The three-dimensional organization of telomeres in the nucleus of mammalian cells
Bibliographic record
Abstract
BACKGROUND: The observation of multiple genetic markers in situ by optical microscopy and their relevance to the study of three-dimensional (3D) chromosomal organization in the nucleus have been greatly developed in the last decade. These methods are important in cancer research because cancer is characterized by multiple alterations that affect the modulation of gene expression and the stability of the genome. It is, therefore, essential to analyze the 3D genome organization of the interphase nucleus in both normal and cancer cells. RESULTS: We describe a novel approach to study the distribution of all telomeres inside the nucleus of mammalian cells throughout the cell cycle. It is based on 3D telomere fluorescence in situ hybridization followed by quantitative analysis that determines the telomeres' distribution in the nucleus throughout the cell cycle. This method enables us to determine, for the first time, that telomere organization is cell-cycle dependent, with assembly of telomeres into a telomeric disk in the G2 phase. In tumor cells, the 3D telomere organization is distorted and aggregates are formed. CONCLUSIONS: The results emphasize a non-random and dynamic 3D nuclear telomeric organization and its importance to genomic stability. Based on our findings, it appears possible to examine telomeric aggregates suggestive of genomic instability in individual interphase nuclei and tissues without the need to examine metaphases. Such new avenues of monitoring genomic instability could potentially impact on cancer biology, genetics, diagnostic innovations and surveillance of treatment response in medicine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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".