Back

Injectable MSC Spheroid and Microgel Granular Composites for Engineering Cartilage Tissue

Di Caprio, N.; Davidson, M. D.; Daly, A. C.; Burdick, J. A.

2022-12-30 bioengineering
10.1101/2022.12.28.522141 bioRxiv
Show abstract

Articular cartilage is important for joint function, yet it can be damaged due to disease or trauma. Cartilage lacks natural healing processes and current clinical treatments are limited in their ability to form functional cartilage for repair. Here, we reimagine cartilage tissue engineering with an approach that combines aggregates of adult MSCs (spheroids) with hydrogel microparticles (microgels) to form granular composites that are injectable, permit cell-cell contacts for chondrogenesis, allow spheroid fusion and growth, and undergo interparticle crosslinking post-injection via light for stability. We use simulations and experimental analyses to establish the importance of initial MSC spheroid to microgel volume ratios in granular composites that balance mechanical support with tissue growth. Long-term chondrogenic cultures of granular composites produce engineered cartilage tissue within the range of native properties, which can be further enhanced via MSC/chondrocyte co-cultures. Altogether, we have developed a new strategy of injectable granular composites for engineering cartilage tissue.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Acta Biomaterialia
○ 92 papers in training set
Top 0.1%
12.3%
Similar papers in this journal
2
Advanced Healthcare Materials
○ 85 papers in training set
Top 0.2%
8.6%
Similar papers in this journal
3
Advanced Functional Materials
○ 46 papers in training set
Top 0.1%
7.6%
Similar papers in this journal
4
Biofabrication
○ 36 papers in training set
Top 0.1%
6.5%
Similar papers in this journal
5
Biomaterials
○ 84 papers in training set
Top 0.3%
6.1%
Similar papers in this journal
6
Advanced Science
○ 286 papers in training set
Top 1%
5.0%
7
Biomaterials Science
● 24 papers in training set
Top 0.1%
4.2%
50% of probability mass above
8
Nature Communications
○ 5641 papers in training set
Top 31%
4.2%
9
Advanced Materials
○ 56 papers in training set
Top 0.3%
3.4%
10
Science Advances
● 1243 papers in training set
Top 12%
3.1%
11
Bioactive Materials
○ 20 papers in training set
Top 0.2%
3.1%
12
Tissue Engineering Part A
○ 15 papers in training set
Top 0.1%
3.1%
13
ACS Biomaterials Science & Engineering
● 37 papers in training set
Top 0.3%
3.1%
14
ACS Applied Materials & Interfaces
● 39 papers in training set
Top 0.4%
2.6%
15
Journal of Biomedical Materials Research Part A
○ 20 papers in training set
Top 0.2%
2.3%
16
Small
○ 78 papers in training set
Top 0.7%
2.3%
17
Biomaterials Advances
○ 22 papers in training set
Top 0.3%
2.1%
18
Materials Today Bio
○ 20 papers in training set
Top 0.3%
2.1%
19
ACS Nano
● 113 papers in training set
Top 1%
1.7%
20
Nature Materials
○ 28 papers in training set
Top 0.3%
1.5%
21
Biomacromolecules
● 29 papers in training set
Top 0.3%
1.3%
22
Cellular and Molecular Bioengineering
○ 22 papers in training set
Top 0.4%
1.0%
23
Bioengineering & Translational Medicine
○ 21 papers in training set
Top 0.6%
0.8%
24
Cell Reports Physical Science
○ 19 papers in training set
Top 0.2%
0.8%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.