A Multicrosslinked Network Composite Hydrogel Scaffold Based on DLP Photocuring Printing for Nasal Cartilage Repair.
BIOTECHNOLOGY AND BIOENGINEERING（2024）
Shanxi Key Laboratory of Micro Nano Sensors & Artificial Intelligence Perception
Abstract
Natural hydrogels are widely employed in tissue engineering and have excellent biodegradability and biocompatibility. Unfortunately, the utilization of such hydrogels in the field of three-dimensional (3D) printing nasal cartilage is constrained by their subpar mechanical characteristics. In this study, we provide a multicrosslinked network hybrid ink made of photocurable gelatin, hyaluronic acid, and acrylamide (AM). The ink may be processed into intricate 3D hydrogel structures with good biocompatibility and high stiffness properties using 3D printing technology based on digital light processing (DLP), including intricate shapes resembling noses. By varying the AM content, the mechanical behavior and biocompatibility of the hydrogels can be adjusted. In comparison to the gelatin methacryloyl (GelMA)/hyaluronic acid methacryloyl (HAMA) hydrogel, adding AM considerably enhances the hydrogel's mechanical properties while also enhancing printing quality. Meanwhile, the biocompatibility of the multicrosslinked network hydrogels and the development of cartilage were assessed using neonatal Sprague-Dawley (SD) rat chondrocytes (CChons). Cells sown on the hydrogels considerably multiplied after 7 days of culture and kept up the expression of particular proteins. Together, our findings point to GelMA/HAMA/polyacrylamide (PAM) hydrogel as a potential material for nasal cartilage restoration. The photocuring multicrosslinked network ink composed of appropriate proportions of GelMA/HAMA/PAM is very suitable for DLP 3D printing and will play an important role in the construction of nasal cartilage, ear cartilage, articular cartilage, and other tissues and organs in the future. Notably, previous studies have not explored the application of 3D-printed GelMA/HAMA/PAM hydrogels for nasal cartilage regeneration.
MoreTranslated text
Key words
biocompatible,biodegradable,GelMA,HAMA,nasal cartilage repair,natural-synthetic polymer biohybrid hydrogel
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined