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Record W2773349905 · doi:10.1021/acsomega.7b01795

Development of a Fluorogenic Reactivity Palette for the Study of Nucleophilic Addition Reactions Based on <i>meso</i>-Formyl BODIPY Dyes

2017· article· en· W2773349905 on OpenAlexafffund
Lana E. Greene, Richard Lincoln, Katerina Krumova, Gonzalo Cosa

Bibliographic record

VenueACS Omega · 2017
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence and Fluorescent Materials
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsBODIPYNucleophileReactivity (psychology)ElectrophileChemistryFluorescencePhotochemistryQuantum yieldNucleophilic additionCombinatorial chemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide We describe herein a fluorescence-based assay to characterize and report on nucleophilic addition to carbonyl moieties and highlight the advantages a fluorescence-based assay and multiplex analysis can offer. The assay relies on the fluorogenic properties of meso -formyl boron-dipyrromethene (BODIPY) dyes that become emissive following nucleophilic addition. A reactivity palette is assembled based on the increasing electrophilic character of five meso -formyl BODIPY compounds tested. We show that increasing rates of emission enhancement correlate with the decreasing electrophilic character of BODIPY dyes in the presence of an acid catalyst and a nucleophile. These results are consistent with the rate-limiting step involving activation of the electrophile. Increasing product formation is shown to correlate with the increasing electrophilic character of the BODIPY dyes, as expected based on thermodynamics. In addition to providing rates of reaction, analysis of the fluorescence parameters for the reaction mixtures, including emission quantum yields and fluorescence lifetimes, enables us to determine the extent of reactant conversion at equilibrium (in our case the estimated yield of a transient species) and the presence of different products, without the need for isolation. We anticipate that our reactivity palette approach, combined with the in-depth fluorescence analysis discussed herein, will provide guidelines toward developing fluorogenic assays of reactivity offering multiplex information, beyond fluorescence intensity.

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)0.000
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 score0.045
Threshold uncertainty score0.489

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.042
GPT teacher head0.291
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 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

Citations14
Published2017
Admission routes2
Has abstractyes

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