Evidence map›Paper›PMID 35056239›Full record

ReviewMicromachines2021

Engineering Biological Tissues from the Bottom-Up: Recent Advances and Future Prospects.

Xiaowen Wang, Zhen Wang, Wenya Zhai, Fengyun Wang, Zhixing Ge, Haibo Yu, Wenguang Yang

Abstract readReview
In one paragraph

Review in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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  3. Article
  4. Review
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  6. Article
  7. Review
  8. Review
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  10. Article
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

7 authors.

Xiaowen WangSchool of Electromechanical and Automotive Engineering, Yantai University, Yantai 264005, China.
Zhen WangSchool of Electromechanical and Automotive Engineering, Yantai University, Yantai 264005, China.
Wenya ZhaiSchool of Energy and Materials Engineering, Shandong Polytechnic College, Jining 272000, China.
Fengyun WangSchool of Electromechanical and Automotive Engineering, Yantai University, Yantai 264005, China.
Zhixing GeState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
Haibo YuState Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
Wenguang YangSchool of Electromechanical and Automotive Engineering, Yantai University, Yantai 264005, China.ORCID 0000-0002-1560-665X

Funding

Joint fund of Science & Technology Department of Liaoning Province and State Key Laboratory of Robotics 2021-KF-22-03Key Research Program of Frontier Science QYZDB-SSW-JSC008National Key R&D Program of China 2018YFB130490National Natural Science Foundation of China 61803323Shandong Province Natural Science Foundation ZR2019BF049Shandong Province Natural Science Foundation ZR2020ME14
6 · The paper itself

Abstract

Tissue engineering provides a powerful solution for current organ shortages, and researchers have cultured blood vessels, heart tissues, and bone tissues in vitro. However, traditional top-down tissue engineering has suffered two challenges: vascularization and reconfigurability of functional units. With the continuous development of micro-nano technology and biomaterial technology, bottom-up tissue engineering as a promising approach for organ and tissue modular reconstruction has gradually developed. In this article, relevant advances in living blocks fabrication and assembly techniques for creation of higher-order bioarchitectures are described. After a critical overview of this technology, a discussion of practical challenges is provided, and future development prospects are proposed.

Indexed as

bottom-up tissue engineeringdrug screeningmicro-fabricationmodular assembly

Identifiers

PMID35056239
PMCPMC8780533

What OpenQuestion holds

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Registered trials

None linked

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.