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Shao H, Wu X, Xiao Y, Yang Y, Ma J, Zhou Y, Chen W, Qin S, Yang J, Wang R, Li H. Recent research advances on polysaccharide-, peptide-, and protein-based hemostatic materials: A review. Int J Biol Macromol 2024; 261:129752. [PMID: 38280705 DOI: 10.1016/j.ijbiomac.2024.129752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 11/05/2023] [Accepted: 01/23/2024] [Indexed: 01/29/2024]
Abstract
Hemorrhage is a potentially life-threatening emergency that can occur at any time or place. Whether traumatic, congenital, surgical, disease-related, or drug-induced, bleeding can lead to severe complications or death. Therefore, the development of efficient hemostatic materials is critical. However, the results and prognosis demonstrated by clinical means of hemostasis do not reach expectations. With the development of technology, novel hemostatic materials have been developed from polysaccharides (chitosan, hyaluronic acid, alginate, cellulose, cyclodextrins, starch, dextran, and carrageenan), peptides (self-assembling peptides), and proteins (silk fibroin, collagen, gelatin, keratin, and thrombin). These new materials exhibit high hemostatic efficacy due to the enhancement or interaction of various hemostatic mechanisms. The main forms include adhesives, sealants, bandages, hemostatic powders, and hemostatic sponges. This article introduces the clotting process and principles of hemostatic methods and reviews the research on polysaccharide-, peptide-, and protein-based hemostatic materials in the last five years. The design ideas and hemostatic principles of polysaccharide-, peptide-, and protein-based hemostatic materials are mainly introduced. Finally, we summarize material designs, advantages, disadvantages, and challenges regarding hemostatic materials.
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Affiliation(s)
- Hanjie Shao
- Ningbo Medical Center Li Huili Hospital, Health Science Center, Ningbo University, Ningbo 315000, PR China; Zhejiang International Scientific and Technological Cooperative Base of Biomedical Materials and Technology, Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, PR China; Ningbo Cixi Institute of Biomedical Engineering, Ningbo 315300, PR China
| | - Xiang Wu
- Ningbo Medical Center Li Huili Hospital, Health Science Center, Ningbo University, Ningbo 315000, PR China; Zhejiang International Scientific and Technological Cooperative Base of Biomedical Materials and Technology, Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, PR China; Ningbo Cixi Institute of Biomedical Engineering, Ningbo 315300, PR China
| | - Ying Xiao
- Zhejiang International Scientific and Technological Cooperative Base of Biomedical Materials and Technology, Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, PR China; Ningbo Cixi Institute of Biomedical Engineering, Ningbo 315300, PR China
| | - Yanyu Yang
- Zhejiang International Scientific and Technological Cooperative Base of Biomedical Materials and Technology, Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, PR China; Ningbo Cixi Institute of Biomedical Engineering, Ningbo 315300, PR China
| | - Jingyun Ma
- Ningbo Institute of Innovation for Combined Medicine and Engineering, The Affiliated Li Huili Hospital, Ningbo University, Ningbo 315100, PR China
| | - Yang Zhou
- Ningbo Institute of Innovation for Combined Medicine and Engineering, The Affiliated Li Huili Hospital, Ningbo University, Ningbo 315100, PR China
| | - Wen Chen
- Ningbo Medical Center Li Huili Hospital, Health Science Center, Ningbo University, Ningbo 315000, PR China
| | - Shaoxia Qin
- Ningbo Medical Center Li Huili Hospital, Health Science Center, Ningbo University, Ningbo 315000, PR China
| | - Jiawei Yang
- Ningbo Medical Center Li Huili Hospital, Health Science Center, Ningbo University, Ningbo 315000, PR China
| | - Rong Wang
- Zhejiang International Scientific and Technological Cooperative Base of Biomedical Materials and Technology, Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, PR China; Ningbo Cixi Institute of Biomedical Engineering, Ningbo 315300, PR China.
| | - Hong Li
- Ningbo Medical Center Li Huili Hospital, Health Science Center, Ningbo University, Ningbo 315000, PR China.
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Raya JG, Duarte A, Wang N, Mazzoli V, Jaramillo D, Blamire AM, Dietrich O. Applications of Diffusion-Weighted MRI to the Musculoskeletal System. J Magn Reson Imaging 2024; 59:376-396. [PMID: 37477576 DOI: 10.1002/jmri.28870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 06/05/2023] [Accepted: 06/05/2023] [Indexed: 07/22/2023] Open
Abstract
Diffusion-weighted imaging (DWI) is an established MRI technique that can investigate tissue microstructure at the scale of a few micrometers. Musculoskeletal tissues typically have a highly ordered structure to fulfill their functions and therefore represent an optimal application of DWI. Even more since disruption of tissue organization affects its biomechanical properties and may indicate irreversible damage. The application of DWI to the musculoskeletal system faces application-specific challenges on data acquisition including susceptibility effects, the low T2 relaxation time of most musculoskeletal tissues (2-70 msec) and the need for sub-millimetric resolution. Thus, musculoskeletal applications have been an area of development of new DWI methods. In this review, we provide an overview of the technical aspects of DWI acquisition including diffusion-weighting, MRI pulse sequences and different diffusion regimes to study tissue microstructure. For each tissue type (growth plate, articular cartilage, muscle, bone marrow, intervertebral discs, ligaments, tendons, menisci, and synovium), the rationale for the use of DWI and clinical studies in support of its use as a biomarker are presented. The review describes studies showing that DTI of the growth plate has predictive value for child growth and that DTI of articular cartilage has potential to predict the radiographic progression of joint damage in early stages of osteoarthritis. DTI has been used extensively in skeletal muscle where it has shown potential to detect microstructural and functional changes in a wide range of muscle pathologies. DWI of bone marrow showed to be a valuable tool for the diagnosis of benign and malignant acute vertebral fractures and bone metastases. DTI and diffusion kurtosis have been investigated as markers of early intervertebral disc degeneration and lower back pain. Finally, promising new applications of DTI to anterior cruciate ligament grafts and synovium are presented. The review ends with an overview of the use of DWI in clinical routine. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- José G Raya
- Department of Radiology, NYU Langone Health, New York, New York, USA
| | - Alejandra Duarte
- Division of Musculoskeletal Radiology, Department of Radiology, Fundación Santa Fe de Bogotá, Bogotá, Colombia
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, Indiana, USA
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, Indiana, USA
| | - Valentina Mazzoli
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Diego Jaramillo
- Department of Radiology, Columbia University Medical Center, New York, New York, USA
| | - Andrew M Blamire
- Magnetic Resonance Centre, Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Olaf Dietrich
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
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Pang Y. Phase-shifted transverse relaxation orientation dependences in human brain white matter. NMR IN BIOMEDICINE 2023:e4925. [PMID: 36908074 DOI: 10.1002/nbm.4925] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/24/2023] [Accepted: 03/02/2023] [Indexed: 06/18/2023]
Abstract
This work aimed to demonstrate an essential phase shift ε 0 $$ {\varepsilon}_0 $$ for better quantifying R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ in human brain white matter (WM), and to further elucidate its origin related to the directional diffusivities from standard diffusion tensor imaging (DTI). ε 0 $$ {\varepsilon}_0 $$ was integrated into a proposed generalized transverse relaxation model for characterizing previously published R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ orientation dependence profiles in brain WM, and then comparisons were made with those without ε 0 $$ {\varepsilon}_0 $$ . It was theorized that anisotropic diffusivity direction ε $$ \varepsilon $$ was collinear with an axon fiber subject to all eigenvalues and eigenvectors from an apparent diffusion tensor. To corroborate the origin of ε 0 $$ {\varepsilon}_0 $$ , R 2 $$ {R}_2 $$ orientation dependences referenced by ε $$ \varepsilon $$ were compared with those referenced by the standard principal diffusivity direction Φ $$ \Phi $$ at b-values of 1000 and 2500 (s/mm2 ). These R 2 $$ {R}_2 $$ orientation dependences were obtained from T 2 $$ {T}_2 $$ -weighted images (b = 0) of ultrahigh-resolution Connectome DTI datasets in the public domain. A normalized root-mean-square error ( NRMSE % $$ NRMSE\% $$ ) and an F $$ F $$ -test were used for evaluating curve-fittings, and statistical significance was considered to be a p of 0.05 or less. A phase-shifted model resulted in significantly reduced NRMSE % $$ NRMSE\% $$ compared with that without ε 0 $$ {\varepsilon}_0 $$ in quantifying various R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ profiles, both in vivo and ex vivo at multiple B 0 $$ {B}_0 $$ fields. The R 2 $$ {R}_2 $$ profiles based on Φ $$ \Phi $$ manifested a right-shifted phase ( ε 0 > 0 $$ {\varepsilon}_0>0 $$ ) at two b-values, while those based on ε $$ \varepsilon $$ became free from ε 0 $$ {\varepsilon}_0 $$ . For all phase-shifted R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ profiles, ε 0 $$ {\varepsilon}_0 $$ generally depended on the directional diffusivities by tan - 1 D ⊥ / D ∥ $$ {\tan}^{-1}\left({D}_{\perp }/{D}_{\parallel}\right) $$ , as predicted. In summary, a ubiquitous phase shift ε 0 $$ {\varepsilon}_0 $$ has been demonstrated as a prerequisite for better quantifying transverse relaxation orientation dependences in human brain WM. Furthermore, the origin of ε 0 $$ {\varepsilon}_0 $$ associated with the directional diffusivities from DTI has been elucidated. These findings could have a significant impact on interpretations of prior R 2 $$ {R}_2 $$ and R 2 * $$ {R}_2^{\ast } $$ datasets and on future research.
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Affiliation(s)
- Yuxi Pang
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
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