Evidence map›Paper›PMID 39349524›Full record

ArticleScientific reports2024

Evaluating the efficacy of uniformly designed square mesh resin 3D printed scaffolds in directing the orientation of electrospun PCL nanofibers.

Evan Fair, Jacob Bornstein, Timothy Lyons, Phillip Sgobba, Alana Hayes, Megan Rourke, Isaac Macwan, Naser Haghbin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Regenerative strategies for intervertebral disc degeneration.Journal of orthopaedic translation · 2025
    Review
  4. 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

8 authors.

Evan FairDepartment of Electrical and Biomedical Engineering, School of Engineering and Computing, Fairfield University, 1073 North Benson Rd, Fairfield, CT, 06824, USA.
Jacob BornsteinDepartment of Electrical and Biomedical Engineering, School of Engineering and Computing, Fairfield University, 1073 North Benson Rd, Fairfield, CT, 06824, USA.
Timothy LyonsDepartment of Mechanical Engineering, School of Engineering and Computing, Fairfield University, 1073 North Benson Rd, Fairfield, CT, 06824, USA.
Phillip SgobbaDepartment of Electrical and Biomedical Engineering, School of Engineering and Computing, Fairfield University, 1073 North Benson Rd, Fairfield, CT, 06824, USA.
Alana HayesDepartment of Mechanical Engineering, School of Engineering and Computing, Fairfield University, 1073 North Benson Rd, Fairfield, CT, 06824, USA.
Megan RourkeDepartment of Mechanical Engineering, School of Engineering and Computing, Fairfield University, 1073 North Benson Rd, Fairfield, CT, 06824, USA.
Isaac MacwanDepartment of Electrical and Biomedical Engineering, School of Engineering and Computing, Fairfield University, 1073 North Benson Rd, Fairfield, CT, 06824, USA. imacwan@fairfield.edu.
Naser HaghbinDepartment of Mechanical Engineering, School of Engineering and Computing, Fairfield University, 1073 North Benson Rd, Fairfield, CT, 06824, USA. nhaghbin@fairfield.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Replicating the architecture of extracellular matrices (ECM) is crucial in tissue engineering to support tissues' natural structure and functionality. The ECM's structure plays a significant role in directing cell alignment. Electrospinning is an effective technique for fabricating nanofibrous substrates that mimic the architecture of extracellular matrices (ECM). This study aims to evaluate the efficacy of resin 3D-printed scaffolds made from a low-conductivity material (i.e., a resin composed of methacrylated oligomers, monomers, and photoinitiators) in directing the alignment of electrospun polycaprolactone (PCL) nanofibers. Six 3D-printed scaffolds were fabricated using stereolithography (SLA) technology and strategically positioned on an aluminum foil collector plate during electrospinning. The structured geometry of the scaffolds, rather than the local electric field distribution, is hypothesized to guide nanofiber alignment. Images acquired through the scanning electron microscopy (SEM) were used to analyze and statistically quantify the nanofibrous scaffolds to evaluate the alignment of nanofibers over the scaffolds compared to a set of randomly deposited control nanofiber samples in the absence of the 3D printed scaffolds. SEM images also showed significant alignment of nanofibers within the pores of scaffolds, using histograms as a means for indicating the distribution of orientation angles. Statistical analysis revealed that this distribution deviates from normality due to the deviations in the tails and the existence of relatively smaller peaks at angles relative to 0°, particularly within a range of ± 50° and ± 40°. It is further found that the average peak orientation angle relative to 0° had a maximum probability of 0.014. Furthermore, the statistical analysis confirmed the distribution and significant differences in orientation between test samples with 3D-printed scaffolds and control samples. These findings demonstrate the effectiveness of resin 3D-printed scaffolds, particularly their geometric filtering effect, leading to controlled nanofiber alignment, which is proposed to be beneficial for enhancing cell adhesion, proliferation, and cell migration in tissue engineering applications.

Indexed as

NanofibersPolyestersPrinting, Three-DimensionalTissue EngineeringTissue ScaffoldsExtracellular MatrixMicroscopy, Electron, ScanningpolycaprolactonePolyestersDual scale 3D printed scaffoldElectrospinningExtracellular matrix (ECM)Nanofiber alignmentResin 3D printingTissue engineering

Identifiers

PMID39349524
PMCPMC11443100

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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.