ABSTRACT
Emergency physicians (EPs) are well positioned to perform medical research. EPs are exposed to a wide range of disease types, medical specialties, and treatment modalities. Furthermore, emergency medicine (EM) serves as the safety net for the U.S. health care system. The diverse exposure provides a vast opportunity for EP to perform many worthwhile research projects. Yet, EM has historically had the lowest amount of funding and a lower number of National Institutes of Health-funded research projects. Many suggest the etiology is a "leaky" educational pipeline with loss of many potential physician-scientists over the training and development course. Current research training options for the EM physician-scientist includes MD-PhD, 4-year EM residency program and postresidency fellowships. While each has its advantages and disadvantages, we describe an additional educational alternative of EM physician-scientists, which we have named the integrated-dedicated research period within an EM residency. We describe the features of these programs and preliminary results from the graduates and current trainees.
ABSTRACT
Blood analysis is a ubiquitous and critical aspect of modern medicine. Analyzing blood samples requires invasive techniques, various testing systems, and samples are limited to relatively small volumes. Photoacoustic imaging (PAI) is a novel imaging modality that utilizes non-ionizing energy that shows promise as an alternative to current methods. This paper seeks to review current applications of PAI in blood analysis for clinical use. Furthermore, we discuss obstacles to implementation and future directions to overcome these challenges. Firstly, we discuss three applications to cellular analysis of blood: sickle cell, bacteria, and circulating tumor cell detection. We then discuss applications to the analysis of blood plasma, including glucose detection and anticoagulation quantification. As such, we hope this article will serve as inspiration for PAI's potential application in blood analysis and prompt further studies to ultimately implement PAI into clinical practice.
ABSTRACT
Surface electromyography (EMG) is a valuable tool in clinical diagnostics and research related to human neuromotor control. Non-linear analysis of EMG data can help with detection of subtle changes of control due to changes of external or internal constraints during motor tasks. However, non-linear analysis is complex and results may be difficult to interpret, particularly in clinical environments. We developed a non-linear analysis tool (SYNERGOS) that evaluates multiple muscle activation (MMA) features and provides a single value for description of activation characteristics. To investigate the responsiveness of SYNERGOS to kinetic changes during cyclic movements, 13 healthy young adults performed squat movements under different loading conditions (100%-120% of body weight). We processed EMG data to generate SYNERGOS indices and used two-way repeated measures ANOVA to determine changes of MMA in response to loading conditions during movement. SYNERGOS values were significantly different for each loading condition. We concluded that the algorithm is sensitive to kinetic changes during cyclic movements, which may have implications for applications in a variety of experimental and diagnostic settings.
