Evidence map›Paper›PMID 39727767›Full record

ArticleBiomimetics (Basel, Switzerland)2024

3D-Printed Self-Assembling Helical Models for Exploring Viral Capsid Structures.

Donald Plante, Keegan Unzen, John R Jungck

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2024. 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

3 authors.

Donald PlanteDepartment of Applied Engineering & Sciences, University of New Hampshire at Manchester, Manchester, NH 03101, USA.ORCID 0000-0003-2415-9369
Keegan UnzenDepartment of Applied Engineering & Sciences, University of New Hampshire at Manchester, Manchester, NH 03101, USA.
John R JungckDepartments of Biological Sciences and Mathematical Sciences, University of Delaware, Newark, DE 19716, USA.ORCID 0000-0003-4621-5333

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work presents a novel application of additive manufacturing in the design of self-assembling helical viral capsids using 3D-printed components. Expanding on prior work with 3D-printed self-assembling spherical capsids, we developed helical models that integrate geometric parameters and magnetic interactions to mimic key features of the assembly process of helical viral capsids. Using dual-helix phyllotactic patterns and simplified electrostatic simulations, these models consistently self-assemble into a cylinder, providing unique insights into the structural organization and stability of helical capsids. This accessible 3D-printed approach demonstrates the potential of additive manufacturing for research in mesoscale self-assembling models and in the education of complex biological assembly processes, promoting hands-on exploration of viral architecture and self-assembly mechanisms.

Indexed as

3D-printing4D-printingcapsidcapsomerehelicalhelixself-assemblyTMVvirus

Identifiers

PMID39727767
PMCPMC11673919

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.