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Record W4387270165 · doi:10.1161/atvb.43.suppl_1.534

Abstract 534: Peripheral Artery Disease Increases Platelet Activity and Promotes a Prothrombotic Platelet Phenotype

2023· article· en· W4387270165 on OpenAlexaff
Vitor De Moura Virginio, Kamelia Drenkova, Florencia Schlamp, Elliot Luttrell‐Williams, Tessa A Barrett, Jeffrey S. Berger

Bibliographic record

VenueArteriosclerosis Thrombosis and Vascular Biology · 2023
Typearticle
Languageen
FieldMedicine
TopicPeripheral Artery Disease Management
Canadian institutionsBerger (Canada)
Fundersnot available
KeywordsPlateletPlatelet activationMedicineThrombosisP-selectinInternal medicineHemostasisFemoral arteryEndocrinologyImmunology

Abstract

fetched live from OpenAlex

Background: Peripheral artery disease (PAD), characterized by lower extremity atherosclerosis, increases the risk of cardiovascular morbidity and mortality. Among their many functions, platelets modulate hemostasis, thrombosis, inflammation, and angiogenesis. Previously, we noted the potent pathogenic role of platelets in PAD. However, how vascular dysfunction impacts the platelet phenotype is not fully understood. Using a mouse model of PAD (hindlimb ischemia), we investigated the platelet phenotype and transcriptome. Methods: Eighteen C57BL/6J mice (10 weeks) underwent femoral artery ligation (HLI) or sham surgery. Platelet activity, P-selectin, JON/A expression, and platelet-leukocyte aggregation, was assessed at day 0, 3, 7, 10, 14, and 21. At day 21, we performed the FeCl3-induced thrombosis model and assessed time to vessel occlusion. To investigate platelet-relevant mechanisms, we induced HLI or sham surgery in 20 mice and collected platelets for RNA sequencing (day 12). Results: Our acute PAD model resulted in >90% drop in blood flow after the procedure with ≈50% recovery at day 21. Following the procedure, platelet activity, defined by PAR4 agonist stimulated P-selectin expression (P=0.001), αIIbβ3 activation (JON/A expression, P=0.002), platelet-neutrophil aggregation (P<0.001) and platelet monocyte aggregation (P=0.047) increased over time in the HLI vs sham group. Mice in the HLI group had faster occlusive carotid thrombosis than the sham group (P=0.026). Comparing the platelet transcriptome in the HLI vs sham group noted 895 differentially expressed transcripts (P<0.05) between groups (516 up-, 79 down-regulated). Pathway analysis between groups demonstrated enrichment of inflammatory pathways, including interleukin-1 mediated signaling (P=0.02), apoptotic process (P=0.02), noncoding RNA processing (P=0.02), and signaling receptor binding (P=0.03). Conclusion: In our murine model of acute PAD, we found increased platelet activity, a proinflammatory platelet transcriptome, and a prothrombotic state. These data highlight the feasibility of the HLI model to further investigate platelet-associated mechanisms that underlie PAD.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.036
GPT teacher head0.284
Teacher spread0.249 · 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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