Antimicrobial Research (AMR) Lab, Department of Biotechnology, University of Mumbai, Vidyanagari, Santacruz (East), Mumbai, 400098, Maharashtra, India.
Department of Bioinformatics, Chikitsak Samuha's S.S & L.S Patkar Varde College, Mumbai, 400062, Maharashtra, India.
Interdiscip Sci. 2022 Dec;14(4):833-840. doi: 10.1007/s12539-022-00534-y. Epub 2022 Jul 25.
The rapid dissemination of antimicrobial resistance (AMR) has emerged as a serious health problem on an unprecedented global scale. AMR is predicted to kill more than 10 million people annually by 2050 leading to huge economic losses worldwide. Therefore, urgent action is required at the national as well as international levels to avert this looming crisis. Effective surveillance can play an important role in the containment of AMR spread by providing data to help determine AMR hotspots, predict an outbreak, maintain proper stewardship and propose immediate and future plans of action in this respect. Although many existing databases provide genetic and molecular information on AMR in microorganisms, there is no dedicated database of AMR from non-clinical samples. The FEAMR database is a one-of-its-kind database to provide manually collated and curated information on the prevalence of AMR in food and the environment. For designing the FEAMR webpage, Microsoft Visual Studio with HTML, CSS, ASP.NET, Bootstrap for the front-end and C# for the back-end were used. The FEAMR database is a free access resource ( https://feamrudbt-amrlab.mu.ac.in/ ), accepting verified food- and environment-related AMR submissions from across the globe. To the best of our knowledge, it is probably the first database providing AMR-related surveillance data from non-clinical samples. It is designed from the 'One Health Approach' perspective to help in the containment of global AMR spread. Flowsheet of steps for making FEAMR database 1. Research articles relating to Antimicrobial Resistance (AMR) were searched on the internet. 2. Data relating to AMR were retrieved from these articles and stored in an MS-Excel sheet. 3. The web pages of the FEAMR database (DB) were created using Microsoft Visual Studio (MVS) and its various tools. HTML, CSS, ASP.NET and Bootstrap were used for the front end and C# used for the back-end of the website. 4. The DB of FEAMR was created using MS SQL Server which was controlled by SQL Server Management Studio (SSMS). 5. The data from the MS-Excel sheet in step 2 was stored in the SQL server and displayed on the web page using GridView tool of MVS and C#. The database created was then uploaded on the University of Mumbai (UoM) website, where it can be accessed by all users having the link to the DB ( https://feamrudbt-amrlab.mu.ac.in/ ).
抗菌药物耐药性(AMR)的快速传播已经成为一个前所未有的全球性严重健康问题。据预测,到 2050 年,AMR 将导致全球每年超过 1000 万人死亡,造成巨大的经济损失。因此,需要在国家和国际层面采取紧急行动,以避免这场迫在眉睫的危机。有效的监测可以通过提供数据来帮助确定 AMR 热点、预测疫情爆发、保持适当的管理,并提出这方面的即时和未来行动计划,从而在遏制 AMR 传播方面发挥重要作用。虽然许多现有的数据库提供了关于微生物中 AMR 的遗传和分子信息,但没有专门针对非临床样本的 AMR 数据库。FEAMR 数据库是一个独一无二的数据库,提供了关于食品和环境中 AMR 流行情况的手动整理和策划信息。为了设计 FEAMR 网页,使用了 Microsoft Visual Studio 与 HTML、CSS、ASP.NET、前端的 Bootstrap 和后端的 C#。FEAMR 数据库是一个免费访问资源(https://feamrudbt-amrlab.mu.ac.in/),接受来自全球各地经过验证的与食品和环境相关的 AMR 提交。据我们所知,它可能是第一个提供非临床样本中 AMR 相关监测数据的数据库。它是从“同一健康方法”的角度设计的,旨在帮助遏制全球 AMR 的传播。创建 FEAMR 数据库的步骤流程图 1. 在互联网上搜索有关抗菌药物耐药性(AMR)的研究文章。 2. 从这些文章中检索与 AMR 相关的数据,并存储在 MS-Excel 工作表中。 3. 使用 Microsoft Visual Studio (MVS) 及其各种工具创建 FEAMR 数据库(DB)的网页。HTML、CSS、ASP.NET 和 Bootstrap 用于前端,C#用于网站的后端。 4. 使用 SQL Server Management Studio (SSMS) 控制的 MS SQL Server 创建 FEAMR 的 DB。 5. 将步骤 2 中的 MS-Excel 工作表中的数据存储在 SQL 服务器中,并使用 MVS 和 C#的 GridView 工具在网页上显示。然后将创建的数据库上传到孟买大学(UoM)网站,所有拥有数据库链接的用户都可以访问该网站(https://feamrudbt-amrlab.mu.ac.in/)。