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9. TENAYA and LUCERNE: Two-Year Results from the Phase 3 Neovascular Age-Related Macular Degeneration Trials of Faricimab with Treat-and-Extend Dosing in Year 2

Author

Abbey, Ashkan, Abdulaeva, Elmira, Abraham, Prema, Adan Civera, Alfredo, Agostini, Hansjurgen, Alezzandrini, Arturo, Alfaro, Virgil, Almony, Arghavan, Altay, Lebriz, Amini, Payam, Antoszyk, Andrew, Aradi, Etelka, Arias, Luis, Arnold, Jennifer, Asaria, Riaz, Astakhov, Sergei, Astakhov, Yury, Awh, Carl C., Balaratnasingam, Chandra, Banerjee, Sanjiv, Baumal, Caroline, Becker, Matthias, Belfort, Rubens, Jr., Bratko, Galina, Bridges, William Z., Jr., Brown, Jamin, Brown, David M., Budzinskaya, Maria, Buffet, Sylvia, Burgess, Stuart, Byon, Iksoo, Cagini, Carlo, Calzada, Jorge, Cameron, Stone, Campochiaro, Peter, Carlson, John, Carneiro, Angela, Chan, Clement, Chang, Emmanuel, Chang, Andrew, Chao, Daniel, Chaudhry, Nauman, Chee, Caroline, Cheek, Andrew, Chen, Shih-Jen, Chen, San-Ni, Cheung, Gemmy, Chexal, Saradha, Chittum, Mark, Chow, David, Cole, Abosede, Connolly, Brian, Cornut, Pierre Loic, Couvillion, Stephen, Danzig, Carl, Daskalov, Vesselin, Dessouki, Amr, Devin, Francois, Dollin, Michael, Dolz, Rosa, Downey, Louise, Dreyer, Richard, Dugel, Pravin, Eichenbaum, David, Eldem, Bora, Engstrom, Robert, Escobar, Joan Josep, Eter, Nicole, Faber, David W., Falk, Naomi, Feiner, Leonard, Vega, Alvaro Fernandez, Ferrone, Philip, Figueroa, Marta, Fine, Howard, Fineman, Mitchell, Fox, Gregory M., Francais, Catherine, Franco, Pablo, Fraser-Bell, Samantha, Fung, Nicholas, Sola, Federico Furno, Gale, Richard, Garcia-Layana, Alfredo, Gasperini, Julie, Gawecki, Maciej, Ghanchi, Faruque, Gill, Manjot, Giunta, Michel, Glaser, David, Goldstein, Michaella, Ulla, Francisco Gomez, Gomi, Fumi, Gonzalez, Victor, Graff, Jordan, Gupta, Sunil, Guthoff, Rainer, Guymer, Robyn, Haas, Anton, Hampton, Robert, Hatz, Katja, Hayashi, Ken, Heier, Jeffrey, Herba, Ewa, Hershberger, Vrinda, Higgins, Patrick, Holekamp, Nancy, Honda, Shigeru, Howard, James, Hu, Allen, Huddleston, Stephen, Iida, Tomohiro, Imaizumi, Hiroko, Ito, Yasuo, Ito, Yasuki, Itty, Sujit, Javey, Golnaz, Javid, Cameron, Kaga, Tatsushi, Kaluzny, Jakub, Kang, Se Woong, Kapoor, Kapil, Karabas, Levent, Kawasaki, Tsutomu, Kelty, Patrick, Kerenyi, Agnes, Khanani, Arshad, Khoramnia, Ramin, Khurana, Rahul, Kimura, Kazuhiro, Klein-Mascia, Kendra, Kobayashi, Namie, Kodjikian, Laurent, Koizumi, Hideki, Kokame, Gregg, Kulikov, Alexey, Kwong, Henry, Kwun, Robert, Lai, Timothy, Lai, Chi-Chun, Lalonde, Laurent, Lanzetta, Paolo, Larsen, Michael, Lavina, Adrian, Lee, Won Ki, Lee, ji Eun, Lee, Seong, Levy, Jaime, Lindsell, Lucas, Liu, Mimi, London, Nikolas, Lotery, Andrew, Lozano Rechy, David, Luckie, Alan, Maberley, David, Maeno, Takatoshi, Mahmood, Sajjad, Makkouk, Fuad, Marcus, Dennis, Margherio, Alan, Masse, Helene, Matsubara, Hisashi, Maturi, Raj, Mehta, Sonia, Menon, Geeta, Mentes, Jale, Michels, Mark, Mitamura, Yoshinori, Mitchell, Paul, Mohamed, Quresh, Mones, Jordi, Lobo, Rodrigo Montemayor, Montero, Javier, Moore, Jeffrey, Mori, Ryusaburo, Morori-Katz, Haia, Mukherjee, Raj, Murata, Toshinori, Muzyka-Wozniak, Maria, Nardi, Marco, Narendran, Niro, Nicolo, Massimo, Nielsen, Jared, Nishimura, Tetsuya, Noda, Kousuke, Nowinska, Anna, Oh, Hideyasu, Ohr, Matthew, Okada, Annabelle, Oleksy, Piotr, Ono, Shinji, Ozdek, Sengul, Ozturk, Banu, Pablo, Luis, Park, Kyu Hyung, Parke, D. Wilk, Parravano, Maria Cristina, Patel, Praveen, Patel, Apurva, Patel, Sunil, Patel, Sugat, Pauleikhoff, Daniel, Pearce, Ian, Pearlman, Joel, Petkova, Iva, Pieramici, Dante, Pozdeyeva, Nadezhda, Qureshi, Jawad, Raczynska, Dorota, Ramirez Estudillo, Juan, Rathod, Rajiv, Razavi, Hessam, Regillo, Carl, Reilly, Gayatri, Ricci, Federico, Rich, Ryan, Romanowska-Dixon, Bożena, Rosenblatt, Irit, Ruiz Moreno, Jose Maria, Sacu, Stefan, Saedon, Habiba, Saeed, Usman, Sagong, Min, Sakamoto, Taiji, Sandhu, Sukhpal, Sararols, Laura, Saravia, Mario, Schadlu, Ramin, Schlottmann, Patricio, Sekiryu, Tetsuju, Seres, András, Sermet, Figen, Shah, Sumit, Shah, Rohan, Shah, Ankur, Sheidow, Thomas, Sheth, Veeral, Shiragami, Chieko, Sikorski, Bartosz, Silva, Rufino, Singerman, Lawrence, Sisk, Robert, Sørensen, Torben L., Souied, Eric, Spinak, David-J., Staurenghi, Giovanni, Steinmetz, Robert, Stoller, Glenn, Stoltz, Robert, Suan, Eric, Suner, Ivan, Yzer, Suzanne, Tadayoni, Ramin, Takahashi, Kanji, Takayama, Kei, Taleb, Alexandre, Talks, James, Terasaki, Hiroko, Thompson, John, Toth-Molnar, Edit, Tran, Khoi, Tuli, Raman, Uchiyama, Eduardo, Vajas, Attila, Lith-Verhoeven, Janneke Van, Varsanyi, Balazs, Viola, Francesco, Virgili, Gianni, Vogt, Gábor, Völker, Michael, Warrow, David, Weber, Pamela, Wells, John A., Wickremasinghe, Sanjeewa, Wieland, Mark, Williams, Geoff, Williams, Thomas, Wong, David, Wong, King, Wong, James, Wong, Ian, Wong, Robert, Wowra, Bogumil, Wykoff, Charles C., Yamashita, Ayana, Yasuda, Kanako, Yilmaz, Gursel, Yiu, Glenn, Yoneda, Ai, Yoon, Young Hee, Yoreh, Barak, Yu, Hyeong Gon, Yu, Seung Young, Yurieva, Tatiana, Zambrano, Alberto, Zatorska, Barbara, Zeolite, Carlos, Khanani, Arshad M., Kotecha, Aachal, Chen, Youxin, Heier, Jeffrey S., Holz, Frank G., Ives, Jane A., Lim, Jennifer I., Lin, Hugh, Michels, Stephan, Quezada Ruiz, Carlos, Schmidt-Erfurth, Ursula, Silverman, David, Singh, Rishi, Swaminathan, Balakumar, and Willis, Jeffrey R.

Published
2024
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10. Intravitreal aflibercept 8 mg in diabetic macular oedema (PHOTON): 48-week results from a randomised, double-masked, non-inferiority, phase 2/3 trial

Author

Abraham, Prema, Aderman, Christopher, Akiyama, Kunihiko, Alfaro, Daniel V., Ali, Fareed A., Amini, Payam, Anzalotta, Andres Emanuelli, Bátor, György, Batlle, Ivan, Berger, Adam, Bhandari, Ramanath, Bridges, William, Brinkmann, Christian, Brown, Jamin, Burgess, Stuart, Calzada, Jorge, Capone Jr., Antonio, Cervena, Dana, Charles, Steven, Chaudhry, Nauman, Chow, David, Clark, W. Lloyd, Conrad III, Paul, Cunningham, Matthew, Dadgostar, Hajir, Dessouki, Amr, Deupree, Dana, Devine, Christopher, Eichenbaum, David, Ernest, Jan, Feltgen, Nicolas, Fenberg, Moss, Ferrone, Philip, Frenkel, Ronald, Friedman, Scott, Gasperini, Julie, Gerstenblith, Adam, Ghorayeb, Ghassan, Giunta, Michel, Goff, Mitchell, Golas, Liliya, Googe Jr., Joseph M., Goren Fein, Jordana, Hagedorn, Curtis, Hagiwara, Akira, Hahn, Paul, Hairston, Richard, Handza, Jason, Hau, Vivienne, Hayashi, Ken, Heier, Jeffrey, Hershberger, Vrinda, Higgins, Patrick, Hirano, Yoshio, Honda, Shigeru, Ikegami, Yasuko, Ishida, Yuichiro, Ishikawa, Isao, Ishii, Kiyoshi, Jablon, Eric P., Jain, Atul, Kaji, Yuichi, Kapoor, Kapil, Kerényi, Ágnes, Kimura, Kazuhiro, Kishino, Genichiro, Kiss, Katalin, Kitaoka, Takashi, Klancnik, James M., Kobayashi, Namie, Kogo, Jiro, Korda, Vladimir, Kruger, Erik, Kusuhara, Sentaro, Lara, Wilfredo, Laud, Ketan, Lee, Seong, Luu, James, Marcus, Dennis, Mein, Calvin, Meleth, Annal, Milibák, Tibor, Mitamura, Yoshinori, Murata, Toshinori, Noge, Sumiyo, Onoe, Hajime, Osher, James, Papp, András, Parschauer, Justin, Patel, Sugat, Patel, Sunil, Pezda, Matthew, Pirouz, Ashkan, Prasad, Pradeep, Punjabi, Omar, Rao, Llewelyn, Roe, Richard, Schadlu, Ramin, Schneider, Eric, Shah, Ankur, Shah, Milan, Shah, Sandeep, Shah, Sumit, Sharma, Ashish, Sheth, Veeral, Shimura, Masahiko, Singerman, Lawrence, Spital, Georg, Stoltz, Robert, Suan, Eric, Suzuma, Kiyoshi, Takahashi, Hidenori, Takamura, Yoshihiro, Takeuchi, Masaru, Tan, Jeffrey, Thomas, Benjamin, Tóth,-Molnár, Edit, Ueda, Tetsuo, Ushida, Hiroaki, Vajas, Attila, Varma, Deepali, Varsányi, Balázs, Veith, Miroslav, Weber, Pamela, Wee, Raymond, Williams, Geoff, Yamada, Haruhiko, Yonekawa, Yoshihiro, Yoshida, Shigeo, Brown, David M, Boyer, David S, Do, Diana V, Wykoff, Charles C, Sakamoto, Taiji, Win, Peter, Joshi, Sunir, Salehi-Had, Hani, Seres, András, Berliner, Alyson J, Leal, Sergio, Vitti, Robert, Chu, Karen W, Reed, Kimberly, Rao, Rohini, Cheng, Yenchieh, Sun, Wei, Voronca, Delia, Bhore, Rafia, Schmidt-Ott, Ursula, Schmelter, Thomas, Schulze, Andrea, Zhang, Xin, Hirshberg, Boaz, Yancopoulos, George D, and Sivaprasad, Sobha

Published
2024
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11. Average semivariance yields accurate estimates of the fraction of marker-associated genetic variance and heritability in complex trait analyses.

Author

Feldmann, Mitchell J, Piepho, Hans-Peter, Bridges, William C, and Knapp, Steven J

Subjects
Animals, Humans, Genetic Markers, Genomics, Genotype, Multifactorial Inheritance, Phenotype, Polymorphism, Single Nucleotide, Alleles, Quantitative Trait Loci, Models, Theoretical, Models, Genetic, Forecasting, Genetic Variation, Genetics, Human Genome, Biotechnology, Generic health relevance, Developmental Biology
Abstract

The development of genome-informed methods for identifying quantitative trait loci (QTL) and studying the genetic basis of quantitative variation in natural and experimental populations has been driven by advances in high-throughput genotyping. For many complex traits, the underlying genetic variation is caused by the segregation of one or more 'large-effect' loci, in addition to an unknown number of loci with effects below the threshold of statistical detection. The large-effect loci segregating in populations are often necessary but not sufficient for predicting quantitative phenotypes. They are, nevertheless, important enough to warrant deeper study and direct modelling in genomic prediction problems. We explored the accuracy of statistical methods for estimating the fraction of marker-associated genetic variance (p) and heritability ([Formula: see text]) for large-effect loci underlying complex phenotypes. We found that commonly used statistical methods overestimate p and [Formula: see text]. The source of the upward bias was traced to inequalities between the expected values of variance components in the numerators and denominators of these parameters. Algebraic solutions for bias-correcting estimates of p and [Formula: see text] were found that only depend on the degrees of freedom and are constant for a given study design. We discovered that average semivariance methods, which have heretofore not been used in complex trait analyses, yielded unbiased estimates of p and [Formula: see text], in addition to best linear unbiased predictors of the additive and dominance effects of the underlying loci. The cryptic bias problem described here is unrelated to selection bias, although both cause the overestimation of p and [Formula: see text]. The solutions we described are predicted to more accurately describe the contributions of large-effect loci to the genetic variation underlying complex traits of medical, biological, and agricultural importance.

Published
2021

13. Pegcetacoplan for the treatment of geographic atrophy secondary to age-related macular degeneration (OAKS and DERBY): two multicentre, randomised, double-masked, sham-controlled, phase 3 trials

Author

Cole, Abosede O, Gerstenblith, Adam T, Kotagiri, Ajay, Edwards, Albert O, Zambrano, Alberto D, Eaton, Alexander M, Rubowitz, Alexander, Lyon, Alice T, Chiang, Allen, Ho, Allen, Hu, Allen Y, Guerami, Amir H, Dessouki, Amr L, de Carvalho, André Corrêa Maia, Emanuelli, Andrés, Chang, Andrew A, Antoszyk, Andrew N, Francone, Anibal Andrés, Prasad, Anita, Wolf, Armin, Khanani, Arshad M, Abbey, Ashkan Michael, Moulana, Asma, Wihelm, Barbara, Sikorski, Bartosz L, Kuppermann, Baruch D, Wolff, Benjamin, Jewart, Brian H, Do, Brian K, Chan-Kai, Brian T, Mein, Calvin, Hoyng, Carel B, Awh, Carl C, Regillio, Carl, Zeolite, Carlos, Baumal, Caroline R, Creuzot-Garcher, Catherine, Maury, Catherine Français, Wykoff, Charles C, Newell, Charles K, Jhaveri, Chirag, Lohmann, Chris P, Dinah, Christiana B, Ma, Colin, Crawford, Courtney, Parke, D Wilkin, Lavinsky, Daniel, Roth, Daniel, Pieramici, Dante J, Moshfeghi, Darius M, Levin, Darrin, Saperstein, David A, Brown, David, Gaucher, David, Lally, David R, Liao, David S, Brown, David Warren, Goldstein, Debra, Marcus, Dennis, Chan, Derek G, Dhoot, Dilsher, Tacite, Domingo, Zalewski, Dominik, Espana, Edgar M, Lad, Eleonora M, Souied, Eric H, Suan, Eric P, Eting, Eva, Sola, Federico Furno, de Bats, Flore, Bandello, Francesco, Gómez-Ulla, Francisco, Devin, François, Holz, Frank G, Chen, Fred K, Makkouk, Fuad, Dyer, Gawain, Spital, George, Staurenghi, Giovanni, Stoller, Glenn, Cousins, Gwen, Salehi-Had, Hani, Agostini, Hansjürgen, Eleftheriadis, Haralabos, Weiss, Harold, Sultan, Harris C, Massé, Hélène, Pearce, Ian, Dias, Indra, Barbazetto, Irene, Rosenblatt, Irit, Suñer, Ivan J, Kovach, Jaclyn L, Kaluzny, Jakub, Borthwick, James, Howard, James G, Wong, James, Ernest, Jan, Němčanský, Jan, Ysasaga, Jason Edward, Handza, Jason M, Moreno, Javier Antonio Montero, Korobelnik, Jean-François, Heier, Jeffrey S, Arnold, Jennifer J, Brown, Jeremiah, Bafalluy, Joaquin, Pearlman, Joel, Pitcher, John D, Kitchens, John, Carlson, John P, Gilhotra, Jolly, Fein, Jordana, Monés, Jordi M, Luna, José Domingo, Moreno, José María Ruiz, Coney, Joseph M, Sallum, Juliana Maria Ferraz, Olsen, Karl R, Blobner, Katharina, Macoul, Katherine A, Oh, Kean T, Malik, Khurram Javed, Hattenbach, Lars-Olof, Kodjikian, Laurent, Neto, Laurentino Biccas, Singerman, Lawrence J, Altay, Lebriz, Sheck, Leo-H, Feiner, Leonard, Harris, Lindsey D, Chishold, Lionel D, Rao, Llewelyn J, Nehemy, Márcio Bittar, Elizalde, Maria Jose Capella, Gamulescu, Maria-Andreea, Saravia, Mario J, Johnson, Mark W, McKibbin, Martin, Maccumber, Mathew, Vidosevich, Matko, Ohr, Matthew P, Samuel, Michael A, Singer, Michael A, Cassell, Michael, Dollin, Michael, Elman, Michael J, Ip, Michael S, Goldstein, Michaella, Busquets, Miguel, Mititelu, Mihai, Shah, Milan, Veith, Miroslav, Fineman, Mitchell, Varano, Monica, Christmas, Nancy, Steinle, Nathan C, Chaudhry, Nauman, Chinskey, Nicholas D, Eter, Nicole, London, Nikolas J S, Mathalone, Nurit, Schlottmann, Patricio G, Coady, Patrick, Higgins, Patrick M, Raskauskas, Paul A, Yates, Paul A, Bernstein, Paul, Mitchell, Paul, Monsour, Paul, Raphaelian, Paul V, Stanga, Paulo E, Stodulka, Pavel, Issa, Peter Charbel, Pavan, Peter, Ferrone, Phil J, Oleksy, Piotr, Abraham, Prema, Mruthyunjaya, Prithvi, Nguyen, Quan Dong, Reddy, Rahul K, Khurana, Rahul N, Tuli, Raman, Tadayoni, Ramin, Katz, Randy Steven, Arora, Rashi, Schlingemann, Reinier O, Rosen, Richard B, Gale, Richard, Scartozzi, Richard, Isernharge, Ricky, Singh, Rishi P, Stoltz, Robert A, Avery, Robert L, Wirthlin, Robert S, Guymer, Robyn, Goldberg, Roger A, Frenkel, Ronald, Belfort, Rubens Jr, Mohand-Said, Saddek, Grisanti, Salvatore, Razavi, Sam, Fraser-Bell, Samantha, Shah, Sandeep N, Wickremasinghe, Sanjeewa, Haug, Sara Joy, Adrean, Sean D, Priglinger, Siegfried G, Esposti, Simona Degli, Guest, Stephen, Huddleston, Stephen, Itty, Sujit, Moon, Suk Jin, Bhatia, Sumit P, Gupta, Sunil, Patel, Sunil S, Garg, Sunir J, Joshi, Sunir, Nghiem-Buffet, Sylvia, Johnson, T Mark, Jaouni, Tareq, Ach, Thomas, Williams, Thomas R, Sheidow, Thomas, Cleland, Timothy P, You, Timothy T, Peto, Tunde, Konidaris, Vasileios, Gonzalez, Victor H, Korda, Vladimir, Freeman, William R, Bridges, William Z, Barak, Yoreh, Zagorski, Zbigniew, Yehoshua, Zohar, Dubska, Zora, Rosenfeld, Philip J, Guymer, Robyn H, Boyer, David, Grossi, Federico, Korobelnik, Jean-Francois, Slakter, Jason S, Waheed, Nadia K, Metlapally, Ravi, Steinle, Nathan, Francone, Anibal A, Hu, Allen, Deschatelets, Pascal, Francois, Cedric, Bliss, Caleb, Monés, Jordi, and Ribeiro, Ramiro

Published
2023
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14. Efficacy and safety of avacincaptad pegol in patients with geographic atrophy (GATHER2): 12-month results from a randomised, double-masked, phase 3 trial

Author

Alezzandrini, Arturo, Francone, Anibal Andres, Bafalluy, Joaquín, Bainttein, Silvina, Luna Pinto, Jose, Saravia, Mario, Vidosevich, Matko, Zeolite, Carlos, Furno Sola, Federico, Chang, Andrew, Cornish, Elisa Eleanor Guida, Nguyen, Thanh, Findl, Oliver, Haas, Anton, Kralinger, Martina, Sacu, Stefan, Postelmans, Laurence Dominique, Farah, Michel, Maia, Mauricio, Nehemy, Marcio, Ali, Fareed, Brent, Michael, Dollin, Michael, Gonder, John, Kherani, Amin, Merkur, Andrew, Tuli, Raman, Lopera, Monica Marie, Rodriguez, Francisco, Bradvica, Mario, Ernest, Jan, Kalijurand, Kuldar, Noor, Kai, Cohen, Yves, Creuzot-Garcher, Catherine, De Bats, Flore, Devin, François, Français-Maury, Catherine, Kodjikian, Laurent, Korobelnik, Jean François, Le Mer, Yannick, Quaranta El Maftouhi, Maddalena, Razavi, Sam, Souied, Eric, Tadayoni, Ramin, Weber, Michel, Eter, Nicole, Feltgen, Nicolas, Grisanti, Salvatore, Walter, Peter, Liegl, Raffael, Lorenz, Katrin, Spital, Georg, Priglinger, Siegfried, Spitzer, Martin, Volker, Michael, Krohne, Tim, Jochmann, Claudia, Lohmann, Chris Patrick, Framme, Carsten, Kerenyi, Agnes, Papp, Andras, Seres, Andras, Toth-Molnar, Edit, Tsorbatzoglou, Alexis, Vajas, Atilla, Varsanyi, Balázs, Vogt, Gabor, Bar, Asaf, Eting, Eva, Hauser, David, Levy, Jamie, Mathalone, Nurit, Morori-Katz, Haia, Rosenblatt, Irit, Soudry-Zayit, Shiri, Trivizky, Omert, Bandello, Francesco, Ciardella, Antonio Pasquale, Figus, Michele, Giansanti, Fabrizio, Lanzetta, Paolo, Mariotti, Cesare, Mastropasqua, Leonardo, Midena, Edoardo, Parmeggiani, Francesco, Ricci, Federico, Simonelli, Francesca, Staurenghi, Giovanni, Viola, Francesco, Varano, Monica, Laganovska, Guna, Cisiecki, Sławomir, Jedrzejewski, Wojciech, Kaluzny, Jakub, Misiuk-Hojło, Marta, Abengoechea, Santiago, Iribarren, Javier Araiz, Ascaso, Franciso Javier, Cubero, Juan Manuel, Gallego-Pinazo, Roberto, Gomez-Ulla De Irazazabal, Francisco, Mestre, Ignasi Jürgens, Mones I Carilla, Jordi Manel, Montero Moreno, Javier, María Ruiz Moreno, José, Sararols Ramsay, Laura, Garcia Layana, Alfredo, Downey, Louise, Abraham, Prema, Alfaro, Daniel Virgil, Bagheri, Nika, Barbazetto, Irene, Benevento, Joseph, Bernstein, Paul, Bertolucci, George, Bhavsar, Abdhish, Bridges, William, Brooks, Jr, Harold Logan, Brown, Jamin, Brucker, Alexander, Calvo, Charles M., Capone, Antonio, Carlson, John, Chan, Clement, Chang, Emmanuel, Chan-Kai, Brian, Chaudhry, Nauman, Chen, Sanford, Csaky, Karl, Cummings, Howard, Danzig, Carl, Dessouki, Amr, Dyer, David, Eaton, Alexander, Eichenbaum, David, Faber, David, Feldman, Robert, Finnen, Neil, Freeman, William, Frenkel, Ronald, Gonzales, Christine, Gonzalez, Victor, Gross, John, Gupta, Sunil, Hall, Edward, Han, Min-Kyu, Heier, Jeffrey, Hershberger, Vrinda, Higgins, Patrick, Hsu, Jason, Ip, Michael, Jablon, Eric, Jewart, Brian, John, Vishak, Jonisch, Jonathan, Joondeph, Brian, Kay, Christine, Khanani, Arshad, Kokame, Gregg T., Kwun, Robert, Lai, Michael, Lally, David, Laud, Ketan, Lavina, Adrian, Lee, Michael, Lin, Phoebe, Lin, Haijiang, Manoharan, Niranjan, Marcus, Dennis, Martidis, Adam, McCabe, Frank, Nielsen, Jared, Osher, James, Palmer, James, Patel, Sunil, Pearlman, Joel, Perkins, Stephen, Pirouz, Ashkan, Qureshi, Jawad, Randolph, John, Piri, Niloofar, Rosenfeld, Phillip, Saperstein, David, Scartozzi, Richard, Schwartz, Steven, Sharma, Ashish, Sharma, Atul, Sheth, Veeral, Singer, Michael, Spinak, David, Suan, Eric, Tabandeh, Homayoun, Tabassian, Ali, Uchiyama, Eduardo, Varenhorst, Michael, Wagner, Alan, Warrow, David, Wells, III, John, Wong, Robert, Wong, Keye, Wykoff, Charles, Xavier, Samantha, Ysasaga, Edward, Khanani, Arshad M, Patel, Sunil S, Danzig, Carl J, Eichenbaum, David A, Wykoff, Charles C, Heier, Jeffrey S, Lally, David R, Monés, Jordi, Nielsen, Jared S, Sheth, Veeral S, Kaiser, Peter K, Clark, Julie, Zhu, Liansheng, Patel, Hersh, Tang, Justin, Desai, Dhaval, and Jaffe, Glenn J

Published
2023
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15. Evaluating and Enhancing Driving Skills for Individuals with Intellectual Disabilities through Simulator Training

Author

Randall, Kristina N., Ryan, Joseph B., Stierle, Jordan N., Walters, Sharon M., and Bridges, William

Abstract

Research consistently demonstrates that attainment of a driver's license and access to a vehicle directly and favorably influence employment outcomes, enhance one's ability to capitalize on quality jobs, and expand one's access to community and independent opportunities. This study used a driving simulator to provide driving lessons to 12 young adults with intellectual disabilities (IDs). The purpose was to use a safe learning environment to screen candidates for those who showed the potential to obtain a driver's license. Instruction was provided using a set of interactive exercises focusing on controlling the vehicle via lane keeping, speed maintenance, and obstacle avoidance tasks. Results revealed that simulator training provided a safe learning environment to identify individuals demonstrating the potential to safely operate a motor vehicle. Participants demonstrated moderate to large gains in maintaining lane position, speed, braking response, and target detection. Implications and suggestions for future research are provided.

Published
2021
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16. Bateman's Data: Inconsistent with “Bateman's Principles”

Author

Hoquet, Thierry, Bridges, William C, and Gowaty, Patricia Adair

Subjects
Biological Sciences, Ecology, Genetics, Bateman, sex differences, sexual selection, variance in number of mates, variance in reproductive success, Evolutionary Biology, Evolutionary biology, Ecological applications
Abstract

A.J. Bateman (1948) hypothesized that a metric of sexual selection is in sex differences of intrasexual variance in number of mates (V NM). AJB predicted that (a) males have greater variance in reproductive success (V RS) than females; (b) males have greater V NM than females; and (c) a positive relationship between V NM and V RS is stronger among males. AJB used phenotypically observable mutations in offspring to identify parents and to count subjects' NM and RS. AJB's conclusions matched his predictions, later called "Bateman's Principles." Empirical challenges to his conclusions guided analyses herein. (a) AJB's analysis pseudo-replicated sample sizes, violating a sexual selection assumption: That is, individuals must be in the same population to choose and compete. (b) AJB's methods overestimated subjects with no mates while underestimating subjects with one or more. (c) A replication (Gowaty et al., 2012) showed that offspring inheriting nametags from both parents often died before expressing adult phenotypes, proving some of AJB's methods produced biased data. Science historian Thierry Hoquet located AJB's archived, handwritten laboratory notes, photocopied, and transcribed them. We tested each of the 65 unique populations for expected combinations in offspring of parental mutations: 41.5% failed Punnett's tests: Offspring carrying nametags simultaneously from both parents were missing showing estimates of parents' NM and V NM were undercounted. 58.5% of populations met Punnett's expectations providing an unparalleled opportunity to re-evaluate AJB's predictions. 34 unbiased populations had no sex differences in V RS; 37 had no sex differences in V NM. No sex differences in slopes of RS and NM occurred in any unbiased population. Regressions showed weak, positive, significant associations between V NM and V RS for females and males, contrary to AJB's prediction that the relationship would be positive in males but not in females. AJB's laboratory data are inconsistent with "Bateman's Principles."

Published
2020

22. Screening Dietary Fat Sources and Concentrations Included in Low- and High-Forage Diets Using an In Vitro Gas Production System.

Author

Hussein, Saad M., Aguerre, Matias J., Jenkins, Thomas C., Bridges, William C., and Lascano, Gustavo J.

Subjects
FEED analysis, HIGH-fat diet, DIETARY fats, SOY oil, COCONUT oil, FAT
Abstract

Including dietary fat can increase the energy density of diets fed to ruminants, reducing dry matter intake (DMI). Effects of different fat sources on nutrient digestion and fermentation can vary depending on dietary fat concentration and the forage-to-concentrate ratio (F:C). Therefore, this study's objective was to screen the effects of fat sources supplemented at different concentrations to high- and low-forage diets on in vitro digestibility and fermentation. Treatments included either low forage (LF; 35%) or high forage (HF; 70%) with two fat levels (6 or 9% DM) using six different fat sources, plus control. The control diet (CON) had a basal level of fat in the diet (3% fat; 0% fat inclusion), and fat sources were added to attain 6% or 9% dietary fat and consisted of the following: Coconut oil, CO; Poultry fat, PF; Palm oil, PO; Palm kernel oil, PKO; Soybean oil, SOY; and Ca Salts, MEG. In vitro Gas Production (GP) modules were randomly assigned to treatments in a 2 × 2 × 7 factorial design and were incubated for four 24 h runs. The CO-fed module had the highest dry matter (DM) apparent digestibility (AD) (p < 0.01), followed by SOY and PF. The true DM digestibility (TDMD) and organic matter (OM) AD were the highest in CO (p < 0.01) than the other fat types. The AD for DM, OM, neutral detergent fiber (NDF), and acid detergent fiber (ADF) was higher in LF (p < 0.01). The 6% fat inclusion had a higher GP (109 vs. 103 mL ± 2.09; p < 0.03). Total volatile fatty acid (VFA) concentration was lower in different fat types than the CON and the acetate molar proportion (p > 0.01). The propionate was the lowest for the CON, which increased the acetate to propionate (A:P) ratio (p < 0.01). These results suggest that LF diets with high fat concentrations can be utilized, and different fat sources may improve DM and fiber digestibility. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Longitudinal trials illustrate interactive effects between declining Bt efficacy against Helicoverpa zea (Lepidoptera: Noctuidae) and planting dates of corn.

Author

Reay-Jones, Francis P F, Buntin, G David, Reisig, Dominic D, and Bridges, William C

Subjects
HELIOTHIS zea, TRANSGENIC plants, BACILLUS thuringiensis, CORN, FIELD research, FALL armyworm, HELICOVERPA armigera
Abstract

Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae) has evolved resistance to insecticidal toxins from Bacillus thuringiensis (Bt) Berliner (Bacillales: Bacillaceae) expressed in genetically engineered corn, Zea mays L. This study provides an overview of field trials from Georgia, North Carolina, and South Carolina evaluating Bt and non-Bt corn hybrids from 2009 to 2022 to show changes in susceptibility in H. zea to Bt corn. The reduction in kernel injury relative to a non-Bt hybrid averaged across planting dates generally declined over time for Cry1A.105 + Cry2Ab2 corn. In addition, there was a significant interaction with planting date used as a covariate. The reduction in kernel injury remained above 80% and did not vary with planting date from 2009 to 2014, whereas a significant decline with planting date was found in this reduction from 2015 to 2022. For Cry1Ab + Cry1F corn, the reduction in kernel injury relative to a non-Bt hybrid averaged across planting dates did not vary among years. The reduction in kernel injury significantly declined with planting date from 2012 to 2022. Kernel injury as a proxy for H. zea pressure was greater in late-planted trials in non-Bt corn hybrids. Our study showed that Bt hybrids expressing Cry1A.105 + Cry2Ab2 are now less effective in later planted trials in reducing H. zea injury; however, this was not the case during the earlier years of adoption of corn expressing these 2 toxins when resistance alleles were likely less frequent in H. zea populations. The implications for management of H. zea and for insect resistance management are discussed. [ABSTRACT FROM AUTHOR]

Published
2024
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24. A Longitudinal Study: Microbiological Quality of Raw Beef from Halal and Non-Halal Meat Markets in the United States.

Author

Al-Mahmood, Omar A., Jiang, Xiuping, Bridges, William C., and Fraser, Angela M.

Subjects
MEAT markets, AUTUMN, FOOD safety, PATHOGENIC bacteria, BEEF marketing
Abstract

Halal means permissible according to Islamic law. Halal meat is obtained by hand slaughtering an animal that is not stunned and that is blessed by a Muslim individual immediately before slaughter. The purpose of this study was to determine the microbiological quality of raw meat from halal meat markets. A total of 138 beef samples were purchased from three halal (n = 72 samples) and three non-halal markets (n = 66 samples) between November 2016 and October 2017. All samples were analyzed for the presence of indicator organisms—aerobic plate counts (APCs), Enterobacteriaceae counts (ECs), total coliform counts (TCCs), and generic Escherichia coli (ECCs). The levels of APCs, ECs, TCCs, and ECCs (mean log CFU/g) in halal samples were 4.93 (100%), 2.89 (91.7%), 2.87 (94.4%), and 1.09 (18.1%), respectively, and those in non-halal samples were 4.92 (100%), 3.07 (95.5%), 3.02 (89.4%), and 1.15 (16.7%), respectively. The levels of TCCs and ECs were higher in halal samples during the summer compared to the other three seasons, whereas the highest ECCs in halal samples were found during autumn. In non-halal samples, significant differences were observed in the ECCs, TCCs, and ECs across seasons, with the highest level of contamination during autumn. Samples having higher levels of indicator organisms (APCs, ECs, TCCs, and ECCs) were more likely to be positive for pathogenic bacteria. The high levels of indicator organisms in both halal and non-halal retail meat samples suggest that the operation size, and not halal or non-halal meat classification, is associated with the microbiological quality. These findings can inform food safety interventions targeting small meat markets in the United States. [ABSTRACT FROM AUTHOR]

Published
2024
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25. Effects of Caffeine Doses on Rumen Fermentation Profile and Nutrient Digestibility Using a Lactating Cow Diet under Continuous Cultures Conditions.

Author

Toledo, Mónica, Hussein, Saad M., Peña, Manuel, Aguerre, Matias J., Bridges, William, and Lascano, Gustavo J.

Subjects
PHYSIOLOGICAL effects of caffeine, RUMEN fermentation, CONTINUOUS culture (Microbiology), DIGESTION, LACTATION in cattle
Abstract

Simple Summary: This study explored the effects of different caffeine doses on nutrient digestion and fermentation in a simulated rumen environment. The main goal was to improve our understanding of how caffeine might influence these important metabolic processes in the rumen when a lactating cow diet is used. Here, we report that a dose of caffeine (50 ppm) improved the digestibility of dry/organic matter and starch while reducing the protozoa numbers and ammonia concentration, which are related to ruminal protein metabolism. However, higher caffeine doses (above 50 ppm) began to negatively impact these parameters. Our observations suggest that caffeine, a naturally occurring compound in several plants such as coffee, cacao, and tea, could potentially be used to enhance digestion and fermentation in ruminants. This research is valuable to our understanding of anaerobic fermentation in the rumen as it demonstrates the use of this plant secondary metabolite to enhance nutrient utilization and milk production and other benefits to management and the environment. Caffeine is a plant secondary metabolite, commonly known for its bioactivity properties. This molecule increases microbial activity during anaerobic digestion. The aim of this study was to determine the effects of caffeine doses on the rumen fermentation profile and nutrient digestibility when continuous culture fermenters were fed a lactating cow's diet. We hypothesize that adding caffeine doses into continuous culture fermenters with a rumen fluid inoculum will not affect anaerobic fermentation or nutrient utilization. Fermenters were fed twice a day (at 0800 and 2000 h) with an experimental diet of high-producing dairy cows (53.55 g/DM day; Forage:Concentrate ratio, F:C of 40:60). Four levels of caffeine (0 ppm, 50 ppm, 100 ppm, and 150 ppm) were added to the diets as a treatment. The experiment was arranged in a randomized complete block design. Two blocks of four fermenters were run in two replicated periods of ten days. Statistical analyses were conducted in SAS version 9.4 for Windows (SAS Institute Inc., Cary, NC, USA) using the GLIMMIX procedure. The addition of caffeine at a 50 ppm dose on continuous culture fermentation decreased the protozoal counts (Diplodinium spp.) (p = 0.03) and ammonia concentrations (p < 0.05). A treatment of 50 ppm of caffeine increased the DM, OM, and starch digestibility (p < 0.05). When caffeine doses increased further than 50 ppm, the OM, DM, and starch digestibility decreased linearly (p = 0.01). The total volatile fatty acids and fatty acid proportions were unaffected. However, the acetate-to-propionate ratio (A:P) tended to decrease linearly among treatments (p = 0.07). The means of pH measurements and maximum pH had a significantly linear decrease effect (p < 0.01). Caffeine may represent a potential rumen fermentation modifier for use in lactating cow diets. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Efficacy, durability, and safety of intravitreal faricimab up to every 16 weeks for neovascular age-related macular degeneration (TENAYA and LUCERNE): two randomised, double-masked, phase 3, non-inferiority trials

Author

Abbey, Ashkan, Abdulaeva, Elmira, Abraham, Prema, Adan Civera, Alfredo, Agostini, Hansjurgen, Alezzandrini, Arturo, Alfaro, Virgil, Almony, Arghavan, Altay, Lebriz, Amini, Payam, Antoszyk, Andrew, Aradi, Etelka, Arias, Luis, Arnold, Jennifer, Asaria, Riaz, Astakhov, Sergei, Astakhov, Yury, Awh, Carl C., Balaratnasingam, Chandra, Banerjee, Sanjiv, Baumal, Caroline, Becker, Matthias, Belfort, Rubens, Jr., Bratko, Galina, Bridges, William Jr. Z, Brown, Jamin, Brown, David M., Budzinskaya, Maria, Buffet, Sylvia, Burgess, Stuart, Byon, Iksoo, Cagini, Carlo, Calzada, Jorge, Cameron, Stone, Campochiaro, Peter, Carlson, John, Carneiro, Angela, Chan, Clement, Chang, Emmanuel, Chang, Andrew, Chao, Daniel, Chaudhry, Nauman, Chee, Caroline, Cheek, Andrew, Chen, Shih-Jen, Chen, San-Ni, Cheung, Gemmy, Chexal, Saradha, Chittum, Mark, Chow, David, Cole, Abosede, Connolly, Brian, Cornut, Pierre Loic, Couvillion, Stephen, Danzig, Carl, Daskalov, Vesselin, Dessouki, Amr, Devin, Francois, Dollin, Michael, Dolz, Rosa, Downey, Louise, Dreyer, Richard, Dugel, Pravin, Eichenbaum, David, Eldem, Bora, Engstrom, Robert, Escobar, Joan Josep, Eter, Nicole, Faber, David W., Falk, Naomi, Feiner, Leonard, Fernandez Vega, Alvaro, Ferrone, Philip, Figueroa, Marta, Fine, Howard, Fineman, Mitchell, Fox, Gregory M., Francais, Catherine, Franco, Pablo, Fraser-Bell, Samantha, Fung, Nicholas, Furno Sola, Federico, Gale, Richard, Garcia-Layana, Alfredo, Gasperini, Julie, Gawecki, Maciej, Ghanchi, Faruque, Gill, Manjot, Giunta, Michel, Glaser, David, Goldstein, Michaella, Gomez Ulla, Francisco, Gomi, Fumi, Gonzalez, Victor, Graff, Jordan, Gupta, Sunil, Guthoff, Rainer, Guymer, Robyn, Haas, Anton, Hampton, Robert, Hatz, Katja, Hayashi, Ken, Heier, Jeffrey, Herba, Ewa, Hershberger, Vrinda, Higgins, Patrick, Holekamp, Nancy, Honda, Shigeru, Howard, James, Hu, Allen, Huddleston, Stephen, Iida, Tomohiro, Imaizumi, Hiroko, Ito, Yasuo, Ito, Yasuki, Itty, Sujit, Javey, Golnaz, Javid, Cameron, Kaga, Tatsushi, Kaluzny, Jakub, Kang, Se Woong, Kapoor, Kapil, Karabas, Levent, Kawasaki, Tsutomu, Kelty, Patrick, Kerenyi, Agnes, Khanani, Arshad, Khoramnia, Ramin, Khurana, Rahul, Kimura, Kazuhiro, Klein-Mascia, Kendra, Kobayashi, Namie, Kodjikian, Laurent, Koizumi, Hideki, Kokame, Gregg, Kulikov, Alexey, Kwong, Henry, Kwun, Robert, Lai, Timothy, Lai, Chi-Chun, Lalonde, Laurent, Lanzetta, Paolo, Larsen, Michael, Lavina, Adrian, Lee, Won Ki, Lee, ji Eun, Lee, Seong, Levy, Jaime, Lindsell, Lucas, Liu, Mimi, London, Nikolas, Lotery, Andrew, Lozano Rechy, David, Luckie, Alan, Maberley, David, Maeno, Takatoshi, Mahmood, Sajjad, Makkouk, Fuad, Marcus, Dennis, Margherio, Alan, Masse, Helene, Matsubara, Hisashi, Maturi, Raj, Mehta, Sonia, Menon, Geeta, Mentes, Jale, Michels, Mark, Mitamura, Yoshinori, Mitchell, Paul, Mohamed, Quresh, Mones, Jordi, Montemayor Lobo, Rodrigo, Montero, Javier, Moore, Jeffrey, Mori, Ryusaburo, Morori-Katz, Haia, Mukherjee, Raj, Murata, Toshinori, Muzyka-Wozniak, Maria, Nardi, Marco, Narendran, Niro, Nicolo, Massimo, Nielsen, Jared, Nishimura, Tetsuya, Noda, Kousuke, Nowinska, Anna, Oh, Hideyasu, Ohr, Matthew, Okada, Annabelle, Oleksy, Piotr, Ono, Shinji, Ozdek, Sengul, Ozturk, Banu, Pablo, Luis, Park, Kyu Hyung, Parke, D. Wilki, Parravano, Maria Cristina, Patel, Praveen, Patel, Apurva, Patel, Sunil, Patel, Sugat, Pauleikhoff, Daniel, Pearce, Ian, Pearlman, Joel, Petkova, Iva, Pieramici, Dante, Pozdeyeva, Nadezhda, Qureshi, Jawad, Raczynska, Dorota, Ramirez Estudillo, Juan, Rathod, Rajiv, Razavi, Hessam, Regillo, Carl, Reilly, Gayatri, Ricci, Federico, Rich, Ryan, Romanowska-Dixon, Bożena, Rosenblatt, Irit, Ruiz Moreno, Jose Maria, Sacu, Stefan, Saedon, Habiba, Saeed, Usman, Sagong, Min, Sakamoto, Taiji, Sandhu, Sukhpal, Sararols, Laura, Saravia, Mario, Schadlu, Ramin, Schlottmann, Patricio, Sekiryu, Tetsuju, Seres, András, Sermet, Figen, Shah, Sumit, Shah, Rohan, Shah, Ankur, Sheidow, Thomas, Sheth, Veeral, Shiragami, Chieko, Sikorski, Bartosz, Silva, Rufino, Singerman, Lawrence, Sisk, Robert, Sørensen, Torben L., Souied, Eric, Spinak, David-J, Staurenghi, Giovanni, Steinmetz, Robert, Stoller, Glenn, Stoltz, Robert, Suan, Eric, Suner, Ivan, Suzanne, Yzer, Tadayoni, Ramin, Takahashi, Kanji, Takayama, Kei, Taleb, Alexandre, Talks, James, Terasaki, Hiroko, Thompson, John, Toth-Molnar, Edit, Tran, Khoi, Tuli, Raman, Uchiyama, Eduardo, Vajas, Attila, Van Lith-Verhoeven, Janneke, Varsanyi, Balazs, Viola, Francesco, Virgili, Gianni, Vogt, Gábor, Völker, Michael, Warrow, David, Weber, Pamela, Wells, John A., Wickremasinghe, Sanjeewa, Wieland, Mark, Williams, Geoff, Williams, Thomas, Wong, David, Wong, King, Wong, James, Wong, Ian, Wong, Robert, Wowra, Bogumil, Wykoff, Charles C., Yamashita, Ayana, Yasuda, Kanako, Yilmaz, Gursel, Yiu, Glenn, Yoneda, Ai, Yoon, Young Hee, Yoreh, Barak, Yu, HyeongGon, Yu, Seung Young, Yurieva, Tatiana, Zambrano, Alberto, Zatorska, Barbara, Zeolite, Carlos, Heier, Jeffrey S, Khanani, Arshad M, Quezada Ruiz, Carlos, Basu, Karen, Ferrone, Philip J, Brittain, Christopher, Figueroa, Marta S, Lin, Hugh, Holz, Frank G, Patel, Vaibhavi, Lai, Timothy Y Y, Silverman, David, Swaminathan, Balakumar, Cheung, Chui Ming Gemmy, and Wong, Tien Y

Published
2022
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28. Contrasting patterns of variation in weedy traits and unique crop features in divergent populations of US weedy rice (Oryza sativa sp.) in Arkansas and California

Author

Kanapeckas, Kimberly L, Tseng, Te‐Ming, Vigueira, Cynthia C, Ortiz, Aida, Bridges, William C, Burgos, Nilda R, Fischer, Albert J, and Lawton‐Rauh, Amy

Subjects
Agricultural Biotechnology, Agricultural, Veterinary and Food Sciences, Biological Sciences, Genetics, Arkansas, Biological Evolution, California, Cluster Analysis, Evolution, Molecular, Genes, Plant, Genetic Variation, Oryza, Phenotype, Plant Weeds, Principal Component Analysis, Weed Control, agricultural weed, agroecosystem, crop wild relatives, ferality, phenotype, weed management, Environmental Science and Management, Crop and Pasture Production, Entomology, Crop and pasture production, Zoology, Environmental management
Abstract

Weed evolution from crops involves changes in key traits, but it is unclear how genetic and phenotypic variation contribute to weed diversification and productivity. Weedy rice is a conspecific weed of rice (Oryza sativa) worldwide. We used principal component analysis and hierarchical clustering to understand how morphologically and evolutionarily distinct US weedy rice populations persist in rice fields in different locations under contrasting management regimes. Further, we used a representative subset of 15 sequence-tagged site fragments of expressed genes from global Oryza to assess genome-wide sequence variation among populations.Crop hull color and crop-overlapping maturity dates plus awns, seed (panicle) shattering (> 50%), pigmented pericarp and stature variation (30.2% of total phenotypic variance) characterize genetically less diverse California weedy rice. By contrast, wild-like hull color, seed shattering (> 50%) and stature differences (55.8% of total phenotypic variance) typify genetically diverse weedy rice ecotypes in Arkansas.Recent de-domestication of weedy species - such as in California weedy rice - can involve trait combinations indistinguishable from the crop. This underscores the need for strict seed certification with genetic monitoring and proactive field inspection to prevent proliferation of weedy plant types. In established populations, tillage practice may affect weed diversity and persistence over time. © 2017 Society of Chemical Industry.

Published
2018

31. Phase 1 DAVIO Trial: EYP-1901 Bioerodible, Sustained-Delivery Vorolanib Insert in Patients with Wet Age-related Macular Degeneration

Author

Patel, Sunil, primary, Storey, Philip P., additional, Barakat, Mark R., additional, Hershberger, Vrinda, additional, Bridges, William Z., additional, Eichenbaum, David A., additional, Lally, David R., additional, Boyer, David S., additional, Bakri, Sophie J., additional, Roy, Monica, additional, and Paggiarino, Dario A., additional

Published
2024
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33. Cycloaddition of Phenyltriazolinedione with Carbazole-Alkynes and Yne-Carbamates to Access Diazacyclobutenes

Author

Miller, Brock A., primary, Narangoda, Chandima J., additional, Kwain, Samuel, additional, Bridges, William T., additional, Noori, Monireh, additional, Solomon, Erin E., additional, Bragg, Alexis A., additional, Sung, Alex T., additional, Iwai, Yusuke, additional, Ulisse, Lauren, additional, Schmidt, William H., additional, McMillen, Colin D., additional, Dominy, Brian N., additional, and Whitehead, Daniel C., additional

Published
2024
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37. Longitudinal trials illustrate interactive effects between declining Bt efficacy against Helicoverpa zea(Lepidoptera: Noctuidae) and planting dates of corn

Author

Reay-Jones, Francis P F, Buntin, G David, Reisig, Dominic D, and Bridges, William C

Abstract

Helicoverpa zea(Boddie) (Lepidoptera: Noctuidae) has evolved resistance to insecticidal toxins from Bacillus thuringiensis(Bt) Berliner (Bacillales: Bacillaceae) expressed in genetically engineered corn, Zea maysL. This study provides an overview of field trials from Georgia, North Carolina, and South Carolina evaluating Bt and non-Bt corn hybrids from 2009 to 2022 to show changes in susceptibility in H. zeato Bt corn. The reduction in kernel injury relative to a non-Bt hybrid averaged across planting dates generally declined over time for Cry1A.105 + Cry2Ab2 corn. In addition, there was a significant interaction with planting date used as a covariate. The reduction in kernel injury remained above 80% and did not vary with planting date from 2009 to 2014, whereas a significant decline with planting date was found in this reduction from 2015 to 2022. For Cry1Ab + Cry1F corn, the reduction in kernel injury relative to a non-Bt hybrid averaged across planting dates did not vary among years. The reduction in kernel injury significantly declined with planting date from 2012 to 2022. Kernel injury as a proxy for H. zeapressure was greater in late-planted trials in non-Bt corn hybrids. Our study showed that Bt hybrids expressing Cry1A.105 + Cry2Ab2 are now less effective in later planted trials in reducing H. zeainjury; however, this was not the case during the earlier years of adoption of corn expressing these 2 toxins when resistance alleles were likely less frequent in H. zeapopulations. The implications for management of H. zeaand for insect resistance management are discussed.

Published
2024
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38. Students' Gendered Perceptions of Mathematics in Middle Grades Single-Sex and Coeducational Classrooms

Author

Kombe, Dennis, Che, S. Megan, and Bridges, William

Abstract

With the introduction of single-sex classroom settings in coeducational public schools, there is an ongoing debate as to whether single-sex education may reduce or reinforce traditional stereotypes and gender roles. In this article we present findings from a study that investigated the extent to which mathematics is perceived as a gendered domain among adolescent students enrolled in single-sex classes and coeducational classes. Further we analyzed the relationships between student characteristics, class-type, and teacher variables on students' perceptions of gender in mathematics. Findings from this study challenge the traditional view of mathematics as a male domain. Female participants more frequently considered mathematics to be a female domain than the male participants. Male participants, on the other hand, typically did not stereotype the mathematics as a gendered domain. Results from this study do not indicate, for girls at least, that participation in single-sex classes results in a greater propensity to stereotype mathematics as a gendered domain than would be the case in coeducational classes. This study contributes to the evolving discourse and understanding of adolescents' gendered attitudes and beliefs towards mathematics--especially in light of stereotyped assertions that have a bearing on efforts to promote the learning of mathematics and science.

Published
2019
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39. Postschool Engagement Predictors for Youth with Intellectual Disability: Results from South Carolina

Author

Prince, Angela M.T, Plotner, Anthony J., and Bridges, William C.

Abstract

Postschool outcomes of youth with intellectual disability (ID) continue to trouble practitioners and scholars. The purpose of this study was to analyze postschool engagement outcome data for 360 survey respondents with ID in South Carolina in the areas of employment and postsecondary education/training. Specifically, we examined the relationship of special education exit reason, as well as, student, school, and district variables to youth's postschool engagement. We used logistic regression to estimate probability of engagement one year after exiting high school. Results indicated that special education exit reason, gender, school retention rates, district attendance rates, percentage of students with disabilities within a district, percentage of students within a district receiving free and reduced lunch, district retention rates, and district suspension/expulsion rates were significantly related to three postschool engagement outcomes. Implications for future research and practice are discussed.

Published
2019
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41. TENAYA and LUCERNE

Author

Khanani, Arshad M., primary, Kotecha, Aachal, additional, Chang, Andrew, additional, Chen, Shih-Jen, additional, Chen, Youxin, additional, Guymer, Robyn, additional, Heier, Jeffrey S., additional, Holz, Frank G., additional, Iida, Tomohiro, additional, Ives, Jane A., additional, Lim, Jennifer I., additional, Lin, Hugh, additional, Michels, Stephan, additional, Quezada Ruiz, Carlos, additional, Schmidt-Erfurth, Ursula, additional, Silverman, David, additional, Singh, Rishi, additional, Swaminathan, Balakumar, additional, Willis, Jeffrey R., additional, Tadayoni, Ramin, additional, Abbey, Ashkan, additional, Abdulaeva, Elmira, additional, Abraham, Prema, additional, Adan Civera, Alfredo, additional, Agostini, Hansjurgen, additional, Alezzandrini, Arturo, additional, Alfaro, Virgil, additional, Almony, Arghavan, additional, Altay, Lebriz, additional, Amini, Payam, additional, Antoszyk, Andrew, additional, Aradi, Etelka, additional, Arias, Luis, additional, Arnold, Jennifer, additional, Asaria, Riaz, additional, Astakhov, Sergei, additional, Astakhov, Yury, additional, Awh, Carl C., additional, Balaratnasingam, Chandra, additional, Banerjee, Sanjiv, additional, Baumal, Caroline, additional, Becker, Matthias, additional, Belfort, Rubens, additional, Bratko, Galina, additional, Bridges, William Z., additional, Brown, Jamin, additional, Brown, David M., additional, Budzinskaya, Maria, additional, Buffet, Sylvia, additional, Burgess, Stuart, additional, Byon, Iksoo, additional, Cagini, Carlo, additional, Calzada, Jorge, additional, Cameron, Stone, additional, Campochiaro, Peter, additional, Carlson, John, additional, Carneiro, Angela, additional, Chan, Clement, additional, Chang, Emmanuel, additional, Chao, Daniel, additional, Chaudhry, Nauman, additional, Chee, Caroline, additional, Cheek, Andrew, additional, Chen, San-Ni, additional, Cheung, Gemmy, additional, Chexal, Saradha, additional, Chittum, Mark, additional, Chow, David, additional, Cole, Abosede, additional, Connolly, Brian, additional, Cornut, Pierre Loic, additional, Couvillion, Stephen, additional, Danzig, Carl, additional, Daskalov, Vesselin, additional, Dessouki, Amr, additional, Devin, Francois, additional, Dollin, Michael, additional, Dolz, Rosa, additional, Downey, Louise, additional, Dreyer, Richard, additional, Dugel, Pravin, additional, Eichenbaum, David, additional, Eldem, Bora, additional, Engstrom, Robert, additional, Escobar, Joan Josep, additional, Eter, Nicole, additional, Faber, David W., additional, Falk, Naomi, additional, Feiner, Leonard, additional, Vega, Alvaro Fernandez, additional, Ferrone, Philip, additional, Figueroa, Marta, additional, Fine, Howard, additional, Fineman, Mitchell, additional, Fox, Gregory M., additional, Francais, Catherine, additional, Franco, Pablo, additional, Fraser-Bell, Samantha, additional, Fung, Nicholas, additional, Sola, Federico Furno, additional, Gale, Richard, additional, Garcia-Layana, Alfredo, additional, Gasperini, Julie, additional, Gawecki, Maciej, additional, Ghanchi, Faruque, additional, Gill, Manjot, additional, Giunta, Michel, additional, Glaser, David, additional, Goldstein, Michaella, additional, Ulla, Francisco Gomez, additional, Gomi, Fumi, additional, Gonzalez, Victor, additional, Graff, Jordan, additional, Gupta, Sunil, additional, Guthoff, Rainer, additional, Haas, Anton, additional, Hampton, Robert, additional, Hatz, Katja, additional, Hayashi, Ken, additional, Heier, Jeffrey, additional, Herba, Ewa, additional, Hershberger, Vrinda, additional, Higgins, Patrick, additional, Holekamp, Nancy, additional, Honda, Shigeru, additional, Howard, James, additional, Hu, Allen, additional, Huddleston, Stephen, additional, Imaizumi, Hiroko, additional, Ito, Yasuo, additional, Ito, Yasuki, additional, Itty, Sujit, additional, Javey, Golnaz, additional, Javid, Cameron, additional, Kaga, Tatsushi, additional, Kaluzny, Jakub, additional, Kang, Se Woong, additional, Kapoor, Kapil, additional, Karabas, Levent, additional, Kawasaki, Tsutomu, additional, Kelty, Patrick, additional, Kerenyi, Agnes, additional, Khanani, Arshad, additional, Khoramnia, Ramin, additional, Khurana, Rahul, additional, Kimura, Kazuhiro, additional, Klein-Mascia, Kendra, additional, Kobayashi, Namie, additional, Kodjikian, Laurent, additional, Koizumi, Hideki, additional, Kokame, Gregg, additional, Kulikov, Alexey, additional, Kwong, Henry, additional, Kwun, Robert, additional, Lai, Timothy, additional, Lai, Chi-Chun, additional, Lalonde, Laurent, additional, Lanzetta, Paolo, additional, Larsen, Michael, additional, Lavina, Adrian, additional, Lee, Won Ki, additional, Lee, ji Eun, additional, Lee, Seong, additional, Levy, Jaime, additional, Lindsell, Lucas, additional, Liu, Mimi, additional, London, Nikolas, additional, Lotery, Andrew, additional, Lozano Rechy, David, additional, Luckie, Alan, additional, Maberley, David, additional, Maeno, Takatoshi, additional, Mahmood, Sajjad, additional, Makkouk, Fuad, additional, Marcus, Dennis, additional, Margherio, Alan, additional, Masse, Helene, additional, Matsubara, Hisashi, additional, Maturi, Raj, additional, Mehta, Sonia, additional, Menon, Geeta, additional, Mentes, Jale, additional, Michels, Mark, additional, Mitamura, Yoshinori, additional, Mitchell, Paul, additional, Mohamed, Quresh, additional, Mones, Jordi, additional, Lobo, Rodrigo Montemayor, additional, Montero, Javier, additional, Moore, Jeffrey, additional, Mori, Ryusaburo, additional, Morori-Katz, Haia, additional, Mukherjee, Raj, additional, Murata, Toshinori, additional, Muzyka-Wozniak, Maria, additional, Nardi, Marco, additional, Narendran, Niro, additional, Nicolo, Massimo, additional, Nielsen, Jared, additional, Nishimura, Tetsuya, additional, Noda, Kousuke, additional, Nowinska, Anna, additional, Oh, Hideyasu, additional, Ohr, Matthew, additional, Okada, Annabelle, additional, Oleksy, Piotr, additional, Ono, Shinji, additional, Ozdek, Sengul, additional, Ozturk, Banu, additional, Pablo, Luis, additional, Park, Kyu Hyung, additional, Parke, D. Wilk, additional, Parravano, Maria Cristina, additional, Patel, Praveen, additional, Patel, Apurva, additional, Patel, Sunil, additional, Patel, Sugat, additional, Pauleikhoff, Daniel, additional, Pearce, Ian, additional, Pearlman, Joel, additional, Petkova, Iva, additional, Pieramici, Dante, additional, Pozdeyeva, Nadezhda, additional, Qureshi, Jawad, additional, Raczynska, Dorota, additional, Ramirez Estudillo, Juan, additional, Rathod, Rajiv, additional, Razavi, Hessam, additional, Regillo, Carl, additional, Reilly, Gayatri, additional, Ricci, Federico, additional, Rich, Ryan, additional, Romanowska-Dixon, Bożena, additional, Rosenblatt, Irit, additional, Ruiz Moreno, Jose Maria, additional, Sacu, Stefan, additional, Saedon, Habiba, additional, Saeed, Usman, additional, Sagong, Min, additional, Sakamoto, Taiji, additional, Sandhu, Sukhpal, additional, Sararols, Laura, additional, Saravia, Mario, additional, Schadlu, Ramin, additional, Schlottmann, Patricio, additional, Sekiryu, Tetsuju, additional, Seres, András, additional, Sermet, Figen, additional, Shah, Sumit, additional, Shah, Rohan, additional, Shah, Ankur, additional, Sheidow, Thomas, additional, Sheth, Veeral, additional, Shiragami, Chieko, additional, Sikorski, Bartosz, additional, Silva, Rufino, additional, Singerman, Lawrence, additional, Sisk, Robert, additional, Sørensen, Torben L., additional, Souied, Eric, additional, Spinak, David-J., additional, Staurenghi, Giovanni, additional, Steinmetz, Robert, additional, Stoller, Glenn, additional, Stoltz, Robert, additional, Suan, Eric, additional, Suner, Ivan, additional, Yzer, Suzanne, additional, Takahashi, Kanji, additional, Takayama, Kei, additional, Taleb, Alexandre, additional, Talks, James, additional, Terasaki, Hiroko, additional, Thompson, John, additional, Toth-Molnar, Edit, additional, Tran, Khoi, additional, Tuli, Raman, additional, Uchiyama, Eduardo, additional, Vajas, Attila, additional, Lith-Verhoeven, Janneke Van, additional, Varsanyi, Balazs, additional, Viola, Francesco, additional, Virgili, Gianni, additional, Vogt, Gábor, additional, Völker, Michael, additional, Warrow, David, additional, Weber, Pamela, additional, Wells, John A., additional, Wickremasinghe, Sanjeewa, additional, Wieland, Mark, additional, Williams, Geoff, additional, Williams, Thomas, additional, Wong, David, additional, Wong, King, additional, Wong, James, additional, Wong, Ian, additional, Wong, Robert, additional, Wowra, Bogumil, additional, Wykoff, Charles C., additional, Yamashita, Ayana, additional, Yasuda, Kanako, additional, Yilmaz, Gursel, additional, Yiu, Glenn, additional, Yoneda, Ai, additional, Yoon, Young Hee, additional, Yoreh, Barak, additional, Yu, Hyeong Gon, additional, Yu, Seung Young, additional, Yurieva, Tatiana, additional, Zambrano, Alberto, additional, Zatorska, Barbara, additional, and Zeolite, Carlos, additional

Published
2024
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47. Predictors of Postschool Education/Training and Employment Outcomes for Youth with Disabilities

Author

Prince, Angela M. T., Hodge, Janie, Bridges, William C., and Katsiyannis, Antonis

Abstract

Youth with disabilities have consistently poor postschool engagement outcomes in employment and postsecondary education and training. At least once every 6 years, states are required to submit a State Performance Plan in which they report performance on the progress of students with disabilities (20 U.S.C. 1416(b)(1)). Indicator 14 requires states to collect postschool outcome data 1 year after students exit high school. The purpose of this exploratory study was to examine the impact of student-, school-, district-level, and combined (student + school + district) factors on engagement outcomes for youth with high incidence disabilities across 3 years. Findings from logistic regression analyses indicate that student-level, district-level, and combined factors were significant in predicting postschool outcomes of employment and postsecondary education.

Published
2018
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48. Impact of Course Policy Changes on Calculus I DFW Rates

Author

Norton, Paran, Bridges, William, and High, Karen

Abstract

This paper examines the impact of departmental policy changes on the trend in DFW proportions for introductory calculus at a large research university, where DFW denotes the proportion of students receiving a grade of D, F, or withdrawing from the course. We defined three distinct policy periods: Traditional (2002-2005), Active Learning (SCALE-UP) (2006-2013), and Return to Traditional (2014-2016). Regression analysis showed DFW proportions were increasing during the Traditional period, significantly decreased after the switch to SCALE-UP, remained fairly consistent during the SCALE-UP period, and then significantly increased during Return to Traditional. Individual trends for D, F, and W proportions were also analyzed. The two policy changes had the greatest influence on the trend in F and W proportions. Potential factors that could influence a student to withdraw from the course were examined. Students who withdrew had midterm averages similar to students who failed the course during the SCALE-UP period, but their averages were significantly lower than the F students during the Return to Traditional period.

Published
2018

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