Evidence map›Paper›PMID 30158182›Full record

ArticleJournal of the Royal Society, Interface2018

Langevin equation in complex media and anomalous diffusion.

Silvia Vitali, Vittoria Sposini, Oleksii Sliusarenko, Paolo Paradisi, Gastone Castellani, Gianni Pagnini

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Superstatistical modelling of protein diffusion dynamics in bacteria.Journal of the Royal Society, Interface · 2021
    Article
  5. Review
  6. 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

6 authors.

Silvia VitaliDepartment of Physics and Astronomy, Bologna University, Viale Berti Pichat 6/2, 40126 Bologna, Italy.
Vittoria SposiniInstitute for Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Strasse 24/25, 14476 Potsdam-Golm, Germany.
Oleksii SliusarenkoBCAM-Basque Center for Applied Mathematics, Alameda de Mazarredo 14, 48009 Bilbao, Basque Country, Spain.
Paolo ParadisiBCAM-Basque Center for Applied Mathematics, Alameda de Mazarredo 14, 48009 Bilbao, Basque Country, Spain paolo.paradisi@cnr.it.ORCID 0000-0002-1036-4583
Gastone CastellaniDepartment of Physics and Astronomy, Bologna University, Viale Berti Pichat 6/2, 40126 Bologna, Italy.
Gianni PagniniBCAM-Basque Center for Applied Mathematics, Alameda de Mazarredo 14, 48009 Bilbao, Basque Country, Spain gpagnini@bcamath.org.ORCID 0000-0001-9917-4614

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The problem of biological motion is a very intriguing and topical issue. Many efforts are being focused on the development of novel modelling approaches for the description of anomalous diffusion in biological systems, such as the very complex and heterogeneous cell environment. Nevertheless, many questions are still open, such as the joint manifestation of statistical features in agreement with different models that can also be somewhat alternative to each other, e.g. continuous time random walk and fractional Brownian motion. To overcome these limitations, we propose a stochastic diffusion model with additive noise and linear friction force (linear Langevin equation), thus involving the explicit modelling of velocity dynamics. The complexity of the medium is parametrized via a population of intensity parameters (relaxation time and diffusivity of velocity), thus introducing an additional randomness, in addition to white noise, in the particle's dynamics. We prove that, for proper distributions of these parameters, we can get both Gaussian anomalous diffusion, fractional diffusion and its generalizations.

Indexed as

Models, BiologicalModels, ChemicalStochastic Processesanomalous diffusionbiological transportfractional Brownian motionGaussian processesheterogeneous mediaspace–time fractional diffusion equation

Identifiers

PMID30158182
PMCPMC6127165

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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.