3D TELOMERE DYNAMICS IN DOWN SYNDROME: FROM CONSTITUTIONAL TO ACQUIRED ABNORMALITIES
Bibliographic record
Abstract
Down syndrome (DS) is characterized by the constitutive trisomy 21, which can result from nondisjunction during maternal meiosis (pre/post-zygotic condition). Hematological disorders are present in almost neonates with DS. In the present study, we introduce for the first time, the three-dimensional telomeric signatures of DS nuclei at different status (DS from pre-zygotic, post-zygotic, and association of DS with leukemia) as an addition biomarker tool suitable for characterizing and stratifying DS, especially those cases related to leukemic evolution. Methodology: We performed 3D FISH telomeric analysis in thirty-six samples, being twenty-five from blood, and eleven from bone marrow were obtained from DS patients (CAE: 87629318.3.0000.0096). All clinical characteristics were confirmed after laboratorial diagnoses by the presence of 21 trisomy chromosome as the sole abnormality (blood samples), and additional chromosomal abnormalities on bone marrow samples. Results: The 3D telomere archtecture revealed an increased number of telomeres aggregates in DS with leukemia cells. Statistical analyses showed significant differences among DS subgroups (p < 0.001). Our findings suggest that the “evolution” of DS samples progresses from a low to a high level of telomere dysfunction, (post-zygotic condition) to a more aggressive stage (DS with AML), followed by transformation, as demonstrated by telomere, additional chromosomal abnormalities, and gene expression profile dynamics. Conclusion: Thus, we demonstrated that 3D telomere organization, in accordance with the genomic instability observed in DS samples were able to distinguish subgroups of patients, based on the origin of the additional extra copy of 21 chromosome, and leukemic transformation.
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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 | 0.000 |
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".