Evidence map›Paper›PMID 37417657›Full record

ReviewACS synthetic biology2023

Engineering Tissue-Scale Properties with Synthetic Cells: Forging One from Many.

Alexander J Lin, Ahmed Z Sihorwala, Brian Belardi

Abstract readReview
In one paragraph

Review in ACS synthetic biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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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

3 authors.

Alexander J LinDepartment of Chemistry, University of Texas at Austin, Austin, Texas 78712, United States.
Ahmed Z SihorwalaMcKetta Department of Chemical Engineering, University of Texas at Austin, Austin, Texas 78712, United States.
Brian BelardiMcKetta Department of Chemical Engineering, University of Texas at Austin, Austin, Texas 78712, United States.ORCID 0000-0003-3608-0164

Funding

A Molecular Toolkit for Controlling and Probing Cell Junction-Actin InteractionsR35GM142941 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI BELARDI, BRIAN · 2021 to 2025
$1.9M
NIGMS NIH HHS R35 GM142941
6 · The paper itself

Abstract

In metazoans, living cells achieve capabilities beyond individual cell functionality by assembling into multicellular tissue structures. These higher-order structures represent dynamic, heterogeneous, and responsive systems that have evolved to regenerate and coordinate their actions over large distances. Recent advances in constructing micrometer-sized vesicles, or synthetic cells, now point to a future where construction of synthetic tissue can be pursued, a boon to pressing material needs in biomedical implants, drug delivery systems, adhesives, filters, and storage devices, among others. To fully realize the potential of synthetic tissue, inspiration has been and will continue to be drawn from new molecular findings on its natural counterpart. In this review, we describe advances in introducing tissue-scale features into synthetic cell assemblies. Beyond mere complexation, synthetic cells have been fashioned with a variety of natural and engineered molecular components that serve as initial steps toward morphological control and patterning, intercellular communication, replication, and responsiveness in synthetic tissue. Particular attention has been paid to the dynamics, spatial constraints, and mechanical strengths of interactions that drive the synthesis of this next-generation material, describing how multiple synthetic cells can act as one.

Indexed as

Artificial CellsCell CommunicationDrug Delivery SystemsTissue Engineeringadhesioncell mechanicsintercellular communicationregenerationsynthetic cellstissue

Identifiers

PMID37417657
PMCPMC11017731

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.