Evidence map›Paper›PMID 38109220›Full record

ArticleACS applied materials & interfaces2024

Biointerface Fiber Technology from Electrospinning to Inflight Printing.

Wenyu Wang, Stanley Gong Sheng Ka, Yifei Pan, Yaqi Sheng, Yan Yan Shery Huang

Abstract read
In one paragraph

Article in ACS applied materials & interfaces, 2024. 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. Review
  3. Review
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

5 authors.

Wenyu WangDepartment of Engineering, University of Cambridge, Trumpington Street, CB2 1PZ Cambridge, United Kingdom.
Stanley Gong Sheng KaDepartment of Engineering, University of Cambridge, Trumpington Street, CB2 1PZ Cambridge, United Kingdom.
Yifei PanDepartment of Engineering, University of Cambridge, Trumpington Street, CB2 1PZ Cambridge, United Kingdom.
Yaqi ShengDepartment of Engineering, University of Cambridge, Trumpington Street, CB2 1PZ Cambridge, United Kingdom.
Yan Yan Shery HuangDepartment of Engineering, University of Cambridge, Trumpington Street, CB2 1PZ Cambridge, United Kingdom.ORCID 0000-0003-2619-730X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Building two-dimensional (2D) and three-dimensional (3D) micro- and nanofibril structures with designable patterns and functionalities will offer exciting prospects for numerous applications spanning from permeable bioelectronics to tissue engineering scaffolds. This Spotlight on Applications highlights recent technological advances in fiber printing and patterning with functional materials for biointerfacing applications. We first introduce the current state of development of micro- and nanofibers with applications in biology and medical wearables. We then describe our contributions in developing a series of fiber printing techniques that enable the patterning of functional fiber architectures in three dimensions. These fiber printing techniques expand the material library and device designs, which underpin technological capabilities from enabling fundamental studies in cell migration to customizable and ecofriendly fabrication of sensors. Finally, we provide an outlook on the strategic pathways for developing the next-generation bioelectronics and "Fiber-of-Things" (FoT) using nano/micro-fibers as architectural building blocks.

Indexed as

NanofibersTissue EngineeringTissue ScaffoldsBiocompatible MaterialsHumansPrinting, Three-DimensionalBiocompatible Materialsadditive manufacturingbioelectronicsbiofabricationfiber printingtissue engineeringwearable devices

Identifiers

PMID38109220
PMCPMC11565474

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.