Bibliographic record
Abstract
Acquired and congenital aplastic anemias recently have been linked molecularly and pathophysiologically by abnormal telomere maintenance. Telomeres are repeated nucleotide sequences that cap the ends of chromosomes and protect them from damage. Telomeres are eroded with cell division, but in hematopoietic stem cells, maintenance of their length is mediated by telomerase. Accelerated telomere shortening is virtually universal in dyskeratosis congenita, caused by mutations in genes encoding components of telomerase or telomere-binding protein (TERT, TERC, DKC1, NOP10, or TINF2). About one-third of patients with acquired aplastic anemia also have short telomeres, which in some cases associate with TERT or TERC mutations. These mutations cause low telomerase activity, accelerated telomere shortening, and diminished proliferative capacity of hematopoietic progenitors. As in other genetic diseases, additional environmental, genetic, and epigenetic modifiers must contribute to telomere erosion and ultimately to disease phenotype. Short telomeres also may cause genomic instability and malignant progression in these marrow failure syndromes. Identification of short telomeres has potential clinical implications: it may be useful in dyskeratosis congenita diagnosis, in suggesting mutations in patients with acquired aplastic anemia, and for selection of suitable hematopoietic stem cell family donors for transplantation in telomerase-deficient patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".