Riboflavin and ultraviolet light treatment of platelets triggers <scp>p</scp>38<scp>MAPK</scp> signaling: inhibition significantly improves in vitro platelet quality after pathogen reduction treatment
Bibliographic record
Abstract
BACKGROUND: Pathogen reduction technologies (PRTs) significantly reduce the risk of transmission of infectious agents in platelet (PLT) concentrates; however, in vitro studies reveal a negative impact on PLT quality after PRT treatment including effects on PLT aggregation, integrin αIIbβ3 conformation, and actin dynamics. Clinically, the interval between transfusions is shortened. STUDY DESIGN AND METHODS: Seeking to understand the biochemical mechanisms underlying these observed effects, we analyzed signal transduction in PLT concentrates after riboflavin and ultraviolet light (UV; Mirasol) treatment and subsequent storage focusing on the phosphorylation levels of selected protein kinases. RESULTS: Among identified candidates, p38MAPK increased fourfold in phosphorylation after PRT. Incubation of PLT concentrates with a p38MAPK-specific inhibitor before PRT significantly improved numerous PLT quality measures. Phosphorylation levels of the p38MAPK substrates AKT, VASP, and HSP27 also decreased with inhibitor treatment. Phospho-HSP27 decrease in the presence of the inhibitor correlated with a reduction in PLT activation determined by surface expression of P-selectin. CONCLUSION: These findings support a model of one dominant underlying molecular signaling mechanism that is impacted by the riboflavin and UV (Mirasol) PRT process resulting in alterations in PLT quality. The identification of such a target should assist in the development of strategies to ameliorate this negative aspect of an otherwise beneficial and important safety development for transfusion medicine.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".