A signaling pathway contributing to platelet storage lesion development: targeting PI3‐kinase–dependent Rap1 activation slows storage‐induced platelet deterioration
Bibliographic record
Abstract
BACKGROUND: The term platelet storage lesion (PSL) describes the structural and biochemical changes in platelets (PLTs) during storage. These are typified by alterations of morphologic features and PLT metabolism leading to reduced functionality and hence reduced viability for transfusion. While the manifestations of the storage lesion are well characterized, the biochemical pathways involved in the initiation of this process are unknown. STUDY DESIGN AND METHODS: A complementary proteomic approach has recently been applied to analyze changes in the PLT proteome during storage. By employing stringent proteomic criteria, 12 proteins were identified as significantly and consistently changing in relative concentration over a 7-day storage period. Microscopy, Western blot analysis, flow cytometry, and PLT functionality analyses were used to unravel the involvement of a subset of these 12 proteins, which are connected through integrin signaling in one potential signaling pathway underlying storage lesion development. RESULTS: Microscopic analysis revealed changes in localization of glycoprotein IIIa, Rap1, and talin during storage. Rap1 activation was observed to correlate with expression of the PLT activation marker CD62P. PLTs incubated for 7 days with the PI3-kinase inhibitor LY294002 showed diminished Rap1 activation as well as a moderate reduction in integrin alphaIIbbeta3 activation and release of alpha-granules. Furthermore, this inhibitor seemed to improve PLT integrity and quality during storage as several in vitro probes showed a deceleration of PLT activation. CONCLUSION: These results provide the first evidence for a signaling pathway mediating PSL in which PI3-kinase-dependent Rap1 activation leads to integrin alphaIIbbeta3 activation and PLT degranulation.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".