Three-dimensional Nuclear Telomere Organization in Multiple Myeloma
Bibliographic record
Abstract
Multiple myeloma (MM) is preceded by monoclonal gammopathy of undetermined significance (MGUS). Up to date, it is difficult to predict an individual's time to disease progression and the treatment response. To examine whether the nuclear telomeric architecture will unravel some of these questions, we carried out. Three-dimensional (3D) telomere analysis on samples from patients diagnosed with MGUS and MM, as well as from patients who went into relapse. Telomere signal intensity, number of telomere aggregates, nuclear volume, and the overall nuclear telomere distribution (a/c ratio) were analyzed. The telomeric profiles allowed for the differentiation of the disease stages. The telomeric profiles of myeloma cells obtained from blood and bone marrow aspirates were identical. Based on this study, we discuss the use of 3D telomere profiling as a potential future tool for risk stratification and personalized treatment decisions.
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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 | 0.001 |
| 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) | 0.000 | 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".