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Your search keyword '"Sluzewski, M. Filip"' showing total 7 results
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7 results on '"Sluzewski, M. Filip"'

1. Integrated intracellular organization and its variations in human iPS cells

Author

Viana, Matheus P., Chen, Jianxu, Knijnenburg, Theo A., Vasan, Ritvik, Yan, Calysta, Arakaki, Joy E., Bailey, Matte, Berry, Ben, Borensztejn, Antoine, Brown, Eva M., Carlson, Sara, Cass, Julie A., Chaudhuri, Basudev, Cordes Metzler, Kimberly R., Coston, Mackenzie E., Crabtree, Zach J., Davidson, Steve, DeLizo, Colette M., Dhaka, Shailja, Dinh, Stephanie Q., Do, Thao P., Domingus, Justin, Donovan-Maiye, Rory M., Ferrante, Alexandra J., Foster, Tyler J., Frick, Christopher L., Fujioka, Griffin, Fuqua, Margaret A., Gehring, Jamie L., Gerbin, Kaytlyn A., Grancharova, Tanya, Gregor, Benjamin W., Harrylock, Lisa J., Haupt, Amanda, Hendershott, Melissa C., Hookway, Caroline, Horwitz, Alan R., Hughes, H. Christopher, Isaac, Eric J., Johnson, Gregory R., Kim, Brian, Leonard, Andrew N., Leung, Winnie W., Lucas, Jordan J., Ludmann, Susan A., Lyons, Blair M., Malik, Haseeb, McGregor, Ryan, Medrash, Gabe E., Meharry, Sean L., Mitcham, Kevin, Mueller, Irina A., Murphy-Stevens, Timothy L., Nath, Aditya, Nelson, Angelique M., Oluoch, Sandra A., Paleologu, Luana, Popiel, T. Alexander, Riel-Mehan, Megan M., Roberts, Brock, Schaefbauer, Lisa M., Schwarzl, Magdalena, Sherman, Jamie, Slaton, Sylvain, Sluzewski, M. Filip, Smith, Jacqueline E., Sul, Youngmee, Swain-Bowden, Madison J., Tang, W. Joyce, Thirstrup, Derek J., Toloudis, Daniel M., Tucker, Andrew P., Valencia, Veronica, Wiegraebe, Winfried, Wijeratna, Thushara, Yang, Ruian, Zaunbrecher, Rebecca J., Labitigan, Ramon Lorenzo D., Sanborn, Adrian L., Johnson, Graham T., Gunawardane, Ruwanthi N., Gaudreault, Nathalie, Theriot, Julie A., and Rafelski, Susanne M.

Published
2023
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2. Segmentation of Cortical Spreading Depression Wavefronts Through Local Similarity Metric

Author

Sluzewski, M. Filip, Tvrdik, Petr, and Acton, Scott T.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing
Abstract

In this paper, we present a novel region-based segmentation method for cortical spreading depressions in 2-photon microscopy images. Fluorescent microscopy has become an important tool in neuroscience, but segmentation approaches are challenged by the opaque properties and structures of brain tissue. These challenges are made more extreme when segmenting events such as cortical spreading depressions, where low signal-to-noise ratios and intensity inhomogeneity dominate images. The method we propose uses a local intensity similarity measure that takes advantage of normalized Euclidean and geodesic distance maps of the image. This method provides a smooth segmentation boundary which is robust to the noise and inhomogeneity within cortical spreading depression images. Experimental results yielded a DICE index of 0.9859, an increase of 6% over the current state-of-the-art, and a reduction of root mean square error by 79.9%.

Published
2019

5. Cell states beyond transcriptomics: Integrating structural organization and gene expression in hiPSC-derived cardiomyocytes

Author

Gerbin, Kaytlyn A., primary, Grancharova, Tanya, additional, Donovan-Maiye, Rory M., additional, Hendershott, Melissa C., additional, Anderson, Helen G., additional, Brown, Jackson M., additional, Chen, Jianxu, additional, Dinh, Stephanie Q., additional, Gehring, Jamie L., additional, Johnson, Gregory R., additional, Lee, HyeonWoo, additional, Nath, Aditya, additional, Nelson, Angelique M., additional, Sluzewski, M. Filip, additional, Viana, Matheus P., additional, Yan, Calysta, additional, Zaunbrecher, Rebecca J., additional, Cordes Metzler, Kimberly R., additional, Gaudreault, Nathalie, additional, Knijnenburg, Theo A., additional, Rafelski, Susanne M., additional, Theriot, Julie A., additional, and Gunawardane, Ruwanthi N., additional

Published
2021
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7. Colony context and size-dependent compensation mechanisms give rise to variations in nuclear growth trajectories.

Author

Dixon JC, Frick CL, Leveille CL, Garrison P, Lee PA, Mogre SS, Morris B, Nivedita N, Vasan R, Chen J, Fraser CL, Gamlin CR, Harris LK, Hendershott MC, Johnson GT, Klein KN, Oluoch SA, Thirstrup DJ, Sluzewski MF, Wilhelm L, Yang R, Toloudis DM, Viana MP, Theriot JA, and Rafelski SM

Abstract

To investigate the fundamental question of how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we focused on nuclear growth in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days, and developed open-source tools for image and data analysis and an interactive timelapse viewer for exploring quantitative features of nuclear size and shape. We performed a data-driven analysis of nuclear growth variations across timescales. We found that individual nuclear volume growth trajectories arise from short timescale variations attributable to their spatiotemporal context within the colony. We identified a strikingly time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited., Competing Interests: Declaration of interests The authors declare no competing interests.

Published
2024
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