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Record W3095988575 · doi:10.1182/blood-2020-137213

Platelet Membrane Procoagulation in Preeclampsia

2020· article· en· W3095988575 on OpenAlexaff
Adrienne Lee, Lorriane Chow, Leslie Skeith, Joshua Nicholas, Man‐Chiu Poon, Alastair W. Poole, Ejaife O. Agbani

Bibliographic record

VenueBlood · 2020
Typearticle
Languageen
FieldMedicine
TopicPregnancy and preeclampsia studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPlateletPreeclampsiaPlatelet activationMedicineInternal medicineEndocrinologyPathophysiologyMean platelet volumeAndrologyImmunologyPregnancyBiology

Abstract

fetched live from OpenAlex

Background: Preeclampsia is a hypertensive disorder in pregnancy that results in significant adverse maternal and neonatal outcomes. Platelet activation is involved in the pathophysiology of preeclampsia and contributes to the prothrombotic state of the disorder. The mechanisms which initiate and sustain platelet activation in preeclampsia, and how platelets are involved in the pathogenesis of coagulation abnormalities in preeclampsia remains unclear.Aim: To utilise a systematic analysis of Procoagulant Membrane Dynamics (PMD) to assess platelet procoagulation in normotensive pregnancies and preeclampsia, compared to age-matched non-pregnant female controls. Methods: Platelets were assessed using 4D live-cell imaging, immunoassay, flow cytometry and impedance aggregometry. Study participants were healthy, non-diabetic, normotensive, non-pregnant controls, (NP, N=9), normotensive pregnant controls (PC, N=9), and pregnant women with preeclampsia (PEE, N=8). Result: Platelets of preeclamptic patients were significantly activated under basal conditions and showed major remodelling of the open canalicular or dense tubular system. Compared to NP and PC controls, PEE platelets showed a marked decrease in dense granule release, and total exposed phosphatidylserine (PS)-laden surface as well as a decreased whole-blood aggregation in response to high concentration collagen stimulation. Notably, in patients who were pregnant, we visualized in both plasma and peripheral whole blood, freely suspended platelet microthrombi ranging from 10-15 µm radius but were more in PEE participants (~75%) than in the normal pregnant controls (~22%). These microthrombi showed fibrin deposits in between procoagulant platelets with ballooned membranes. Unstimulated PEE platelets showed more than a 2-fold increase in the membrane expression of the facultative glucose transporter GLUT3 which normally reside within the intracellular membrane of alpha granules. Multiplex immunoassay for inflammatory markers confirmed the elevation of previously unreported i-309 and C-TACK inflammatory cytokines in PEE participants. Discussion: We elucidated a platelet-based mechanism of procoagulation in patients with preeclampsia; and demonstrated that platelets were highly activated in the basal, resting state in preeclampsia. Platelet hyperactivation in preeclampsia is complex; there is evidence of procoagulant morphologic membrane changes and p-selectin expression, yet platelets were less able to adhere to exposed collagen to form primary hemostatic plugs. Additionally, novel platelet activation and inflammatory markers such as GLUT3, i-309, and C-TACK cytokines requires further study to understand how they mediate the platelet activation process and the pathophysiology of preeclampsia. Conclusion: Platelet hyperactivation and increased GLUT3 membrane expression may contribute to the progression of preeclampsia, and to the thrombotic and coagulopathic maternal complications of the disease. The platelet activation process itself may provide biomarkers for staging and phenotyping preeclampsia and for the prediction of its severity, clinical manifestations, and disease progression. Disclosures Lee: Takeda: Consultancy, Honoraria, Speakers Bureau; Bayer: Honoraria. Poon:Takeda: Other: honoraria for advisory board meeting attendance; Pfizer: Other: honoraria for advisory board meeting attendance; Novo Nordisk: Other: honoraria for advisory board meeting attendance; Roche: Other: honoraria for advisory board meeting attendance; Bayer: Other: honoraria for advisory board meeting attendance, Research Funding; Bioverative/Sanofi: Other: honoraria for advisory board meeting attendance; CSL-Behring: Other: honoraria for advisory board meeting attendance, Research Funding.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.030
GPT teacher head0.256
Teacher spread0.226 · 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 designBench or experimental
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".

Quick stats

Citations7
Published2020
Admission routes1
Has abstractyes

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