Comparison of Four Staining Methods for Detection of Mast Cells in Equine Bronchoalveolar Lavage Fluid
Bibliographic record
Abstract
Mast cells normally are present in equine bronchoalveolar lavage fluid (BALF), but usually represent <2% of all cells in healthy horses. An increased percentage of mast cells has been associated with airway hyperactivity and inflammatory airway diseases, but marked differences are reported between studies in normal and diseased horses. Because an abnormal mast cell count may be of clinical relevance, we compared the ability of a fast Romanowsky method to stain mast cell granules with that of 3 metachromatic stains: automated Romanowsky, May-Grünwald Giemsa, and toluidine blue stains. The BALF cells from 24 horses were studied. A differential cell count was performed blindly on 400 cells. The percentages of mast cells obtained were analyzed by means of repeated-measures analysis of variance and Fischer's PLSD test. The Bland and Altman method was used to assess agreement among stains. The mean percentage of mast cells in BALF was significantly lower with the fast Romanowsky than with the automated Romanowsky, May-Grünwald Giemsa, and toluidine blue stains. With the fast Romanowsky stain, the metachromatic granules of mast cells were not stained, and their identification was based on morphologic criteria. Toluidine blue staining allowed detection of the highest mean percentage of mast cells, but was inadequate for performing a differential cell count on other cell types. In conclusion, fast Romanosky stain may be inadequate for detection of mast cells in equine BALF, whereas automated Romanowsky, May-Grünwald Giemsa, and toluidine blue stains provide metachromatic staining of mast cell granules.
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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 | 0.001 | 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".