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Record W2084569287 · doi:10.3109/1061186x.2010.521159

Biphasic interactions between a cationic dendrimer and actin

2010· article· en· W2084569287 on OpenAlexaff
Pakatip Ruenraroengsak, Alexander T. Florence

Bibliographic record

VenueJournal of drug targeting · 2010
Typearticle
Languageen
FieldMaterials Science
TopicDendrimers and Hyperbranched Polymers
Canadian institutionsCentre for Drug Research and Development
Fundersnot available
KeywordsDendrimerPolymerizationCationic polymerizationBiophysicsCytoplasmChemistryActinActin remodelingPolymer chemistryPolymerCytoskeletonCellActin cytoskeletonBiochemistryOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Gene delivery systems face the problem not only of the route toward the cell and tissues in question, but also of the molecularly crowded environment of both the cytoplasm and the nucleus itself. One of the physical barriers in the cytoplasm for diffusing nanoparticles is an actin network. Here, we describe the finding that a self-fluorescent sixth generation cationic dendrimer (6 nm in diameter) interacts reversibly and possibly electrostatically with actin filaments in vitro. Not only does this interaction slow the diffusion of the dendrimer but it also affects actin polymerization in a biphasic manner. At low concentrations the dendrimer behaves like a G-binding actin protein, retarding actin polymerization, whereas at high concentrations the dendrimer acts as a nucleating protein accelerating the polymerization. Thus in vivo the diffusion of a dendrimer carrier such as this has both physical and chemical elements: by decreasing polymerization it might accelerate its own transport, and by enhancing actin polymerization retard it. This finding suggests that such a dendrimer may have a role as an anticancer agent through its inhibitory effect on actin polymerization.

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 score0.001
Threshold uncertainty score0.005

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.267
Teacher spread0.258 · 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

Citations17
Published2010
Admission routes1
Has abstractyes

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