Lucia Cevidanes

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We have developed and tested machine learning approaches to integrate quantitative markers for diagnosis and assessment of progression of TMJ OA, as well as extended the capabilities of 3D Slicer4 into web-based tools and disseminated open source image analysis tools. Our aims use data processing and in-depth analytics combined with learning using privileged information, integrated feature selection, and testing the performance of longitudinal risk predictors. Our long term goals are to improve diagnosis and risk prediction of TemporoMandibular Osteoarthritis in future multicenter studies.

The Spectrum of Data Science for Diagnosis of Osteoarthritis of the Temporomandibular Joint

Kenichi Kuroda

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Synthetic polymers have been used as a molecular platform to develop host-defense antimicrobial peptide (AMP) mimics toward the development of “polymer antibiotics” which are effective in killing drug-resistant bacteria. Our research has been centered on the AMP-mimetic design and chemical optimization strategies as well as the biological and biophysical implications of AMP mimicry by synthetic polymers. The AMP-mimetic polymers showed broad-spectrum activity, rapid bactericidal activity, and low propensity for resistance development in bacteria, which represent the hallmarks of AMPs. The polymers form amphipathic conformations capable of membrane disruption upon binding to bacterial membrane, which recapitulates the folding of alpha-helical AMPs. We propose a new perception that AMP-mimetic polymers are an inherently bioactive platform as whole molecules, which mimic more than the side chain functionalities of AMPs. The chemical and structural diversity of polymers will expand the possibilities for new antimicrobial materials including macromolecules and molecular assemblies with tailored activity. This type of synthetic polymers is cost-effective, suitable for large-scale production, and tunable for diverse applications, providing great potential for the development of versatile platforms that can be used as direct therapeutics or attached on surfaces.

Romesh P. Nalliah

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Dr. Nalliah’s research expertise is process evaluation. He has studied various healthcare processes, educational processes and healthcare economics. Dr. Nalliah’s research studies were the first time nationwide data was used to highlight emergency room resource utilization for managing dental conditions in the United States. Dr. Nalliah is internationally recognized as a pioneer in the field of nationwide hospital dataset research for dental conditions and has numerous publications in peer reviewed journals. After completing a masters degree at Harvard School of Public Health, Dr. Nalliah’s interests have expanded and he has studied various public health issues including sports injuries, poisoning, child abuse, motor vehicle accidents and surgical processes (like stem cell transplants, cardiac valve surgery and fracture reduction). National recognition of his expertise in these broader topics of medicine have given rise to opportunities to lecture to medical residents, nurse practitioners, students in medical, pharmacy and nursing programs about oral health. This is his passion- that his research should inform an evolution of health education curriculum and practice.

Dr. Nalliah’s professional mission is to improve healthcare delivery systems and he is interested in improving processes, minimizing inefficiencies, reducing healthcare bottlenecks, increasing quality, and increase task sharing which will lead to a patient-centered, coherent healthcare system. Dr. Nalliah’s research has identified systems constraints and his goal is to influence policy and planning to break those constraints and improve healthcare delivery.

 


Research Highlights