Comparative DNA Flow Cytometric Study of Primary Intraocular and Central Nervous System Lymphomas
Bibliographic record
Abstract
Primary intraocular lymphoma is generally considered as a subset of primary CNS lymphoma. This study attempts to show that they may in fact represent distinct entities by comparing their respective proliferation rates using DNA flow cytometry. Four samples of primary intraocular lymphoma and seven samples of primary CNS lymphoma were analyzed, all from paraffin-embedded tissue. All tumors were of the large B-cell type. A normal human tonsil sample was used as a control. Tissue samples were analyzed by DNA flow cytometry, which is a precise and objective method to measure DNA content and cell proliferation of a tumor. S-phase fraction (SPF) and DNA content were measured for each sample. The average SPF for primary intraocular lymphoma was significantly higher than that of primary CNS lymphoma, 23.8 (range: 18.9 to 29.6) versus 15.1 (range: 1.1 to 25.1) respectively. Of the 11 tumors analyzed, 2 brain tumors were aneuploid and 1 eye tumor was peridiploid. All other tumors were diploid. Thus, no significant pattern was detected in the DNA content of the tumors. This lack of clinical significance of tumor aneuploidy is consistent with data reported in the literature. The results of this study indicate that primary intraocular lymphoma is more aggressive and of higher grade than primary CNS lymphoma. The different proliferation rates of intraocular and CNS lymphomas may be explained by either their different spatial location or a distinct genetic composition, the latter reinforcing the hypothesis that the two are fundamentally different entities
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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 | 0.003 | 0.001 |
| 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) | 0.002 | 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".