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Record W2755724325 · doi:10.1039/c7cs00040e

Chemistry and engineering of cyclodextrins for molecular imaging

2017· review· en· W2755724325 on OpenAlexaff
Wing‐Fu Lai, Andrey L. Rogach, Wing‐Tak Wong

Bibliographic record

VenueChemical Society Reviews · 2017
Typereview
Languageen
FieldChemistry
TopicSupramolecular Chemistry and Complexes
Canadian institutionsHealth Sciences Centre
FundersHong Kong Polytechnic University
KeywordsAmphiphileChemistryNanotechnologyPayload (computing)Translation (biology)Molecular recognitionMolecular engineeringCombinatorial chemistryMoleculeComputer scienceMaterials scienceOrganic chemistryBiochemistryPolymer

Abstract

fetched live from OpenAlex

Cyclodextrins (CDs) are naturally occurring cyclic oligosaccharides bearing a basket-shaped topology with an "inner-outer" amphiphilic character. The abundance of hydroxyl groups enables CDs to be functionalized with multiple targeting ligands and imaging elements. The imaging time, and the payload of different imaging elements, can be tuned by taking advantage of the commercial availability of CDs with different sizes of the cavity. This review aims to offer an outlook of the chemistry and engineering of CDs for the development of molecular probes. Complexation thermodynamics of CDs, and the corresponding implications for probe design, are also presented with examples demonstrating the structural and physiochemical roles played by CDs in the full ambit of molecular imaging. We hope that this review not only offers a synopsis of the current development of CD-based molecular probes, but can also facilitate translation of the incremental advancements from the laboratory to real biomedical applications by illuminating opportunities and challenges for future research.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.056
GPT teacher head0.331
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations123
Published2017
Admission routes1
Has abstractyes

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