Evidence map›Paper›PMID 34132558›Full record

ArticleLangmuir : the ACS journal of surfaces and colloids2021

Tuning the Properties of Active Microtubule Networks by Depletion Forces.

Vahid Nasirimarekani, Tobias Strübing, Andrej Vilfan, Isabella Guido

Abstract read
In one paragraph

Article in Langmuir : the ACS journal of surfaces and colloids, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Vahid NasirimarekaniUniversity of the Basque Country UPV/EHU, 01006 Vitoria-Gasteiz, Spain.
Tobias StrübingMax Planck Institute for Dynamics and Self-Organization, 37077 Göttingen, Germany.
Andrej VilfanMax Planck Institute for Dynamics and Self-Organization, 37077 Göttingen, Germany.ORCID 0000-0001-8985-6072
Isabella GuidoMax Planck Institute for Dynamics and Self-Organization, 37077 Göttingen, Germany.ORCID 0000-0002-1781-3767

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Suspensions of microtubules and nonadsorbing particles form thick and long bundles due to depletion forces. Such interactions act at the nanometer scale and define the structural and dynamical properties of the resulting networks. In this study, we analyze the depletion forces exerted by two types of nonadsorbing particles, namely, the polymer, poly(ethylene glycol) (PEG), and the block copolymer, Pluronic. We characterize their effects both in passive and active networks by adding motor proteins to the suspensions. By exploiting its bundling effect via entropic forces, we observed that PEG generates a network with thick structures showing a nematic order and larger mesh size. On the other hand, Pluronic builds up a much denser gel-like network without a recognizable mesh structure. This difference is also reflected in the network activity. PEG networks show moderate contraction in lateral directions while Pluronic networks exhibit faster and isotropic contraction. Interestingly, by mixing the two nonadsorbing polymers in different ratios, we observed that the system showed a behavior that exhibited properties of both agents, leading to a robust and fast responsive structure compared to the single-depletant networks. In conclusion, we show how passive osmotic compression modifies the distribution of biopolymers. Its combination with active motors results in a new active material with potential for nanotechnological applications.

Indexed as

MicrotubulesPolyethylene GlycolsKinesinsPoloxamerPolymersKinesinsPoloxamerPolyethylene GlycolsPolymers

Identifiers

PMID34132558
PMCPMC8264947

What OpenQuestion holds

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Registered trials

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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.