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Record W4400944477 · doi:10.1016/j.jacbts.2024.05.014

Inhibiting the P2Y12 Receptor in Megakaryocytes and Platelets Suppresses Interferon-Associated Responses

2024· article· en· W4400944477 on OpenAlexfundno aff
Marcin A. Sowa, Haoyu Sun, Tricia T. Wang, Vitor W. Virginio, Florencia Schlamp, Hanane El Bannoudi, MacIntosh Cornwell, Hannah Bash, Peter Izmirly, H. Michael Belmont, Kelly V. Ruggles, Jill P. Buyon, Deepak Voora, Tessa J. Barrett, Jeffrey S. Berger

Bibliographic record

VenueJACC Basic to Translational Science · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdenosine and Purinergic Signaling
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteNational Institutes of HealthSchool of Medicine, New York UniversityYork University
KeywordsP2Y12PlateletReceptorInterferonPlatelet activationMedicineImmunologyInternal medicineCell biologyBiologyPlatelet aggregation

Abstract

fetched live from OpenAlex

We investigated the impact of antiplatelet therapy on the megakaryocyte (MK) and platelet transcriptome. RNA-sequencing was performed on MKs treated with aspirin or P2Y12 inhibitor, platelets from healthy volunteers receiving aspirin or P2Y12 inhibition, and platelets from patients with systemic lupus erythematosus (SLE). P2Y12 inhibition reduced gene expression and inflammatory pathways in MKs and platelets. In SLE, the interferon (IFN) pathway was elevated. In vitro experiments demonstrated the role of P2Y12 inhibition in reducing IFNα-induced platelet-leukocyte interactions and IFN signaling pathways. These results suggest that P2Y12 inhibition may have therapeutic potential for proinflammatory and autoimmune conditions like SLE.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.012
GPT teacher head0.274
Teacher spread0.262 · 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

Citations9
Published2024
Admission routes1
Has abstractyes

Explore more

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