The TET Family of Proteins: Functions and Roles in Disease
Bibliographic record
Abstract
Translocated in liposarcoma, Ewing's sarcoma and TATA-binding protein-associated factor 15 constitute an interesting and important family of proteins known as the TET proteins. The proteins function in several aspects of cell growth control, including multiple different steps in gene expression, and they are also found mutated in a number of specific diseases. For example, all contain domains for binding nucleic acids and have been shown to function in both RNA polymerase II-mediated transcription and pre-mRNA splicing, possibly connecting these two processes. Chromosomal translocations in human sarcomas result in a fusion of the amino terminus of these proteins, which contains a transcription activation domain, to the DNA-binding domain of a transcription factor. Although the fusion proteins have been characterized in a clinical environment, the function of the cognate full-length protein in normal cells is a more recent topic of study. The first part of this review will describe the TET proteins, followed by detailed descriptions of their multiple roles in cells. The final sections will examine changes that occur in gene regulation in cells expressing the fusion proteins. The clinical implications and treatment of sarcomas will not be addressed but have recently been reviewed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".