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2. Examining the role of common variants in rare neurodevelopmental conditions

Author

Huang, Qin Qin, Wigdor, Emilie M., Malawsky, Daniel S., Campbell, Patrick, Samocha, Kaitlin E., Chundru, V. Kartik, Danecek, Petr, Lindsay, Sarah, Marchant, Thomas, Koko, Mahmoud, Amanat, Sana, Bonfanti, Davide, Sheridan, Eamonn, Radford, Elizabeth J., Barrett, Jeffrey C., Wright, Caroline F., Firth, Helen V., Warrier, Varun, Strudwick Young, Alexander, Hurles, Matthew E., and Martin, Hilary C.

Published
2024
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5. Impacts of the COVID-19 economic slowdown on soybean crop yields in the United States.

Author

Tong, Daniel, Campbell, Patrick, Ma, Siqi, and Christopoulos, Julianna

Subjects
United States, Humans, Air Pollutants, Particulate Matter, Soybeans, Ozone, Pandemics, COVID-19, Air Pollution, Environmental Monitoring
Abstract

It is without question that the COVID-19 pandemic has taken its toll on the U.S. economy. Stay-at-home orders led to reduced vehicular traffic and widespread declines in anthropogenic emissions (e.g., nitrogen oxides (NOx)). This study is the first to explore the potential consequences of O3 changes resulting from the economic shutdown in the United States on soybean crop yields for 2020. The pandemics impact on surface O3 is quantified using the NOAAs National Air Quality Forecasting Capability (NAQFC), which is based on the Community Multi-Scale Air Quality (CMAQ) model for May-July 2020. The would-be, 2020 level business-as-usual (BAU) emissions are compared to a simulation that uses representative COVID-19 (C19) emissions. For each emissions scenario, crop exposures are calculated using the AOT40 cumulative exposure index and then combined with county-level soybean production totals to determine regional yield losses. Exposure changes ranged between - 2 and 2 ppmVhr-1. It was further shown that increased exposures (0.5 to 1.10 ppmVhr-1) in the Southeast U.S. counteracted decreased exposures (0.8 to 0.5 ppmVhr-1) in the other soybean-producing regions. As a result, corresponding yield improvements counteracted yield losses around the Mississippi River Valley and allowed for minimal improvements in soybean production loss totaling $6.5 million over CONUS.

Published
2023

7. Machine Learning for Deferral of Care Prediction

Author

Ahmad, Muhammad Aurangzeb, Ahmed, Raafia, Overman, Steve, Campbell, Patrick, Stroum, Corinne, and Karunakaran, Bipin

Subjects
Computer Science - Computers and Society
Abstract

Care deferral is the phenomenon where patients defer or are unable to receive healthcare services, such as seeing doctors, medications or planned surgery. Care deferral can be the result of patient decisions, service availability, service limitations, or restrictions due to cost. Continual care deferral in populations may lead to a decline in population health and compound health issues leading to higher social and financial costs in the long term. Consequently, identification of patients who may be at risk of deferring care is important towards improving population health and reducing care total costs. Additionally, minority and vulnerable populations are at a greater risk of care deferral due to socioeconomic factors. In this paper, we (a) address the problem of predicting care deferral for well-care visits; (b) observe that social determinants of health are relevant explanatory factors towards predicting care deferral, and (c) compute how fair the models are with respect to demographics, socioeconomic factors and selected comorbidities. Many health systems currently use rules-based techniques to retroactively identify patients who previously deferred care. The objective of this model is to identify patients at risk of deferring care and allow the health system to prevent care deferrals through direct outreach or social determinant mediation.

Published
2022

10. Kickin' it offshore

Author

Campbell, Patrick, Brennan, Rebekah, and McQueen, Erica

Published
2014

11. Who is Nation?

Author

Brennan, Rebekah and Campbell, Patrick

Published
2014

13. An ISHLT consensus statement on strategies to prevent and manage hemocompatibility related adverse events in patients with a durable, continuous-flow ventricular assist device

Author

Hollis, Ian B., Jennings, Douglas L., Krim, Selim, Ton, Van-Khue, Ducharme, Anique, Cowger, Jennifer, Looby, Mary, Eulert-Green, J.J., Bansal, Neha, Horn, Ed, Byku, Mirnela, Katz, Jason, Michaud, C.J., Rajapreyar, Indranee, Campbell, Patrick, Vale, Cassandra, Cosgrove, Richard, Hernandez-Montfort, Jaime, Otero, Jessica, Ingemi, Amanda, Raj, Shashi, Weeks, Phillip, Agarwal, Richa, Martinez, Elena S., Tops, Laurens F., Ahmed, Mustafa M., Kiskaddon, Amy, Kremer, Jamila, Keebler, Mary, and Ratnagiri, Ravi K.

Published
2024
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22. Extracorporeal Life Support Organization Registry International Report 2022: 100,000 Survivors

Author

Tonna, Joseph E., Boonstra, Philip S., MacLaren, Graeme, Paden, Matthew, Brodie, Daniel, Anders, Marc, Hoskote, Aparna, Ramanathan, Kollengode, Hyslop, Rob, Fanning, Jeffrey J., Rycus, Peter, Stead, Christine, Barrett, Nicholas A., Mueller, Thomas, Gómez, Rene D., Malhotra Kapoor, Poonam, Fraser, John F., Bartlett, Robert H., Alexander, Peta M.A., Barbaro, Ryan P., Abbasi, Adeel, Said Abdalmohsen, Ahmad, Abdelbary, Akram M., Abecasis, Francisco, Abel, Peter, Abu-Omar, Yasir, Adams, Douglas R, Manuel Africano, Juan, Aganga, Devon, Agati, Salvatore, Agerstrand, Cara, Aguillon, Mario V., Akers, Crystal S., Akhtarekhavari, Julia, Alazzam, Mohammad Izzat Salah, Albert, Martin, Alberti, Angela, Al-Fares, Abdulrahman A., Alfoudri, Huda, Allaert, Silvie, Allbert, Keesha N., Allen, Christopher T., Lescano Alva, Miguel Ángel, Alwardt, Cory M., Amigoni, Angela, Anandamurthy, Balaram, Anastasiadis, Kyriakos, Anders, Nicholas R., Anderson, Scott A., Anderson, Patricia L., Andrijević, Ana, Annoni, Alice, Anselmi, Michael, Anstey, James R., Antonini, Marta V., Antonitsis, Polychronis, Stein Araujo, Tays, Arcalas, Rhodney, Areinamo, Igor, Martin Arias, Anibal, Armijo-Garcia, Veronica, Aronsky, Vladimir, Arora, Lovkesh, Arora, Madhur, Leigh Aspenleiter, Marit, Atik, Fernando A., AugustGeorg Auzinger, Erin Colleen, Azzam, Ismail, Bacchetta, Matthew, Bak, Erica I., Balcells, Joan, Sánchez Ballesteros, Jesús, Banjac, Igor S., Barbaria, Jacqueline M., Barrigoto, Cleide L., Bass, Stephanie D., Batranović, Uroš, Bauer, Matthew H., Fernando Bautista, Diego, Beck, Robert M., Giraldo Bejarano, Estefania, Belohlavek, Jan, Bembea, Melania M., Benes, Jan, Benharash, Peyman, Benish, Lynne A., Bennett, Suzanne, Bento, Luís F.N., Bermudez, Christian A., Bertini, Pietro, Best, Derek, Bharat, Ankit, Bhutta, Omar J., Bizzell, Samantha J., Blakeman, Stephanie A., Blanco-Schweizer, Pablo, Blanton, Jessica K., Blood, Peggy S., Bohlmann, Allison S., Kyle Bohman, John, Bombino, Michela, Kathleen Bonadonna, Desiree, Bond, Ashley, Borgmann, Kristina M., Bourgoin, Pierre, Boville, Brian M., Boza, Raquel, Brady, Heather L., Brady, Alison, Braunlich, Jessica M., Bridges, Brian C., Brinkley, Karen K., Brookshire, Robert S., Brozzi Nicole Brueggemann, Nicolas A., Buckley, Dwight P., Jr., Buckley, Klayton, Budhani, Irfan B., Bukamal, Nazar, Burgos, Lucrecia M, Burša, Filip, Busby, Landon K., Buscher, Hergen, Butler, Menoly, Butt, Warwick W., Byrnes, Jonathan W., Calaritis, Christos, Caldwell, Lisa R., Calligaro, Gregory L., Campbell, Patrick T., Camporota, Luigi, Fernando Caneo, Luiz, Jovo Carapic, Vladimir, Carrasco-Carrasco, Cristina, Ivan Carrizo, Nestor, Carrow, Heidi, Carton, Edmund G., Casabella, Christian, Gomez Casal, Vanesa, Casey, Francis L., III, Castillo, Andres, Castleberry, Anthony W., Alexandros Cavayas, Yiorgos, Cerqua, Karey, Ming Chan, Kai Man ChanWai, Brian Chapman, Jason, Brahma Chari, Hari, Cheifetz, Omair ChaudharyIra M., Chen, Robin H.S, Chen, Weiting, Cheung, Eva W., Cheung, Anson, Chico, Juan I., Chiletti, Roberto, Jin Cho, Hwa, Cholette, Jill M., Christensen, Steffen, Chui, Betty S., Circelli, Alessandro, Clement, Katherine C., Cleuziou, Julie, Clouse, Brian, Cole, Gwendolen, Coles, Garrett M., Collins, Monika F., Collins, Monika F., Connelly, James, Conrad, Steven A., Cook, Marlene, Copeland, Hannah, Copus, Scott C., Cox, Charles S., Jr, Craig, Lynne K., Crain, Natasha, Cremonese, Ricardo V., Criswell, Emily A., Cross, Lisa M., Crowley, Moira A., Crowley, Jerome C., Cruz, Leonora, Cypel, Marcelo, Czarnik, Tomasz, Czuczwa, Miroslaw E., Sica da Rocha, Taís, Daddow, Samuel, Dali, Dante C., Dalton, Heidi J., Daly, Kathleen J.R., Damuth, Emily, Daniel, Dennis A., Daniel IV, John M., Daniel, Josiane M., Danis, Max D., Danko, Melissa E., Rodrigues Dantas, Joao Alberto, Daoust, Isabelle, Dauwe, Dieter F., Davidson, Mark, Davis, Joel C., Davis, Mitchell, D’Cunha, Jonathan, de Arruda Bravim, Bruno, de BoodeKim T. De La Cruz, Willem P., Gray DeAngelis, Kathryn, Debeuckelaere, Gerdy, Deitemyer, Matthew A., DellaVolpe, Jeffrey, Deneau, Jamie L., DeNino, Walter F., Denmark, Christopher G., Denney, Derek, DeValeria, Patrick A., Dewulf, Petra, Di Nardo, Matteo, DiBardino, Daniel J., DiMartino, Joseph, Dimopoulos, Stavros, Domico, Michele B., Dominy, Meaghan E., Donker, Dirk W., Dresbach, Till, Droogh, Joep M., Dunlap, Tiffany W., Dupon, Allsion, Durham, Lucian A., III, Durward, Andrew, Dvorak, Anna, Dyett, John F., Dziedzina, Carol L., Eaken, Carmen L., Eaton, Jonathan S., Eberle, Christopher J., Edwards, Linda, Efseviou, Christakis, Eigner, Juliann M., Ahmed Elhamrawi, Hazem, Elhazmi, Alyaa M., Elizondo, Tammy, Ellersick, Beverly L., Emling, Jonathan A., Ernst, Andreas, Pablo Escalante, Juan, Espinoza, Otoniel, Evey, Lee W., Fan, Eddy, Fang, Gary, Faulkner, Gail M., Fauman, Karen R, Ferguson, Niall, Ferreira, Benigno, Fiane, Arnt E., Andrade Fierro, Dario, Martha Filippi, María, Findeisen, Michael C., Finlay, Katie, Finlayson, Gordon, Fischer, Gwenyth A., Fischer, Courtney D., Fischer, William J., III, Fisher, Caleb M., Fitriasari, Reni, Fitzgerald, Jillian, Fix, Melissa K., Fleming, Sarah B., Flynn, Brigid C., Forst, Beth A., Fortuna, Philip P., Foti, Giuseppe, Fox, Matthew P., Franco, Thais O., David Freeland, C., Fried, Justin A., Friedman, Matthew L., Furlanetto, Beatriz, Fux, Thomas, Gaião, Sérgio, Gale, Michael J., Garcia, Joann Kathleen G., Garcia-Montilla, Romel, Gardner, Eric R., Garg, Meena, Garrison, Lawrence L., Gavrilovic, Srdjan M., Gawda, Ryszard, Geer, Laura W., Gelandt, Elton A., Gelvin, Michael G., Genovese, Bradley M., George, Jeffrey A., George, Timothy J, George, Sangley, Ghimire, Anup, Giani, Marco, Gill, Baljit S., Glikes, Erin, Golecki, Michael, Gongora, Enrique, Govener, Sara, Graf, Amanda, Grasselli, Giacomo, Gray, Brian W., Greenlee, Joseph A., III, Gregoric, Igor D., Gregory, Melinda, Grins, Edgars, Volker Groesdonk, Heinrich, Group, Kimberly F., Guarracino, Fabio, Joy Guidi-Solloway, Alexandra, Gunn, Tyler M., Guru, Pramod K, Haddle, John C., Haft, Jonathan W., Haisz, Emma, Hall, Julie L., Hall, Cameron, Hamaguchi, Jun, Hammond, Terese C., Han, Peggy K., Hardison, Daphne C., Harischandra, Dickwelle T., Hart, Shaun M., Harting, Matthew T., Hartley, Louise, Harvey, Chris J., Hasan, Zubair, Fawzy Hassan, Ibrahim, Hastings, Jennifer R., Hatcher, Renee’, Hatton, Kevin W., Haught, Christopher K., Awori Hayanga, Jeremiah, Peter Haydon, Timothy, Healy, Aaron H., Heard, Micheal L., Heather, Beth M., Hendrix, Rik H.J., Hennig, Felix, Hermens, Greet HermansJeannine A.J., Hernandez, Deborah A., Hernandez-Montfort, Jaime, Herrera, Guillermo, Hickman, Keri, Hittel, Ashley, Hobbs, Crystal, Hoffman, Jordan R.H., Hollinger, Laura E., Homishak, Michael, Horigoshi, Nelson K., Hoshino, Kota, Huang, Shu-Chien, Huenges, Katharina, Hussey, Alexander D., Hyslop, Robert W., Ihle, Rayan E., Ingemansson, Ola, Ivulich, Daniel, Jackson, Amanda L., Garcia Jacques, Rogelio, Jain, Harsh, Jakobs, Sharon M., Jan, Robert, Janowiak, Lisa M., Jara, Claire B., Jarden, Angela M., Jarzembowski, Jamie L., Jaudon, Andrew, Kishore Jayanthi, Venkata Krishna, Jennings, Joseph A., Jeong, Inseok, Meza Jiménez, Rafael, Jimenez-Rodriguez, Gian M., Joachim, Sabrina, Joelsons, Daniel, Johnson, Caroline A., Johnson, Andrea L., Jones, Jeffry H., Joseph, Mark, Joseph, Sunimol, Joshi, Raja, Joyce, Christopher J., Seung Jung, Jae, Carone Junior, José, Kallas, Harry J., KamerkarPilje Kang, Asavari, Kar, Biswajit, Karapanagiotidis, Georgios T., Kattan, Javier, Kaufman, David A., Kawauchi, Akira, Keene, Sarah D., Keller, Norma M., Keller, Roberta, Kelley, Emily W., Kelley, Kellie, Kelly-Geyer, Janet F., Kenderessy, Peter, Kenny, Laura E., Keshavjee, Shaf, Kessel, D., Kessler, Heather, Keuler, Suzanne, Khicha, Sanjay, Wan Kim, Do, Kim, Richard Y., Maxwell Kime, Aaron, Kincade, Robert C., Kipfmueller, Florian, Kirk, Douglas A., Klein, Liviu, Knapp, Randall S., Knapp, Randall S., Kneyber, Martin C.J., Knowles, Andrea L., Koch, Jillian M., Koepke, Stephanie, Kogelmann, Klaus M., Elzo Kraemer, Carlos, Krauklis, Amanda, Krumroy, Samantha L., Kumar, Madhan, Kumar, Arun, Kumpf, Matthias E, Kyle, Kimberly, Laffin, Anna, Kees Lagrand, Wim, Lahiji, Parshawn A., Keung Lai, Peter Chi, Ka Lai, Cally Ho, Danielle Laird, Amanda, Landsberg, Michelle LaMarreDavid M., Lanmueller, Pia, Oude Lansink-Hartgring, Annemieke, Beth Larson, Sharon, Laufenberg, De’Ann M., Lavana, Jayshree, Layne, Tracie L., John Lazar, Michael, Ledoux, Matthew R., Lee, Raymond C., Leek, Thomas M., Lequier, Laurance, Lesbekov, Timur, Leslie, Robert, Anne Leung, Kit Hung, Lillie, Jon, Phang Lim, Yeong, Lim, Sang-Hyun, Lin, Ling, Lindsey, Thomas, Ho Ling, Steven Kin, Lingle, Kaitlyn J., Lipes, Jed, Liu, Songqiao, Llevadias, Judit, Lomas, Erin A., Longenecker, Robert D., Lorusso, Roberto, Ann Low, Tracy, Steven Lubinsky, Anthony, Lucas, Matthias LubnowMark T., Lucchini, Alberto, Luze, Lisa E., Lynch, William R., Manoj, M.C., Maas, Jacinta J., MacNamara, Vanessa, Madden, Jesse L., Maimone, Justin, Malhotra, Rajiv, Malone, Matthew P., Mangukia, Chirantan, Manzur-Sandoval, Daniel, Maráczi, Veronika, Marinaro, Jonathan L., Marinucci, Christina R., Marshall, Tammy, Martin, Mark, Marwali, Eva M., Maslach-Hubbard, Anna, Matijašević, Jovan, Mattke, Adrian, Mattucci, Joseph, Maul, Timothy M., Maybauer, Marc O., Mayette, Michael, Mayville, Joni R., McAllister, Catherine, McBride, Martha W., Scott McCaul, David, McClelland, Samantha L.S., Gregory McCloskey, Colin, McGregor, Randy, McKamie, Wesley A., McKee, Andrew D., McMahon, Chelsea M., McMullin, Kaye, McNicol, Jane, McNulty, John P., McRae, Thomas, Meade, Maureen E., Meersseman, Philippe, Mekeirele, Michael, Ito Mendes, Elisa, Menon, Anuradha P., Meyer, Jason P., Meyers, Jourdan E., Meyns, Bart, Mignone, John L., Miller, Brittany D., Miller, Malcolm G.A., Miller, Deborah, Mintak, Renee, Minter, Sarah M., Reis Miranda, Dinis, Mirza, Farrukh, Mishkin, Joseph D., Modelewski, Paul, Mohan, Rajeev C., Hui Mok, Yee, Money, Dustin, Monteagudo, Julie, Moores, Russell R., Jr., Moran, Patrick, Morelock, Shawn, Moreno, Marsha R., Blanco Morillo, Juan, Morrison, Tracy, Morton, John M., Morton, Brenda, Moscatelli, Andrea, Mosier, Jarrod M., Muellenbach, Ralf M., Mueller, Andreas, Mueller, Dale, Musca, Steven C., Nagpal, Dave, Najaf, Tasnim, Narasimhan, Mangala, Nater, Melissa, Natividad, Zynthia, Nedeljkov, Djordje, Nelson, Bryan D., Newman, Sally F., Newton, Debra E., Neyman, Jonathan L., George Ng, Wing Yiu, Nicholson, Meghan C., Nicolaas, Christine, Nix, Charlie, Nkwantabisa, Raymond, Nolan, Shirley, Norese, Mariano, Norton, Bridget M., Norton, Bridget M., O’Brien, Serena G., O’Callaghan, Maura, Oishi, Peter, O’Leary, Tony D., Olia, Salim E., O’Meara, Carlisle, Oppel, Emily E., Arias Ortiz, Julian, Oza, Pranay L., Ozment, Caroline P., Pacific, Marjorie, Pálizas, Fernando, Palmer, David, Paoletti, Luca, Pardo, Diego H., Paredes, Pablo, Patel, Thomas PasgaardMrunal G., Patel, Sandeep M., Patel, Vijay S., Patel, Brijesh V., PatelDrisya Paul, Sameer, Pawale, Amit A., Pearson, Nicole M., Renee Pearson, Crystal, Peek, Giles J., Pellecchia, Crescens M., Pellegrino, Vincent, Peperstraete, Harlinde, Perkins, Rebecca L., Perkins, Brandon, Peterec, Steven, Peterman, Claire, Phillips, Cooper W., Piekutowski, Richard R., Pilan, María L., Luisa Pilan, Maria, Mark Pincus, Jason, Pino, Melissa, Plambeck, Robert W., Plisco, Michael S., Plumley, Donald A., Plunkett, Mark D., Poffo, Robinson, Poh, Pei-Fen, Polito, Angelo, Pollema, Travis L, Pozzi, Matteo, Pozzi, Matteo, Pranikoff, Thomas, Prekker, Matthew E., Prossen, Erik F., Puligandla, Pramod S., Puslecki, Mateusz, Raheel Qureshi, Muhammad, Emilia Rabanal, Lily, Abdulhamid Rabie, Ahmed, Rackley, Craig R., Radovancevic, Rajko, Raes, Matthias, Allen Raff, Lauren Desiree, Rahban, Youssef, Raimer, Patricia L., Rajbanshi, Bijoy G., Ramanan, Raj, Rambaud, Jerome, Ramírez-Arce, Jorge A., Simões Ramos, Ana Carolina, Rao, Suresh G., Rector, Raymond, Redfors, Bengt, Regmi, Ashim, Alejandro Rey, Jose, Miguel Ribeiro, Joao, Richards, Chelsea E, Joan Richardson, C., Riddle, Christy C., Riera, Jordi, Ripardo, Marina, Rivas, Fernando M., Roan, Ronald M., Robertson, Elizabeth, Robinson, Megan, Röder, Daniel, Rodrigus, Inez E.R., Paul Roeleveld, Peter, Romano, Jennifer C., Rona, Roberto, Ann Rosenberg, Carol, Rosenow, Felix, Rowe, Robert J., Rower, Katy E., Rudolph, Kristina L., Fernando Rueda, Luis, Ruf, Bettina, Russell, Hyde M., Russell, Nichole, Ryan, Kathleen, Saberi, Asif A., Said, Ahmed S., Sailor, Caitlin, Sakal, Angela, Lujan Salas, Gisela, Salazar, Leonardo, Saleem, Kashif, Samoukovic, Gordan, Sanchez, Pablo G., Marie Santiago, Lian, Sargin, Murat, Miguel Sassine, Assad, Satou, Nancy L., Saunders, Paul C., Schachinger, Scott, Schaible, Thomas, Schellongowski, Peter, Schlager, Gerald W., Schmid, Christof, Schmitt, Joachim, Schnell, LeeAndra, Schnur, Janos, Schroeder, Lukas, Schubach, Scott, Schuetz, Michael T., Schwartz, Gary S., Schwarz, Patricia, Scriven, Nicole M., Seabrook, Ruth B., Seefeldt, Cassandra, Seelhammer, Troy G., Segura-Matute, Susana, Sen, Ayan, Adrian Seoane, Leonardo, Shaffer, Jamie, Shafi, Bilal M., Shambley, Shannon, Shankar, Shyam, Shapland, Amanda, Sharng, Yih, Shavelle, David, Sheldrake, Jayne, Mohan Shetty, Rajesh, Shiber, Joseph R., Shimzu, Naoki, Lou Short, Billie, Sichting, Kay A., Sidehamer, Keith E., Siebenaler, Teka, Silvestry, Scott C., Sinclair, Jennifer T, Sinclair, Andrew, Singh, Aalok R., Singh, Gurmeet, Skinner, Sean C., Smart, Alexandra, Smith, Reanna M., Smith, Adam, Smith, Karen, Sommer-Candelario, Sherri, Song, Seunghwan, Sorensen, Gro, Sousa, Eduardo, Sower, Christopher T., Spadea, Nicholas V, Spangle, April, Speicher, David G., Spieth, Peter M., Srivastava, Ankur, Srivastava, Neeraj, Stahl, Mark, Stallkamp, Eric D., Jr, Stanley, Vanessa J., Starr, Joanne P., Staudinger, Thomas, Stevens, Berkeley E., Stevens, Kimberly, Stocker, Christian, Strickland, Richard, Suarez, Erik E., Kumar Subramanian, Rakesh, Sudakevych, Serhii, Summerall, Charlene, Sundararajan, Santosh, Susupaus, Attapoom, Suzuki, Hiroyuki, Sweberg, Todd, Sydzyik, Troy, Anh Ta, Tuan, Tagliari, Luciana, Tanaka, Hiroyuki, Tanski, Christopher T., Tasset, Mark, Taylor, Donna M., Teman, Nicholas R., Ramesh Thangaraj, Paul, Thiagarajan, Ravi R., Thiruchelvam, Timothy, Thomas, James A., Thomas, Owain D., Thompson, Shaun L., Thomson, David A., Thukaram, Roopa, Todd, Mark L., Toeg, Hadi, Torres, Silvio F., Trautner, Simon, Trombino, Terry, Tuazon, Divina M., Tuel, Julie, Tukacs, Monika, Turner, April N., Tyree, Melissa M., Uchiyama, Prashant Vaijyanath, Makoto, van den Brule, Judith M.D., van Dyck, Marlice A., van Gijlswijk, Mascha, Van Meurs, Krisa P., VanDyck, Tyler J., Vardi, Amir, Vega, Alejandra, Ventetuolo, Corey E., Vera, Magdalena, Vercaemst, Leen, Vets, Philippe, Viamonte, Heather, Vidlund, Mårten, Vitali, Sally H., Vlaa, Alexander P.J., Vuylsteke, Alain, Loon Wan, Kah, Watkins, Reuben, Watson, Pia, Weast, Travis A., Weaver, Karen E., Welkovics, Norbert, Wellner, Heidi L., Wells, Jason C., Welter, Karen, Westpheling, Amber G., Whalen, Lesta D.S., Whebell, Stephen, Wiersema, Ubbo, Wiisanen, Matthew E., Eugene Wilcox, Bradley, Wille, Keith, Jan Will, Ellyne, Wilson, Brock J., Win, April M., Winearls, James R., Wise, Linda J., Witter, Tobias, Ruby Wong, Hoi Mei, Worku, Berhane, Wright, Tina M, Wu, James K., Yalon, Larissa A., Yantosh, Garrett, Yaranov, Dmitry M., Yee, Pat, Yi, Cassia, Yost, Christian C., Young, John, Younger, Katrina, Zaborowski, Steven, Zachmann, Brenda, Zainab, Asma, Zanai, Rosanna, Zhao, Ju, Zhou, Chengbin, and Zinger, Marcia

Published
2024
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23. Top Regulators Speak At The New York City Bar Association's Compliance Institute

Author

Campbell, Patrick

Subjects
United States. Securities and Exchange Commission -- Officials and employees, United States. Department of Justice -- Officials and employees, Regulatory compliance -- Laws, regulations and rules -- Conferences, meetings and seminars, Corporations -- Ethical aspects, Government regulation, Business, international, New York City Association of the Bar -- Conferences, meetings and seminars
Abstract

Key Takeaways On October 23, 2024, the New York City Bar Association hosted its third annual Compliance Institute with noteworthy keynote remarks from U.S. Securities and Exchange Commission (SEC) Commissioner [...]

Published
2024

24. FCC National Security And Law Enforcement Rules For Team Telecom Review Are Now Effective

Author

Campbell, Patrick S.

Subjects
United States. Federal Communications Commission -- Powers and duties, Telecommunications services industry -- Laws, regulations and rules, Communications industry -- Laws, regulations and rules, Government regulation, Telecommunications services industry, Business, international
Abstract

Recently the Federal Communications Commission (the 'Commission' or 'FCC') issued a Public Notice announcing that certain rules adopted in its September 2020 ' Executive Branch Review Order' and September 2021 [...]

Published
2024

27. Association between plasminogen activator inhibitor‐1 in young adulthood and nonalcoholic fatty liver disease in midlife: CARDIA

Author

Campbell, Patrick T, VanWagner, Lisa B, Colangelo, Laura A, Lewis, Cora E, Henkel, Anne, Ajmera, Veeral H, Lloyd‐Jones, Donald M, Vaughan, Douglas E, and Khan, Sadiya S

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Digestive Diseases, Clinical Research, Prevention, Chronic Liver Disease and Cirrhosis, Liver Disease, Adult, Cross-Sectional Studies, Female, Humans, Male, Non-alcoholic Fatty Liver Disease, Obesity, Plasminogen Activator Inhibitor 1, Risk Factors, Young Adult, computed tomography, hepatic, metabolic syndrome, obesity, steatosis, Gastroenterology & Hepatology, Clinical sciences
Abstract

BackgroundPrior studies have demonstrated a cross-sectional association between elevated plasminogen activator inhibitor-1 (PAI-1) levels and nonalcoholic fatty liver disease (NAFLD). However, there are no prospective longitudinal assessments of the association between PAI-1 and NAFLD. We aimed to describe the association between PAI-1 levels in early adulthood with NAFLD in midlife.MethodsAmong the 5115 participants in the coronary artery risk development in young adults (CARDIA) study, participants were randomly selected from a subset that was free of obesity, diabetes and hypertension at the 1992-1993 exam and attended the 2005-2006 exam (n = 996). A subset of participants (n = 896) also had CT liver fat measured (2010-2011). Participants with secondary causes of steatosis were excluded (n = 87). NAFLD was defined as liver attenuation ≤51 Hounsfield units. Logistic regression models assessed the association between PAI-1 and NAFLD.ResultsOf 809 participants, 53% were female, 37% black with a mean age of 32 years. Median PAI-1 level at 1st assessment (1992-1993) was 23.4 ng/mL among participants with NAFLD vs 11.9 ng/mL among those without NAFLD (P

Published
2020

30. CHRONIC CONDITIONS: Managing patients with HEART ARRHYTHMIA

Author

Campbell, Patrick

Subjects
Arrhythmia -- Care and treatment, Business, Economics, Health care industry
Abstract

Risk Factors for AF Deepak Bhatt, M.D., M.P.H.: AF is the most common arrhythmia in the United States and worldwide, with a prevalence that is growing. Why is the prevalence [...]

Published
2022

31. Performance Metrics for the Objective Assessment of Capacitive Deionization Systems

Author

Hawks, Steven A., Ramachandran, Ashwin, Porada, Slawomir, Campbell, Patrick G., Suss, Matthew E., Biesheuvel, P. M., Santiago, Juan G., and Stadermann, Michael

Subjects
Physics - Chemical Physics
Abstract

In the growing field of capacitive deionization (CDI), a number of performance metrics have emerged to describe the desalination process. Unfortunately, the separation conditions under which these metrics are measured are often not specified, resulting in optimal performance at minimal removal. Here we outline a system of performance metrics and reporting conditions that resolves this issue. Our proposed system is based on volumetric energy consumption (Wh/m$^3$) and throughput productivity (L/h/m$^2$) reported for a specific average concentration reduction, water recovery, and feed salinity. To facilitate and rationalize comparisons between devices, materials, and operation modes, we propose a nominal standard testing condition of removing 5 mM from a 20 mM NaCl feed solution at 50% water recovery for CDI research. Using this separation, we compare the desalination performance of a flow-through electrode (fte-CDI) cell and a flow between membrane (fb-MCDI) device, showing how significantly different systems can be compared in terms of generally desirable desalination characteristics. In general, we find that performance analysis must be considered carefully so to not allow for ambiguous separation conditions or the maximization of one metric at the expense of another. Additionally, for context we discuss a number of important underlying performance indicators and cell characteristics that are not performance measures in and of themselves but can be examined to better understand differences in performance.

Published
2018
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32. Capacitive Deionization

Author

Hawks, Steven A., primary, Oyarzun, Diego I., additional, Ramachandran, Ashwin, additional, Campbell, Patrick G., additional, Santiago, Juan G., additional, and Stadermann, Michael, additional

Published
2022
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33. USPSTF lowers recommended screening age for breast cancer to 40 years

Author

Campbell, Patrick

Subjects
Task forces, Medicine, Preventive, Cancer -- Diagnosis, Mammography, Preventive health services, Breast cancer, Health
Abstract

The US Preventive Services Task Force (USPSTF) has released updated recommendations for the screening for breast cancer in women, with the organization now lowering their recommended age for biennial screenings [...]

Published
2024

36. The Development of Normative Fitness Data and Analyzing the Relationships Between 20MSFT and 2.4-km Run Performance in Australian Police Recruits.

Author

Campbell, Patrick, Maupin, Danny, Lockie, Robert G., Dawes, J. Jay, Simas, Vinicius, Canetti, Elisa, Schram, Ben, and Orr, Robin

Subjects
*REFERENCE values, *RUNNING, *SEX distribution, *RETROSPECTIVE studies, *AGE distribution, *GOAL (Psychology), *LONGITUDINAL method, *EMPLOYEE recruitment, *MEDICAL records, *ACQUISITION of data, *EXERCISE tests, *POLICE, *REGRESSION analysis
Abstract

Aerobic fitness testing plays a significant role in the academy training of law enforcement recruits. There is a lack of normative data for law enforcement recruits and substantial interchangeability for choice of field-based aerobic tests. Therefore, this study aimed to develop normative percentile rankings for the 20-m multistage fitness tests (20MSFT) and 2.4-km run specific to law enforcement recruits; and to analyze the relationship between the 2 tests by linear regression. Data from 5 cohorts of law enforcement recruits completing 20MSFT (n 5 1,536) and 2.4-km run (n 5 1,499) testing during basic training at an Australian Police Academy were retrospectively analyzed. Percentile ranks were calculated (20th, 40th, 50th, 60th, 80th, and 99th) based on the number of shuttles completed and time (seconds) to complete the 2.4-km run. Results were split by sex and age (i.e., ,20 years, 20-29 years, 30-39 years, and 40-49 years). Linear regression analyzed the relationship between the 20MSFT to the 2.4-km run (using both seconds and km·h21), producing predictive equations to translate scores between the 2 assessments. These data presented the first detailed normative values by age and sex for Australian law enforcement recruits. Furthermore, the results demonstrated regression models could explain 65-74% of the variance observed (r2 5 0.649-0.741) between 20MSFT performance and 2.4-km run performance. This study's findings allow for normative performance for the purpose of benchmarking fitness, setting performance goal, and rehabilitation from injury. In addition, a valid conversion through a linear regression affords cross-agency comparisons and temporal changes in test selection/recruit cohorts. [ABSTRACT FROM AUTHOR]

Published
2024

41. CNS Langerhans cell histiocytosis: Common hematopoietic origin for LCH-associated neurodegeneration and mass lesions.

Author

McClain, Kenneth, Picarsic, Jennifer, Chakraborty, Rikhia, Zinn, Daniel, Lin, Howard, Abhyankar, Harshal, Scull, Brooks, Shih, Albert, Lim, Karen, Eckstein, Olive, Lubega, Joseph, Peters, Tricia, Olea, Walter, Burke, Thomas, Ahmed, Nabil, Hicks, M, Tran, Brandon, Jones, Jeremy, Dauser, Robert, Jeng, Michael, Baiocchi, Robert, Goldman, Stanton, Heym, Kenneth, Wilson, Harry, Carcamo, Benjamin, Kumar, Ashish, Rodriguez-Galindo, Carlos, Whipple, Nicholas, Campbell, Patrick, Murdoch, Geoffrey, Kofler, Julia, Heales, Simon, Malone, Marian, Woltjer, Randy, Quinn, Joseph, Orchard, Paul, Kruer, Michael, Jaffe, Ronald, Manz, Markus, Lira, Sergio, Parsons, D, Merad, Miriam, Man, Tsz-Kwong, Allen, Carl, and Schiff, Deborah

Subjects
BRAF-V600E, CNS neoplasms, Langerhans cell histiocytosis, neurodegeneration, osteopontin, Adolescent, Adult, Biomarkers, Biopsy, Brain, Brain Neoplasms, Child, Child, Preschool, Diagnosis, Differential, Female, Hematopoietic Stem Cells, Histiocytosis, Langerhans-Cell, Humans, Infant, Infant, Newborn, Leukocytes, Mononuclear, MAP Kinase Signaling System, Male, Neurodegenerative Diseases, Osteopontin, Proto-Oncogene Proteins B-raf, Retrospective Studies, Young Adult
Abstract

BACKGROUND: Central nervous system Langerhans cell histiocytosis (CNS-LCH) brain involvement may include mass lesions and/or a neurodegenerative disease (LCH-ND) of unknown etiology. The goal of this study was to define the mechanisms of pathogenesis that drive CNS-LCH. METHODS: Cerebrospinal fluid (CSF) biomarkers including CSF proteins and extracellular BRAFV600E DNA were analyzed in CSF from patients with CNS-LCH lesions compared with patients with brain tumors and other neurodegenerative conditions. Additionally, the presence of BRAFV600E was tested in peripheral mononuclear blood cells (PBMCs) as well as brain biopsies from LCH-ND patients, and the response to BRAF-V600E inhibitor was evaluated in 4 patients with progressive disease. RESULTS: Osteopontin was the only consistently elevated CSF protein in patients with CNS-LCH compared with patients with other brain pathologies. BRAFV600E DNA was detected in CSF of only 2/20 (10%) cases, both with LCH-ND and active lesions outside the CNS. However, BRAFV600E+ PBMCs were detected with significantly higher frequency at all stages of therapy in LCH patients who developed LCH-ND. Brain biopsies of patients with LCH-ND demonstrated diffuse perivascular infiltration by BRAFV600E+ cells with monocyte phenotype (CD14+ CD33+ CD163+ P2RY12- ) and associated osteopontin expression. Three of 4 patients with LCH-ND treated with BRAF-V600E inhibitor experienced significant clinical and radiologic improvement. CONCLUSION: In LCH-ND patients, BRAFV600E+ cells in PBMCs and infiltrating myeloid/monocytic cells in the brain is consistent with LCH-ND as an active demyelinating process arising from a mutated hematopoietic precursor from which LCH lesion CD207+ cells are also derived. Therapy directed against myeloid precursors with activated MAPK signaling may be effective for LCH-ND. Cancer 2018;124:2607-20. © 2018 American Cancer Society.

Published
2018

44. Cabozantinib with immune checkpoint inhibitor versus cabozantinib monotherapy in patients with metastatic clear cell renal cell carcinoma progressing after prior immune checkpoint inhibitor

Author

Gebrael, Georges, primary, Jo, Yeonjung, additional, Mathew Thomas, Vinay, additional, Li, Haoran, additional, Sayegh, Nicolas, additional, Tripathi, Nishita, additional, Srivastava, Ayana, additional, Nordblad, Blake, additional, Dal, Emre, additional, Narang, Arshit, additional, Brundage, James, additional, Campbell, Patrick, additional, Galarza Fortuna, Gliceida, additional, Hage Chehade, Chadi, additional, Maughan, Benjamin L., additional, Agarwal, Neeraj, additional, and Swami, Umang, additional

Published
2024
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46. Toward improved myocardial maturity in an organ-on-chip platform with immature cardiac myocytes

Author

Sheehy, Sean P, Grosberg, Anna, Qin, Pu, Behm, David J, Ferrier, John P, Eagleson, Mackenzie A, Nesmith, Alexander P, Krull, David, Falls, James G, Campbell, Patrick H, McCain, Megan L, Willette, Robert N, Hu, Erding, and Parker, Kevin K

Subjects
Heart Disease, Cardiovascular, Stem Cell Research, Stem Cell Research - Nonembryonic - Non-Human, Regenerative Medicine, Heart Disease - Coronary Heart Disease, 2.1 Biological and endogenous factors, Aetiology, Animals, Cell Differentiation, Cells, Cultured, Gene Expression Profiling, Heart Ventricles, Lab-On-A-Chip Devices, Microchip Analytical Procedures, Myocardial Contraction, Myocytes, Cardiac, Rats, Rats, Sprague-Dawley, Tissue Engineering, Ventricular Function, Muscular thin films, cardiac contractility, Heart-on-a-Chip, cardiac tissue engineering, Medical and Health Sciences, Biochemistry & Molecular Biology
Abstract

In vitro studies of cardiac physiology and drug response have traditionally been performed on individual isolated cardiomyocytes or isotropic monolayers of cells that may not mimic desired physiological traits of the laminar adult myocardium. Recent studies have reported a number of advances to Heart-on-a-Chip platforms for the fabrication of more sophisticated engineered myocardium, but cardiomyocyte immaturity remains a challenge. In the anisotropic musculature of the heart, interactions between cardiac myocytes, the extracellular matrix (ECM), and neighboring cells give rise to changes in cell shape and tissue architecture that have been implicated in both development and disease. We hypothesized that engineered myocardium fabricated from cardiac myocytes cultured in vitro could mimic the physiological characteristics and gene expression profile of adult heart muscle. To test this hypothesis, we fabricated engineered myocardium comprised of neonatal rat ventricular myocytes with laminar architectures reminiscent of that observed in the mature heart and compared their sarcomere organization, contractile performance characteristics, and cardiac gene expression profile to that of isolated adult rat ventricular muscle strips. We found that anisotropic engineered myocardium demonstrated a similar degree of global sarcomere alignment, contractile stress output, and inotropic concentration-response to the β-adrenergic agonist isoproterenol. Moreover, the anisotropic engineered myocardium exhibited comparable myofibril related gene expression to muscle strips isolated from adult rat ventricular tissue. These results suggest that tissue architecture serves an important developmental cue for building in vitro model systems of the myocardium that could potentially recapitulate the physiological characteristics of the adult heart. Impact statement With the recent focus on developing in vitro Organ-on-Chip platforms that recapitulate tissue and organ-level physiology using immature cells derived from stem cell sources, there is a strong need to assess the ability of these engineered tissues to adopt a mature phenotype. In the present study, we compared and contrasted engineered tissues fabricated from neonatal rat ventricular myocytes in a Heart-on-a-Chip platform to ventricular muscle strips isolated from adult rats. The results of this study support the notion that engineered tissues fabricated from immature cells have the potential to mimic mature tissues in an Organ-on-Chip platform.

Published
2017

49. Langerhans cell histiocytosis: NACHO update on progress, chaos, and opportunity on the path to rational cures.

Author

Bielamowicz, Kevin, Dimitrion, Peter, Abla, Oussama, Bomken, Simon, Campbell, Patrick, Collin, Matthew, Degar, Barbara, Diamond, Eli L., Eckstein, Olive S., El‐Mallawany, Nader, Fluchel, Mark, Goyal, Gaurav, Henry, Michael M., Hermiston, Michelle, Hogarty, Michael, Jeng, Michael, Jubran, Rima, Lubega, Joseph, Kumar, Ashish, and Ladisch, Stephan

Subjects
MITOGEN-activated protein kinases, SOMATIC mutation, TREATMENT failure, SYMPTOMS, ERDHEIM-Chester disease, LANGERHANS-cell histiocytosis
Abstract

Langerhans cell histiocytosis (LCH) is a myeloid neoplastic disorder characterized by lesions with CD1a‐positive/Langerin (CD207)‐positive histiocytes and inflammatory infiltrate that can cause local tissue damage and systemic inflammation. Clinical presentations range from single lesions with minimal impact to life‐threatening disseminated disease. Therapy for systemic LCH has been established through serial trials empirically testing different chemotherapy agents and durations of therapy. However, fewer than 50% of patients who have disseminated disease are cured with the current standard‐of‐care vinblastine/prednisone/(mercaptopurine), and treatment failure is associated with long‐term morbidity, including the risk of LCH‐associated neurodegeneration. Historically, the nature of LCH—whether a reactive condition versus a neoplastic/malignant condition—was uncertain. Over the past 15 years, seminal discoveries have broadly defined LCH pathogenesis; specifically, activating mitogen‐activated protein kinase pathway mutations (most frequently, BRAFV600E) in myeloid precursors drive lesion formation. LCH therefore is a clonal neoplastic disorder, although secondary inflammatory features contribute to the disease. These paradigm‐changing insights offer a promise of rational cures for patients based on individual mutations, clonal reservoirs, and extent of disease. However, the pace of clinical trial development behind lags the kinetics of translational discovery. In this review, the authors discuss the current understanding of LCH biology, clinical characteristics, therapeutic strategies, and opportunities to improve outcomes for every patient through coordinated agent prioritization and clinical trial efforts. Langerhans cell histiocytosis is an inflammatory myeloid neoplastic disorder driven by activating somatic mutations in mitogen‐activated protein kinase pathway genes. Rapid advances in mechanistic understanding of Langerhans cell histiocytosis now offer opportunities to improve outcomes for patients. [ABSTRACT FROM AUTHOR]

Published
2024
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50. Evaluation of an In‐Canopy Wind and Wind Adjustment Factor Model for Wildfire Spread Applications Across Scales.

Author

Hung, Wei‐Ting, Campbell, Patrick C., Moon, Zachary, Saylor, Rick, Kochendorfer, John, Lee, Temple R., and Massman, William

Subjects
*WILDFIRES, *FOREST fires, *NUMERICAL weather forecasting, *WIND speed, *STANDARD deviations, *FOREST canopies
Abstract

The representation of vegetative sub‐canopy wind is critical in numerical weather prediction (NWP) models for the determination of the air‐surface exchange processes of heat, momentum, and trace gases. Because of the relationship between wind speed and fire behaviors, the influence of the canopy on near‐surface wind speed is critical for prognostic fire spread models used in regional NWP models. In practice, the wind speed at the midflame point of fires (midflame wind speed) is used to determine the rate of fire spread. However, the wind speeds from most in situ measurements and NWP models are taken at some reference height above the canopy and fire flames. Hence, this study develops a modular and computationally‐efficient one‐dimensional model set composed of a canopy wind model and a wind adjustment factor (WAF) model for NWP applications across scales. The model set uses prescribed foliage shape functions to represent the vertical vegetation profile and its impacts on the three‐dimensional structure of horizontal wind speeds. Results from the canopy wind model well agree with ground‐based observations with average mean absolute bias, root mean square error and determination coefficients around 0.18 m s−1, 0.40 m s−1and 0.90, respectively. The WAF model provides midflame wind speeds by estimating the WAF based on canopy, fire and flame characteristics. Various user‐definable options provide flexibility to adapt to variations in canopy characteristics and additional complexities associated with wildfires. The model set is expected to improve NWP models by providing an improved representation of the sub‐grid wind flows at any spatial scale. Plain Language Summary: Compared to bare ground, wind speeds are reduced by the presence of vegetation at the surface by the leaves and woody parts of plants, especially within forest canopies. The altered wind speeds affect the atmosphere's stability and transport processes, as well as the spread of wildfires. Several fire prediction models are connected with weather models; however, most weather models do not consider such sub‐canopy effects on reducing wind speeds as the vertical structure of vegetation are not included in the models. Thus, this study presents a canopy model that can simulate the effects of vegetation, primarily forest canopies, on horizontal wind speeds used in weather models. The canopy model also provides the estimation of the wind speeds at the height of the midpoint of flame above ground level (midflame wind speed), which can better describe fire behaviors for general use in fire prediction models. The model results agree well with both above and below canopy top wind speed observations, and the midflame wind speeds are reliable when compared to previous studies. The canopy model is expected to improve weather modeling by providing a better representation of near‐surface wind flow, particularly for areas covered by dense forest canopies. Key Points: This study presents and evaluates a canopy wind model that simulates horizontal wind speeds above and within vegetation canopiesModel results agree well with observations and should provide a better representation of wind flow in numerical weather prediction modelsThe wind adjustment factor model provides midflame wind speed estimation, which can be used for the estimation of the rate of fire spread [ABSTRACT FROM AUTHOR]

Published
2024
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