Evidence map›Paper›PMID 34260387›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2021

An effective and efficient model of the near-field hydrodynamic interactions for active suspensions of bacteria.

Bokai Zhang, Premkumar Leishangthem, Yang Ding, Xinliang Xu

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Bokai ZhangComplex Systems Division, Beijing Computational Science Research Center, Beijing 100193, China.
Premkumar LeishangthemComplex Systems Division, Beijing Computational Science Research Center, Beijing 100193, China.ORCID 0000-0002-7762-2655
Yang DingMechanics Division, Beijing Computational Science Research Center, Beijing 100193, China; dingyang@csrc.ac.cn xinliang@csrc.ac.cn.ORCID 0000-0002-8252-2421
Xinliang XuComplex Systems Division, Beijing Computational Science Research Center, Beijing 100193, China; dingyang@csrc.ac.cn xinliang@csrc.ac.cn.ORCID 0000-0003-4940-3612

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Near-field hydrodynamic interactions in active fluids are essential to determine many important emergent behaviors observed, but have not been successfully modeled so far. In this work, we propose an effective model capturing the essence of the near-field hydrodynamic interactions through a tensorial coefficient of resistance, validated numerically by a pedagogic model system consisting of an

Indexed as

HydrodynamicsModels, BiologicalComputer SimulationEscherichia coliSuspensionsSuspensionsbacterial motionlow Reynolds number fluidnear-field hydrodynamics

Identifiers

PMID34260387
PMCPMC8285906

What OpenQuestion holds

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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.