Abstract 10537: A Comparison of Endothelial Nitric Oxide Synthase(eNOS)-Based Platelet Subpopulation Ratios and Platelet VEGF Content Within Covid-19
Bibliographic record
Abstract
Background: Nitric oxide (NO) regulates both thrombosis and vascular leakage, two of the major complications of severe Covid19. Platelet-derived NO inhibits adhesion/aggregation and within microvascular endothelial cells NO-signalling mediates vascular endothelial growth factor (VEGF/VPF)-induced permeability. Recently, we identified novel platelet subpopulations with a differential ability to produce NO and the presence/absence of endothelial nitric oxide synthase (eNOS). We showed that eNOS-negative (eNOS neg ) platelets initiate adhesion and aggregation, while eNOS-positive (eNOS pos ) platelets limit aggregate growth. As inflammatory cytokines are known to counter-regulate eNOS and VEGF expression, we hypothesized that the ratio of eNOS-negative to -positive platelets may be increased in COVID-19 patients along with their VEGF content. Aims: To determine the eNOS-positive to -negative platelet ratio and platelet VEGF levels within the blood of hospitalized COVID-19 patients. Methods: Platelets were isolated from age- and sex-matched COVID-19 patients (ICU and non-ICU) and COVID-negative healthy controls. Isolated platelets were intracellularly stained for eNOS, VEGF, and for surface CD62P and analyzed using flow cytometry. A multiplex assay was used to measure plasma cytokines. Results: The percentage of eNOS neg platelets within the blood of COVID-19 patients (ICU and non-ICU) was higher than that within healthy controls and their levels correlated with disease severity (81.2±2.8% ICU vs. 66.0 ±3.1% non-ICU vs. 6.1± 1.3% controls, P -value < 0.0001). Accordingly, the percentage of eNOS pos platelets in COVID-19 patients was lower compared to controls, while the platelet VEGF content and surface CD62P of COVID-19 patients in ICU was higher than that of healthy controls. Further, COVID-19 patients demonstrated higher TNFα, IL-6, and IL-1β plasma concentrations than controls. Conclusion: Preliminary data suggests that eNOS-negative to -positive platelet ratios and VEGF content increase with COVID-19 severity, potentially predisposing patients to thrombosis and enhanced vascular permeability upon platelet activation. These platelet changes may be due to the actions of inflammatory cytokines on megakaryocytes.
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 | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".