My interest in the cardiovascular effects of airborne toxins stemmed from a combination of educational, professional, and personal interests.
While earning a PhD in Environmental Health Sciences, I worked for the EPA, where I analyzed rat ECGs for air pollutant-induced arrhythmias and changes in heart rate variability. Excellent mentors at the EPA, and a strong team of public health researchers focused on environmental determinants of cardiovascular disease during my postdoc at Harvard, furthered my interests in this field.
I also have a vested personal interest in the potential impacts of air pollution being an outdoor enthusiast.
What does the general landscape of this research currently look like?
The landscape I’m now most familiar with is largely dictated by funding opportunities and government priorities, which includes characterizing health effects and understanding biological mechanisms of toxicity.
For example, the FDA is more interested in characterization of health effects given their responsibility to evaluate the safety of food and drugs, whereas the NIH is perhaps more interested in work that determines the mechanisms of toxicity.
Attention has recently shifted away from airborne particulate matter (classic air pollutants) to multi-pollutant interactions and volatile organic compounds (VOCs). In inhalation toxicology, emphasis has shifted to some extent to e-cigarette research, given the novelty and our limited understanding of the public health implications of e-cigarettes.
Increasingly sensitive tools are allowing researchers to demonstrate toxicity at lower, more real-world levels. And so, researchers depend all the more on the reliability and sensitivity of their instruments.
What are the real-world implications of your research?
My research mostly uses rodents to identify the cardiac risks of inhaled toxins, but it is also designed to clarify whether links between exposures and adverse human health outcomes might causally relate. Right now, there is a proposed menthol ban in combustible cigarettes. This may someday play out for e-cigarettes as well. My research could impact the chosen route forward for regulation of e-cigarettes.
How long have you been an EMKA user?
I have used EMKA’s ecgAUTO software for 16 years.
I used it throughout my training at the U.S. EPA and UNC Chapel Hill, as well as Harvard University, and now here at the University of Louisville.
How has using EMKA software helped with improving the translatability and reproducibility of your research?
After using ecgAUTO to analyze animal ECGs for over a decade, I began applying it to human data a few years ago. This has enhanced the translatability of my research by allowing me to use the same software and analysis procedures.
The ability to reapply the same configurations across various studies for automated detection of heart beats is a major advantage.
The ability to analyze data from conscious, unrestrained animals ensures a greater level of reproducibility, since anesthetics can interfere with the toxic effects of aerosols and the mechanisms underlying them.
The autonomy to adjust fiduciary points of the library waveforms for pattern recognition in ECG analysis sets ecgAUTO apart from competing software. The software can handle large datasets with multiple physiological signals per file as well.
What were some insights that the EMKA solutions helped you obtain?
Throughout my 16 years of working with EMKA, I have truly felt like I am working with the EMKA team. There has been a constant two-way communication to optimize the software and figure out workarounds for various challenges. EMKA has consistently provided me direct, honest, and unfiltered feedback on the limitations and advantages of their products. I really can’t think of a more responsive company.
What features of the equipment or software do you find most useful?
The ability of ecgAUTO to handle staggering amounts of data with relative ease has proven highly advantageous.
The customizability of parameters has enabled us to estimate relatively novel endpoints in the field of cardiovascular toxicology. For instance, in rats, we have used negative ST area as a surrogate for ST segment amplitude to indicate myocardial ischemia.
As well, the interlead analysis option has enabled us to estimate excitation-contraction coupling time or electro-mechanical delay when pairing ECG with left ventricular pressure. Spontaneous baroreflex has also been another useful and relatively novel parameter provided in ecgAUTO.
What was the reasoning behind selecting your animal model?
I began my research in rats given how conducive their size is to telemetry surgeries as well as their representativeness of human cardiac physiology. However, I made the switch to mice, given the variety of genetic models available for testing biological mechanisms.
What advice do you have for someone starting out in this research area?
Glom onto someone knowledgeable in the field and learn everything you can from them. Never stop asking questions, and if your peers and mentors don’t know the answer to the most interesting questions, figure out how to find the answer yourself.
What’s next for your lab and your research?
We have some major publications in the works that examine the ability of e-cigarettes to induce cardiac arrhythmia. I also plan to further enhance the translational aspects of my current research program
Dr. Alex Carll works in the department of Physiology, at the University of Louisville, KY, USA. He studies the biological mechanisms by which air pollutants weaken the heart, impair cardiac conduction, and compromise hemodynamics, and whether such effects occur through the autonomic nervous system. He uses ecgAUTO software to analyze ECG, blood pressure, and left ventricular pressure in rodents.
