Browsing by Author "Richmond, Ann"
Now showing 1 - 2 of 2
- Results Per Page
- Sort Options
Item Open Access Bimodal analysis reveals a general scaling law governing nondirected and chemotactic cell motility.(Biophysical journal, 2010-07) Gruver, J Scott; Potdar, Alka A; Jeon, Junhwan; Sai, Jiqing; Anderson, Bridget; Webb, Donna; Richmond, Ann; Quaranta, Vito; Cummings, Peter T; Chung, Chang YCell motility is a fundamental process with relevance to embryonic development, immune response, and metastasis. Cells move either spontaneously, in a nondirected fashion, or in response to chemotactic signals, in a directed fashion. Even though they are often studied separately, both forms of motility share many complex processes at the molecular and subcellular scale, e.g., orchestrated cytoskeletal rearrangements and polarization. In addition, at the cellular level both types of motility include persistent runs interspersed with reorientation pauses. Because there is a great range of variability in motility among different cell types, a key challenge in the field is to integrate these multiscale processes into a coherent framework. We analyzed the motility of Dictyostelium cells with bimodal analysis, a method that compares time spent in persistent versus reorientation mode. Unexpectedly, we found that reorientation time is coupled with persistent time in an inverse correlation and, surprisingly, the inverse correlation holds for both nondirected and chemotactic motility, so that the full range of Dictyostelium motility can be described by a single scaling relationship. Additionally, we found an identical scaling relationship for three human cell lines, indicating that the coupling of reorientation and persistence holds across species and making it possible to describe the complexity of cell motility in a surprisingly general and simple manner. With this new perspective, we analyzed the motility of Dictyostelium mutants, and found four in which the coupling between two modes was altered. Our results point to a fundamental underlying principle, described by a simple scaling law, unifying mechanisms of eukaryotic cell motility at several scales.Item Open Access Co-Clinical Imaging Resource Program (CIRP): Bridging the Translational Divide to Advance Precision Medicine.(Tomography (Ann Arbor, Mich.), 2020-09) Shoghi, Kooresh I; Badea, Cristian T; Blocker, Stephanie J; Chenevert, Thomas L; Laforest, Richard; Lewis, Michael T; Luker, Gary D; Manning, H Charles; Marcus, Daniel S; Mowery, Yvonne M; Pickup, Stephen; Richmond, Ann; Ross, Brian D; Vilgelm, Anna E; Yankeelov, Thomas E; Zhou, RongThe National Institutes of Health's (National Cancer Institute) precision medicine initiative emphasizes the biological and molecular bases for cancer prevention and treatment. Importantly, it addresses the need for consistency in preclinical and clinical research. To overcome the translational gap in cancer treatment and prevention, the cancer research community has been transitioning toward using animal models that more fatefully recapitulate human tumor biology. There is a growing need to develop best practices in translational research, including imaging research, to better inform therapeutic choices and decision-making. Therefore, the National Cancer Institute has recently launched the Co-Clinical Imaging Research Resource Program (CIRP). Its overarching mission is to advance the practice of precision medicine by establishing consensus-based best practices for co-clinical imaging research by developing optimized state-of-the-art translational quantitative imaging methodologies to enable disease detection, risk stratification, and assessment/prediction of response to therapy. In this communication, we discuss our involvement in the CIRP, detailing key considerations including animal model selection, co-clinical study design, need for standardization of co-clinical instruments, and harmonization of preclinical and clinical quantitative imaging pipelines. An underlying emphasis in the program is to develop best practices toward reproducible, repeatable, and precise quantitative imaging biomarkers for use in translational cancer imaging and therapy. We will conclude with our thoughts on informatics needs to enable collaborative and open science research to advance precision medicine.