Tissue Prior to the Initial Hematoxylin-Eosin Section Demonstrates Value as an Alternative Source of DNA for Molecular Testing
Bibliographic record
Abstract
CONTEXT.—: Small biopsies are used for histologic, immunophenotypic, cytogenetic, molecular genetic, and other ancillary studies. Occasionally, this diagnostic tissue is exhausted before molecular testing can be performed. OBJECTIVE.—: To investigate a simple banking protocol for currently discarded tissues trimmed off prior to the initial hematoxylin-eosin section, as an alternative source of DNA for molecular studies. DESIGN.—: Mock biopsies of lung adenocarcinomas, benign testes, and B-cell lymphomas were constructed from biobank blocks; these simulated biopsies were assessed via epidermal growth factor receptor (EGFR) p.L858R droplet digital polymerase chain reaction (PCR), Biomed B-cell clonality testing by PCR, or a custom next-generation sequencing panel for lymphomas. For each cancer mock biopsy, DNA amounts and molecular test results from the "trimmings" samples were compared to data from corresponding molecular samples acquired via a "standard" clinical protocol. RESULTS.—: The data show that although trimmings samples usually contained less DNA than standard samples, both sample classes generally had sufficient DNA for testing and produced essentially identical molecular results. A single sample showed low-level carryover contamination on droplet digital PCR testing. CONCLUSIONS.—: Tissue trimmings banked by using the studied protocol demonstrated value as a potential alternative sample for molecular testing.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".