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Li HP, Cheng HL, Ding K, Zhang Y, Gao F, Zhu G, Zhang Z. New recognition of the heart-brain axis and its implication in the pathogenesis and treatment of PTSD. Eur J Neurosci 2024; 60:4661-4683. [PMID: 39044332 DOI: 10.1111/ejn.16445] [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: 03/28/2024] [Accepted: 06/04/2024] [Indexed: 07/25/2024]
Abstract
Post-traumatic stress disorder (PTSD) is a complex psychological disorder provoked by distressing experiences, and it remains without highly effective intervention strategies. The exploration of PTSD's underlying mechanisms is crucial for advancing diagnostic and therapeutic approaches. Current studies primarily explore PTSD through the lens of the central nervous system, investigating concrete molecular alterations in the cerebral area and neural circuit irregularities. However, the body's response to external stressors, particularly the changes in cardiovascular function, is often pronounced, evidenced by notable cardiac dysfunction. Consequently, examining PTSD with a focus on cardiac function is vital for the early prevention and targeted management of the disorder. This review undertakes a comprehensive literature analysis to detail the alterations in brain and heart structures and functions associated with PTSD. It also synthesizes potential mechanisms of heart-brain axis interactions relevant to the development of PTSD. Ultimately, by considering cardiac function, this review proposes novel perspectives for PTSD's prophylaxis and therapy.
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Affiliation(s)
- Hai-Peng Li
- Anhui University of Chinese Medicine, Hefei, China
| | - Hong-Liang Cheng
- The Affiliated Hospital of Acupuncture and Moxibustion, Anhui University of Chinese Medicine, Hefei, Anhui Province, China
| | - Keke Ding
- Anhui University of Chinese Medicine, Hefei, China
| | - Yang Zhang
- Anhui University of Chinese Medicine, Hefei, China
| | - Fang Gao
- Anhui University of Chinese Medicine, Hefei, China
| | - Guoqi Zhu
- Anhui University of Chinese Medicine, Hefei, China
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Chen Y, Shi Y, Liang C, Min Z, Deng Q, Yu R, Zhang J, Chang K, Chen L, Yan K, Wang C, Tan Y, Wang X, Chen J, Hua Q. MicrobeTCM: A comprehensive platform for the interactions of microbiota and traditional Chinese medicine. Pharmacol Res 2024; 201:107080. [PMID: 38272335 DOI: 10.1016/j.phrs.2024.107080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/10/2024] [Accepted: 01/21/2024] [Indexed: 01/27/2024]
Abstract
Thanks to the advancements in bioinformatics, drugs, and other interventions that modulate microbes to treat diseases have been emerging continuously. In recent years, an increasing number of databases related to traditional Chinese medicine (TCM) or gut microbes have been established. However, a database combining the two has not yet been developed. To accelerate TCM research and address the traditional medicine and micro ecological system connection between short board, we have developed the most comprehensive micro-ecological database of TCM. This initiative includes the standardization of the following advantages: (1) A repeatable process achieved through the standardization of a retrieval strategy to identify literature. This involved identifying 419 experiment articles from PubMed and six authoritative databases; (2) High-quality data integration achieved through double-entry extraction of literature, mitigating uncertainties associated with natural language extraction; (3) Implementation of a similar strategy aiding in the prediction of mechanisms of action. Leveraging drug similarity, target entity similarity, and known drug-target entity association, our platform enables the prediction of the effects of a new herb or acupoint formulas using the existing data. In total, MicrobeTCM includes 171 diseases, 725 microbes, 1468 herb-formulas, 1032 herbs, 15780 chemical compositions, 35 acupoint-formulas, and 77 acupoints. For further exploration, please visit https://www.microbetcm.com.
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Affiliation(s)
- Yufeng Chen
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Yu Shi
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Chengbang Liang
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Zhuochao Min
- School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China; School of Zoology, The George S. Wise Faculty of Life Sciences Tel Aviv Tel Aviv University, Tel Aviv 69978, Israel
| | - Qiqi Deng
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Rui Yu
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Jiani Zhang
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Kexin Chang
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Luyao Chen
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Ke Yan
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Chunxiang Wang
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Yan Tan
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Xu Wang
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China
| | - Jianxin Chen
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China.
| | - Qian Hua
- School of Traditional Chinese Medicine, School of Life Science, School of Acupuncture-Moxibustion and Tuina, Beijing University of Chinese medicine, Beijing 100029, China.
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