Scientific Approaches to Accomplish Our Vision and Mission at the RIPLRT Institute

flowchart diagram with a human figure, showing exposure to a pollutant, and questions about biomarkers and individual features affecting biomarker profiles.

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

Flowchart showing the relationship between pollutant exposure and biomarkers in a human body. It depicts a human silhouette with arrows indicating sources of pollutants, which affect specific features and biomarkers.

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

A diagram illustrating the data science process, starting from developing expectations with data, collecting data, and matching expectations with data, followed by five interconnected gears representing steps: stating the question, exploratory data analysis, model building, interpreting, and communicating.

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.