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Wang M, Wu XM, He M, Liu H, Yang ZB, Li Y, Wang GM, Zhao HR, Zhang CG. Mastoparan M extracted from Vespa magnifica alleviates neuronal death in global cerebral ischemia-reperfusion rat model. Iran J Basic Med Sci 2022; 25:320-329. [PMID: 35656190 PMCID: PMC9148409 DOI: 10.22038/ijbms.2022.60745.13461] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 02/20/2022] [Indexed: 11/24/2022]
Abstract
Objective(s): Global cerebral ischemia (GCI), a consequence of cardiac arrest (CA), can significantly damage the neurons located in the vulnerable hippocampus CA1 areas. Clinically, neurological injury after CA contributes to death in most patients. Mastoparan-M extracted from Vespa magnifica (Smith) can be used to treat major neurological disorders. Hence, this study aimed to assess the effects of Mastoparan-M on GCI. Materials and Methods: To evaluate the neurotoxicity and neuroprotective effect of Mastoparan-M, the CCK8 and Annexin V-FITC/PI apoptosis assays were first performed in hippocampal HT22 neuronal cells in vitro. Then, Pulsinelli’s 4-vascular occlusion model was constructed in rats. After treatment with Mastoparan-M (0.05, 0.1, and 0.2 mg/kg, IP) for 3 or 7 days, behavioral tests, H&E staining or Nissl staining, immunohistochemistry, and ELISA were employed to investigate neuroprotective effects of Mastoparan-M on GCI in rats. Results: In vitro, the growth of HT22 neuronal cells was restrained at concentrations of 30-300 µg/ml (at 24 hr, IC50=105.2 µg/ml; at 48 hr, IC50=46.81 µg/ml), and Mastoparan-M treatment (0.1,1 and 5 µg/ml) restrained apoptosis. In vivo, Mastoparan-M improved neurocognitive function and neuronal loss in the hippocampal CA1 area of rats. In addition, these effects were associated with the prevention of neuroinflammation, oxidative stress, and apoptosis. Conclusion: Mastoparan-M acts as a neuroprotective agent to alleviate neuronal death in rats.
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Affiliation(s)
- Mei Wang
- Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali University, Dali 671000, China, National-Local Joint Engineering Research Center of Entomoceutics, Dali University, Dali 671000, China
| | - Xiu-Mei Wu
- Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali University, Dali 671000, China, National-Local Joint Engineering Research Center of Entomoceutics, Dali University, Dali 671000, China
| | - Miao He
- Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali University, Dali 671000, China, National-Local Joint Engineering Research Center of Entomoceutics, Dali University, Dali 671000, China
| | - Heng Liu
- Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali University, Dali 671000, China, National-Local Joint Engineering Research Center of Entomoceutics, Dali University, Dali 671000, China
| | - Zhi-Bing Yang
- Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali University, Dali 671000, China, Genetic Testing Center, The First Affiliated Hospital of Dali University, Dali University, Dali 671000, Yunnan, China
| | - Yue Li
- Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali University, Dali 671000, China, National-Local Joint Engineering Research Center of Entomoceutics, Dali University, Dali 671000, China
| | - Guang-Ming Wang
- Genetic Testing Center, The First Affiliated Hospital of Dali University, Dali University, Dali 671000, Yunnan, China
| | - Hai-Rong Zhao
- Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali University, Dali 671000, China, National-Local Joint Engineering Research Center of Entomoceutics, Dali University, Dali 671000, China, Genetic Testing Center, The First Affiliated Hospital of Dali University, Dali University, Dali 671000, Yunnan, China,Corresponding authors: Hai-Rong Zhao; Cheng-Gui Zhang. Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali University, Dali 671000, China; Genetic Testing Center, The First Affiliated Hospital of Dali University, Dali University, Dali 671000, Yunnan, China; National-Local Joint Engineering Research Center of Entomoceutics, Dali University, Dali 671000, China. ;
| | - Cheng-Gui Zhang
- Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali University, Dali 671000, China, National-Local Joint Engineering Research Center of Entomoceutics, Dali University, Dali 671000, China,Corresponding authors: Hai-Rong Zhao; Cheng-Gui Zhang. Yunnan Provincial Key Laboratory of Entomological Biopharmaceutical R&D, Dali University, Dali 671000, China; Genetic Testing Center, The First Affiliated Hospital of Dali University, Dali University, Dali 671000, Yunnan, China; National-Local Joint Engineering Research Center of Entomoceutics, Dali University, Dali 671000, China. ;
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Shi B, Ye H, Zheng L, Lyu J, Chen C, Heidari AA, Hu Z, Chen H, Wu P. Evolutionary warning system for COVID-19 severity: Colony predation algorithm enhanced extreme learning machine. Comput Biol Med 2021; 136:104698. [PMID: 34426165 PMCID: PMC8323529 DOI: 10.1016/j.compbiomed.2021.104698] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 07/20/2021] [Accepted: 07/23/2021] [Indexed: 12/22/2022]
Abstract
Coronavirus Disease 2019 (COVID-19) was distributed globally at the end of December 2019 due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Early diagnosis and successful COVID-19 assessment are missing, clinical care is ineffective, and deaths are high. In this study, we investigate whether the level of biochemical indicators helps to discriminate and classify the severity of the COVID-19 using the machine learning method. This research creates an efficient intelligence method for the diagnosis of COVID-19 from the perspective of biochemical indexes. The framework is proposed by integrating an enhanced new stochastic called the colony predation algorithm (CPA) with a kernel extreme learning machine (KELM), abbreviated as ECPA-KELM. The core feature of the approach is the ECPA algorithm which incorporates the two main operators that have been abstained from the grey wolf optimizer and moth-flame optimizer to improve and restore the CPA research functions and are simultaneously used to optimize the parameters and to select features for KELM. The ECPA output is checked thoroughly using IEEE CEC2017 benchmark to verify the capacity of the proposed methodology. Finally, in the diagnosis of COVID-19 using biochemical indexes, the designed ECPA-KELM model and other competing KELM models based on other optimization are used. Checking statistical results will display improved predictive properties for all metrics and higher stability. ECPA-KELM can also be used to discriminate and classify the severity of the COVID-19 as a possible computer-aided method and provide effective early warning for the treatment and diagnosis of COVID-19.
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Affiliation(s)
- Beibei Shi
- Affiliated People's Hospital of Jiangsu University, 8 Dianli Road, Zhenjiang, Jiangsu, 212000, China.
| | - Hua Ye
- Department of Pulmonary and Critical Care Medicine, Affiliated Yueqing Hospital, Wenzhou Medical University, Yueqing, 325600, China.
| | - Long Zheng
- Department of Pulmonary and Critical Care Medicine, Affiliated Yueqing Hospital, Wenzhou Medical University, Yueqing, 325600, China.
| | - Juncheng Lyu
- Weifang Medical University School of Public Health, China.
| | - Cheng Chen
- Center of Clinical Research, Wuxi People's Hospital of Nanjing Medical University, Wuxi, Jiangsu, 214023, China.
| | - Ali Asghar Heidari
- School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran.
| | - Zhongyi Hu
- College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325035, China.
| | - Huiling Chen
- College of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou, 325035, China.
| | - Peiliang Wu
- Department of Pulmonary and Critical Care Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.
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Alhazmi HA, Najmi A, Javed SA, Sultana S, Al Bratty M, Makeen HA, Meraya AM, Ahsan W, Mohan S, Taha MME, Khalid A. Medicinal Plants and Isolated Molecules Demonstrating Immunomodulation Activity as Potential Alternative Therapies for Viral Diseases Including COVID-19. Front Immunol 2021; 12:637553. [PMID: 34054806 PMCID: PMC8155592 DOI: 10.3389/fimmu.2021.637553] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 04/26/2021] [Indexed: 12/19/2022] Open
Abstract
Plants have been extensively studied since ancient times and numerous important chemical constituents with tremendous therapeutic potential are identified. Attacks of microorganisms including viruses and bacteria can be counteracted with an efficient immune system and therefore, stimulation of body’s defense mechanism against infections has been proven to be an effective approach. Polysaccharides, terpenoids, flavonoids, alkaloids, glycosides, and lactones are the important phytochemicals, reported to be primarily responsible for immunomodulation activity of the plants. These phytochemicals may act as lead molecules for the development of safe and effective immunomodulators as potential remedies for the prevention and cure of viral diseases. Natural products are known to primarily modulate the immune system in nonspecific ways. A number of plant-based principles have been identified and isolated with potential immunomodulation activity which justify their use in traditional folklore medicine and can form the basis of further specified research. The aim of the current review is to describe and highlight the immunomodulation potential of certain plants along with their bioactive chemical constituents. Relevant literatures of recent years were searched from commonly employed scientific databases on the basis of their ethnopharmacological use. Most of the plants displaying considerable immunomodulation activity are summarized along with their possible mechanisms. These discussions shall hopefully elicit the attention of researchers and encourage further studies on these plant-based immunomodulation products as potential therapy for the management of infectious diseases, including viral ones such as COVID-19.
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Affiliation(s)
- Hassan A Alhazmi
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, Jazan, Saudi Arabia.,Substance Abuse and Toxicology Research Centre, Jazan University, Jazan, Saudi Arabia
| | - Asim Najmi
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
| | - Sadique A Javed
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
| | - Shahnaz Sultana
- Department of Pharmacognosy, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
| | - Mohammed Al Bratty
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
| | - Hafiz A Makeen
- Department of Clinical Pharmacy, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
| | - Abdulkarim M Meraya
- Department of Clinical Pharmacy, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
| | - Waquar Ahsan
- Department of Pharmaceutical Chemistry, College of Pharmacy, Jazan University, Jazan, Saudi Arabia
| | - Syam Mohan
- Substance Abuse and Toxicology Research Centre, Jazan University, Jazan, Saudi Arabia
| | - Manal M E Taha
- Substance Abuse and Toxicology Research Centre, Jazan University, Jazan, Saudi Arabia
| | - Asaad Khalid
- Substance Abuse and Toxicology Research Centre, Jazan University, Jazan, Saudi Arabia
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Fleck JD, Betti AH, da Silva FP, Troian EA, Olivaro C, Ferreira F, Verza SG. Saponins from Quillaja saponaria and Quillaja brasiliensis: Particular Chemical Characteristics and Biological Activities. Molecules 2019; 24:E171. [PMID: 30621160 PMCID: PMC6337100 DOI: 10.3390/molecules24010171] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2018] [Revised: 12/13/2018] [Accepted: 12/28/2018] [Indexed: 12/21/2022] Open
Abstract
Quillaja saponaria Molina represents the main source of saponins for industrial applications. Q. saponaria triterpenoids have been studied for more than four decades and their relevance is due to their biological activities, especially as a vaccine adjuvant and immunostimulant, which have led to important research in the field of vaccine development. These saponins, alone or incorporated into immunostimulating complexes (ISCOMs), are able to modulate immunity by increasing antigen uptake, stimulating cytotoxic T lymphocyte production (Th1) and cytokines (Th2) in response to different antigens. Furthermore, antiviral, antifungal, antibacterial, antiparasitic, and antitumor activities are also reported as important biological properties of Quillaja triterpenoids. Recently, other saponins from Q. brasiliensis (A. St.-Hill. & Tul.) Mart. were successfully tested and showed similar chemical and biological properties to those of Q. saponaria barks. The aim of this manuscript is to summarize the current advances in phytochemical and pharmacological knowledge of saponins from Quillaja plants, including the particular chemical characteristics of these triterpenoids. The potential applications of Quillaja saponins to stimulate further drug discovery research will be provided.
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Affiliation(s)
- Juliane Deise Fleck
- Molecular Microbiology Laboratory, Institute of Health Sciences, Feevale University, Novo Hamburgo 93525-075, RS, Brazil.
| | - Andresa Heemann Betti
- Bioanalysis Laboratory, Institute of Health Sciences, Feevale University, Novo Hamburgo 93525-075, RS, Brazil.
| | - Francini Pereira da Silva
- Molecular Microbiology Laboratory, Institute of Health Sciences, Feevale University, Novo Hamburgo 93525-075, RS, Brazil.
| | - Eduardo Artur Troian
- Molecular Microbiology Laboratory, Institute of Health Sciences, Feevale University, Novo Hamburgo 93525-075, RS, Brazil.
| | - Cristina Olivaro
- Science and Chemical Technology Department, University Center of Tacuarembó, Udelar, Tacuarembó 45000, Uruguay.
| | - Fernando Ferreira
- Organic Chemistry Department, Carbohydrates and Glycoconjugates Laboratory, Udelar, Mondevideo 11600, Uruguay.
| | - Simone Gasparin Verza
- Molecular Microbiology Laboratory, Institute of Health Sciences, Feevale University, Novo Hamburgo 93525-075, RS, Brazil.
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