As described in our mission, our main scientific interest is addressing the physiological human health respiratory effects in response to environmental stressors: pollutants of different chemical origins and environmental sources. In line with our scientific mission, we employ,
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) and 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, here in RIPLRT 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 (refer to the bottom of the page of this link).
Computational Data Science. 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.
To contact the RIPL_Effect Research Team,