MétaCan
Menu
Back to cohort
Record W2793475974 · doi:10.1080/14756366.2018.1437155

Synthesis and biological evaluation of<i>N</i>-arylpiperazine derivatives of 4,4-dimethylisoquinoline-1,3(2<i>H</i>,4<i>H</i>)-dione as potential antiplatelet agents

2018· article· en· W2793475974 on OpenAlexfundno aff
Monika Marcinkowska, Magdalena Kotańska, Agnieszka Zagórska, Joanna Śniecikowska, Monika Kubacka, Agata Siwek, Adam Bucki, Maciej Pawłowski, Marek Bednarski, Jacek Sapa, Małgorzata Starek, Monika Dąbrowska, Marcin Kołaczkowski

Bibliographic record

VenueJournal of Enzyme Inhibition and Medicinal Chemistry · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsnot available
FundersFaculté de pharmacie, Université de MontréalNarodowym Centrum NaukiUniwersytet Jagielloński Collegium Medicum
KeywordsClopidogrelChemistryPharmacologyAspirinMechanism of actionReceptorPlateletAlpha (finance)Platelet aggregationStereochemistryIn vitroMedicineBiochemistryInternal medicineSurgery

Abstract

fetched live from OpenAlex

Despite the substantial clinical success of aspirin and clopidogrel in secondary prevention of ischemic stroke, up to 40% of patients remain resistant to the available antiplatelet treatment. Therefore, there is an urgent clinical need to develop novel antiplatelet agents with a novel mechanism of action. Recent studies revealed that potent alpha 2B-adrenergic receptor (alpha 2B-ARs) antagonists could constitute alternative antiplatelet therapy. We have synthesized a series of N-arylpiperazine derivatives of 4,4-dimethylisoquinoline-1,3(2H,4H)-dione as potential alpha 2B receptor antagonists. The most potent compound 3, effectively inhibited the platelet-aggregation induced both by collagen and ADP/adrenaline with IC50 of 26.9 μM and 20.5 μM respectively. Our study confirmed that the alpha 2B-AR antagonists remain an interesting target for the development of novel antiplatelet agents with an alternative mechanism of action.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.003
Threshold uncertainty score0.437

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.023
GPT teacher head0.290
Teacher spread0.267 · 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 teacher head, 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

Citations15
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Enzyme Inhibition and Medicinal ChemistrySame topicReceptor Mechanisms and SignalingFrench-language works237,207