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Cited by 608

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Recent advances in bioprinting techniques: approaches, applications and future prospects

Open access
Li, Jipeng, Chen, Mingjiao, Fan, Xianqun, Zhou, Huifang·2016·Journal of Translational Medicine

Abstract

Bioprinting technology shows potential in tissue engineering for the fabrication of scaffolds, cells, tissues and organs reproducibly and with high accuracy. Bioprinting technologies are mainly divided into three categories, inkjet-based bioprinting, pressure-assisted bioprinting and laser-assisted bioprinting, based on their underlying printing principles. These various printing technologies have their advantages and limitations. Bioprinting utilizes biomaterials, cells or cell factors as a "bioink" to fabricate prospective tissue structures. Biomaterial parameters such as biocompatibility, cell viability and the cellular microenvironment strongly influence the printed product. Various printing technologies have been investigated, and great progress has been made in printing various types of tissue, including vasculature, heart, bone, cartilage, skin and liver. This review introduces basic principles and key aspects of some frequently used printing technologies. We focus on recent advances in three-dimensional printing applications, current challenges and future directions.

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Metadata

Authors
Li, J., Chen, M., Fan, X., & Zhou, H.
Venue
Journal of Translational Medicine
Published
2016-09-20
Volume
14
Issue
1
Pages
271-271
ISSN
1479-5876 (ISSN-L)
OpenAlex
W2522881937
Cited by
608
References
7
FWCI
21.28
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Recent advances in bioprinting techniques: approaches, applications and future prospects. https://app.cochat.ai/papers/10.1186/s12967-016-1028-0
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Li, J., Chen, M., Fan, X., & Zhou, H. (2016). Recent advances in bioprinting techniques: approaches, applications and future prospects. Journal of Translational Medicine. https://doi.org/10.1186/s12967-016-1028-0

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.