Scientific Approaches to Accomplish Our Mission at the RIPLRT Institute
Exposure Science
As stated by the US National Academies of Science in the book Exposure Science in the 21st Century: A Vision and a Strategy, exposure science (with regards to human beings) links the a) origin of the pollutant and its concentration from a giving source, b) the human behavior during or as result of the exposure, c) the interaction between the pollutant and the human subject, and d) the outcome of this interaction. Depending on the nature of the question we want to address, and the project (often in a collaborative manner) in which we engage, we often address two or more of the concepts of exposure science
Human-Based Immunotoxicology
To align our findings of biomarker profiles in response to environmental pollutants, we employ human-based immunological approaches (see the red arrow in the image). Our PI and mentor (Dr. Rivera-Mariani) has a long track of expanding the utility of immunological approaches into new areas of research as evidenced here
Computational Data Science and Data Management
It is a difficult case for science when there are relevant findings, but the statistical approaches are not reproducible. In RIPLRT, we employ R, Python, and Matlab to make our data science reproducible. We also make our data science scripts, and often our raw data, available in online repositories such as Github, the Open Science Framework, FigShare, or Zenodo.