Correlation of Leukocyte Telomere Length Measurement Methods in Patients with Dyskeratosis Congenita and in Their Unaffected Relatives
Bibliographic record
Abstract
Several methods have been employed to measure telomere length (TL) in human studies. It has been difficult to directly compare the results from these studies because of differences in the laboratory techniques and output parameters. We compared TL measurements (TLMs) by the three most commonly used methods, quantitative polymerase chain reaction (qPCR), flow cytometry with fluorescence in situ hybridization (flow FISH) and Southern blot, in a cohort of patients with the telomere biology disorder dyskeratosis congenita (DC) and in their unaffected relatives (controls). We observed a strong correlation between the Southern blot average TL and the flow FISH total lymphocyte TL in both the DC patients and their unaffected relatives (R2 of 0.68 and 0.73, respectively). The correlation between the qPCR average TL and that of the Southern blot method was modest (R2 of 0.54 in DC patients and of 0.43 in unaffected relatives). Similar results were noted when comparing the qPCR average TL and the flow FISH total lymphocyte TL (R2 of 0.49 in DC patients and of 0.42 in unaffected relatives). In conclusion, the strengths of the correlations between the three widely used TL assays (qPCR, flow FISH, and Southern blot) were significantly different. Careful consideration is warranted when selecting the method of TL measurement for research and for clinical studies.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".