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Record W3100247758 · doi:10.1021/acsomega.0c04358

Synthesis of Novel Biocompatible Thienopyrimidine Chromophores with Aggregation-Induced Emission Sensitive to Molecular Aggregation

2020· article· en· W3100247758 on OpenAlexaff
Mostafa Ahmed, Osama Younis, Esam A. Orabi, Ahmed M. Sayed, Adel M. Kamal El‐Dean, Reda Hassanien, Rebecca L. Davis, Osamu Tsutsumi, Mahmoud S. Tolba

Bibliographic record

VenueACS Omega · 2020
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsUniversity of Manitoba
FundersJapan Society for the Promotion of ScienceAcademy of Scientific Research and Technology
KeywordsChromophoreChemistryProton NMRCombinatorial chemistryConjugated systemThermal stabilityDensity functional theoryIntermolecular forceQuantum yieldFourier transform infrared spectroscopyCarbon-13 NMRMaterials scienceMoleculePhotochemistryComputational chemistryOrganic chemistryPolymerChemical engineeringFluorescence

Abstract

fetched live from OpenAlex

C NMR spectra. The photophysical properties of some compounds were investigated in the solution and solid states. Density functional theory calculations were also performed to confirm the observed photophysical properties of the compounds. The studied dyes displayed AIE properties with spectral shapes related to the aggregate structure and a quantum yield up to 10.8%. The emission efficiency of the powder is attributed to the incorporation of multiply rotatable and twisted aryl groups to the fused heterocyclic moieties. The dyes also showed high thermal stability and potent antimicrobial activities against numerous bacterial and fungal strains. Additionally, the cytotoxicity of the new compounds was evaluated against the Caco-2 cell line, and molecular docking was used to investigate the binding conformation of the most effective compound with the MNK2 enzyme. Therefore, the presented structures may potentially be used for bioapplications.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.660

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.022
GPT teacher head0.248
Teacher spread0.225 · 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

Citations24
Published2020
Admission routes1
Has abstractyes

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