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Biomedicines
Special Issues
Advanced Research in Cell and Tissue Engineering
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Advanced Research in Cell and Tissue Engineering

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Biomedical Engineering and Materials".

Deadline for manuscript submissions: 30 December 2026 | Viewed by 1946

Special Issue Editor

Dr. Yoshitaka Miyamoto

E-Mail Website
Guest Editor
Department of Precision Biomedical Engineering, Institute of Biomaterials and Bioengineering, 2-3-10 Kanda-Surugadai, Chiyoda-ku, Tokyo 101-0062, Japan
Interests: cell therapy; regenerative therapy; cell biotechnology; 3D culture; nanoparticles; bioimaging; biobank; cryopreservation; stem cell; health technology assessment; bioactive gels
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

From the 20th to the 21st century, culture techniques for regenerating tissues and organs using biomaterials such as biologically derived substances and synthetic polymers rapidly developed. Eventually, Langer and Vacanti (1993) proposed “tissue engineering” to develop organ and tissue substitutes that enable the regeneration, maintenance, and repair of life functions.

In recent years, interdisciplinary research has been conducted across various fields, including stem cell research, materials engineering, mechanical engineering, electrical and electronic engineering, chemical engineering, and information engineering, to create multiple tissues and organs from cells within the body, advancing medical and drug development.

In this Special Issue, we encourage submissions of papers on cutting-edge engineering technologies and previously testified research in cell and tissue engineering, including spheroid and organoid research, microfabrication, and microphysiological systems (MPSs), the use of decellularized tissues, and applications in regenerative medicine and transplantation medicine.

Dr. Yoshitaka Miyamoto
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 250 words) can be sent to the Editorial Office for assessment.

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. Biomedicines 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 2600 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

  • cell and tissue engineering
  • regenerative medicine
  • stem cells
  • organoid
  • biomaterials
  • extracellular matrix (ECM)
  • micro electro mechanical systems (MEMSs)
  • microphysiological systems (MPSs)
  • medical device
  • decellularization (decellularized tissue)

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Published Papers (2 papers)

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15 pages, 2353 KB  
Article
VeritaCell-Derived Autologous Skin Cell Suspensions Enhance Wound Closure Dynamics and Tissue Architecture in a Rat Excisional Wound Model
by Michael Peake, Olafs Volrāts, Vladimirs Pilipenko, Jolanta Upīte, Arseniy Sergeyev, Baiba Jansone and Nikolaos T. Georgopoulos
Biomedicines 2026, 14(5), 1079; https://doi.org/10.3390/biomedicines14051079 - 9 May 2026
Viewed by 648
Abstract
Background/Objectives: Autologous cell suspension (ACS)-based therapy is a promising strategy to enhance wound healing, yet limitations in current methodologies hinder clinical efficacy. We have previously developed VeritaCell, a rapid isolation method that yields highly viable skin cell populations, including epidermal stem cells, [...] Read more.
Background/Objectives: Autologous cell suspension (ACS)-based therapy is a promising strategy to enhance wound healing, yet limitations in current methodologies hinder clinical efficacy. We have previously developed VeritaCell, a rapid isolation method that yields highly viable skin cell populations, including epidermal stem cells, and demonstrated their wound healing-enhancing biological properties in vitro (such as acceleration of keratinocyte proliferation and suppression of scarring-associated molecular responses). In the present study, we have assessed the efficacy of VeritaCell-derived ACS cell populations in enhancing both the rate and quality of healing using an in vivo rat excisional wound model. Methods: Full-thickness wounds were treated with ACS at donor-to-wound area ratios of 1:1, 1:10, and 1:20. Wound progression was monitored by standardised image-based quantification of percentage wound closure and healing quality was evaluated by histological assessment of tissue architecture. Results: ACS-treated wounds demonstrated improved early healing dynamics, with enhanced wound closure evident by Day 6 across all ACS treatment groups. Histological assessment revealed improved neo-epithelial organisation and reduced scarring-associated epidermal thickening in the 1:10 and 1:20 groups, with the 1:10 group exhibiting tissue architecture most closely resembling unwounded skin. Conclusions: Collectively, these findings provide preclinical validation that ACS isolates generated using the VeritaCell methodology exhibit functional activity in vivo and support improved tissue-level repair at clinically relevant donor-to-wound coverage ratios. Our observations offer insights into the strong potential of our ACS approach in providing a practical and cost-effective medical solution that will facilitate more aesthetically favourable healing outcomes. Full article
(This article belongs to the Special Issue Advanced Research in Cell and Tissue Engineering)
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13 pages, 2759 KB  
Article
Prospective Assessment of Embryoid Body by Deep Learning on Label-Free Time-Lapse Images from the Microwell Array
by Yoshinori Inoue, Yoshitaka Miyamoto, Shuya Suda, Koji Ikuta and Masashi Ikeuchi
Biomedicines 2026, 14(2), 445; https://doi.org/10.3390/biomedicines14020445 - 16 Feb 2026
Viewed by 576
Abstract
Background: Embryoid bodies (EBs) play a central role in organoid engineering, where their formation fidelity and size critically influence downstream differentiation outcomes. Current EB production workflows primarily rely on retrospective quality assessment, which limits reproducibility in high-throughput culture systems. Objective: This study aimed [...] Read more.
Background: Embryoid bodies (EBs) play a central role in organoid engineering, where their formation fidelity and size critically influence downstream differentiation outcomes. Current EB production workflows primarily rely on retrospective quality assessment, which limits reproducibility in high-throughput culture systems. Objective: This study aimed to develop a prospective, non-invasive framework that integrates early-phase bright-field time-lapse imaging with a three-dimensional convolutional neural network to predict EB formation outcomes and final EB diameter within the microwell platform. Methods: Time-lapse image sequences collected during the first hours after cell seeding on the microwell array were used to train 3D-CNN models for classification (formation vs. non-formation) and regression (final diameter). A balanced dataset was constructed through under-sampling, and five-fold cross-validation with data augmentation was applied to evaluate model performance. Results: The classification model achieved an accuracy of 96.5%, reliably distinguishing between successful and failed EB formation using short-duration image sequences. The regression model predicted the final EB diameter with a mean absolute error of ±7.1 µm, reflecting strong agreement with measured values and capturing seeding-density-dependent size variations. Conclusions: Early aggregation dynamics captured by bright-field time-lapse imaging contain sufficient spatiotemporal information to enable accurate, prospective EB quality prediction. The proposed framework provides a label-free and automation-compatible strategy for improving reproducibility in large-scale EB manufacturing and supports the future development of adaptive and closed-loop organoid culture systems for clinical applications. Full article
(This article belongs to the Special Issue Advanced Research in Cell and Tissue Engineering)
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