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Chen H, Shen H, Han J, Wang P, Song D, Shen H, Wei X, Yang B, Li J. Performance of ATT and UDFF in the diagnosis of non-alcoholic fatty liver: An animal experiment. Heliyon 2024; 10:e27993. [PMID: 38560108 PMCID: PMC10981026 DOI: 10.1016/j.heliyon.2024.e27993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 03/01/2024] [Accepted: 03/10/2024] [Indexed: 04/04/2024] Open
Abstract
Objective To establish a Bama minipigs model with Non-Alcoholic Fatty Liver (NAFL) induced by a high-fat diet and investigate the application of attenuation coefficient (ATT) and ultrasound-derived fat fraction (UDFF) in the diagnosis of NAFL. Methods Six-month-old male Bama minipigs were randomly divided into normal control and high-fat groups (n = 3 pigs per group), and fed with a control diet and high-fat diet for 32 weeks. Weight and body length were measured every four weeks, followed by quantitative ultrasound imaging (ATT and UDFF), blood biochemical markers, and liver biopsies on the same day. Using the Non-Alcoholic Fatty Liver Disease (NAFLD) Activity Score (NAS) as a reference, we analyzed the correlation between ATT, UDFF, and their score results. Results Compared with the normal control group, the body weight, body mass index (BMI), and serum levels of triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in the High-fat group were significantly different at Week 12 (P < 0.05). Spearman correlation analysis showed that the ATT value was significantly correlated with NAS score (r = 0.76, P < 0.001), and the UDFF value was significantly correlated with NAS score (r = 0.80, P < 0.001). The optimal cut-off value of ATT and UDFF were 0.59 dB/cm/MHz and 5.5%, respectively. These values are optimal for diagnosis of NAFL in Bama minipig model. Conclusion ATT and UDFF have a high correlation with steatosis, and can be used as a non-invasive method for early screening of hepatic steatosis, which can dynamically monitor the change of disease course.
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Affiliation(s)
- Huihui Chen
- Department of Ultrasound, Zhongda Hospital, Medical School, Southeast University, Nanjing, 210009, China
| | - Huiming Shen
- Department of Ultrasound, Zhongda Hospital, Medical School, Southeast University, Nanjing, 210009, China
| | - Jiahao Han
- Department of Ultrasound, Zhongda Hospital, Medical School, Southeast University, Nanjing, 210009, China
| | - Pingping Wang
- Department of Ultrasound, Zhongda Hospital, Medical School, Southeast University, Nanjing, 210009, China
| | - Danlei Song
- Department of Ultrasound, Zhongda Hospital, Medical School, Southeast University, Nanjing, 210009, China
| | - Hongyuan Shen
- Department of Ultrasound, Zhongda Hospital, Medical School, Southeast University, Nanjing, 210009, China
| | - Xiaoying Wei
- Department of Pathology, Zhongda Hospital, Medical School, Southeast University, Nanjing, 210009, China
| | - Bingjie Yang
- Department of Ultrasound, Zhongda Hospital, Medical School, Southeast University, Nanjing, 210009, China
| | - Jia Li
- Department of Ultrasound, Zhongda Hospital, Medical School, Southeast University, Nanjing, 210009, China
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Wang G, Hua R, Chen X, He X, Dingming Y, Chen H, Zhang B, Dong Y, Liu M, Liu J, Liu T, Zhao J, Zhao YQ, Qiao L. MX1 and UBE2L6 are potential metaflammation gene targets in both diabetes and atherosclerosis. PeerJ 2024; 12:e16975. [PMID: 38406276 PMCID: PMC10893863 DOI: 10.7717/peerj.16975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 01/29/2024] [Indexed: 02/27/2024] Open
Abstract
Background The coexistence of diabetes mellitus (DM) and atherosclerosis (AS) is widespread, although the explicit metabolism and metabolism-associated molecular patterns (MAMPs) responsible for the correlation are still unclear. Methods Twenty-four genetically wild-type male Ba-Ma mini pigs were randomly divided into five groups distinguished by different combinations of 90 mg/kg streptozotocin (STZ) intravenous injection and high-cholesterol/lipid (HC) or high-lipid (HL) diet feeding for 9 months in total. Pigs in the STZ+HC and STZ+HL groups were injected with STZ first and then fed the HC or HL diet for 9 months. In contrast, pigs in the HC+STZ and HL+STZ groups were fed the HC or HL diet for 9 months and injected with STZ at 3 months. The controls were only fed a regular diet for 9 months. The blood glucose and abdominal aortic plaque observed through oil red O staining were used as evaluation indicators for successful modelling of DM and AS. A microarray gene expression analysis of all subjects was performed. Results Atherosclerotic lesions were observed only in the HC+STZ and STZ+HC groups. A total of 103 differentially expressed genes (DEGs) were identified as common between them. The most significantly enriched pathways of 103 common DEGs were influenza A, hepatitis C, and measles. The global and internal protein-protein interaction (PPI) networks of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The top 10 hub proteins, namely, ISG15, IRG6, IRF7, IFIT3, MX1, UBE2L6, DDX58, IFIT2, USP18, and IFI44L, drive aspects of DM and AS. MX1 and UBE2L6 were the intersection of internal and global PPI networks. The expression of MX1 and UBE2L6 was 507.22 ± 342.56 and 96.99 ± 49.92 in the HC+STZ group, respectively, which was significantly higher than others and may be linked to the severity of hyperglycaemia-related atherosclerosis. Further PPI network analysis of calcium/micronutrients, including MX1 and UBE2L6, consisted of 58 and 18 nodes, respectively. The most significantly enriched KEGG pathways were glutathione metabolism, pyrimidine metabolism, purine metabolism, and metabolic pathways. Conclusions The global and internal PPI network of the 103 common DEGs consisted of 648 and 14 nodes, respectively. The intersection of the nodes of internal and global PPI networks was MX1 and UBE2L6, suggesting their key role in the comorbidity mechanism of DM and AS. This inference was partly verified by the overexpression of MX1 and UBE2L6 in the HC+STZ group but not others. Further calcium- and micronutrient-related enriched KEGG pathway analysis supported that MX1 and UBE2L6 may affect the inflammatory response through micronutrient metabolic pathways, conceptually named metaflammation. Collectively, MX1 and UBE2L6 may be potential common biomarkers for DM and AS that may reveal metaflammatory aspects of the pathological process, although proper validation is still needed to determine their contribution to the detailed mechanism.
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Affiliation(s)
- Guisheng Wang
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Rongrong Hua
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xiaoxia Chen
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Xucheng He
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yao Dingming
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Hua Chen
- Laboratory Animal Center, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Buhuan Zhang
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yuru Dong
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Muqing Liu
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jiaxiong Liu
- Department of Radiology, Third Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Ting Liu
- Department of Radiology, Beijing YouAn Hospital, Capital Medical University, Beijing, China
| | - Jingwei Zhao
- Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yu Qiong Zhao
- Laboratory Animal Center, Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Li Qiao
- Department of International Business, Business College of Beijing Union University, Beijing, China
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Li C, Zhang K, Liu L, Shen J, Wang Y, Tan Y, Feng X, Liu W, Zhang H, Sun J. Study of the Mechanism of Astragali Radix in Treating Type 2 Diabetes Mellitus and Its Renal Protection Based on Enzyme Activity, Network Pharmacology, and Experimental Verification. Molecules 2023; 28:8030. [PMID: 38138520 PMCID: PMC10745890 DOI: 10.3390/molecules28248030] [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: 11/15/2023] [Revised: 11/26/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
Astragali Radix (AR) is a common Chinese medicine and food. This article aims to reveal the active role of AR in treating Type 2 diabetes mellitus (T2DM) and its renal protective mechanism. The hypoglycemic active fraction was screened by α-glucosidase and identified by UPLC-QE-Orbitrap-MS spectrometry. The targets and KEGG pathway were determined through the application of network pharmacology methodology. Molecular docking and molecular dynamics simulation technology were used for virtual verification. Subsequently, a mouse model of T2DM was established, and the blood glucose and renal function indexes of the mice after administration were analyzed to further prove the pharmacodynamic effect and mechanism of AR in the treatment of T2DM. HA was determined as the best hypoglycemic active fraction by the α-glucosidase method, with a total of 23 compounds identified. The main active components, such as calycoside-7-O-β-D-glucoside, methylnisoline, and formononetin, were revealed by network pharmacology. In addition, the core targets and the pathway have also been determined. Molecular docking and molecular dynamics simulation techniques have verified that components and targets can be well combined. In vivo studies have shown that AR can reduce blood sugar levels in model mice, enhance the anti-inflammatory and antioxidant activities of kidney tissue, and alleviate kidney damage in mice. And it also has regulatory effects on proteins such as RAGE, PI3K, and AKT. AR has a good therapeutic effect on T2DM and can repair disease-induced renal injury by regulating the RAGE/PI3K/Akt signaling pathway. This study provides ideas for the development of new drugs or dietary interventions for the treatment of T2DM.
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Affiliation(s)
- Chunnan Li
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (C.L.); (K.Z.); (L.L.); (J.S.); (Y.W.); (Y.T.); (X.F.); (W.L.)
- Jilin Correction Pharmacy New Drug Development Co., Ltd., Changchun 130012, China
| | - Kaiyue Zhang
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (C.L.); (K.Z.); (L.L.); (J.S.); (Y.W.); (Y.T.); (X.F.); (W.L.)
| | - Lu Liu
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (C.L.); (K.Z.); (L.L.); (J.S.); (Y.W.); (Y.T.); (X.F.); (W.L.)
| | - Jiaming Shen
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (C.L.); (K.Z.); (L.L.); (J.S.); (Y.W.); (Y.T.); (X.F.); (W.L.)
| | - Yuelong Wang
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (C.L.); (K.Z.); (L.L.); (J.S.); (Y.W.); (Y.T.); (X.F.); (W.L.)
| | - Yiying Tan
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (C.L.); (K.Z.); (L.L.); (J.S.); (Y.W.); (Y.T.); (X.F.); (W.L.)
| | - Xueqin Feng
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (C.L.); (K.Z.); (L.L.); (J.S.); (Y.W.); (Y.T.); (X.F.); (W.L.)
| | - Wanjie Liu
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (C.L.); (K.Z.); (L.L.); (J.S.); (Y.W.); (Y.T.); (X.F.); (W.L.)
| | - Hui Zhang
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (C.L.); (K.Z.); (L.L.); (J.S.); (Y.W.); (Y.T.); (X.F.); (W.L.)
| | - Jiaming Sun
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun 130117, China; (C.L.); (K.Z.); (L.L.); (J.S.); (Y.W.); (Y.T.); (X.F.); (W.L.)
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