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Record W3082618557 · doi:10.3390/molecules25173995

Telodendrimers: Promising Architectural Polymers for Drug Delivery

2020· review· en· W3082618557 on OpenAlexafffund
Søren Leth Mejlsøe, Ashok Kakkar

Bibliographic record

VenueMolecules · 2020
Typereview
Languageen
FieldMaterials Science
TopicDendrimers and Hyperbranched Polymers
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDendrimerNanocarriersNanotechnologyDrug deliveryMacromoleculeLinear polymerPolymerVariety (cybernetics)Polymer architectureMaterials scienceComputer scienceCombinatorial chemistryChemistryOrganic chemistryPolymer chemistry

Abstract

fetched live from OpenAlex

Architectural complexity has played a key role in enhancing the efficacy of nanocarriers for a variety of applications, including those in the biomedical field. With the continued evolution in designing macromolecules-based nanoparticles for drug delivery, the combination approach of using important features of linear polymers with dendrimers has offered an advantageous and viable platform. Such nanostructures, which are commonly referred to as telodendrimers, are hybrids of linear polymers covalently linked with different dendrimer generations and backbones. There is considerable variety in selection from widely studied linear polymers and dendrimers, which can help tune the overall composition of the resulting hybrid structures. This review highlights the advances in articulating syntheses of these macromolecules, and the contributions these are making in facilitating therapeutic administration. Limited progress has been made in the design and synthesis of these hybrid macromolecules, and it is through an understanding of their physicochemical properties and aqueous self-assembly that one can expect to fully exploit their potential in 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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.031
GPT teacher head0.296
Teacher spread0.264 · 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.

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

Citations12
Published2020
Admission routes2
Has abstractyes

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