Measurement of telomere length in haematopoietic cells using <i>in situ</i> hybridization techniques
Bibliographic record
Abstract
The DNA of human chromosomes terminates in several kilobases of telomere repeats that are gradually lost with; age and with replication in vitro. Defective telomere maintenance has been shown to be causally linked to cell cycle exit and apoptosis. In order to overcome the limitations imposed by Southern blotting, we have established a quantitative fluorescence in situ hybridization (Q-FISH) technique. This technique allows estimation of telomere length in specific chromosome arms from metaphase cell preparations. Furthermore, we have extended quantitative in situ hybridization to flow cytometry (flow FISH) in order to obtain information on the mean telomere repeat content in suspended cells. Telomere length in granulocytes, monocytes, CD8 and CD4 T lymphocytes and natural killer cells was found to differ slightly in the peripheral blood of adults. However, strikingly longer telomeres were observed in B lymphocytes (approximately 1.3 kb longer), suggesting a functional role for telomere maintenance in this cell subset. In summary, Q-FISH and flow FISH represent new methods for measuring telomere length in single cells and allow studies of telomere dynamics in haematopoietic subpopulations at various stages of normal and abnormal antigen responses.
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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 | 0.001 | 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 | 0.001 |
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".