Differences in Nuclear DNA Organization Between Lymphocytes, Hodgkin and Reed–Sternberg Cells Revealed by Structured Illumination Microscopy
Bibliographic record
Abstract
ABSTRACT Advances in light microscopy have enabled the visualization of DNA in the interphase nucleus with more detail than is visible with conventional light microscopy. The nuclear architecture is assumed to be different in cancer cells compared to normal cells. In this paper we have studied, for the first time, the organization of nuclear DNA and that of DNA‐free space in control lymphocytes, Hodgkin cells and Reed–Sternberg cells using 3D structured illumination microscopy (SIM). We have observed detail in these SIM images that was not observed in conventional widefield images. We have measured the size distribution of the DNA structure using granulometry and noted a significant, progressive increase in the amount of sub‐micron structures from control lymphocytes to Hodgkin cells to Reed–Sternberg cells. The DNA‐free space changes as well; “holes” in the DNA distribution start to appear in the malignant cells. We have studied whether these “holes” are nucleoli by staining for upstream binding factor (UBF), a protein associated with the nucleolus. We have found that the relative UBF content progressively and significantly decreases—or is absent—in the DNA‐free space when measured as either the Pearson correlation coefficient with the DNA‐free space or as the number of “holes” that contain UBF. Similar differences exist within the population of Reed–Sternberg cells between binucleated and multinucleated cells with four or more subnuclei. To our knowledge, this is the first study that investigates the changes of the nuclear DNA structure in any disease with superresolution light microscopy. J. Cell. Biochem. 115: 1441–1448, 2014. © 2014 The Authors. Journal of Cellular Biochemistry published by Wiley Periodicals, Inc. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
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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 | 0.000 | 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) | 0.000 | 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".