Telomeres in the Haemopoietic System
Bibliographic record
Abstract
The limited life span of most blood cells requires the continuous production of cells, which in adults exceeds 10(12) cells/day. This impressive production of cells (approximately 4 x 10(16) cells over a lifetime) is achieved by the proliferation and differentiation of committed progenitor cells, which themselves are derived from a population of pluripotent stem cells with self-renewal potential. Paradoxically, the large majority of stem cells in adult bone marrow are quiescent cells. One possibility is that stem cells, like other somatic cells, have only a limited replicative potential (< 100 divisions). This hypothesis is supported by two key observations and the consideration that, in theory, 55 divisions can yield 4 x 10(16) cells. First, it was shown that 'candidate' stem cells purified from fetal and adult tissue showed dramatic functional differences in turn-over time and the ability to produce cells with stem cell properties, Second, these functional differences were found to correlate with a measurable loss of telomere repeats despite the presence of low but readily detectable levels of telomerase in all purified cell fractions. In order to address questions about the role of telomeres in normal and malignant haemopoiesis, we developed a quantitative fluorescence in situ hybridization technique. Here we review the characteristics of this novel tool to assess the number of telomere repeats at the end of individual chromosomes and provide an overview of recent observations.
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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 | 0.001 | 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 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".