Tendon healing after ligament or tendon reconstruction remains a significant challenge. Regenerative tissue engineering, an interdisciplinary field that combines biology, materials science, and engineering, offers promising solutions. Recent developments have introduced scaffold materials designed to enhance the proliferation and differentiation of tendon-to-bone tissue cells. These scaffolds possessing three-dimensional composites of tissue cells and biomaterials, have proven effective in facilitating tendon-to-bone curing post-surgery. The successful development of the tendon-to-bone interface is a critical factor for early rehabilitation and functional recovery. In this mini-review, we present a comprehensive update on contemporary strategies for synthetic scaffold-based materials and their influence on tendon-to-bone healing. We described the synthetic materials compositions, structures and features of single-layer, multi-layer, and gradient scaffolds with their special mechanical properties. We examined the construction of engineering scaffolds from the perspectives of biomaterials and design strategies, providing a comprehensive evaluation of the advantages and disadvantages associated with each approach. Ultimately, this review articulates clear research directions aimed at achieving breakthroughs in future studies.
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http://dx.doi.org/10.2147/ORR.S501260 | DOI Listing |
Orthop Res Rev
March 2025
Department of Molecular Biology, School of Laboratory Medicine, Beihua University, Jilin, Jilin, 132013, People's Republic of China.
Tendon healing after ligament or tendon reconstruction remains a significant challenge. Regenerative tissue engineering, an interdisciplinary field that combines biology, materials science, and engineering, offers promising solutions. Recent developments have introduced scaffold materials designed to enhance the proliferation and differentiation of tendon-to-bone tissue cells.
View Article and Find Full Text PDFAdv Sci (Weinh)
February 2025
Institute of Precision Optical Engineering, School of Physics Science and Engineering, Tongji University, Shanghai, 200092, China.
Generation of controllable illusions has raised widespread interest. Over the past few decades, this field has been revolutionized by the emergence of metamaterials and metasurfaces. However, current efforts utilizing single-layer metasurfaces are limited to simple illusion demonstrations by reproducing electromagnetic field distributions, which also struggle to achieve both broad bandwidths and wide angular ranges.
View Article and Find Full Text PDFNeural Netw
May 2025
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China; Guangdong Key Laboratory of Big Data Analysis and Processing, Guangzhou, China. Electronic address:
With its ability of joint representation learning and clustering via deep neural networks, the deep clustering have gained significant attention in recent years. Despite the considerable progress, most of the previous deep clustering methods still suffer from three critical limitations. First, they tend to associate some distribution-based clustering loss to the neural network, which often overlook the sample-wise contrastiveness for discriminative representation learning.
View Article and Find Full Text PDFJ Pharm Sci
February 2025
Department of Pharmaceutics, College of Pharmacy, King Saud University, POBOX-2457, Riyadh 11451, Kingdom of Saudi Arabia; Kayyali Chair for Pharmaceutical Industries, Department of Pharmaceutics, College of Pharmacy, King Saud University, Riyadh 11451, Kingdom of Saudi Arabia. Electronic address:
Background And Purpose: Liquid self-nanoemulsifying drug delivery systems (SNEDDS) face challenges related to stability, handling, and storage. In particular, lipophilic and unstable drugs, such as ramipril (RMP) and thymoquinone (THQ), face challenges in oral administration due to poor aqueous solubility and chemical instability. This study aimed to develop and optimize multi-layer self-nanoemulsifying pellets (ML-SNEP) to enhance the stability and dissolution of ramipril (RMP) and thymoquinone (THQ).
View Article and Find Full Text PDFMethodsX
June 2025
Department of Royal Rainmaking and Agricultural Aviation, Bangkok 10900, Thailand.
Rainfall prediction is a crucial aspect of climate science, particularly in monsoon-influenced regions where accurate forecasts are essential. This study evaluates rainfall prediction models in the Eastern Thailand by examining an optimal lag time associated with the Oceanic Niño Index (ONI). Five deep learning models-RNN with ReLU, LSTM, GRU (single-layer), LSTM+LSTM, and LSTM+GRU (multi-layer)-were compared using mean absolute error (MAE) and root mean square error (RMSE).
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