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Record W2253073670 · doi:10.7508/ijnd.2010.02.001

Functionalized CNTs for delivery of therapeutics

2010· article· en· W2253073670 on OpenAlexaff
Farshid S. Garmaroudi, R.A.R. Vahdati

Bibliographic record

VenueInternational journal of nanodimension. · 2010
Typearticle
Languageen
FieldMaterials Science
TopicCarbon Nanotubes in Composites
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsNanomedicineCarbon nanotubeNanobiotechnologyNanotechnologyDrug deliveryMaterials scienceSurface modificationBiomoleculeSmall moleculeMacromoleculeMoleculeChemistryNanoparticleOrganic chemistry

Abstract

fetched live from OpenAlex

Carbon nanotubes (CNTs) are high aspect ratio allotropes of carbon. Because of their unique physical and chemical characteristics, they are nominated for a vast variety of applications in the biomedical field. Their very low solubility is the only problem of them which is solved by different methods of Functionalization. After discoveries in the last few years of the capacity of CNTs to penetrate into the cells, and because of the low toxicity they display and are not immunogenic, CNT are known to have impressive potentials to be used as drug and medicine carriers and therefore they hold great potential in the field of nanobiotechnology and nanomedicine. CNTs can be functionalized with different therapeutic molecules and internalized by a variety of cell types to deliver therapeutic and diagnostic small molecules and macromolecules to cells. In this review, we will describe the potential of functionalized carbon nanotubes to deliver different types of therapeutic molecules.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.017
GPT teacher head0.290
Teacher spread0.273 · 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

Citations7
Published2010
Admission routes1
Has abstractyes

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Same venueInternational journal of nanodimension.Same topicCarbon Nanotubes in CompositesFrench-language works237,207