寻找对不同病因感染有效的植物源性新药的展望方向

N. Mehdiyeva
{"title":"寻找对不同病因感染有效的植物源性新药的展望方向","authors":"N. Mehdiyeva","doi":"10.29228/PROC.90","DOIUrl":null,"url":null,"abstract":"The global community is concerned about the COVID-19 pandemic. Existing capacities are mobilized and new ways to counter the growing threat are actively sought. The scientific development of traditional medicine is a promising way of solving this problem. Information on the use of medicinal plants by different peoples is fragmented and largely unavailable to the world scientific community. The flora of Azerbaijan including almost 1600 species of medicinal plants with antiviral, anti-inflammatory, immunomodulatory, vitamin, general tonic and other properties are distributed in the Flora of Azerbaijan. Modern protocols for the treatment of infection caused by COVID-19, along with other therapeutic agents, will include drugs with the above properties. The article contains information about a computer database of medicinal plants in Azerbaijan, developed by the author in the frame of the doctoral thesis in the 2006 year. These data enable us to distinguish species with a set of biologically active substances that determine their required necessary physiological activity from the total number of medicinal plants. Therefore, the intensification of work on the study of traditional medicine and the creation of a worldwide information platform on medicinal plants can become the basis for the search and development of new antiviral drugs, including those effective and against COVID-19.","PeriodicalId":54068,"journal":{"name":"Proceedings of the Institute of Mathematics and Mechanics","volume":"1 1","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prospective directions for searching new medicines of plant origin, effective in infections of different etiology\",\"authors\":\"N. Mehdiyeva\",\"doi\":\"10.29228/PROC.90\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The global community is concerned about the COVID-19 pandemic. Existing capacities are mobilized and new ways to counter the growing threat are actively sought. The scientific development of traditional medicine is a promising way of solving this problem. Information on the use of medicinal plants by different peoples is fragmented and largely unavailable to the world scientific community. The flora of Azerbaijan including almost 1600 species of medicinal plants with antiviral, anti-inflammatory, immunomodulatory, vitamin, general tonic and other properties are distributed in the Flora of Azerbaijan. Modern protocols for the treatment of infection caused by COVID-19, along with other therapeutic agents, will include drugs with the above properties. The article contains information about a computer database of medicinal plants in Azerbaijan, developed by the author in the frame of the doctoral thesis in the 2006 year. These data enable us to distinguish species with a set of biologically active substances that determine their required necessary physiological activity from the total number of medicinal plants. Therefore, the intensification of work on the study of traditional medicine and the creation of a worldwide information platform on medicinal plants can become the basis for the search and development of new antiviral drugs, including those effective and against COVID-19.\",\"PeriodicalId\":54068,\"journal\":{\"name\":\"Proceedings of the Institute of Mathematics and Mechanics\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Institute of Mathematics and Mechanics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.29228/PROC.90\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATHEMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Institute of Mathematics and Mechanics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.29228/PROC.90","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS","Score":null,"Total":0}
引用次数: 0

摘要

当前,国际社会对新冠肺炎疫情十分关注。调动现有的能力,积极寻求对付日益严重的威胁的新方法。传统医学的科学发展是解决这一问题的一条有希望的途径。关于不同民族使用药用植物的资料支离破碎,世界科学界基本上无法获得。阿塞拜疆植物区系包括近1600种具有抗病毒、抗炎、免疫调节、维生素、一般滋补和其他特性的药用植物,分布在阿塞拜疆植物区系。治疗COVID-19引起的感染的现代方案以及其他治疗剂将包括具有上述特性的药物。这篇文章包含关于阿塞拜疆药用植物计算机数据库的信息,该数据库是作者在2006年的博士论文框架内开发的。这些数据使我们能够用一组生物活性物质来区分物种,这些生物活性物质决定了它们所需的必要生理活性与药用植物的总数。因此,加强对传统医学的研究和建立一个全球药用植物信息平台,可以成为寻找和开发新的抗病毒药物的基础,包括有效和对抗COVID-19的药物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Prospective directions for searching new medicines of plant origin, effective in infections of different etiology
The global community is concerned about the COVID-19 pandemic. Existing capacities are mobilized and new ways to counter the growing threat are actively sought. The scientific development of traditional medicine is a promising way of solving this problem. Information on the use of medicinal plants by different peoples is fragmented and largely unavailable to the world scientific community. The flora of Azerbaijan including almost 1600 species of medicinal plants with antiviral, anti-inflammatory, immunomodulatory, vitamin, general tonic and other properties are distributed in the Flora of Azerbaijan. Modern protocols for the treatment of infection caused by COVID-19, along with other therapeutic agents, will include drugs with the above properties. The article contains information about a computer database of medicinal plants in Azerbaijan, developed by the author in the frame of the doctoral thesis in the 2006 year. These data enable us to distinguish species with a set of biologically active substances that determine their required necessary physiological activity from the total number of medicinal plants. Therefore, the intensification of work on the study of traditional medicine and the creation of a worldwide information platform on medicinal plants can become the basis for the search and development of new antiviral drugs, including those effective and against COVID-19.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
1.80
自引率
27.30%
发文量
14
期刊介绍: Proceedings of the Institute of Mathematics and Mechanics (PIMM), National Academy of Sciences of Azerbaijan is an open access journal that publishes original, high quality research papers in all fields of mathematics. A special attention is paid to the following fields: real and complex analysis, harmonic analysis, functional analysis, approximation theory, differential equations, calculus of variations and optimal control, differential geometry, algebra, number theory, probability theory and mathematical statistics, mathematical physics. PIMM welcomes papers that establish interesting and important new results or solve significant problems. All papers are refereed for correctness and suitability for publication. The journal is published in both print and online versions.
期刊最新文献
EXPONENTIAL STABILITY OF BAM-TYPE NEURAL NETWORKS WITH CONFORMABLE DERIVATIVE ON THE GROWTH OF m-TH DERIVATIVES OF ALGEBRAIC POLYNOMIALS IN REGIONS WITH CORNERS IN A WEIGHTED BERGMAN SPACE LONG-RUN BEHAVIOR OF MULTIVARIATE MEANS APPLICATIONS OF CESARO SUBMETHOD TO ` APPROXIMATION OF FUNCTIONS IN WEIGHTED ORLICZ SPACES SOME PARSEVAL-GOLDSTEIN TYPE IDENTITIES WITH ILLUSTRATIVE EXAMPLES
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1