CytoLyt® Fixation and Decalcification Pretreatments Alter Antigenicity in Normal Tissues Compared With Standard Formalin Fixation
Bibliographic record
Abstract
Immunohistochemistry is used on cell blocks constructed from cytopathology samples fixed in methanol-based fixatives, such as CytoLyt (Cytyc Corp), and on surgical pathology tissues exposed to decalcifying agents, often without technical validation. We evaluated a panel of commonly utilized antibodies in normal tissues exposed to differing preanalytic conditions as follows: CytoLyt fixation, formalin fixation followed by exposure to decalcifying agents (Leica Decalcifier I-10% formic acid or Leica Decalcifier II-5% hydrochloric acid), or standard formalin fixation. Altered expression was observed with several antibodies compared with standard formalin fixation. Specifically, there was absent or near absent expression of thyroid transcription factor 1 (TTF-1), D2-40, and CD20 in CytoLyt-fixed tissues, whereas reduced expression was observed for p63, estrogen receptor, S100 protein, CD3, calretinin, chromogranin, and synaptophysin. Absent or near absent expression of TTF-1 was also observed with exposure to hydrochloric acid, whereas reduced expression was observed for CK5/6, CK7, p63, estrogen receptor, leukocyte common antigen, CD3, CD20, and synaptophysin. Exposure to formic acid had less impact with reduced expression observed for only 3 antibodies (CK8/18, CK7, and TTF-1). The results of this study demonstrate the need to validate immunohistochemical protocols on control tissue treated in the same manner as test tissue, including CytoLyt fixation and exposure of tissue to decalcifying agents.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".