Role of platelet surface glycoprotein Ibα and P‐selectin in the clearance of transfused platelet concentrates
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Role of P-selectin (CD62) and glycoprotein (GP) Ibalpha in posttransfusion clearance of platelet concentrates (PCs) is unclear. STUDY DESIGN AND METHODS: Platelet (PLT) activation in vitro was determined by flow cytometry using anti-CD62 and anti-GPIbalpha. PC clearance in vivo was evaluated in an animal model using rabbits with an inhibited reticuloendothelial system, as measured by 0.5-hour (R(0.5)), 24-hour (R(24)), and total (R( summation operator )) PLT recoveries, and survival time (ST). Correlations were analyzed between in vitro assays of PLT activation and in vivo clearance of conventional (Days 2-5), outdated (Days 7-8), and refrigerated PCs. RESULTS: Binding of anti-CD62 to the PLT surface was significantly increased and of anti-GPIbalpha decreased in outdated and refrigerated PCs compared to conventional PCs. Negative correlation was observed between in vitro anti-CD62 binding and the fast (R(0.5)) PLT clearance, but not with delayed (R(24) and ST) clearance. In contrast, anti-GPIbalpha binding showed positive correlations with delayed but not with fast PLT clearance. Overall (R( summation operator )) clearance correlated better with anti-GPIbalpha than with anti-CD62 binding. CD62 density on the PLT surface was decreased after PC transfusion, whereas GPIbalpha density remained unchanged. CONCLUSION: These data suggest that CD62 exposure on the PLT surface during PC storage triggers fast CD62-mediated PC clearance, whereas in vitro GPIbalpha changes are involved in delayed GPIbalpha-mediated PC clearance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it