| Literature DB >> 31450605 |
Yung-Cheng Chiu1,2, Yu-Fang Shen3,4, Alvin Kai-Xing Lee1,5, Shu-Hsien Lin5, Yu-Chen Wu5, Yi-Wen Chen6,7.
Abstract
Cardiovascular diseases are currently the most common cause of death globally and of which, the golden treatment method for severe cardiovascular diseases or coronary artery diseases are implantations of synthetic vascular grafts. However, such grafts often come with rejections and hypersensitivity reactions. With the emergence of regenerative medicine, researchers are now trying to explore alternative ways to produce grafts that are less likely to induce immunological reactions in patients. The main goal of such studies is to produce biocompatible artificial vascular grafts with the capability of allowing cellular adhesion and cellular proliferation for tissues regeneration. The Design of Experimental concepts is employed into the manufacturing process of digital light processing (DLP) 3D printing technology to explore near-optimal processing parameters to produce artificial vascular grafts with vascular characteristics that are close to native vessels by assessing for the cause and effect relationships between different ratios of amino resin (AR), 2-hydroxyethyl methacrylate (HEMA), dopamine, and curing durations. We found that with proper optimization of fabrication procedures and ratios of materials, we are able to successfully fabricate vascular grafts with good printing resolutions. These had similar physical properties to native vessels and were able to support cellular adhesion and proliferation. This study could support future studies in exploring near-optimal processes for fabrication of artificial vascular grafts that could be adapted into clinical applications.Entities:
Keywords: DLP Technology; amino resin; blood vascular graft; design of experiments; dopamine; tissue engineering
Year: 2019 PMID: 31450605 PMCID: PMC6780824 DOI: 10.3390/polym11091394
Source DB: PubMed Journal: Polymers (Basel) ISSN: 2073-4360 Impact factor: 4.329
Experimental factors and levels.
| Experimental Factor | AR con. (%) | DA con. (mg/mL) | Curing time(sec) |
|---|---|---|---|
| Low level | 40 | 0.1 | 23 |
| High Level | 80 | 3 | 40 |
Experimental factors (columns 2–4) and response variables (columns 5-7) of the 23 fractional factorial screening design (#1–#11).
| Run# | AR con. (%) | DA con. (mg/mL) | Curing Time (sec) | Resolution (mm2) | Young’s Modulus (MPa) | Cell Viability (%) |
|---|---|---|---|---|---|---|
| 1 | 40.00 | 3.00 | 40.00 | 2.76 | 1.33 | 67.26 |
| 2 | 40.00 | 3.00 | 24.00 | 3.05 | 2.71 | 65.76 |
| 3 | 60.00 | 1.55 | 32.00 | 1.24 | 0.92 | 70.14 |
| 4 | 80.00 | 0.10 | 24.00 | 0.05 | 0.82 | 68.64 |
| 5 | 80.00 | 3.00 | 40.00 | 1.86 | 3.46 | 77.30 |
| 6 | 60.00 | 1.55 | 32.00 | 1.59 | 0.86 | 74.28 |
| 7 | 60.00 | 1.55 | 32.00 | 0.88 | 1.22 | 81.02 |
| 8 | 40.00 | 0.10 | 40.00 | 0.00 | 4.30 | 89.23 |
| 9 | 80.00 | 0.10 | 40.00 | 0.00 | 0.00 | 72.76 |
| 10 | 40.00 | 0.10 | 24.00 | 1.68 | 0.48 | 76.06 |
| 11 | 80.00 | 3.00 | 24.00 | 0.00 | 0.00 | 0.00 |
Figure 1The design of the bi-layer engineering blood vessel scaffold.
Figure 2The design of resolution test specimens.
Figure 3The main effect of (A) amine-based resin (AR) concentration and (B) dopamine (DA) concentration on the resolution.
Figure 4The main effect of (A) AR concentration, (B) curing time, and (C) AR-curing time-DA interaction on the Young’s modulus.
Figure 5The main effect of (A) AR concentration, (B) DA concentration, (C) curing time, and (D) AR-curing time-DA interaction on the cell viability.
Figure 6Three-dimensional scatter plot of resolution, Young’s modulus and cell viability.
The distance between the response variables and the coordinate values of the expected values.
| Run# | X: | Y: | Z: | Distance | Order |
|---|---|---|---|---|---|
| 1 | 2.76 | 1.333 | 67.26 | 32.79 | 9 |
| 2 | 3.05 | 2.707 | 65.76 | 34.34 | 10 |
| 3 | 1.24 | 0.917 | 70.14 | 29.86 | 7 |
| 4 | 0.05 | 0.822 | 68.64 | 31.37 | 8 |
| 5 | 1.86 | 3.456 | 77.30 | 22.85 | 3 |
| 6 | 1.59 | 0.856 | 74.28 | 25.73 | 5 |
| 7 | 0.88 | 1.218 | 81.02 | 18.98 | 2 |
| 8 | 0.00 | 4.298 | 89.23 | 11.31 | 1 |
| 9 | 0.00 | 0.00 | 72.76 | 27.26 | 6 |
| 10 | 1.68 | 0.484 | 76.06 | 23.95 | 4 |
| 11 | 0.00 | 0.00 | 0.00 | 100 | 11 |
The optimal factor-level combination.
| Run# | AR con. (%) | DA con. (mg/mL) | Curing time (sec) | Resolution (mm2) | Young’s Modulus (MPa) | Cell Viability (%) |
|---|---|---|---|---|---|---|
| 1 | 40.00 | 0.10 | 26.62 | 1.39 | 0.98 | 82.19 |
| 2 | 40.00 | 0.10 | 26.54 | 1.39 | 0.96 | 82.12 |
| 3 | 40.00 | 0.10 | 26.47 | 1.40 | 0.94 | 82.06 |
| 4 | 41.75 | 0.10 | 26.53 | 1.34 | 0.98 | 81.37 |
| 5 | 40.00 | 0.10 | 26.74 | 1.48 | 0.78 | 81.47 |
Figure 7The images of the 3D-printed blood vessels with the optimization parameter. The blood vessels with bi-layer structure and triangle pore. Scale bar is 1 mm.
Optimization parameter verification.
| Parameter | AR con. (%) | DA con. (mg/mL) | Curing Time (sec) | Resolution (mm2) | Young’s Modulus (MPa) | Cell Viability (%) |
|---|---|---|---|---|---|---|
| Expectation value | 40.00 | 0.10 | 26.62 | 1.39 | 0.983 | 82.19 |
| Experimental value | 40.00 | 0.10 | 26.60 | 1.35 | 0.988 | 88.37 |
| Deviation (%) | 0 | 0 | 0.75 | -2.68 | 0.55 | 6.99 |