Functional Characterization of Telomerase RNA Variants Found in Patients with Hematological Disorders.
Bibliographic record
Abstract
Abstract Human telomerase uses a portion of its integral RNA component (hTER) as the template to synthesize telomeres at chromosome ends. hTER sequence polymorphisms have been observed in some patients with bone marrow failure syndromes such as aplastic anemia, but the functional significance of most such variants is unknown. Here, we report the functional characteristics of ten previously-described and two newly discovered hTER disease-associated polymorphisms. Most of these hTER variants adversely affected telomerase enzymatic function as measured in the telomerase reconstituted human cells. Similar loss-of-function effects were also seen directly in primary lymphocytes collected from two of the patients. The majority of the functional deficits stemmed from perturbations of the predicted hTER RNA secondary structure, and corresponded well with the degrees of telomere shortening observed in patients. In contrast, hTER variants anticipated to be inconsequential polymorphisms, which were also found in healthy subjects, did not interfere with telomerase function. Loss of telomerase activity and of telomere maintenance resulting from inherited hTER mutations may predispose some patients to aplastic anemia and other marrow failure disorders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".