Effects of fixation and demineralization on histomorphology and DNA amplification of canine bone marrow
Bibliographic record
Abstract
Fixation and demineralization protocols for bone marrow (BM) across diagnostic laboratories are not standardized. How different protocols affect histomorphology and DNA amplification is incompletely understood. In this study, 2 fixatives and 3 demineralization methods were tested on canine BM samples. Twenty replicate sternal samples obtained within 24 hours of death were fixed overnight in either acetic acid-zinc-formalin (AZF) or 10% neutral-buffered formalin (NBF) and demineralized with formic acid for 12 hours. Another 53 samples were fixed in AZF and demineralized with hydrochloric acid for 1-hour, formic acid for 12 hours, or ethylenediamine tetraacetic acid (EDTA) for 24 hours. Histologic sections were scored by 4 raters as of insufficient, marginal, good, or excellent quality. In addition, DNA samples extracted from sections treated with the different fixation and demineralization methods were amplified with 3 sets of primers to conserved regions of T cell receptor gamma and immunoglobulin heavy chain genes. Amplification efficiency was graded based on review of capillary electrophoretograms. There was no significant difference in the histomorphology scores of sections fixed in AZF or NBF. However, EDTA-based demineralization yielded higher histomorphology scores than demineralization with hydrochloric or formic acid, whereas formic acid resulted in higher scores than hydrochloric acid. Demineralization with EDTA yielded DNA amplification in 29 of 36 (81%) samples, whereas demineralization with either acid yielded amplification in only 2 of 72 (3%) samples. Although slightly more time-consuming and labor-intensive, tissue demineralization with EDTA results in superior morphology and is critical for polymerase chain reaction (PCR) amplification with the DNA extraction method described in this article.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".