Diagnosing Platelet δ-Storage Pool Disease in Children by Flow Cytometry
Bibliographic record
Abstract
Bleeding problems are symptomatic of platelet delta-storage pool diseases (SPDs) such as Hermansky-Pudlak syndrome. Although at present no cure is available for delta-SPD, early diagnosis is of great importance for prophylactic and supportive treatment. This study tested the usefulness of a flow cytometric assay for platelet serotonin in children. The assay was used to diagnose delta-SPD in a 10-year-old girl. Platelet serotonin levels were significantly lower in the patient than in all healthy control subjects (10 children and 10 adults). The serotonin results were supported by traditional tests, which are transmission electron microscopy of whole mounts and adenosine triphosphate release by lumi-aggregometry. The flow cytometric serotonin assay is a major improvement to current pediatric diagnostics. The advantages of this test are small sample volume of fresh or fixed/frozen platelets, availability of objective results within 2 hours of obtaining the blood sample, and automated analysis by flow cytometry.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 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".