Cytological Detection of Iron Overload and Cytomorphometric Changes in buccal Mucosa of Βeta Thalassemia Major Patients
Bibliographic record
Abstract
Aim: In this study, the phenomenon of oral exfoliative cytology is explored and buccal squamous cells are examined for intracytoplasmic, Prussian blue stained, iron containing granules. In addition, these buccal squamous cells are subjected to morphometric measurements of their nuclear and cytoplasmic diameter along with their ratios. Methods: It was a Descriptive, Cross sectional study including 120patients of Thalassemia Major, ranging from 4 -18 years with repeated blood transfusions and a serum ferritin level of 1000ng/ml at minimum. Scrapings were obtained from buccal mucosa for cytological examination and stained with Prussian Blue Stain. Results: The study included 45 female and 75 male patients with a mean age 11.04(± 3.81) years. 56out of 120 patients were positive for Prussian blue and thus showed 46.6% positivity. The mean cytoplasmic diameter was 50.90 (± 0.64) microns and mean nuclear diameter was 9.31(±0.53) microns. Mean Nuclear to cytoplasmic (NC) ratio was 0.182(± 0.01) and ranged from 0.165 and 0.211 microns. Conclusion: The positivity of Prussian blue in our study is clearly less than most of the quoted figures while alterations in morphometric features of buccal squamous cells are quite consistent with reported data. In our study, we observed iron containing granules not only in the cytoplasm but also on surface of cells like a clue cell dispersed outside the cell, individually or in discrete clusters and as faint bluish hue in background. Keywords: Iron overload, Cytomorphometry, buccal smear, Prussian blue, Beta Thalassemia
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".