MétaCan
Menu
Back to cohort
Record W2331740800 · doi:10.1021/mz5006298

Combined A<sup>3</sup> Coupling and Click Chemistry Approach for the Synthesis of Dendrimer-Based Biological Tools

2014· article· en· W2331740800 on OpenAlexafffund
Anjali Sharma, Diana Mejı́a, Aurélie Regnaud, Nick Uhlig, Chao‐Jun Li, Dušica Maysinger, Ashok Kakkar

Bibliographic record

VenueACS Macro Letters · 2014
Typearticle
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsMcGill University
FundersCanadian Institutes of Health Research
KeywordsDendrimerClick chemistryAlkyneAzideMacromoleculeCombinatorial chemistryNanotechnologyChemistryDrug deliveryCoupling reactionChemical biologyMaterials scienceOrganic chemistry

Abstract

fetched live from OpenAlex

We report a versatile approach in which two highly efficient chemical reactions, multicomponent A 3 coupling and alkyne–azide click chemistry, are combined to construct dendrimer-based tools for applications in biology. Using a convergent approach, dendrons with desired architecture and an alkyne at the focal point are first assembled and then stitched together via multicomponent A 3 coupling reaction. The desired functional groups, including a stealth agent, imaging dye, and drug molecules, could be easily covalently linked to the surfaces of these hyperbranched macromolecules using alkyne–azide click chemistry. These A 3 -click dendrimers are noncytotoxic at concentrations as high as 1 μM and in fact reduce the toxicity of the drug. The dye-coated dendrimers specifically target and localize in lipid droplets. This unison methodology represents an attractive chemical strategy in exploiting the untapped potential of A 3 coupling and facilitating the development of nanodevices for imaging and drug delivery.

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 score0.002
Threshold uncertainty score0.005

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.028
GPT teacher head0.243
Teacher spread0.215 · 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

Citations23
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueACS Macro LettersSame topicClick Chemistry and ApplicationsFrench-language works237,207