BUILDING A DATABASE FOR NANOMATERIAL EXPOSURE
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Nanomaterials is a type of material with more advanced properties than conventional materials, and both scientists and engineers have a strong motivation to apply them in lots of areas. However, before they are widely applied, it is necessary to understand their toxicity on organisms. To date, large amounts of studies have explored the toxicity of nanomaterials, and they have greatly helped people understand how nanomaterials impact organisms. However, the developing speed of this field is getting slower because it is becoming more difficult for researchers to effectively search for information they need. Building a user-friendly database for nanomaterials and bioactivity is the main objective of this project and it is also an effective solution to address this problem by strengthening the information dissemination in this field. Based on the basic database structure developed by researchers in the Center of Environmental Implications of Nanotechnology (CEINT), exposure data for carbon nanotubes (CNTs) will be collected and imported into the database, and in the meanwhile, the database structure will be further optimized to fit new dataset imported. The method of this project is based on five steps: 1. Finding related studies and sources. 2. Extracting data from sources. 3. Preparing source files for the database. 4. Imputing data into MySQL database. 5. Query data from the database. The database consists of six sections: 1. Materials section: Recording the properties of nanomaterials tested in each study. 2. Environmental System section: Describing the environmental system in which the study was conducted. 3. Biological System section: Recording information about the organisms chosen to conduct exposure experiments. 4. Functional Assay section: Recording the assay that provides a parameter that can be used to describe fate or effects of nanomaterials exposure. 5. Study section: Serving as the main section to connect each previous part and functionalize the whole database. 6. Study_PI_Publication section: Recording information about primary investigator and publication, and connecting this information with Study table. Based on this database structure, I have imported data from 21 studies for CNTs into the database. The whole database works well and several applications have been developed. In my project report, two applications are introduced in detail. Application #1: The impacts of exposing the same organism to different CNTs. Different CNTs usually have different impacts on the same organism. However, most of studies usually focus on one of more types of CNTs. It would be a time-consuming process to review all published papers to understand how organism responds to different CNTs exposure. Building a database is an effective way to help reduce time for searching data. In this project, I targeted at C.elegans as an example to show this application. As a result, C.elegans were exposed to three types of CNTs, and about 359 functional assays were found. Further analysis was conducted based on this selected data. Application #2: The impacts of exposing the same type of CNTs to different organisms. The Same type of CNTs may have different impacts on different organisms. The database is a useful tool to help address this issue. In this project, I wanted to know how single wall carbon nanotubes (SWCNTs) influence different organisms. As a result, among all the dataset stored in my database, there were six organisms were exposed to SWCNTs and considerable amount of functional assays were conducted post SWCNTs exposure. However, currently, the impacts of exposing the same CNTs to different organisms are incomparable, because of following reasons. The first one is that CNTs used in each study is not completely the same, although they are called with the same name. The second is that, due to the limited amount of data, all functional assays are different, and it means that simple comparison is not available to know which organism are more vulnerable to CNTs exposure. This report also provides several key points of the database and recommendations to make a better database for nanomaterials exposure and boost the development of the field of nanomaterials safety. 1. The database can help researchers to avoid doing redundant studies and strengthen the communication between them. Moreover, it is a different search engine by focusing on specific study instead of keywords that is applied by conventional search method 2. The database structure should be further optimized in order to better fit the newly imported dataset. 3. The data quantity can be further expanded by developing a platform for database users to self-report their data. 4. Designing a series of standards for conducting exposure experiment and nanomaterials manufacturing will help to make the results of different studies more comparable. It is also an effective way to help increase the usability of dataset imported into the database. 5. Designing a series of indices, which include results of some normal tests (e.g. biouptake, death rate) and other important biomarkers. Based on analyzing these indices, a model can be built to evaluate the toxicity of exposing a certain type of nanomaterial to an organism.
CitationHe, Linchen (2015). BUILDING A DATABASE FOR NANOMATERIAL EXPOSURE. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/9626.
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