Evidence map›Paper›PMID 37056052›Full record

ArticleBiophysical journal2023

Coarse-grained modeling of polystyrene-modified CNTs and their interactions with lipid bilayers.

Gulsah Gul, Roland Faller, Nazar Ileri-Ercan

Open access · bronzeAbstract read
In one paragraph

Article in Biophysical journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 2 countries.

Gulsah GulDepartment of Chemical Engineering, Bogazici University, Istanbul, Turkey; Department of Chemical Engineering, University of California, Davis, Davis, California.
Roland FallerDepartment of Chemical Engineering, University of California, Davis, Davis, California.
Nazar Ileri-ErcanDepartment of Chemical Engineering, Bogazici University, Istanbul, Turkey. Electronic address: nazar.ileri@boun.edu.tr.
Boğaziçi University · TRUniversity of California, Davis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the present work, we describe Martini3 coarse-grained models of polystyrene and carboxyl-terminated polystyrene functionalized carbon nanotubes (CNTs) and investigate their interactions with lipid bilayers with and without cholesterol (CHOL) using molecular dynamics simulations. By changing the polystyrene chain length and grafting density at the end ring of the CNTs at two different nanotube concentrations, we observe the translocation of nanoparticles as well as changes in the lipid bilayer properties. Our results show that all developed models passively diffuse into the membranes without causing any damage to the membrane integrity, although high concentrations of CNTs induce structural and elastic changes in lipid bilayers. In the presence of CHOL, increasing CNT concentration results in decreased rates of CHOL transmembrane motions. On the other hand, CNTs are prone to lipid and polystyrene blockage, which affects their equilibrated configurations, and tilting behavior within the membranes. Hence, we demonstrate that polystyrene-functionalized CNTs are promising drug-carrier agents. However, polystyrene chain length and grafting density are important factors to consider to enhance the efficiency of drug delivery.

Indexed as

Lipid BilayersNanotubes, CarbonCholesterolMolecular Dynamics SimulationPolystyrenesCholesterolLipid BilayersNanotubes, CarbonPolystyrenes

Identifiers

PMID37056052
PMCPMC10209035
OpenAlexW4365453092

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.