Traditional Chinese exercises (TCEs) have great value in the prevention and effective treatment of cardiovascular diseases (CVD). Our purpose in this study was to summarize present research trends and future directions regarding the link between TCEs and CVD by bibliometrics analysis. We searched the Web of Science Core Collection (WoSCC) for all original articles and reviews on TCEs for CVD published in English before August 7, 2022 using CiteSpace 5.8.R3 and Microsoft Excel 2019 software, and we displayed the results in the form of network maps, line graphs, and tables. We initially obtained 725 articles. Our results showed that the United States was the most influential country in this line of research, with Harvard University the most prolific institution in the field, and, was the most productive journal for these articles. The highest-frequency keywords in this research area were Tai Chi, exercise, blood pressure, quality of life, and older adult. Additionally, important research topics included heart rate variability, quality of life, meta-analysis, Baduanjin exercise, and breathing exercise. In addition, our results revealed that among all the TCEs, Tai Chi, Baduanjin, and Qigong emerged as the most extensively studied. However, it's important to note our exclusive focus on literature published in English may have led to our missing important results. Future investigators should broaden their search to include other databases and languages to present a still more comprehensive overview of this field.
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http://dx.doi.org/10.1177/00315125241230599 | DOI Listing |
Biomed Phys Eng Express
January 2025
Shandong University of Traditional Chinese Medicine, Qingdao Academy of Chinese Medical Sciences, Jinan, Shandong, 250355, CHINA.
Mild cognitive impairment (MCI) is a significant predictor of the early progression of Alzheimer's disease, and it can be used as an important indicator of disease progression. However, many existing methods focus mainly on the image itself when processing brain imaging data, ignoring other non-imaging data (e.g.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
State Key Laboratory of Superhard Materials, College of Physics, Jilin University, Changchun 130012, China.
The abrupt drop of resistance to zero at a critical temperature is a key signature of the current paradigm of the metal-superconductor transition. However, the emergence of an intermediate bosonic insulating state characterized by a resistance peak preceding the onset of the superconducting transition has challenged this traditional understanding. Notably, this phenomenon has been predominantly observed in disordered or chemically doped low-dimensional systems, raising intriguing questions about the generality of the effect and its underlying fundamental physics.
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January 2025
1Department of Neurology, Centre for Leading Medicine and Advanced Technologies of IHM, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui.
Objective: Endovascular treatment (EVT) is an effective treatment for patients with acute vertebrobasilar artery complex occlusion (VBAO). However, the benefit of bridging thrombolysis prior to EVT remains controversial. The purpose of the present study is to explore the best treatment strategy between bridging treatment (BT) and direct EVT in patients with acute VBAO.
View Article and Find Full Text PDFPLoS One
January 2025
Nanjing Hospital of Chinese Medicine Affiliated to Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China.
Preeclampsia is characterized by insufficient invasion of extravillous trophoblasts and is a consequence of failed adaption of extravillous trophoblasts to changes in the intrauterine environment developing embryo. Specific miRNAs are implicated in the development of preeclampsia (PE). miR-455-5p is present at low levels in PE but its role is not known.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Guizhou Provincial Engineering Technology Research Center for Chemical Drug R&D, School of Pharmacy, Guizhou Medical University, Guiyang, Guizhou 550025, P. R. China.
Traditional machine learning methods face significant challenges in predicting the properties of highly symmetric molecules. In this study, we developed a machine learning model based on graph neural networks (GNNs) to accurately and swiftly predict the thermodynamic and photochemical properties of fullerenols, such as C(OH) ( = 1 to 30). First, we established a global method for generating fullerenol isomers through isomer fingerprinting, which can generate all possible isomers or produce diverse structural types on demand.
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