A Preliminary Study into the Emergence of Tendon Microstructure During Postnatal Development
Matrix Biology Plus(2024)
Wellcome Centre for Cell Matrix Research
Abstract
Tendons maintain mechanical function throughout postnatal development whilst undergoing significant microstructural changes. We present a study of postnatal tendon growth and characterise the major changes in collagen fibril architecture in mouse tail tendon from birth to eight weeks by analysing the geometries of cross-sectional transmission electron microscopy images. This study finds that a bimodal distribution of fibril diameters emerges from a unimodal distribution of narrow fibrils as early as the eighth day postnatal, and three distinct fibril populations are visible at around 14 days. The tendons in this study do not show evidence of precise hexagonal packing, even at birth, and the spaces between the fibrils remain constant throughout development. The fibril number in the tissue stabilises around day 28, and the fibril area fraction stabilises around day 26. This study gives coarse-grained insight into the transition periods in early tendon development.
MoreTranslated text
Key words
Flexor Tendon Repair
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