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1. Quantifying brain development in the HEALthy Brain and Child Development (HBCD) Study: The magnetic resonance imaging and spectroscopy protocol.

Author

Dean, Douglas, Tisdall, M, Wisnowski, Jessica, Feczko, Eric, Gagoski, Borjan, Alexander, Andrew, Edden, Richard, Gao, Wei, Hendrickson, Timothy, Howell, Brittany, Huang, Hao, Humphreys, Kathryn, Riggins, Tracy, Sylvester, Chad, Weldon, Kimberly, Yacoub, Essa, Ahtam, Banu, Beck, Natacha, Banerjee, Suchandrima, Boroday, Sergiy, Caprihan, Arvind, Caron, Bryan, Carpenter, Samuel, Chang, Yulin, Chung, Ai, Cieslak, Matthew, Clarke, William, Dale, Anders, Das, Samir, Davies-Jenkins, Christopher, Dufford, Alexander, Evans, Alan, Fesselier, Laetitia, Ganji, Sandeep, Gilbert, Guillaume, Graham, Alice, Gudmundson, Aaron, Macgregor-Hannah, Maren, Harms, Michael, Hilbert, Tom, Hui, Steve, Irfanoglu, M, Kecskemeti, Steven, Kober, Tobias, Kuperman, Joshua, Lamichhane, Bidhan, Landman, Bennett, Lecour-Bourcher, Xavier, Lee, Erik, Li, Xu, MacIntyre, Leigh, Madjar, Cecile, Manhard, Mary, Mayer, Andrew, Mehta, Kahini, Moore, Lucille, Murali-Manohar, Saipavitra, Navarro, Cristian, Nebel, Mary, Newman, Sharlene, Newton, Allen, Noeske, Ralph, Norton, Elizabeth, Oeltzschner, Georg, Ongaro-Carcy, Regis, Ou, Xiawei, Ouyang, Minhui, Parrish, Todd, Pekar, James, Pengo, Thomas, Pierpaoli, Carlo, Poldrack, Russell, Rajagopalan, Vidya, Rettmann, Dan, Rioux, Pierre, Rosenberg, Jens, Salo, Taylor, Satterthwaite, Theodore, Scott, Lisa, Shin, Eunkyung, Simegn, Gizeaddis, Simmons, W, Song, Yulu, Tikalsky, Barry, Tkach, Jean, van Zijl, Peter, Vannest, Jennifer, Versluis, Maarten, Zhao, Yansong, Zöllner, Helge, Fair, Damien, Smyser, Christopher, and Elison, Jed

Subjects
Development, HBCD, Infant, MRI, MRS, Protocol
Abstract

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The acquisition of multimodal magnetic resonance-based brain development data is central to the studys core protocol. However, application of Magnetic Resonance Imaging (MRI) methods in this population is complicated by technical challenges and difficulties of imaging in early life. Overcoming these challenges requires an innovative and harmonized approach, combining age-appropriate acquisition protocols together with specialized pediatric neuroimaging strategies. The HBCD MRI Working Group aimed to establish a core acquisition protocol for all 27 HBCD Study recruitment sites to measure brain structure, function, microstructure, and metabolites. Acquisition parameters of individual modalities have been matched across MRI scanner platforms for harmonized acquisitions and state-of-the-art technologies are employed to enable faster and motion-robust imaging. Here, we provide an overview of the HBCD MRI protocol, including decisions of individual modalities and preliminary data. The result will be an unparalleled resource for examining early neurodevelopment which enables the larger scientific community to assess normative trajectories from birth through childhood and to examine the genetic, biological, and environmental factors that help shape the developing brain.

Published
2024

3. TCuPGAN: A novel framework developed for optimizing human-machine interactions in citizen science

Author

Sankar, Ramanakumar, Mantha, Kameswara, Fortson, Lucy, Spiers, Helen, Pengo, Thomas, Mashek, Douglas, Mo, Myat, Sanders, Mark, Christensen, Trace, Salisbury, Jeffrey, and Trouille, Laura

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

In the era of big data in scientific research, there is a necessity to leverage techniques which reduce human effort in labeling and categorizing large datasets by involving sophisticated machine tools. To combat this problem, we present a novel, general purpose model for 3D segmentation that leverages patch-wise adversariality and Long Short-Term Memory to encode sequential information. Using this model alongside citizen science projects which use 3D datasets (image cubes) on the Zooniverse platforms, we propose an iterative human-machine optimization framework where only a fraction of the 2D slices from these cubes are seen by the volunteers. We leverage the patch-wise discriminator in our model to provide an estimate of which slices within these image cubes have poorly generalized feature representations, and correspondingly poor machine performance. These images with corresponding machine proposals would be presented to volunteers on Zooniverse for correction, leading to a drastic reduction in the volunteer effort on citizen science projects. We trained our model on ~2300 liver tissue 3D electron micrographs. Lipid droplets were segmented within these images through human annotation via the `Etch A Cell - Fat Checker' citizen science project, hosted on the Zooniverse platform. In this work, we demonstrate this framework and the selection methodology which resulted in a measured reduction in volunteer effort by more than 60%. We envision this type of joint human-machine partnership will be of great use on future Zooniverse projects., Comment: 5 pages, 1 figure, accepted for publication at HLDM '23 (ECML PKDD 2023 workshop)

Published
2023

4. From fat droplets to floating forests: cross-domain transfer learning using a PatchGAN-based segmentation model

Author

Mantha, Kameswara Bharadwaj, Sankar, Ramanakumar, Zheng, Yuping, Fortson, Lucy, Pengo, Thomas, Mashek, Douglas, Sanders, Mark, Christensen, Trace, Salisbury, Jeffrey, Trouille, Laura, Byrnes, Jarrett E. K., Rosenthal, Isaac, Houskeeper, Henry, and Cavanaugh, Kyle

Subjects
Computer Science - Machine Learning, Computer Science - Computer Vision and Pattern Recognition
Abstract

Many scientific domains gather sufficient labels to train machine algorithms through human-in-the-loop techniques provided by the Zooniverse.org citizen science platform. As the range of projects, task types and data rates increase, acceleration of model training is of paramount concern to focus volunteer effort where most needed. The application of Transfer Learning (TL) between Zooniverse projects holds promise as a solution. However, understanding the effectiveness of TL approaches that pretrain on large-scale generic image sets vs. images with similar characteristics possibly from similar tasks is an open challenge. We apply a generative segmentation model on two Zooniverse project-based data sets: (1) to identify fat droplets in liver cells (FatChecker; FC) and (2) the identification of kelp beds in satellite images (Floating Forests; FF) through transfer learning from the first project. We compare and contrast its performance with a TL model based on the COCO image set, and subsequently with baseline counterparts. We find that both the FC and COCO TL models perform better than the baseline cases when using >75% of the original training sample size. The COCO-based TL model generally performs better than the FC-based one, likely due to its generalized features. Our investigations provide important insights into usage of TL approaches on multi-domain data hosted across different Zooniverse projects, enabling future projects to accelerate task completion., Comment: 5 pages, 4 figures, accepted for publication at the Proceedings of the ACM/CIKM 2022 (Human-in-the-loop Data Curation Workshop)

Published
2022

5. Quantifying brain development in the HEALthy Brain and Child Development (HBCD) Study: The magnetic resonance imaging and spectroscopy protocol

Author

Dean, Douglas C., III, Tisdall, M Dylan, Wisnowski, Jessica L., Feczko, Eric, Gagoski, Borjan, Alexander, Andrew L., Edden, Richard A.E., Gao, Wei, Hendrickson, Timothy J., Howell, Brittany R., Huang, Hao, Humphreys, Kathryn L., Riggins, Tracy, Sylvester, Chad M., Weldon, Kimberly B., Yacoub, Essa, Ahtam, Banu, Beck, Natacha, Banerjee, Suchandrima, Boroday, Sergiy, Caprihan, Arvind, Caron, Bryan, Carpenter, Samuel, Chang, Yulin, Chung, Ai Wern, Cieslak, Matthew, Clarke, William T., Dale, Anders, Das, Samir, Davies-Jenkins, Christopher W., Dufford, Alexander J., Evans, Alan C., Fesselier, Laetitia, Ganji, Sandeep K., Gilbert, Guillaume, Graham, Alice M., Gudmundson, Aaron T., Macgregor-Hannah, Maren, Harms, Michael P., Hilbert, Tom, Hui, Steve C.N., Irfanoglu, M. Okan, Kecskemeti, Steven, Kober, Tobias, Kuperman, Joshua M., Lamichhane, Bidhan, Landman, Bennett A., Lecour-Bourcher, Xavier, Lee, Erik G., Li, Xu, MacIntyre, Leigh, Madjar, Cecile, Manhard, Mary Kate, Mayer, Andrew R., Mehta, Kahini, Moore, Lucille A., Murali-Manohar, Saipavitra, Navarro, Cristian, Nebel, Mary Beth, Newman, Sharlene D., Newton, Allen T., Noeske, Ralph, Norton, Elizabeth S., Oeltzschner, Georg, Ongaro-Carcy, Regis, Ou, Xiawei, Ouyang, Minhui, Parrish, Todd B., Pekar, James J., Pengo, Thomas, Pierpaoli, Carlo, Poldrack, Russell A., Rajagopalan, Vidya, Rettmann, Dan W., Rioux, Pierre, Rosenberg, Jens T., Salo, Taylor, Satterthwaite, Theodore D., Scott, Lisa S., Shin, Eunkyung, Simegn, Gizeaddis, Simmons, W. Kyle, Song, Yulu, Tikalsky, Barry J., Tkach, Jean, van Zijl, Peter C.M., Vannest, Jennifer, Versluis, Maarten, Zhao, Yansong, Zöllner, Helge J., Fair, Damien A., Smyser, Christopher D., and Elison, Jed T.

Published
2024
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6. Spatial mapping of cellular senescence: emerging challenges and opportunities

Author

Gurkar, Aditi U., Gerencser, Akos A., Mora, Ana L., Nelson, Andrew C., Zhang, Anru R., Lagnado, Anthony B., Enninful, Archibald, Benz, Christopher, Furman, David, Beaulieu, Delphine, Jurk, Diana, Thompson, Elizabeth L., Wu, Fei, Rodriguez, Fernanda, Barthel, Grant, Chen, Hao, Phatnani, Hemali, Heckenbach, Indra, Chuang, Jeffrey H., Horrell, Jeremy, Petrescu, Joana, Alder, Jonathan K., Lee, Jun Hee, Niedernhofer, Laura J., Kumar, Manoj, Königshoff, Melanie, Bueno, Marta, Sokka, Miiko, Scheibye-Knudsen, Morten, Neretti, Nicola, Eickelberg, Oliver, Adams, Peter D., Hu, Qianjiang, Zhu, Quan, Porritt, Rebecca A., Dong, Runze, Peters, Samuel, Victorelli, Stella, Pengo, Thomas, Khaliullin, Timur, Suryadevara, Vidyani, Fu, Xiaonan, Bar-Joseph, Ziv, Ji, Zhicheng, and Passos, João F.

Published
2023
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7. Reproducible brain-wide association studies require thousands of individuals

Author

Marek, Scott, Tervo-Clemmens, Brenden, Calabro, Finnegan J., Montez, David F., Kay, Benjamin P., Hatoum, Alexander S., Donohue, Meghan Rose, Foran, William, Miller, Ryland L., Hendrickson, Timothy J., Malone, Stephen M., Kandala, Sridhar, Feczko, Eric, Miranda-Dominguez, Oscar, Graham, Alice M., Earl, Eric A., Perrone, Anders J., Cordova, Michaela, Doyle, Olivia, Moore, Lucille A., Conan, Gregory M., Uriarte, Johnny, Snider, Kathy, Lynch, Benjamin J., Wilgenbusch, James C., Pengo, Thomas, Tam, Angela, Chen, Jianzhong, Newbold, Dillan J., Zheng, Annie, Seider, Nicole A., Van, Andrew N., Metoki, Athanasia, Chauvin, Roselyne J., Laumann, Timothy O., Greene, Deanna J., Petersen, Steven E., Garavan, Hugh, Thompson, Wesley K., Nichols, Thomas E., Yeo, B. T. Thomas, Barch, Deanna M., Luna, Beatriz, Fair, Damien A., and Dosenbach, Nico U. F.

Published
2022
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11. Away from resolution, assessing the information content of super-resolution images

Author

Pengo, Thomas, Olivier, Nicolas, and Manley, Suliana

Subjects
Physics - Biological Physics
Abstract

Super-resolution microscopy has revolutionized optical fluorescence imaging by improving 3D resolution by 1-2 orders of magnitude. While different methods can successfully increase the resolution, all methods share significant differences with standard imaging methods, making the usual measures of resolution inapplicable. In particular image quality and information content are spatially heterogeneous with variabilities that can be comparable to their mean values, limiting the use of the average resolution as a predictor for local information. A common use of super-resolution data is to test or establish structural models, and in these cases it would be valuable to assess the capacity of the data to validate a model. We focus here on single-molecule localization methods and present a new way of assessing the quality and reliability of super-resolution data.

Published
2015

12. The crucial role of bioimage analysts in scientific research and publication

Author

Cimini, Beth A., Bankhead, Peter, D'Antuono, Rocco, Fazeli, Elnaz, Fernandez-Rodriguez, Julia, Fuster-Barceló, Caterina, Haase, Robert, Jambor, Helena Klara, Jones, Martin L., Jug, Florian, Klemm, Anna H., Kreshuk, Anna, Marcotti, Stefania, Martins, Gabriel G., Mcardle, Sara, Miura, Kota, Muñoz-Barrutia, Arrate, Murphy, Laura C., Nelson, Michael S., Nørrelykke, Simon F., Paul-Gilloteaux, Perrine, Pengo, Thomas, Pylvänäinen, Joanna W., Pytowski, Lior, Ravera, Arianna, Reinke, Annika, Rekik, Yousr, Strambio-De-Castillia, Caterina, Thédié, Daniel, Uhlmann, Virginie, Umney, Oliver, Wiggins, Laura, Eliceiri, Kevin W., Cimini, Beth A., Bankhead, Peter, D'Antuono, Rocco, Fazeli, Elnaz, Fernandez-Rodriguez, Julia, Fuster-Barceló, Caterina, Haase, Robert, Jambor, Helena Klara, Jones, Martin L., Jug, Florian, Klemm, Anna H., Kreshuk, Anna, Marcotti, Stefania, Martins, Gabriel G., Mcardle, Sara, Miura, Kota, Muñoz-Barrutia, Arrate, Murphy, Laura C., Nelson, Michael S., Nørrelykke, Simon F., Paul-Gilloteaux, Perrine, Pengo, Thomas, Pylvänäinen, Joanna W., Pytowski, Lior, Ravera, Arianna, Reinke, Annika, Rekik, Yousr, Strambio-De-Castillia, Caterina, Thédié, Daniel, Uhlmann, Virginie, Umney, Oliver, Wiggins, Laura, and Eliceiri, Kevin W.

Abstract

Bioimage analysis (BIA), a crucial discipline in biological research, overcomes the limitations of subjective analysis in microscopy through the creation and application of quantitative and reproducible methods. The establishment of dedicated BIA support within academic institutions is vital to improving research quality and efficiency and can significantly advance scientific discovery. However, a lack of training resources, limited career paths and insufficient recognition of the contributions made by bioimage analysts prevent the full realization of this potential. This Perspective - the result of the recent The Company of Biologists Workshop 'Effectively Communicating Bioimage Analysis', which aimed to summarize the global BIA landscape, categorize obstacles and offer possible solutions - proposes strategies to bring about a cultural shift towards recognizing the value of BIA by standardizing tools, improving training and encouraging formal credit for contributions. We also advocate for increased funding, standardized practices and enhanced collaboration, and we conclude with a call to action for all stakeholders to join efforts in advancing BIA.

Published
2024
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13. Improved 3D Superresolution Localization Microscopy Using Adaptive Optics

Author

Piro, Nicolas, Pengo, Thomas, Olivier, Nicolas, and Manley, Suliana

Subjects
Physics - Optics, Physics - Biological Physics
Abstract

We demonstrate a new versatile method for 3D super-resolution microscopy by using a deformable mirror to shape the point spread function of our microscope in a continuous and controllable way. We apply this for 3D STORM imaging of microtubules., Comment: 9 pages, 3 figures

Published
2014

18. Publisher Correction: Reproducible brain-wide association studies require thousands of individuals

Author

Marek, Scott, Tervo-Clemmens, Brenden, Calabro, Finnegan J., Montez, David F., Kay, Benjamin P., Hatoum, Alexander S., Donohue, Meghan Rose, Foran, William, Miller, Ryland L., Hendrickson, Timothy J., Malone, Stephen M., Kandala, Sridhar, Feczko, Eric, Miranda-Dominguez, Oscar, Graham, Alice M., Earl, Eric A., Perrone, Anders J., Cordova, Michaela, Doyle, Olivia, Moore, Lucille A., Conan, Gregory M., Uriarte, Johnny, Snider, Kathy, Lynch, Benjamin J., Wilgenbusch, James C., Pengo, Thomas, Tam, Angela, Chen, Jianzhong, Newbold, Dillan J., Zheng, Annie, Seider, Nicole A., Van, Andrew N., Metoki, Athanasia, Chauvin, Roselyne J., Laumann, Timothy O., Greene, Deanna J., Petersen, Steven E., Garavan, Hugh, Thompson, Wesley K., Nichols, Thomas E., Yeo, B. T. Thomas, Barch, Deanna M., Luna, Beatriz, Fair, Damien A., and Dosenbach, Nico U. F.

Published
2022
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19. A biologist’s guide to planning and performing quantitative bioimaging experiments

Author

Senft, Rebecca A., primary, Diaz-Rohrer, Barbara, additional, Colarusso, Pina, additional, Swift, Lucy, additional, Jamali, Nasim, additional, Jambor, Helena, additional, Pengo, Thomas, additional, Brideau, Craig, additional, Llopis, Paula Montero, additional, Uhlmann, Virginie, additional, Kirk, Jason, additional, Gonzales, Kevin Andrew, additional, Bankhead, Peter, additional, Evans, Edward L., additional, Eliceiri, Kevin W., additional, and Cimini, Beth A., additional

Published
2023
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20. A biologist’s guide to planning and performing quantitative bioimaging experiments

Author

Senft, Rebecca a., Diaz-Rohrer, Barbara, Colarusso, Pina, Swift, Lucy, Jamali, Nasim, Jambor, Helena, Pengo, Thomas, Brideau, Craig, Llopis, Paula montero, Uhlmann, Virginie, Kirk, Jason, Gonzales, Kevin andrew, Bankhead, Peter, Evans, Edward l., Eliceiri, Kevin w., and Cimini, Beth a.

Abstract

Technological advancements in biology and microscopy have empowered a transition from bioimaging as an observational method to a quantitative one. However, as biologists are adopting quantitative bioimaging and these experiments become more complex, researchers need additional expertise to carry out this work in a rigorous and reproducible manner. This Essay provides a navigational guide for experimental biologists to aid understanding of quantitative bioimaging from sample preparation through to image acquisition, image analysis, and data interpretation. We discuss the interconnectedness of these steps, and for each, we provide general recommendations, key questions to consider, and links to high-quality open-access resources for further learning. This synthesis of information will empower biologists to plan and execute rigorous quantitative bioimaging experiments efficiently.

Published
2023
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21. Supplementaty data from Cytotoxic T Cells and Granzyme B Associated with Improved Colorectal Cancer Survival in a Prospective Cohort of Older Women

Author

Prizment, Anna E., primary, Vierkant, Robert A., primary, Smyrk, Thomas C., primary, Tillmans, Lori S., primary, Nelson, Heather H., primary, Lynch, Charles F., primary, Pengo, Thomas, primary, Thibodeau, Stephen N., primary, Church, Timothy R., primary, Cerhan, James R., primary, Anderson, Kristin E., primary, and Limburg, Paul J., primary

Published
2023
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22. Tissue-Like 3D Standard and Protocols for Microscope Quality Management

Author

Abrams, Benjamin, primary, Pengo, Thomas, additional, Wee, Tse-Luen, additional, Deagle, Rebecca C, additional, Vuillemin, Nelly, additional, Callahan, Linda M, additional, Smith, Megan A, additional, Kubow, Kristopher E, additional, Girard, Anne-Marie, additional, Rappoport, Joshua Z, additional, Bayles, Carol J, additional, Cameron, Lisa A, additional, Cole, Richard, additional, and Brown, Claire M, additional

Published
2023
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23. A biologist's guide to the field of quantitative bioimaging

Author

Senft, Rebecca A., Diaz-Rohrer, Barbara, Colarusso, Pina, Swift, Lucy, Jamali, Nasim, Jambor, Helena, Pengo, Thomas, Brideau, Craig, Llopis, Paula Montero, Uhlmann, Virginie, Kirk, Jason, Gonzales, Kevin Andrew, Bankhead, Peter, Evans, Edward L III, Eliceiri, Kevin W, and Cimini, Beth A

Abstract

Technological advancements in biology and microscopy have empowered a transition from bioimaging as an observational method to a quantitative one. However, as biologists are adopting quantitative bioimaging and these experiments become more complex, researchers need additional expertise to carry out this work in a rigorous and reproducible manner. Here we provide a navigational guide for experimental biologists to understand quantitative bioimaging from sample preparation through image acquisition, image analysis, and data interpretation. We discuss the interconnectedness of these steps, and for each, we provide general recommendations, key questions to consider, and links to high-quality open access resources for further learning. This synthesis of information will empower biologists to plan and execute rigorous quantitative bioimaging experiments efficiently., Funding was provided by the National Institutes of Health (NIH COBA P41 GM135019 to BAC and KWE). This project has been made possible in part by grant number 2020-225720 to BAC from the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation. VU is supported by EMBL internal funding. ELE is supported by a Morgridge Postdoctoral Fellowship.

Published
2022
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24. Motion Impact Score for Detecting Spurious Brain-Behavior Associations

Author

Kay, Benjamin P., primary, Montez, David F., additional, Marek, Scott, additional, Tervo-Clemmens, Brenden, additional, Siegel, Joshua S., additional, Adeyemo, Babatunde, additional, Laumann, Timothy O., additional, Metoki, Athanasia, additional, Chauvin, Roselyne J., additional, Van, Andrew N., additional, Krimmel, Samuel R., additional, Miller, Ryland L., additional, Newbold, Dillan J., additional, Zheng, Annie, additional, Seider, Nicole A., additional, Scheidter, Kristen M., additional, Monk, Julia, additional, Feczko, Eric, additional, Randolph, Anita, additional, Miranda-Dominguez, Oscar, additional, Moore, Lucille A., additional, Perrone, Anders J., additional, Conan, Gregory M., additional, Earl, Eric A., additional, Malone, Stephen M., additional, Cordova, Michaela, additional, Doyle, Olivia, additional, Lynch, Benjamin J., additional, Wilgenbusch, James C., additional, Pengo, Thomas, additional, Graham, Alice M., additional, Roland, Jarod L., additional, Gordon, Evan M., additional, Snyder, Abraham Z., additional, Barch, Deanna M., additional, Fair, Damien A., additional, and Dosenbach, Nico U.F., additional

Published
2022
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28. Publisher Correction: Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software

Author

Sage, Daniel, Pham, Thanh-An, Babcock, Hazen, Lukes, Tomas, Pengo, Thomas, Chao, Jerry, Velmurugan, Ramraj, Herbert, Alex, Agrawal, Anurag, Colabrese, Silvia, Wheeler, Ann, Archetti, Anna, Rieger, Bernd, Ober, Raimund, Hagen, Guy M., Sibarita, Jean-Baptiste, Ries, Jonas, Henriques, Ricardo, Unser, Michael, and Holden, Seamus

Published
2019
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29. Tissue-Like 3D Standard and Protocols for Microscope Quality Management

Author

Abrams, Benjamin, primary, Pengo, Thomas, additional, Wee, Tse-Luen, additional, Deagle, Rebecca C., additional, Vuillemin, Nelly, additional, Callahan, Linda M., additional, Smith, Megan A., additional, Kubow, Kristopher E., additional, Girard, Anne-Marie, additional, Rappoport, Joshua Z., additional, Bayles, Carol J., additional, Cameron, Lisa A., additional, Cole, Richard, additional, and Brown, Claire M., additional

Published
2022
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33. ssDNA nanotubes for selective targeting of glioblastoma and delivery of doxorubicin for enhanced survival

Author

Harris, Michael A., primary, Kuang, Huihui, additional, Schneiderman, Zachary, additional, Shiao, Maple L., additional, Crane, Andrew T., additional, Chrostek, Matthew R., additional, Tăbăran, Alexandru-Flaviu, additional, Pengo, Thomas, additional, Liaw, Kevin, additional, Xu, Beibei, additional, Lin, Lucy, additional, Chen, Clark C., additional, O’Sullivan, M. Gerard, additional, Kannan, Rangaramanujam M., additional, Low, Walter C., additional, and Kokkoli, Efrosini, additional

Published
2021
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37. Abstract 3085: Steroid receptor co-activators regulate metabolic kinases to drive therapy resistant ER+ breast cancer

Author

Truong, Thu Ha, primary, Benner, Elizabeth, additional, Hagen, Kyla M., additional, Temiz, Nuri A., additional, Kerkvliet, Carlos Perez, additional, Wang, Ying, additional, Cortes-Sanchez, Emilio, additional, Yang, Chieh-Hsiang, additional, Pengo, Thomas, additional, Guillen, Katrin P., additional, Welm, Bryan E., additional, Telang, Sucheta, additional, Lange, Carol A., additional, and Ostrander, Julie H., additional

Published
2021
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38. MethodsJ2: A Software Tool to Improve Microscopy Methods Reporting

Author

Ryan, Joel, primary, Pengo, Thomas, additional, Rigano, Alex, additional, Llopis, Paula Montero, additional, Itano, Michelle S., additional, Cameron, Lisa, additional, Marqués, Guillermo, additional, Strambio-De-Castillia, Caterina, additional, Sanders, Mark A., additional, and Brown, Claire M., additional

Published
2021
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39. ABRF Light Microscopy Research Group Study 3: The Development and Implementation of New Tools for Microscope Quality Assurance Testing

Author

Abrams, Ben, Brown, Claire, Callahan, Linda, Cole, Richard, Pengo, Thomas, and Wee, Tse-Luen

Subjects
Session Abstracts
Abstract

The goal of this study was to create a 3D biologically-relevant standard test sample and imaging protocol which would allow a microscopist to evaluate the performance of their imaging system as a function of imaging depth in the following areas: (1) system resolution and point spread function quality in 3D, (2) reliability of intensity quantification, and (3) image signal-to-noise. We developed two test samples that each consist of a mixture of fluorescence microspheres embedded in a 100µm-thick layer of CyGel, a thermo-reversible 3D cell growth media with refractive index of 1.37. We will present a summary of our methodology and quantitative analysis of approximately 140 laser scanning confocal datasets collected from over 50 participants across 15 countries and including instruments from four major microscope manufacturers. The results show some interesting and unexpected trends and provide tools and benchmarks that investigators can use to evaluate systems at their own institutions.

Published
2020

41. Steroid Receptor Co-Activators Regulate Metabolic Kinases to Drive Therapy Resistant ER+ Breast Cancer

Author

Truong, Thu Ha, primary, Benner, Elizabeth A, additional, Hagen, Kyla M, additional, Temiz, Nuri A, additional, Kerkvliet, Carlos Perez, additional, Wang, Ying, additional, Cortes-Sanchez, Emilio, additional, Yang, Chieh-Hsiang, additional, Pengo, Thomas, additional, Guillen, Katrin P, additional, Welm, Bryan E, additional, Telang, Sucheta, additional, Lange, Carol A, additional, and Ostrander, Julie Hanson, additional

Published
2021
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42. Associations between tissue‐based CD3+ T‐lymphocyte count and colorectal cancer survival in a prospective cohort of older women

Author

Oyenuga, Mosunmoluwa, primary, Vierkant, Robert A., additional, Lynch, Charles F., additional, Pengo, Thomas, additional, Tillmans, Lori S., additional, Cerhan, James R., additional, Church, Timothy R., additional, Lazovich, DeAnn, additional, Anderson, Kristin E., additional, Limburg, Paul J., additional, and Prizment, Anna E., additional

Published
2020
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45. PELP1/SRC-3-dependent regulation of metabolic kinases drives therapy resistant ER+ breast cancer

Author

Truong, Thu H., primary, Benner, Elizabeth A., additional, Hagen, Kyla M., additional, Temiz, Nuri A., additional, Kerkvliet, Carlos Perez, additional, Wang, Ying, additional, Cortes-Sanchez, Emilio, additional, Yang, Chieh-Hsiang, additional, Pengo, Thomas, additional, Guillen, Katrin P., additional, Welm, Bryan E., additional, Telang, Sucheta, additional, Lange, Carol A., additional, and Ostrander, Julie H., additional

Published
2020
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49. Imaging in Developmental Biology: An Essential Tool with No Instructions

Author

Marques, Guillermo, Pengo, Thomas, and Sanders, Mark A.

Subjects
Poster Abstracts
Abstract

Imaging is a fundamental tool in biomedical disciplines. A critical aspect in the acquisition and evaluation of imaging data is a detailed and accurate description of the technology used in the literature. In our work at a major imaging core, we are often met with the situation in which the experiments our clients want to recreate are poorly described, making analysis and replication of the published literature difficult. In order to evaluate the extent and severity of this problem, we have analyzed Developmental Biology publications. Research articles in three leading journals were analyzed for the importance of imaging (fraction of figure panels that contained original images) and compared with the detail given to the experimental specifics of image acquisition (fraction of the materials and methods section devoted to image acquisition and analysis). Finally, the quality of the imaging information given was evaluated for its completeness with a simple pass/fail grade. Results indicate that imaging is an essential tool in Developmental Biology, with over 80% of the figures being images, largely microscopy. However, less than 5% of the text in the methods section of the analyzed articles is devoted to experimental details of image acquisition and analysis (on average 57 words). Furthermore, the overall quality of the information provided is dismal, with a large majority of publications obtaining a failing grade (83%), and many examples containing no usable information (10%). The lack of information on the imaging methodologies used in published articles makes it impossible to accurately replicate the reported data. This is a serious problem that requires immediate attention. Imaging shared resources have a key role to play in ensuring accurate reporting of critical imaging parameters. This role includes providing off the shelf descriptions for the methods section of manuscripts and client education on the importance of reporting that information.

Published
2019

50. Registration of the extracellular matrix components constituting the fibroblastic focus in idiopathic pulmonary fibrosis

Author

Herrera, Jeremy, Forster, Colleen, Pengo, Thomas, Montero, Angeles, Swift, Joe, Schwartz, Martin A., Henke, Craig A., and Bitterman, Peter B.

Subjects
respiratory tract diseases, Research Article
Abstract

The extracellular matrix (ECM) in idiopathic pulmonary fibrosis (IPF) drives fibrosis progression; however, the ECM composition of the fibroblastic focus (the hallmark lesion in IPF) and adjacent regions remains incompletely defined. Herein, we serially sectioned IPF lung specimens constructed into tissue microarrays and immunostained for ECM components reported to be deregulated in IPF. Immunostained sections were imaged, anatomically aligned, and 3D reconstructed. The myofibroblast core of the fibroblastic focus (defined by collagen I, α-smooth muscle actin, and procollagen I immunoreactivity) was associated with collagens III, IV, V, and VI; fibronectin; hyaluronan; and versican immunoreactivity. Hyaluronan immunoreactivity was also present at the fibroblastic focus perimeter and at sites where early lesions appear to be forming. Fibrinogen immunoreactivity was often observed at regions of damaged epithelium lining the airspace and the perimeter of the myofibroblast core but was absent from the myofibroblast core itself. The ECM components of the fibroblastic focus were distributed in a characteristic and reproducible manner in multiple patients. This information can inform the development of high-fidelity model systems to dissect mechanisms by which the IPF ECM drives fibrosis progression.

Published
2019
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