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Heshmat-Ghahdarijani K, Modaresi R, Pourmasjedi S, Korani SS, Roudkoli AR, Ziaei R, Farid A, Salehi M, Heidari A, Neshat S. Reducing Cardiac Steatosis: Interventions to Improve Diastolic Function - A Narrative Review. Curr Probl Cardiol 2023; 48:101739. [PMID: 37040852 DOI: 10.1016/j.cpcardiol.2023.101739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 04/06/2023] [Indexed: 04/13/2023]
Abstract
Heart failure is one of the main causes of morbidity and mortality around the globe. Heart failure with preserved ejection fraction is primarily caused by diastolic dysfunction. Adipose tissue deposition in the heart has been previously explained in the pathogenesis of diastolic dysfunction. In this article, we aim to discuss the potential interventions that can reduce the risk of diastolic dysfunction by reducing cardiac adipose tissue. A healthy diet with reduced dietary fat content can reduce visceral adiposity and improve diastolic function. Aerobic and resistance exercises also reduce visceral and epicardial fat and ameliorate diastolic dysfunction. Some medications, include metformin, glucagon-like peptide-1 analogues, dipeptidyl peptidase-4 inhibitors, thiazolidinediones, sodium-glucose co-transporter-2, inhibitors, statins, ACE-Is, and ARBs, have shown different degrees of effectiveness in improving cardiac steatosis and diastolic function. Bariatric surgery has also shown promising results in this field.
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Affiliation(s)
- Kiyan Heshmat-Ghahdarijani
- Heart Failure Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Roya Modaresi
- School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Sobhan Pourmasjedi
- Heart Failure Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Setayesh Sotoudehnia Korani
- Hormozgan Cardiovascular Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran; Department of Radiology, Mayo Clinic, MN, USA
| | - Ali Rezazadeh Roudkoli
- Hormozgan Cardiovascular Research Center, Hormozgan University of Medical Sciences, Bandar Abbas, Iran
| | - Razieh Ziaei
- School of Medicine, Najafabad Islamic Azad University of Medical Sciences, Isfahan, Iran
| | - Armita Farid
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Mehrnaz Salehi
- School of Medicine, Shahrekord University of Medical Sciences, Shahrekord, Iran
| | - Afshin Heidari
- School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Sina Neshat
- School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.
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Deng JP, Liu X, Li Y, Ni SH, Sun SN, Ou-Yang XL, Ye XH, Wang LJ, Lu L. Drug vector representation and potential efficacy prediction based on graph representation learning and transcriptome data: Acacetin from traditional Chinese Medicine model. JOURNAL OF ETHNOPHARMACOLOGY 2023; 305:115966. [PMID: 36572325 DOI: 10.1016/j.jep.2022.115966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 11/03/2022] [Accepted: 11/22/2022] [Indexed: 06/17/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Acacetin is widely distributed in traditional Chinese medicine and traditional herbs, with strong biological activity. Perhaps there are many potential effects that have not been explored. In the field of drug discovery, Mainstream methods focus on chemical structure. Traditional medicine cannot adapt to the mainstream prediction methods due to its complex composition. AIM OF THE STUDY Our aim is that provide a prediction method more suitable for traditional medicine by graph representation learning and transcriptome data. And use this method to predict acacetin. MATERIALS AND METHODS Our method mainly consists of two parts. The first part is to use the method of graph representation learning to vectorize drugs as a database. The original data of this part comes from transcriptome data on Gene Expression Omnibus. The method of graph representation learning is an unsupervised learning. If there is no prior knowledge as the label data, the training effect cannot be analyzed. Therefore, we define a standard score to evaluate our results through the idea of Jaccard index. The second part is to put the target drug into our database. The potential similarity between drugs was evaluated by the Euclidean distance between vectors, and the potential efficacy of the target drug is predicted by combining the chemical-disease relationship data in the Comparative Toxicogenomics Database. The target drug in this paper uses acacetin. We compared the predicted results with existing reports, and we also experimentally verified the efficacy of improving insulin resistance in the predicted results. RESULTS The prediction results are relatively consistent with the existing reports, which demonstrated that our method has a certain degree of predictive performance. And for the efficacy of improving insulin resistance in the predicted result, we verified it through experiments. CONCLUSIONS We propose a method to predict the potential efficacy of drugs based on transcriptome data, using Graph representation learning, which is very suitable for traditional medicine. Through this method, we predicted the efficacy of acacetin, and the results are relatively consistent with the current reports. This provides a new idea for unsupervised learning to apply medical information.
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Affiliation(s)
- Jian-Ping Deng
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; Lingnan Medical Research Center, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; University Key Laboratory of Traditional Chinese Medicine Prevention and Treatment of Chronic Heart Failure, Guangdong Province, Guangzhou, 510407, China
| | - Xin Liu
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; Lingnan Medical Research Center, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; University Key Laboratory of Traditional Chinese Medicine Prevention and Treatment of Chronic Heart Failure, Guangdong Province, Guangzhou, 510407, China
| | - Yue Li
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; Lingnan Medical Research Center, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; University Key Laboratory of Traditional Chinese Medicine Prevention and Treatment of Chronic Heart Failure, Guangdong Province, Guangzhou, 510407, China
| | - Shi-Hao Ni
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; Lingnan Medical Research Center, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; University Key Laboratory of Traditional Chinese Medicine Prevention and Treatment of Chronic Heart Failure, Guangdong Province, Guangzhou, 510407, China
| | - Shu-Ning Sun
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; Lingnan Medical Research Center, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; University Key Laboratory of Traditional Chinese Medicine Prevention and Treatment of Chronic Heart Failure, Guangdong Province, Guangzhou, 510407, China
| | - Xiao-Lu Ou-Yang
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; Lingnan Medical Research Center, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; University Key Laboratory of Traditional Chinese Medicine Prevention and Treatment of Chronic Heart Failure, Guangdong Province, Guangzhou, 510407, China
| | - Xiao-Han Ye
- Dongguan Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China.
| | - Ling-Jun Wang
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; Lingnan Medical Research Center, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; University Key Laboratory of Traditional Chinese Medicine Prevention and Treatment of Chronic Heart Failure, Guangdong Province, Guangzhou, 510407, China.
| | - Lu Lu
- The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; Lingnan Medical Research Center, Guangzhou University of Chinese Medicine, Guangzhou, 510407, China; University Key Laboratory of Traditional Chinese Medicine Prevention and Treatment of Chronic Heart Failure, Guangdong Province, Guangzhou, 510407, China.
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Teng D, Gong Y, Wu Z, Li W, Tang Y, Liu G. In Silico Prediction of Potential Drug Combinations for Type 2 Diabetes Mellitus by an Integrated Network and Transcriptome Analysis. ChemMedChem 2021; 17:e202100620. [PMID: 34755485 DOI: 10.1002/cmdc.202100620] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 10/26/2021] [Indexed: 12/21/2022]
Abstract
Type 2 diabetes mellitus (T2DM) is a heterogeneous disorder, so achieving the desired therapeutic efficacy through monotherapy is tricky. Drug combinations play a vital role in treating multiple complex diseases by providing increased efficacy and reduced toxicity. Here, we adopted a computational framework to discover potential drugs and drug pairs for T2DM. Firstly, we collected T2DM-associated genes and constructed the disease module for T2DM. Then, by quantifying the proximity between drugs and the disease module, we found out potential drugs. Based on the drug-induced gene expression profiles, we further performed Gene Set Enrichment Analysis (GSEA) on these drugs and identified several potential candidates. In addition, through network-based separation, potential drug combinations for T2DM were predicted. Results from this study could provide insights for anti-T2DM drug discovery and rational drug use of existing agents. As a useful computational framework, our approach could also be applied in drug research for other complex diseases.
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Affiliation(s)
- Dan Teng
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, China
| | - Yuning Gong
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, China
| | - Zengrui Wu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, China
| | - Weihua Li
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, China
| | - Yun Tang
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, China
| | - Guixia Liu
- Shanghai Key Laboratory of New Drug Design, School of Pharmacy, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, China
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Ning D, Yang X, Wang T, Jiang Q, Yu J, Wang D. Atorvastatin treatment ameliorates cardiac function and remodeling induced by isoproterenol attack through mitigation of ferroptosis. Biochem Biophys Res Commun 2021; 574:39-47. [PMID: 34438345 DOI: 10.1016/j.bbrc.2021.08.017] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2021] [Accepted: 08/06/2021] [Indexed: 12/11/2022]
Abstract
Ferroptosis has been identified as an important role in damaged heart. Meanwhile, statin therapy has been reported to be beneficial for the treatment of heart failure(HF) under different conditions. However, the beneficial effects of statin treatment on regulation of ferroptosis in failing heart is unveiled. The aim of this study is to explore the protective efficacy of atorvastatin against the ferroptosis related signaling pathway in isoproterenol(ISO)-induced HF. We found that ATV and ferrostatin-1(Fer-1,as a positive control) significantly improved ISO-decreased cell viability and cell survival by reducing oxidative stress and Fe2+-dependent lipid peroxidation in H9C2 cells. Additionally, ISO triggered marked ferritinophagy accompanied by up-regulating protein levels of LC3BII,NCOA4 and Beclin1 and down-regulating protein levels of P62 and FTH1 in damaged cells, which nevertheless was significantly blocked by administration of ATV and these results were in parallel with the results obtained after 3-methyadenine(3-MA) treatment. Consistently, C57BL/6J mice were used in used in this study and administered 5 mg/kg/day ISO for 2 weeks to simulate cardiac injury. 20 mg/kg/day ATV treatment for 2 weeks simultaneously markedly improved cardiac dysfunction and remodeling induced by ISO attack. ATV showed significantly protective effects through suppressing the activation of ferroptosis related signaling, as evidenced by decreasing the mRNA levels of PTGS2(a marker of ferroptosis), contents of malonaldehyde and protein levels of NOX4 and increasing the contents of glutathione(GSH), the ratio of GSH/GSSG and protein levels of GPX4 and SLC7A11. Moreover, ISO evidently triggered degradation of FTH1 in failing heart. However, ATV significantly prevented these changes in damaged heart. Overall, these results reveal atorvastatin suppresses ferroptosis and exhibits protective effect on failing myocardium of mice after ISO insult though inhibiting ferritinophagy-mediated ferroptosis, which might be a potential therapeutic strategy in the prevention of ISO-associated cardiomyopathy.
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Affiliation(s)
- Dong Ning
- Department of Cardiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xinquan Yang
- Department of Cardiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; The First Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Ti Wang
- School of Medicine, Yangzhou University, Yangzhou, Jiangsu, China
| | - Qiaohui Jiang
- School of Medicine, Yangzhou University, Yangzhou, Jiangsu, China
| | - Jiangquan Yu
- School of Medicine, Yangzhou University, Yangzhou, Jiangsu, China; Clinical Medical College of Yangzhou University(Northern Jiangsu Province Hospital),Yangzhou, Jiangsu, China.
| | - Daxin Wang
- The Hospital Affiliated to Medical School of Yangzhou University(Taizhou People' Hospital), Taizhou, Jiangsu, China; Yangzhou Biomedical Engineering Research Center, China.
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Regulatory mechanisms of sub-inhibitory levels antibiotics agent in bacterial virulence. Appl Microbiol Biotechnol 2021; 105:3495-3505. [PMID: 33893838 DOI: 10.1007/s00253-021-11291-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 04/01/2021] [Accepted: 04/11/2021] [Indexed: 01/13/2023]
Abstract
Antibiotics play a key role in the prevention and treatment of bacterial diseases for human and animals. The widespread use of antibiotics results in bacterial exposure to the concentrations that are lower than the MIC (that is, sub-inhibitory concentration (sub-MIC)) in the environment, humans, and livestock, which can lead to antibiotic resistance. In this review, we focus on the impact of sub-MIC antibiotics in bacterial virulence. This paper summarized the known relationships between sub-MIC antibiotics in the environment and bacterial virulence. Together, considering the impact of sub-MIC antibiotics and their alternative products in the virulence of bacteria, it is helpful to the rational use of antibiotics and the development of antibiotic alternative products to provide new insights.Key points• Sub-MIC level antibiotics exist in the environment, humans, and livestock.• The review includes mechanisms of sub-MIC antibiotics in bacterial virulence.• New antibacterial strategies and agents are being a new way to weaken virulence. Graphical Abstract.
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