The Use of Archival Bone Marrow Specimens in Detecting B-Cell Non-Hodgkin's Lymphomas Using Polymerase Chain Reaction Methods
Bibliographic record
Abstract
The detection of B-cell non-Hodgkin's lymphoma (B-NHL) involving the bone marrow (BM) can be enhanced by assessing immunoglobulin heavy chain (IgH/JH) gene rearrangement using PCR. While the fresh BM aspirate has been the most commonly used specimen, the utility of archival BM tissues has not been extensively evaluated. We studied the BM from 13 patients with nodal B-NHL (7 low-grade and 6 intermediate grade), which were categorized into three groups based on the histologic finding of lymphoma (H) and the presence of a monoclonal IgH/JH band by PCR using fresh BM aspirates (M): (1) H(+)/M(+), 4 cases; (2) H(+)/M(-), 4 cases; and (3) H(equivocal)/M(-), 5 cases. Archival tissues available for study included paraffin-embedded trephine biopsy (TB)/aspirate clots (AC) and air-dried aspirate smears (AS). All TB (13/13) and a subset of AC (5/13) were B5-fixed, and all these tissues failed to yield analyzable DNA. In contrast, sufficient DNA was consistently obtained in AC that were formalin-fixed (8/13). Of these 8 cases, 2/3 of group 1, 3/3 of group 2, and 0/2 of group 3 had a monoclonal IgH band. Using DNA extracted from microdissected lymphoid aggregates morphologically evident in the AC sections, additional positive cases were identified: 1/3 of group 1 and 2/2 of group 3. In those 5 cases that did not have formalin-fixed TB/AC, sufficient DNA was extracted from AS in all cases; one additional positive case was identified in group 1. Overall, 4/4 (100%) of group 1, 3/4 (75%) of group 2, and 2/5 (40%) of group 3 showed molecular evidence of lymphoma. To conclude, archival BM specimens are a useful source of DNA for molecular detection of B-NHL involvement, and formalin appears to be a better fixative than B5. The use of these samples may improve the overall detection sensitivity.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".