Antibody Selection in Immunohistochemical Detection of Cyclin D1 in Mantle Cell Lymphoma
Bibliographic record
Abstract
An assessment in Nordic immunohistochemical Quality Control (NordiQC) revealed that only 23% of participant laboratories performed optimal staining for detection of cyclin D1 (CyD1) in mantle cell lymphoma (MCL). False-negative results were secondary to suboptimal protocols. We compared the 5 anti-CyD1 antibodies (monoclonal SP4, P2D11F11, and DCS-6 and polyclonal CP236 and 06–137) used in the Scandinavian laboratories. Evaluated were 31 MCLs, 16 other malignant lymphomas, and 19 samples of normal tissues. Sensitivity was as follows: CP236, 100%; SP4, 95%; P2D11F11, 90%; DCS-6, 84%; and 06–137, 53%. SP4 produced the strongest staining. Correlation of CyD1 with the proliferative index was best with polyclonal antibodies CP236 and 06–137. The use of heat-induced epitope retrieval in an alkaline buffer such as 10/1 mmol/L of Tris-EDTA buffer, pH 9, seemed mandatory. For the optimal detection of CyD1 expression, both SP4 and CP236 antibodies should be available in the laboratory.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".