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Zeng M, Liu M, Tao X, Yin X, Shen C, Wang X. Emerging Trends in the Application of Extracellular Vesicles as Novel Oral Delivery Vehicles for Therapeutics in Inflammatory Diseases. Int J Nanomedicine 2024; 19:8573-8601. [PMID: 39185348 PMCID: PMC11345024 DOI: 10.2147/ijn.s475532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 08/08/2024] [Indexed: 08/27/2024] Open
Abstract
Inflammation involves complex immune responses where cytokines such as TNF-α, IL-1, and IL-6 promote vasodilation and increased vascular permeability to facilitate immune cell migration to inflammation sites. Persistent inflammation is linked to diseases like cancer, arthritis, and neurodegenerative disorders. Although oral anti-inflammatory drugs are favored for their non-invasiveness and cost-effectiveness, their efficacy is often compromised due to gastrointestinal degradation and limited bioavailability. Recent advancements highlight the potential of extracellular vesicles (EVs) as nanocarriers that enhance drug delivery by encapsulating therapeutic agents, ensuring targeted release and reduced toxicity. These EVs, derived from dietary sources and cell cultures, exhibit excellent biocompatibility and stability, presenting a novel approach in anti-inflammatory therapies. This review discusses the classification and advantages of orally administered EVs (O-EVs), their mechanism of action, and their emerging role in treating inflammatory conditions, positioning them as promising vectors in the development of innovative anti-inflammatory drug delivery systems.
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Affiliation(s)
- Mingtang Zeng
- Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Maozhu Liu
- Center of Infectious Diseases, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Xuelin Tao
- Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Xi Yin
- Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Chao Shen
- Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China
| | - Xueyan Wang
- Department of Pharmacy, West China Hospital, Sichuan University, Chengdu, 610041, People’s Republic of China
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Rui F, Yeo YH, Xu L, Zheng Q, Xu X, Ni W, Tan Y, Zeng QL, He Z, Tian X, Xue Q, Qiu Y, Zhu C, Ding W, Wang J, Huang R, Xu Y, Chen Y, Fan J, Fan Z, Qi X, Huang DQ, Xie Q, Shi J, Wu C, Li J. Development of a machine learning-based model to predict hepatic inflammation in chronic hepatitis B patients with concurrent hepatic steatosis: a cohort study. EClinicalMedicine 2024; 68:102419. [PMID: 38292041 PMCID: PMC10827491 DOI: 10.1016/j.eclinm.2023.102419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 12/21/2023] [Accepted: 12/22/2023] [Indexed: 02/01/2024] Open
Abstract
Background With increasingly prevalent coexistence of chronic hepatitis B (CHB) and hepatic steatosis (HS), simple, non-invasive diagnostic methods to accurately assess the severity of hepatic inflammation are needed. We aimed to build a machine learning (ML) based model to detect hepatic inflammation in patients with CHB and concurrent HS. Methods We conducted a multicenter, retrospective cohort study in China. Treatment-naive CHB patients with biopsy-proven HS between April 2004 and September 2022 were included. The optimal features for model development were selected by SHapley Additive explanations, and an ML algorithm with the best accuracy to diagnose moderate to severe hepatic inflammation (Scheuer's system ≥ G3) was determined and assessed by decision curve analysis (DCA) and calibration curve. This study is registered with ClinicalTrials.gov (NCT05766449). Findings From a pool of 1,787 treatment-naive patients with CHB and HS across eleven hospitals, 689 patients from nine of these hospitals were chosen for the development of the diagnostic model. The remaining two hospitals contributed to two independent external validation cohorts, comprising 509 patients in validation cohort 1 and 589 in validation cohort 2. Eleven features regarding inflammation, hepatic and metabolic functions were identified. The gradient boosting classifier (GBC) model showed the best performance in predicting moderate to severe hepatic inflammation, with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% CI 0.83-0.88) in the training cohort, and 0.89 (95% CI 0.86-0.92), 0.76 (95% CI 0.73-0.80) in the first and second external validation cohorts, respectively. A publicly accessible web tool was generated for the model. Interpretation Using simple parameters, the GBC model predicted hepatic inflammation in CHB patients with concurrent HS. It holds promise for guiding clinical management and improving patient outcomes. Funding This research was supported by the National Natural Science Foundation of China (No. 82170609, 81970545), Natural Science Foundation of Shandong Province (Major Project) (No. ZR2020KH006), Natural Science Foundation of Jiangsu Province (No.BK20231118), Tianjin Key Medical Discipline (Specialty), Construction Project, TJYXZDXK-059B, Tianjin Health Science and Technology Project key discipline special, TJWJ2022XK034, and Research project of Chinese traditional medicine and Chinese traditional medicine combined with Western medicine of Tianjin municipal health and Family Planning Commission (2021022).
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Affiliation(s)
- Fajuan Rui
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
- Department of Infectious Disease, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, China
| | - Yee Hui Yeo
- Karsh Division of Gastroenterology and Hepatology, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Liang Xu
- Clinical School of the Second People's Hospital, Tianjin Medical University, Tianjin, China
- Department of Hepatology, Tianjin Second People's Hospital, Tianjin, China
- Tianjin Research Institute of Liver Diseases, Tianjin, China
| | - Qi Zheng
- Department of Hepatology, Hepatology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China
| | - Xiaoming Xu
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
- Department of Infectious Disease, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, China
| | - Wenjing Ni
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
- Department of Infectious Disease, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, China
| | - Youwen Tan
- Department of Hepatology, The Third Hospital of Zhenjiang Affiliated Jiangsu University, Zhenjiang, Jiangsu, China
| | - Qing-Lei Zeng
- Department of Infectious Diseases and Hepatology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China
| | - Zebao He
- Department of Infectious Diseases, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, Zhejiang, China
| | - Xiaorong Tian
- School of Computer Science, China University of Geosciences, Wuhan, Hubei, China
- Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, Hubei, China
| | - Qi Xue
- Department of Infectious Disease, Shandong Provincial Hospital Affiliated to Shandong Frist Medical University, Ji'nan, Shandong, China
| | - Yuanwang Qiu
- Department of Infectious Diseases, The Fifth People's Hospital of Wuxi, Wuxi, Jiangsu, China
| | - Chuanwu Zhu
- Department of Infectious Diseases, The Affiliated Infectious Diseases Hospital of Soochow University, Suzhou, Jiangsu, China
| | - Weimao Ding
- Department of Hepatology, Huai'an No.4 People's Hospital, Huai'an, Jiangsu, China
| | - Jian Wang
- Department of Infectious Disease, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, China
| | - Rui Huang
- Department of Infectious Disease, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, China
| | - Yayun Xu
- Department of Infectious Disease, Shandong Provincial Hospital, Shandong University, Ji'nan, Shandong, China
| | - Yunliang Chen
- School of Computer Science, China University of Geosciences, Wuhan, Hubei, China
- Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, Hubei, China
| | - Junqing Fan
- School of Computer Science, China University of Geosciences, Wuhan, Hubei, China
- Hubei Key Laboratory of Intelligent Geo-Information Processing, China University of Geosciences, Wuhan, Hubei, China
| | - Zhiwen Fan
- Department of Pathology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China
| | - Xiaolong Qi
- Center of Portal Hypertension, Department of Radiology, Zhongda Hospital, Medical of School, Southeast University, Nanjing, Jiangsu, China
| | - Daniel Q. Huang
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Division of Gastroenterology and Hepatology, Department of Medicine, National University Health System, Singapore
| | - Qing Xie
- Department of Infectious Diseases, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China
| | - Junping Shi
- Department of Infectious & Hepatology Diseases, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Chao Wu
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
- Department of Infectious Disease, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, China
| | - Jie Li
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China
- Department of Infectious Disease, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, China
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Alshammary AF, Farzan R, Alsobaie SF, Alageel AA, Ali Khan I. Strategy for immunological analysis of pro-inflammatory cytokine marker studies with chronic hepatitis B virus in Southwestern region of Saudi Arabia. J Infect Public Health 2023; 16:1613-1618. [PMID: 37579699 DOI: 10.1016/j.jiph.2023.07.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 07/16/2023] [Accepted: 07/30/2023] [Indexed: 08/16/2023] Open
Abstract
BACKGROUND Hepatitis B Virus (HBV) is one of the leading causes of infectious disease in the global population, and its prevalence has been increasing globally. Human HBV infection is complex, involving both innate and adaptive immune systems. Cytokines play a role in both physiologic and pathologic processes in the liver. This study was designed to screen serum levels using an enzyme linked immunosorbent assay (ELISA) and genetic variants in the TNF-α and IL6 genes using polymerase chain reactions (PCR). The aim of this study was to screen the serum levels and genotype levels with TNF-α (C-308 T/G-308A) and IL-6 (G-174 C) genes in HBV patients and control subjects. METHODS In this study, we have selected 50 HBV patients and 40 control subjects from Saudi Population. Patient serum samples was used for measuring the serum levels and PCR analysis using RFLP analysis. Prior to this, HBV patients were confirmed with PCR analysis followed by Sanger sequencing analysis. RESULTS The current study results confirmed positive association in serum levels (p < 0.05) and negative association with both genotype and allele frequencies in TNF-α (C-308 T) and IL-6 (G-174 C) genes among HBV patients and controls (p > 0.05). Positive associations between blood levels of TNF-α and IL-6 were confirmed, while negative associations were found between PCR investigations involving the TNF-α (G-308A) and IL-6 (G-174 C) genes with the HBV prevalence in the Saudi population. CONCLUSION This study confirmed serum levels are strongly associated with HBV patients in the Saudi population. However, PCR studies showed the negative association with the couple of variants selected for this study.
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Affiliation(s)
- Amal F Alshammary
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia
| | - Raed Farzan
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia
| | - Sarah F Alsobaie
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia
| | - Arwa A Alageel
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia
| | - Imran Ali Khan
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Saud University, Riyadh 11433, Saudi Arabia.
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Jiang S, Wang J, Zhang Z, Zhan J, Xue R, Qiu Y, Zhu L, Zhang S, Pan Y, Yan X, Chen Y, Li J, Liu X, Zhu C, Huang R, Wu C. Development and Validation of a Nomogram to Predict Significant Liver Inflammation in Patients with Chronic Hepatitis B. Infect Drug Resist 2023; 16:5065-5075. [PMID: 37576516 PMCID: PMC10416784 DOI: 10.2147/idr.s417007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 07/26/2023] [Indexed: 08/15/2023] Open
Abstract
Background Noninvasive diagnosis of liver inflammation is important for patients with chronic hepatitis B (CHB). This study aimed to develop a nomogram to predict significant liver inflammation for CHB patients. Methods CHB patients who underwent liver biopsy were retrospectively collected and randomly divided into a development set and a validation set. The least absolute shrinkage and selection operator regression and logistic regression analysis were used to select independent predictors of significant liver inflammation, and a nomogram was developed. The performance of nomogram was assessed by receiver operating characteristic (ROC) curves, calibration curves and decision curve analysis (DCA). Results A total of 1019 CHB patients with a median age of 39.0 years were included. Alanine aminotransaminase (ALT, P = 0.018), gamma-glutamyl transpeptidase (P = 0.013), prothrombin time (P < 0.001), and HBV DNA level (P = 0.030) were identified as independent predictors of significant liver inflammation in the development set. A model namely AGPD-nomogram was developed based on the above parameters. The area under the ROC curve in predicting significant inflammation was 0.765 (95% CI: 0.727-0.803) and 0.766 (95% CI: 0.711-0.821) in the development and validation sets, which were significantly higher than other indexes. The AGPD-nomogram had a high predictive value in patients with normal ALT. Moreover, the nomogram was proven to be clinically useful by DCA. Conclusion A visualized AGPD-nomogram which incorporated routine clinical parameters was proposed to facilitate the prediction of significant liver inflammation in CHB patients. This nomogram had high accuracy in the identification of significant liver inflammation and would be a useful tool for the better management of CHB patients, especially for those with normal ALT.
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Affiliation(s)
- Suling Jiang
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China
| | - Jian Wang
- Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
| | - Zhiyi Zhang
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China
| | - Jie Zhan
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China
| | - Ruifei Xue
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China
| | - Yuanwang Qiu
- Department of Infectious Diseases, The Fifth People’s Hospital of Wuxi, Wuxi, Jiangsu, People’s Republic of China
| | - Li Zhu
- Department of Infectious Diseases, The Affiliated Infectious Diseases Hospital of Soochow University, Suzhou, Jiangsu, People’s Republic of China
| | - Shaoqiu Zhang
- Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
| | - Yifan Pan
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China
| | - Xiaomin Yan
- Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
| | - Yuxin Chen
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
- Department of Laboratory Medicine, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
| | - Jie Li
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China
- Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China
| | - Xingxiang Liu
- Department of Clinical Laboratory, Huai’an No. 4 People’s Hospital, Huai’an, Jiangsu, People’s Republic of China
| | - Chuanwu Zhu
- Department of Infectious Diseases, The Affiliated Infectious Diseases Hospital of Soochow University, Suzhou, Jiangsu, People’s Republic of China
| | - Rui Huang
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China
- Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China
| | - Chao Wu
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, Jiangsu, People’s Republic of China
- Department of Infectious Diseases, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, People’s Republic of China
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, People’s Republic of China
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Wei X, Li X, Zhang Y, Wang J, Shen S. Advances in the Therapeutic Applications of Plant-Derived Exosomes in the Treatment of Inflammatory Diseases. Biomedicines 2023; 11:1554. [PMID: 37371649 DOI: 10.3390/biomedicines11061554] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 05/14/2023] [Accepted: 05/23/2023] [Indexed: 06/29/2023] Open
Abstract
Plant-derived exosomes (PLDEs) are small extracellular vesicles that encapsulate proteins, nucleic acids and lipids, and they are usually involved in intercellular communication and molecular transport in plants. PLDEs are widely used in the therapy of diseases due to their abundance and easy availability. The diverse roles of PLDEs, which include transportation of drugs, acting as biomarkers for diagnosis of diseases and their roles in different therapies, suggest that there is a need to fully understand all the mechanisms involved in order to provide the optimum conditions for their therapeutic use. This review summarizes the biogenesis, components and functions of PLDEs and focuses on their use as therapeutic agents in the treatment of inflammatory diseases. It also explores new ideas for novel approaches in which PLDEs could potentially help patients with inflammatory diseases in the future.
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Affiliation(s)
- Xiaofang Wei
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Xiuyu Li
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
- Guangyuan Academy of Agricultural Sciences, Guangyuan 628017, China
| | - Yuejun Zhang
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Jian Wang
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi Key Laboratory of Animal Breeding and Disease Control, College of Animal Science and Technology, Guangxi University, Nanning 530004, China
| | - Shuibao Shen
- College of Animal Science and Technology, Guangxi University, Nanning 530004, China
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