Evidence map›Paper›PMID 38856284›Full record

ArticlePhysical review letters2024

Cell Division and Motility Enable Hexatic Order in Biological Tissues.

Yiwen Tang, Siyuan Chen, Mark J Bowick, Dapeng Bi

Abstract read
In one paragraph

Article in Physical review letters, 2024. 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.

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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.

Yiwen TangDepartment of Physics, Northeastern University, Boston, Massachusetts 02115, USA.
Siyuan ChenDepartment of Physics, University of California, Santa Barbara, Santa Barbara, California 93106, USA.
Mark J BowickDepartment of Physics, University of California, Santa Barbara, Santa Barbara, California 93106, USA.
Dapeng BiDepartment of Physics, Northeastern University, Boston, Massachusetts 02115, USA.

Funding

Integrative biophysical modeling for collective tissue mechanicsR35GM150494 · NIGMS · NORTHEASTERN UNIVERSITY · PI DAPENG BI · 2023 to 2026
$1.6M
NIGMS NIH HHS R35 GM150494
6 · The paper itself

Abstract

Biological tissues transform between solid- and liquidlike states in many fundamental physiological events. Recent experimental observations further suggest that in two-dimensional epithelial tissues these solid-liquid transformations can happen via intermediate states akin to the intermediate hexatic phases observed in equilibrium two-dimensional melting. The hexatic phase is characterized by quasi-long-range (power-law) orientational order but no translational order, thus endowing some structure to an otherwise structureless fluid. While it has been shown that hexatic order in tissue models can be induced by motility and thermal fluctuations, the role of cell division and apoptosis (birth and death) has remained poorly understood, despite its fundamental biological role. Here we study the effect of cell division and apoptosis on global hexatic order within the framework of the self-propelled Voronoi model of tissue. Although cell division naively destroys order and active motility facilitates deformations, we show that their combined action drives a liquid-hexatic-liquid transformation as the motility increases. The hexatic phase is accessed by the delicate balance of dislocation defect generation from cell division and the active binding of disclination-antidisclination pairs from motility. We formulate a mean-field model to elucidate this competition between cell division and motility and the consequent development of hexatic order.

Indexed as

Cell DivisionCell MovementModels, BiologicalApoptosis

Identifiers

PMID38856284
PMCPMC11267118

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.