Non-random length distribution of individual telomeres in immunodeficiency, centromeric instability and facial anomalies syndrome, type I
Bibliographic record
Abstract
Mutations in the de novo DNA methyltransferase DNMT3B lead to Immunodeficiency, Centromeric Instability and Facial anomalies (ICF) syndrome, type I. This syndrome is characterized, among other hypomethylated genomic loci, by severe subtelomeric hypomethylation that is associated with abnormally short telomere length. While it was demonstrated that the mean telomere length is significantly shorter in ICF type I cells, it is unknown whether all telomeres are equally vulnerable to shortening. To study this question we determined by combined telomere-FISH and spectral karyotyping the relative length of each individual telomere in lymphoblastoid cell lines (LCLs) generated from multiple ICF syndrome patients and control individuals. Here we confirm the short telomere lengths, and demonstrate that telomere length variance in the ICF patient group is much larger than in the control group, suggesting that not all telomeres shorten in a uniform manner. We identified a subgroup of telomeres whose relatively short lengths can distinguish with a high degree of certainty between a control and an ICF metaphase, proposing that in ICF syndrome cells, certain individual telomeres are consistently at greater risk to shorten than others. The majority of these telomeres display high sequence identity at the distal 2 kb of their subtelomeres, suggesting that the attenuation in DNMT3B methylation capacity affects individual telomeres to different degrees based, at least in part, on the adjacent subtelomeric sequence composition.
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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".