To analyze the research hotspots and trends of traditional Chinese medicine(TCM) for neurogenesis with use of CiteSpace 5.7.R3 software. The bibliometrics analysis on the literatures of TCM for neurogenesis from 1987 to 2020 included in the CNKI database was conducted to visualize the number of papers, authors, institutions and keywords. Totally 736 literatures were included and the volume of annual publications showed an upward in volatility. At present, several stable research teams have been formed, which were represented by DING Fei, ZHOU Chong-jian and ZHOU Yong-hong, but the cooperation was not close among the teams. According to the analysis of research institutions, Institute of Diagnostics of Hunan University of Chinese Medicine and Acupuncture Research Center of Tianjin University of Traditional Chinese Medicine produced largest number of literatures. The cooperation among institutions, with universities of TCM and affiliated hospitals as the main research force, was characterized by dominant cooperation among regional institutions and less cross-regional cooperation. Keywords analysis showed that in the field of TCM for neurogenesis, a lot of studies mainly focused on the disease field, treatment and medication, TCM therapy and molecular mechanism. The research on TCM therapy and molecular mechanism for neurogenesis of central nervous system will be the research hotspots in future.
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http://dx.doi.org/10.19540/j.cnki.cjcmm.20210409.501 | 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.
View Article and Find Full Text PDFJ Neurosurg
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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