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Elevated levels of pro-thrombotic eNOS-negative platelets in COVID-19 patients

2024· article· en· W4403096839 on OpenAlexafffund
Amir Asgari, Aleksandra Franczak, Alex Herchen, Glen C. Jickling, Paul Jurasz

Bibliographic record

VenueThrombosis Research · 2024
Typearticle
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsUniversity of Alberta
FundersFaculty of Medicine and Dentistry, University of AlbertaLi Ka Shing Institute of Virology, University of AlbertaCanadian Institutes of Health ResearchUniversity of Alberta
KeywordsCoronavirus disease 2019 (COVID-19)PlateletEnosInternal medicineMedicine2019-20 coronavirus outbreakPlatelet activationSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)CardiologyADAMTS13Thrombotic thrombocytopenic purpuraVirologyNitric oxideDiseaseNitric oxide synthase

Abstract

fetched live from OpenAlex

BACKGROUND: Platelet-rich microvascular thrombi are common in severe COVID-19. Endogenous nitric oxide (NO)-signaling limits thrombus formation and previously we identified platelet subpopulations with a differential ability to produce NO based on the presence or absence of endothelial nitric oxide synthase (eNOS). eNOS expression is counter-regulated by cytokines, and COVID-19-associated immune/inflammatory responses may affect the transcriptome profile of megakaryocytes and their platelet progeny. OBJECTIVES: We investigated whether the percentage of eNOS-negative to eNOS-positive platelets increases in COVID-19 patients and whether this change may be due to the actions of pro-inflammatory cytokines on megakaryocytes. METHODS: Platelets were isolated from hospitalized COVID-19 patients and COVID-19-negative controls. Platelet eNOS was measured by flow cytometry and plasma inflammatory cytokines by ELISA. Megakaryocytes from eNOS-GFP transgenic mice and the Meg-01 cell line were characterized to identify an appropriate model to study eNOS-based platelet subpopulation formation in response to inflammatory cytokines. RESULTS: COVID-19 patients demonstrated a significant increase in eNOS-negative and a concomitant decrease in eNOS-positive platelets compared to controls, and this change was associated with disease severity as assessed by ICU admission. A higher eNOS-negative to -positive platelet percentage was associated with enhanced platelet activation as measured by surface CD62P. Accordingly, COVID-19 patients demonstrated higher TNF-α, IL-6, and IL-1β plasma concentrations than controls. Inflammatory cytokines associated with COVID-19 promoted eNOS-negative Meg-01 formation and enhanced subsequent eNOS-negative platelet-like particle formation. CONCLUSIONS: COVID-19 patients have a higher percentage of eNOS-negative to -positive platelets, likely as a result of inflammatory response reducing megakaryocyte eNOS expression, which predisposes to thrombosis.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.182
GPT teacher head0.456
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations4
Published2024
Admission routes2
Has abstractno

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