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Bioengineering
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Advance in Bioprinting for Tissue Engineering and Regenerative Medicine
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Advance in Bioprinting for Tissue Engineering and Regenerative Medicine

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Regenerative Engineering".

Deadline for manuscript submissions: closed (28 February 2025) | Viewed by 10748

Special Issue Editor

Dr. Wei Long Ng

E-Mail Website
Guest Editor
Singapore Centre for 3D Printing (SC3DP), School of Mechanical and Aerospace Engineering, Nanyang Technological University (NTU), 50 Nanyang Avenue, Singapore 639798, Singapore
Interests: 3D bioprinting; bio-inks; tissue engineering; cultivated meat; machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the years, significant advances have been made in the field of 3D bioprinting. This involves the deposition of biocompatible bio-inks and living cells for a wide variety of applications such as tissue engineering and regenerative medicine, food printing, pharmaceutical and chemical testing, and fundamental biological studies. Furthermore, the integration of machine learning with 3D bioprinting techniques can potentially help in the optimization of the printing process, in situ monitoring and correction, and bio-ink development.

In this Special Issue, “3D Bioprinting: Recent Advances and Applications”, we aim to solicit manuscripts that highlight the recent developments and advances in 3D bioprinting along with the various applications of 3D bioprinting. Original research, reviews, perspectives and opinions are welcome in this collection. This Special Issue aims to inspire, inform, and provide direction and guidance to researchers in this field.

  • 3D Bioprinting: tissue engineering and regenerative medicine;
  • Food printing;
  • Drug printing;
  • Machine learning in 3D bioprinting.

Dr. Wei Long Ng
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • 3D bioprinting
  • food printing
  • drug printing
  • machine learning

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Published Papers (3 papers)

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Research

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16 pages, 4126 KiB  
Article
Deep Learning for Predicting Spheroid Viability: Novel Convolutional Neural Network Model for Automating Quality Control for Three-Dimensional Bioprinting
by Zyva A. Sheikh, Oliver Clarke, Amatullah Mir and Narutoshi Hibino
Bioengineering 2025, 12(1), 28; https://doi.org/10.3390/bioengineering12010028 - 1 Jan 2025
Cited by 1 | Viewed by 1281
Abstract
Spheroids serve as the building blocks for three-dimensional (3D) bioprinted tissue patches. When larger than 500 μm, the desired size for 3D bioprinting, they tend to have a hypoxic core with necrotic cells. Therefore, it is critical to assess the viability of spheroids [...] Read more.
Spheroids serve as the building blocks for three-dimensional (3D) bioprinted tissue patches. When larger than 500 μm, the desired size for 3D bioprinting, they tend to have a hypoxic core with necrotic cells. Therefore, it is critical to assess the viability of spheroids in order to ensure the successful fabrication of high-viability patches. However, current viability assays are time-consuming, labor-intensive, require specialized training, or are subject to human bias. In this study, we build a convolutional neural network (CNN) model to efficiently and accurately predict spheroid viability, using a phase-contrast image of a spheroid as its input. A comprehensive dataset of mouse mesenchymal stem cell (mMSC) spheroids of varying sizes with corresponding viability percentages, which was obtained through CCK-8 assays, was established and used to train and validate the model. The model was trained to automatically classify spheroids into one of four distinct categories based on their predicted viability: 0–20%, 20–40%, 40–70%, and 70–100%. The model achieved an average accuracy of 92%, with a consistent loss below 0.2. This deep-learning model offers a non-invasive, efficient, and accurate method to streamline the assessment of spheroid quality, thereby accelerating the development of bioengineered cardiac tissue patches for cardiovascular disease therapies. Full article
(This article belongs to the Special Issue Advance in Bioprinting for Tissue Engineering and Regenerative Medicine)
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Review

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41 pages, 3571 KiB  
Review
Three-Dimensional Bioprinting: A Comprehensive Review for Applications in Tissue Engineering and Regenerative Medicine
by Nicholas A. Mirsky, Quinn T. Ehlen, Jason A. Greenfield, Michael Antonietti, Blaire V. Slavin, Vasudev Vivekanand Nayak, Daniel Pelaez, David T. Tse, Lukasz Witek, Sylvia Daunert and Paulo G. Coelho
Bioengineering 2024, 11(8), 777; https://doi.org/10.3390/bioengineering11080777 - 31 Jul 2024
Cited by 6 | Viewed by 7434
Abstract
Since three-dimensional (3D) bioprinting has emerged, it has continuously to evolved as a revolutionary technology in surgery, offering new paradigms for reconstructive and regenerative medical applications. This review highlights the integration of 3D printing, specifically bioprinting, across several surgical disciplines over the last [...] Read more.
Since three-dimensional (3D) bioprinting has emerged, it has continuously to evolved as a revolutionary technology in surgery, offering new paradigms for reconstructive and regenerative medical applications. This review highlights the integration of 3D printing, specifically bioprinting, across several surgical disciplines over the last five years. The methods employed encompass a review of recent literature focusing on innovations and applications of 3D-bioprinted tissues and/or organs. The findings reveal significant advances in the creation of complex, customized, multi-tissue constructs that mimic natural tissue characteristics, which are crucial for surgical interventions and patient-specific treatments. Despite the technological advances, the paper introduces and discusses several challenges that remain, such as the vascularization of bioprinted tissues, integration with the host tissue, and the long-term viability of bioprinted organs. The review concludes that while 3D bioprinting holds substantial promise for transforming surgical practices and enhancing patient outcomes, ongoing research, development, and a clear regulatory framework are essential to fully realize potential future clinical applications. Full article
(This article belongs to the Special Issue Advance in Bioprinting for Tissue Engineering and Regenerative Medicine)
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Other

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12 pages, 3263 KiB  
Technical Note
Quantitative Assessment of Acetabular Defects in Revision Hip Arthroplasty Based on 3D Modeling: The Area Increase Ratio (AIR) Method
by Giuseppe Marongiu, Antonio Campacci and Antonio Capone
Bioengineering 2024, 11(4), 341; https://doi.org/10.3390/bioengineering11040341 - 30 Mar 2024
Viewed by 1387
Abstract
The most common classifications for acetabular bone defects are based on radiographic two-dimensional imaging, with low reliability and reproducibility. With the rise of modern processing techniques based on 3D modelling, methodologies for the volumetric quantification of acetabular bone loss are available. Our study [...] Read more.
The most common classifications for acetabular bone defects are based on radiographic two-dimensional imaging, with low reliability and reproducibility. With the rise of modern processing techniques based on 3D modelling, methodologies for the volumetric quantification of acetabular bone loss are available. Our study aims to describe a new methodology for the quantitative assessment of acetabular defects based on 3D modelling, focused on surface analysis of the integrity of the main anatomical structures of the acetabulum represented by four corresponding sectors (posterior, superior, anterior, and medial). The defect entity is measured as the area increase ratio (AIR) detected in all the sectors analyzed on three planes of view (frontal, sagittal, and axial) compared to healthy hemipelvises. The analysis was performed on 3D models from the CT-scan of six exemplary specimens with a unilateral pathological hemipelvis. The AIR between the native and the pathological hemipelvis was calculated for each sector, for a total of 48 analyses (range, +0.93–+171.35%). An AIR of >50% were found in 22/48 (45.8%) sectors and affected mostly the posterior, medial, and superior sectors (20/22, 90.9%). Qualitative analysis showed consistency between the data and the morphological features of the defects. Further studies with larger samples are needed to validate the methodology and potentially develop a new classification scheme. Full article
(This article belongs to the Special Issue Advance in Bioprinting for Tissue Engineering and Regenerative Medicine)
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