the predicted amino acid sequence showed low homology to human RET43. Our data suggest that RET isoforms are evolutionarily highly conserved over a broad range of species, which may indicate that each isoform has a distinct role in normal RET function.
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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".