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3. Bayesian profile regression to study the ecologic associations of correlated environmental exposures with excess mortality risk during the first year of the Covid-19 epidemic in lombardy, Italy

Author

Coker, E, Molitor, J, Liverani, S, Martin, J, Maranzano, P, Pontarollo, N, Vergalli, S, Coker, Eric S., Molitor, John, Liverani, Silvia, Martin, James, Maranzano, Paolo, Pontarollo, Nicola, Vergalli, Sergio, Coker, E, Molitor, J, Liverani, S, Martin, J, Maranzano, P, Pontarollo, N, Vergalli, S, Coker, Eric S., Molitor, John, Liverani, Silvia, Martin, James, Maranzano, Paolo, Pontarollo, Nicola, and Vergalli, Sergio

Abstract

Many countries, including Italy, have experienced significant social and spatial inequalities in mortality during the Covid-19 pandemic. This study applies a multiple exposures framework to investigate how joint place-based factors influence spatial inequalities of excess mortality during the first year of the Covid −19 pandemic in the Lombardy region of Italy. For the Lombardy region, we integrated municipality-level data on all-cause mortality between 2015 and 2020 with 13 spatial covariates, including 5-year average concentrations of six air pollutants, the average temperature in 2020, and multiple socio-demographic factors, and health facilities per capita. Using the clustering algorithm Bayesian profile regression, we fit spatial covariates jointly to identify clusters of municipalities with similar exposure profiles and estimated associations between clusters and excess mortality in 2020. Cluster analysis resulted in 13 clusters. Controlling for spatial autocorrelation of excess mortality and health-protective agency, two clusters had significantly elevated excess mortality than the rest of Lombardy. Municipalities in these highest-risk clusters are in Bergamo, Brescia, and Cremona provinces. The highest risk cluster (C11) had the highest long-term particulate matter air pollution levels (PM2.5 and PM10) and significantly elevated NO2 and CO air pollutants, temperature, proportion ≤18 years, and male-to-female ratio. This cluster is significantly lower for income and ≥65 years. The other high-risk cluster, Cluster 10 (C10), is elevated significantly for ozone but significantly lower for other air pollutants. Covariates with elevated levels for C10 include proportion 65 years or older and a male-to-female ratio. Cluster 10 is significantly lower for income, temperature, per capita health facilities, ≤18 years, and population density. Our results suggest that joint built, natural, and socio-demographic factors influenced spatial inequalities of excess mortality

Published
2023

7. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

Author

Menden M, Wang D, Mason M, Szalai B, Bulusu K, Guan Y, Yu T, Kang J, Jeon M, Wolfinger R, Nguyen T, Zaslavskiy M, Jang I, Ghazoui Z, Ahsen M, Vogel R, Neto E, Norman T, Tang E, Garnett M, Di Veroli G, Fawell S, Stolovitzky G, Guinney J, Dry J, Saez-Rodriguez J, Abante J, Abecassis B, Aben N, Aghamirzaie D, Aittokallio T, Akhtari F, Al-lazikani B, Alam T, Allam A, Allen C, de Almeida M, Altarawy D, Alves V, Amadoz A, Anchang B, Antolin A, Ash J, Aznar V, Ba-alawi W, Bagheri M, Bajic V, Ball G, Ballester P, Baptista D, Bare C, Bateson M, Bender A, Bertrand D, Wijayawardena B, Boroevich K, Bosdriesz E, Bougouffa S, Bounova G, Brouwer T, Bryant B, Calaza M, Calderone A, Calza S, Capuzzi S, Carbonell-Caballero J, Carlin D, Carter H, Castagnoli L, Celebi R, Cesareni G, Chang H, Chen G, Chen H, Cheng L, Chernomoretz A, Chicco D, Cho K, Cho S, Choi D, Choi J, Choi K, Choi M, De Cock M, Coker E, Cortes-Ciriano I, Cserzo M, Cubuk C, Curtis C, Van Daele D, Dang C, Dijkstra T, Dopazo J, Draghici S, Drosou A, Dumontier M, Ehrhart F, Eid F, ElHefnawi M, Elmarakeby H, van Engelen B, Engin H, de Esch I, Evelo C, Falcao A, Farag S, Fernandez-Lozano C, Fisch K, Flobak A, Fornari C, Foroushani A, Fotso D, Fourches D, Friend S, Frigessi A, Gao F, Gao X, Gerold J, Gestraud P, Ghosh S, Gillberg J, Godoy-Lorite A, Godynyuk L, Godzik A, Goldenberg A, Gomez-Cabrero D, Gonen M, de Graaf C, Gray H, Grechkin M, Guimera R, Guney E, Haibe-Kains B, Han Y, Hase T, He D, He L, Heath L, Hellton K, Helmer-Citterich M, Hidalgo M, Hidru D, Hill S, Hochreiter S, Hong S, Hovig E, Hsueh Y, Hu Z, Huang J, Huang R, Hunyady L, Hwang J, Hwang T, Hwang W, Hwang Y, Isayev O, Walk O, Jack J, Jahandideh S, Ji J, Jo Y, Kamola P, Kanev G, Karacosta L, Karimi M, Kaski S, Kazanov M, Khamis A, Khan S, Kiani N, Kim A, Kim J, Kim K, Kim S, Kim Y, Kirk P, Kitano H, Klambauer G, Knowles D, Ko M, Kohn-Luque A, Kooistra A, Kuenemann M, Kuiper M, Kurz C, Kwon M, van Laarhoven T, Laegreid A, Lederer S, Lee H, Lee J, Lee Y, Leppaho E, Lewis R, Li J, Li L, Liley J, Lim W, Lin C, Liu Y, Lopez Y, Low J, Lysenko A, Machado D, Madhukar N, De Maeyer D, Malpartida A, Mamitsuka H, Marabita F, Marchal K, Marttinen P, Mason D, Mazaheri A, Mehmood A, Mehreen A, Michaut M, Miller R, Mitsopoulos C, Modos D, Van Moerbeke M, Moo K, Motsinger-Reif A, Movva R, Muraru S, Muratov E, Mushthofa M, Nagarajan N, Nakken S, Nath A, Neuvial P, Newton R, Ning Z, De Niz C, Oliva B, Olsen C, Palmeri A, Panesar B, Papadopoulos S, Park J, Park S, Pawitan Y, Peluso D, Pendyala S, Peng J, Perfetto L, Pirro S, Plevritis S, Politi R, Poon H, Porta E, Prellner I, Preuer K, Pujana M, Ramnarine R, Reid J, Reyal F, Richardson S, Ricketts C, Rieswijk L, Rocha M, Rodriguez-Gonzalvez C, Roell K, Rotroff D, de Ruiter J, Rukawa P, Sadacca B, Safikhani Z, Safitri F, Sales-Pardo M, Sauer S, Schlichting M, Seoane J, Serra J, Shang M, Sharma A, Sharma H, Shen Y, Shiga M, Shin M, Shkedy Z, Shopsowitz K, Sinai S, Skola D, Smirnov P, Soerensen I, Soerensen P, Song J, Song S, Soufan O, Spitzmueller A, Steipe B, Suphavilai C, Tamayo S, Tamborero D, Tang J, Tanoli Z, Tarres-Deulofeu M, Tegner J, Thommesen L, Tonekaboni S, Tran H, De Troyer E, Truong A, Tsunoda T, Turu G, Tzeng G, Verbeke L, Videla S, Vis D, Voronkov A, Votis K, Wang A, Wang H, Wang P, Wang S, Wang W, Wang X, Wennerberg K, Wernisch L, Wessels L, van Westen G, Westerman B, White S, Willighagen E, Wurdinger T, Xie L, Xie S, Xu H, Yadav B, Yau C, Yeerna H, Yin J, Yu M, Yun S, Zakharov A, Zamichos A, Zanin M, Zeng L, Zenil H, Zhang F, Zhang P, Zhang W, Zhao H, Zhao L, Zheng W, Zoufir A, Zucknick M, AstraZeneca-Sanger Drug Combinatio, Ege Üniversitesi, Gönen, Mehmet (ORCID 0000-0002-2483-075X & YÖK ID 237468), Menden, Michael P., Wang, Dennis, Mason, Mike J., Szalai, Bence, Bulusu, Krishna C., Guan, Yuanfang, Yu, Thomas, Kang, Jaewoo, Jeon, Minji, Wolfinger, Russ, Nguyen, Tin, Zaslavskiy, Mikhail, Jang, In Sock, Ghazoui, Zara, Ahsen, Mehmet Eren, Vogel, Robert, Neto, Elias Chaibub, Norman, Thea, Tang, Eric K. Y., Garnett, Mathew J., Di Veroli, Giovanni Y., Fawell, Stephen, Stolovitzky, Gustavo, Guinney, Justin, Dry, Jonathan R., Saez-Rodriguez, Julio, Abante, Jordi, Abecassis, Barbara Schmitz, Aben, Nanne, Aghamirzaie, Delasa, Aittokallio, Tero, Akhtari, Farida S., Al-lazikani, Bissan, Alam, Tanvir, Allam, Amin, Allen, Chad, de Almeida, Mariana Pelicano, Altarawy, Doaa, Alves, Vinicius, Amadoz, Alicia, Anchang, Benedict, Antolin, Albert A., Ash, Jeremy R., Romeo Aznar, Victoria, Ba-alawi, Wail, Bagheri, Moeen, Bajic, Vladimir, Ball, Gordon, Ballester, Pedro J., Baptista, Delora, Bare, Christopher, Bateson, Mathilde, Bender, Andreas, Bertrand, Denis, Wijayawardena, Bhagya, Boroevich, Keith A., Bosdriesz, Evert, Bougouffa, Salim, Bounova, Gergana, Brouwer, Thomas, Bryant, Barbara, Calaza, Manuel, Calderone, Alberto, Calza, Stefano, Capuzzi, Stephen, Carbonell-Caballero, Jose, Carlin, Daniel, Carter, Hannah, Castagnoli, Luisa, Celebi, Remzi, Cesareni, Gianni, Chang, Hyeokyoon, Chen, Guocai, Chen, Haoran, Chen, Huiyuan, Cheng, Lijun, Chernomoretz, Ariel, Chicco, Davide, Cho, Kwang-Hyun, Cho, Sunghwan, Choi, Daeseon, Choi, Jaejoon, Choi, Kwanghun, Choi, Minsoo, De Cock, Martine, Coker, Elizabeth, Cortes-Ciriano, Isidro, Cserzo, Miklos, Cubuk, Cankut, Curtis, Christina, Van Daele, Dries, Dang, Cuong C., Dijkstra, Tjeerd, Dopazo, Joaquin, Draghici, Sorin, Drosou, Anastasios, Dumontier, Michel, Ehrhart, Friederike, Eid, Fatma-Elzahraa, ElHefnawi, Mahmoud, Elmarakeby, Haitham, van Engelen, Bo, Engin, Hatice Billur, de Esch, Iwan, Evelo, Chris, Falcao, Andre O., Farag, Sherif, Fernandez-Lozano, Carlos, Fisch, Kathleen, Flobak, Asmund, Fornari, Chiara, Foroushani, Amir B. K., Fotso, Donatien Chedom, Fourches, Denis, Friend, Stephen, Frigessi, Arnoldo, Gao, Feng, Gao, Xiaoting, Gerold, Jeffrey M., Gestraud, Pierre, Ghosh, Samik, Gillberg, Jussi, Godoy-Lorite, Antonia, Godynyuk, Lizzy, Godzik, Adam, Goldenberg, Anna, Gomez-Cabrero, David, de Graaf, Chris, Gray, Harry, Grechkin, Maxim, Guimera, Roger, Guney, Emre, Haibe-Kains, Benjamin, Han, Younghyun, Hase, Takeshi, He, Di, He, Liye, Heath, Lenwood S., Hellton, Kristoffer H., Helmer-Citterich, Manuela, Hidalgo, Marta R., Hidru, Daniel, Hill, Steven M., Hochreiter, Sepp, Hong, Seungpyo, Hovig, Eivind, Hsueh, Ya-Chih, Hu, Zhiyuan, Huang, Justin K., Huang, R. Stephanie, Hunyady, Laszlo, Hwang, Jinseub, Hwang, Tae Hyun, Hwang, Woochang, Hwang, Yongdeuk, Isayev, Olexandr, Walk, Oliver Bear Don't, Jack, John, Jahandideh, Samad, Ji, Jiadong, Jo, Yousang, Kamola, Piotr J., Kanev, Georgi K., Karacosta, Loukia, Karimi, Mostafa, Kaski, Samuel, Kazanov, Marat, Khamis, Abdullah M., Khan, Suleiman Ali, Kiani, Narsis A., Kim, Allen, Kim, Jinhan, Kim, Juntae, Kim, Kiseong, Kim, Kyung, Kim, Sunkyu, Kim, Yongsoo, Kim, Yunseong, Kirk, Paul D. W., Kitano, Hiroaki, Klambauer, Gunter, Knowles, David, Ko, Melissa, Kohn-Luque, Alvaro, Kooistra, Albert J., Kuenemann, Melaine A., Kuiper, Martin, Kurz, Christoph, Kwon, Mijin, van Laarhoven, Twan, Laegreid, Astrid, Lederer, Simone, Lee, Heewon, Lee, Jeon, Lee, Yun Woo, Leppaho, Eemeli, Lewis, Richard, Li, Jing, Li, Lang, Liley, James, Lim, Weng Khong, Lin, Chieh, Liu, Yiyi, Lopez, Yosvany, Low, Joshua, Lysenko, Artem, Machado, Daniel, Madhukar, Neel, De Maeyer, Dries, Malpartida, Ana Belen, Mamitsuka, Hiroshi, Marabita, Francesco, Marchal, Kathleen, Marttinen, Pekka, Mason, Daniel, Mazaheri, Alireza, Mehmood, Arfa, Mehreen, Ali, Michaut, Magali, Miller, Ryan A., Mitsopoulos, Costas, Modos, Dezso, Van Moerbeke, Marijke, Moo, Keagan, Motsinger-Reif, Alison, Movva, Rajiv, Muraru, Sebastian, Muratov, Eugene, Mushthofa, Mushthofa, Nagarajan, Niranjan, Nakken, Sigve, Nath, Aritro, Neuvial, Pierre, Newton, Richard, Ning, Zheng, De Niz, Carlos, Oliva, Baldo, Olsen, Catharina, Palmeri, Antonio, Panesar, Bhawan, Papadopoulos, Stavros, Park, Jaesub, Park, Seonyeong, Park, Sungjoon, Pawitan, Yudi, Peluso, Daniele, Pendyala, Sriram, Peng, Jian, Perfetto, Livia, Pirro, Stefano, Plevritis, Sylvia, Politi, Regina, Poon, Hoifung, Porta, Eduard, Prellner, Isak, Preuer, Kristina, Angel Pujana, Miguel, Ramnarine, Ricardo, Reid, John E., Reyal, Fabien, Richardson, Sylvia, Ricketts, Camir, Rieswijk, Linda, Rocha, Miguel, Rodriguez-Gonzalvez, Carmen, Roell, Kyle, Rotroff, Daniel, de Ruiter, Julian R., Rukawa, Ploy, Sadacca, Benjamin, Safikhani, Zhaleh, Safitri, Fita, Sales-Pardo, Marta, Sauer, Sebastian, Schlichting, Moritz, Seoane, Jose A., Serra, Jordi, Shang, Ming-Mei, Sharma, Alok, Sharma, Hari, Shen, Yang, Shiga, Motoki, Shin, Moonshik, Shkedy, Ziv, Shopsowitz, Kevin, Sinai, Sam, Skola, Dylan, Smirnov, Petr, Soerensen, Izel Fourie, Soerensen, Peter, Song, Je-Hoon, Song, Sang Ok, Soufan, Othman, Spitzmueller, Andreas, Steipe, Boris, Suphavilai, Chayaporn, Tamayo, Sergio Pulido, Tamborero, David, Tang, Jing, Tanoli, Zia-ur-Rehman, Tarres-Deulofeu, Marc, Tegner, Jesper, Thommesen, Liv, Tonekaboni, Seyed Ali Madani, Tran, Hong, De Troyer, Ewoud, Truong, Amy, Tsunoda, Tatsuhiko, Turu, Gabor, Tzeng, Guang-Yo, Verbeke, Lieven, Videla, Santiago, Vis, Daniel, Voronkov, Andrey, Votis, Konstantinos, Wang, Ashley, Wang, Hong-Qiang Horace, Wang, Po-Wei, Wang, Sheng, Wang, Wei, Wang, Xiaochen, Wang, Xin, Wennerberg, Krister, Wernisch, Lorenz, Wessels, Lodewyk, van Westen, Gerard J. P., Westerman, Bart A., White, Simon Richard, Willighagen, Egon, Wurdinger, Tom, Xie, Lei, Xie, Shuilian, Xu, Hua, Yadav, Bhagwan, Yau, Christopher, Yeerna, Huwate, Yin, Jia Wei, Yu, Michael, Yu, MinHwan, Yun, So Jeong, Zakharov, Alexey, Zamichos, Alexandros, Zanin, Massimiliano, Zeng, Li, Zenil, Hector, Zhang, Frederick, Zhang, Pengyue, Zhang, Wei, Zhao, Hongyu, Zhao, Lan, Zheng, Wenjin, Zoufir, Azedine, Zucknick, Manuela, College of Engineering, Department of Industrial Engineering, Institute of Data Science, RS: FSE DACS IDS, Bioinformatica, RS: NUTRIM - R1 - Obesity, diabetes and cardiovascular health, RS: FHML MaCSBio, Promovendi NTM, Tero Aittokallio / Principal Investigator, Bioinformatics, Institute for Molecular Medicine Finland, Hu, Z, Fotso, DC, Menden, M, Wang, D, Mason, M, Szalai, B, Bulusu, K, Guan, Y, Yu, T, Kang, J, Jeon, M, Wolfinger, R, Nguyen, T, Zaslavskiy, M, Abante, J, Abecassis, B, Aben, N, Aghamirzaie, D, Aittokallio, T, Akhtari, F, Al-lazikani, B, Alam, T, Allam, A, Allen, C, de Almeida, M, Altarawy, D, Alves, V, Amadoz, A, Anchang, B, Antolin, A, Ash, J, Aznar, V, Ba-alawi, W, Bagheri, M, Bajic, V, Ball, G, Ballester, P, Baptista, D, Bare, C, Bateson, M, Bender, A, Bertrand, D, Wijayawardena, B, Boroevich, K, Bosdriesz, E, Bougouffa, S, Bounova, G, Brouwer, T, Bryant, B, Calaza, M, Calderone, A, Calza, S, Capuzzi, S, Carbonell-Caballero, J, Carlin, D, Carter, H, Castagnoli, L, Celebi, R, Cesareni, G, Chang, H, Chen, G, Chen, H, Cheng, L, Chernomoretz, A, Chicco, D, Cho, K, Cho, S, Choi, D, Choi, J, Choi, K, Choi, M, Cock, M, Coker, E, Cortes-Ciriano, I, Cserzo, M, Cubuk, C, Curtis, C, Daele, D, Dang, C, Dijkstra, T, Dopazo, J, Draghici, S, Drosou, A, Dumontier, M, Ehrhart, F, Eid, F, Elhefnawi, M, Elmarakeby, H, van Engelen, B, Engin, H, de Esch, I, Evelo, C, Falcao, A, Farag, S, Fernandez-Lozano, C, Fisch, K, Flobak, A, Fornari, C, Foroushani, A, Fotso, D, Fourches, D, Friend, S, Frigessi, A, Gao, F, Gao, X, Gerold, J, Gestraud, P, Ghosh, S, Gillberg, J, Godoy-Lorite, A, Godynyuk, L, Godzik, A, Goldenberg, A, Gomez-Cabrero, D, Gonen, M, de Graaf, C, Gray, H, Grechkin, M, Guimera, R, Guney, E, Haibe-Kains, B, Han, Y, Hase, T, He, D, He, L, Heath, L, Hellton, K, Helmer-Citterich, M, Hidalgo, M, Hidru, D, Hill, S, Hochreiter, S, Hong, S, Hovig, E, Hsueh, Y, Huang, J, Huang, R, Hunyady, L, Hwang, J, Hwang, T, Hwang, W, Hwang, Y, Isayev, O, Don't Walk, O, Jack, J, Jahandideh, S, Ji, J, Jo, Y, Kamola, P, Kanev, G, Karacosta, L, Karimi, M, Kaski, S, Kazanov, M, Khamis, A, Khan, S, Kiani, N, Kim, A, Kim, J, Kim, K, Kim, S, Kim, Y, Kirk, P, Kitano, H, Klambauer, G, Knowles, D, Ko, M, Kohn-Luque, A, Kooistra, A, Kuenemann, M, Kuiper, M, Kurz, C, Kwon, M, van Laarhoven, T, Laegreid, A, Lederer, S, Lee, H, Lee, J, Lee, Y, Lepp_aho, E, Lewis, R, Li, J, Li, L, Liley, J, Lim, W, Lin, C, Liu, Y, Lopez, Y, Low, J, Lysenko, A, Machado, D, Madhukar, N, Maeyer, D, Malpartida, A, Mamitsuka, H, Marabita, F, Marchal, K, Marttinen, P, Mason, D, Mazaheri, A, Mehmood, A, Mehreen, A, Michaut, M, Miller, R, Mitsopoulos, C, Modos, D, Moerbeke, M, Moo, K, Motsinger-Reif, A, Movva, R, Muraru, S, Muratov, E, Mushthofa, M, Nagarajan, N, Nakken, S, Nath, A, Neuvial, P, Newton, R, Ning, Z, Niz, C, Oliva, B, Olsen, C, Palmeri, A, Panesar, B, Papadopoulos, S, Park, J, Park, S, Pawitan, Y, Peluso, D, Pendyala, S, Peng, J, Perfetto, L, Pirro, S, Plevritis, S, Politi, R, Poon, H, Porta, E, Prellner, I, Preuer, K, Pujana, M, Ramnarine, R, Reid, J, Reyal, F, Richardson, S, Ricketts, C, Rieswijk, L, Rocha, M, Rodriguez-Gonzalvez, C, Roell, K, Rotroff, D, de Ruiter, J, Rukawa, P, Sadacca, B, Safikhani, Z, Safitri, F, Sales-Pardo, M, Sauer, S, Schlichting, M, Seoane, J, Serra, J, Shang, M, Sharma, A, Sharma, H, Shen, Y, Shiga, M, Shin, M, Shkedy, Z, Shopsowitz, K, Sinai, S, Skola, D, Smirnov, P, Soerensen, I, Soerensen, P, Song, J, Song, S, Soufan, O, Spitzmueller, A, Steipe, B, Suphavilai, C, Tamayo, S, Tamborero, D, Tang, J, Tanoli, Z, Tarres-Deulofeu, M, Tegner, J, Thommesen, L, Tonekaboni, S, Tran, H, Troyer, E, Truong, A, Tsunoda, T, Turu, G, Tzeng, G, Verbeke, L, Videla, S, Vis, D, Voronkov, A, Votis, K, Wang, A, Wang, H, Wang, P, Wang, S, Wang, W, Wang, X, Wennerberg, K, Wernisch, L, Wessels, L, van Westen, G, Westerman, B, White, S, Willighagen, E, Wurdinger, T, Xie, L, Xie, S, Xu, H, Yadav, B, Yau, C, Yeerna, H, Yin, J, Yu, M, Yun, S, Zakharov, A, Zamichos, A, Zanin, M, Zeng, L, Zenil, H, Zhang, F, Zhang, P, Zhang, W, Zhao, H, Zhao, L, Zheng, W, Zoufir, A, Zucknick, M, Jang, I, Ghazoui, Z, Ahsen, M, Vogel, R, Neto, E, Norman, T, Tang, E, Garnett, M, Veroli, G, Fawell, S, Stolovitzky, G, Guinney, J, Dry, J, Saez-Rodriguez, J, Menden, Michael P. [0000-0003-0267-5792], Mason, Mike J. [0000-0002-5652-7739], Yu, Thomas [0000-0002-5841-0198], Kang, Jaewoo [0000-0001-6798-9106], Nguyen, Tin [0000-0001-8001-9470], Ahsen, Mehmet Eren [0000-0002-4907-0427], Stolovitzky, Gustavo [0000-0002-9618-2819], Guinney, Justin [0000-0003-1477-1888], Saez-Rodriguez, Julio [0000-0002-8552-8976], Apollo - University of Cambridge Repository, Menden, Michael P [0000-0003-0267-5792], Mason, Mike J [0000-0002-5652-7739], Pathology, CCA - Cancer biology and immunology, Medical oncology laboratory, Neurosurgery, Chemistry and Pharmaceutical Sciences, AIMMS, Medicinal chemistry, Universidade do Minho, Department of Computer Science, Professorship Marttinen P., Aalto-yliopisto, and Aalto University

Subjects
Drug Resistance, 02 engineering and technology, 13, PATHWAY, Antineoplastic Combined Chemotherapy Protocols, Molecular Targeted Therapy, Càncer, lcsh:Science, media_common, Cancer, Tumor, Settore BIO/18, Settore BIO/11, Drug combinations, High-throughput screening, Drug Synergism, purl.org/becyt/ford/1.2 [https], Genomics, Machine Learning, predictions, 3. Good health, ddc, Technologie de l'environnement, contrôle de la pollution, Benchmarking, 5.1 Pharmaceuticals, Cancer treatment, Farmacogenètica, Science & Technology - Other Topics, Development of treatments and therapeutic interventions, 0210 nano-technology, Human, Drug, media_common.quotation_subject, Science, 49/23, ADAM17 Protein, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, SDG 3 - Good Health and Well-being, RESOURCE, Machine learning, Genetics, Chimie, Humans, BREAST-CANCER, CELL, 49/98, Science & Technology, Antineoplastic Combined Chemotherapy Protocol, 45, MUTATIONS, Computational Biology, Androgen receptor, Breast-cancer, Gene, Cell, Inhibition, Resistance, Pathway, Mutations, Landscape, Resource, 631/114/1305, medicine.disease, Drug synergy, 49, 030104 developmental biology, Pharmacogenetics, Mutation, Ciências Médicas::Biotecnologia Médica, lcsh:Q, 631/154/1435/2163, Biomarkers, RESISTANCE, 0301 basic medicine, ING-INF/06 - BIOINGEGNERIA ELETTRONICA E INFORMATICA, Statistical methods, Computer science, General Physics and Astronomy, Datasets as Topic, Drug resistance, purl.org/becyt/ford/1 [https], Phosphatidylinositol 3-Kinases, Biotecnologia Médica [Ciências Médicas], Neoplasms, Science and technology, Phosphoinositide-3 Kinase Inhibitors, Multidisciplinary, Biomarkers, Tumor, Cell Line, Tumor, Drug Antagonism, Drug Resistance, Neoplasm, Treatment Outcome, Pharmacogenetic, article, ANDROGEN RECEPTOR, 49/39, 631/114/2415, 021001 nanoscience & nanotechnology, 692/4028/67, Multidisciplinary Sciences, 317 Pharmacy, Patient Safety, Systems biology, 3122 Cancers, INHIBITION, Computational biology, Cell Line, medicine, LANDSCAPE, Physique, Human Genome, Data Science, General Chemistry, AstraZeneca-Sanger Drug Combination DREAM Consortium, Astronomie, GENE, Good Health and Well Being, Pharmacogenomics, Genomic, Neoplasm, 631/553, Phosphatidylinositol 3-Kinase
Abstract

PubMed: 31209238, The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells. © 2019, The Author(s)., National Institute for Health Research, NIHR Wellcome Trust, WT: 102696, 206194 Magyar Tudományos Akadémia, MTA Bayer 668858 PrECISE AstraZeneca, We thank the Genomics of Drug Sensitivity in Cancer and COSMIC teams at the Wellcome Trust Sanger Institute for help with the preparation of the molecular data, Denes Turei for help with Omnipath, and Katjusa Koler for help with matching drug names across combination screens. We thank AstraZeneca for funding and provision of data to the DREAM Consortium to run the challenge, and funding from the European Union Horizon 2020 research (under grant agreement No 668858 PrECISE to J.S.R.), the Joint Research Center for Computational Biomedicine (which is partially funded by Bayer AG) to J.S.R., National Institute for Health Research (NIHR) Sheffield Biomedical Research Center, Premium Postdoctoral Fellowship Program of the Hungarian Academy of Sciences. M.G lab is supported by Wellcome Trust (102696 and 206194)., Competing interests: K.C.B., Z.G., G.Y.D., E.K.Y.T., S.F., and J.R.D. are AstraZeneca employees. K.C.B., Z.G., E.K.Y.T., S.F., and J.R.D. are AstraZeneca shareholders. Y.G. receives personal compensation from Eli Lilly and Company, is a shareholder of Cleerly, Inc., and Ann Arbor Algorithms, Inc. M.G. receives research funding from AstraZeneca and has performed consultancy for Sanofi. The remaining authors declare no competing interests.

Published
2019
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16. Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

Author

Menden, M, Wang, D, Mason, M, Szalai, B, Bulusu, K, Guan, Y, Yu, T, Kang, J, Jeon, M, Wolfinger, R, Nguyen, T, Zaslavskiy, M, Abante, J, Abecassis, B, Aben, N, Aghamirzaie, D, Aittokallio, T, Akhtari, F, Al-lazikani, B, Alam, T, Allam, A, Allen, C, de Almeida, M, Altarawy, D, Alves, V, Amadoz, A, Anchang, B, Antolin, A, Ash, J, Aznar, V, Ba-alawi, W, Bagheri, M, Bajic, V, Ball, G, Ballester, P, Baptista, D, Bare, C, Bateson, M, Bender, A, Bertrand, D, Wijayawardena, B, Boroevich, K, Bosdriesz, E, Bougouffa, S, Bounova, G, Brouwer, T, Bryant, B, Calaza, M, Calderone, A, Calza, S, Capuzzi, S, Carbonell-Caballero, J, Carlin, D, Carter, H, Castagnoli, L, Celebi, R, Cesareni, G, Chang, H, Chen, G, Chen, H, Cheng, L, Chernomoretz, A, Chicco, D, Cho, K, Cho, S, Choi, D, Choi, J, Choi, K, Choi, M, Cock, M, Coker, E, Cortes-Ciriano, I, Cserzo, M, Cubuk, C, Curtis, C, Daele, D, Dang, C, Dijkstra, T, Dopazo, J, Draghici, S, Drosou, A, Dumontier, M, Ehrhart, F, Eid, F, Elhefnawi, M, Elmarakeby, H, van Engelen, B, Engin, H, de Esch, I, Evelo, C, Falcao, A, Farag, S, Fernandez-Lozano, C, Fisch, K, Flobak, A, Fornari, C, Foroushani, A, Fotso, D, Fourches, D, Friend, S, Frigessi, A, Gao, F, Gao, X, Gerold, J, Gestraud, P, Ghosh, S, Gillberg, J, Godoy-Lorite, A, Godynyuk, L, Godzik, A, Goldenberg, A, Gomez-Cabrero, D, Gonen, M, de Graaf, C, Gray, H, Grechkin, M, Guimera, R, Guney, E, Haibe-Kains, B, Han, Y, Hase, T, He, D, He, L, Heath, L, Hellton, K, Helmer-Citterich, M, Hidalgo, M, Hidru, D, Hill, S, Hochreiter, S, Hong, S, Hovig, E, Hsueh, Y, Hu, Z, Huang, J, Huang, R, Hunyady, L, Hwang, J, Hwang, T, Hwang, W, Hwang, Y, Isayev, O, Don't Walk, O, Jack, J, Jahandideh, S, Ji, J, Jo, Y, Kamola, P, Kanev, G, Karacosta, L, Karimi, M, Kaski, S, Kazanov, M, Khamis, A, Khan, S, Kiani, N, Kim, A, Kim, J, Kim, K, Kim, S, Kim, Y, Kirk, P, Kitano, H, Klambauer, G, Knowles, D, Ko, M, Kohn-Luque, A, Kooistra, A, Kuenemann, M, Kuiper, M, Kurz, C, Kwon, M, van Laarhoven, T, Laegreid, A, Lederer, S, Lee, H, Lee, J, Lee, Y, Lepp_aho, E, Lewis, R, Li, J, Li, L, Liley, J, Lim, W, Lin, C, Liu, Y, Lopez, Y, Low, J, Lysenko, A, Machado, D, Madhukar, N, Maeyer, D, Malpartida, A, Mamitsuka, H, Marabita, F, Marchal, K, Marttinen, P, Mason, D, Mazaheri, A, Mehmood, A, Mehreen, A, Michaut, M, Miller, R, Mitsopoulos, C, Modos, D, Moerbeke, M, Moo, K, Motsinger-Reif, A, Movva, R, Muraru, S, Muratov, E, Mushthofa, M, Nagarajan, N, Nakken, S, Nath, A, Neuvial, P, Newton, R, Ning, Z, Niz, C, Oliva, B, Olsen, C, Palmeri, A, Panesar, B, Papadopoulos, S, Park, J, Park, S, Pawitan, Y, Peluso, D, Pendyala, S, Peng, J, Perfetto, L, Pirro, S, Plevritis, S, Politi, R, Poon, H, Porta, E, Prellner, I, Preuer, K, Pujana, M, Ramnarine, R, Reid, J, Reyal, F, Richardson, S, Ricketts, C, Rieswijk, L, Rocha, M, Rodriguez-Gonzalvez, C, Roell, K, Rotroff, D, de Ruiter, J, Rukawa, P, Sadacca, B, Safikhani, Z, Safitri, F, Sales-Pardo, M, Sauer, S, Schlichting, M, Seoane, J, Serra, J, Shang, M, Sharma, A, Sharma, H, Shen, Y, Shiga, M, Shin, M, Shkedy, Z, Shopsowitz, K, Sinai, S, Skola, D, Smirnov, P, Soerensen, I, Soerensen, P, Song, J, Song, S, Soufan, O, Spitzmueller, A, Steipe, B, Suphavilai, C, Tamayo, S, Tamborero, D, Tang, J, Tanoli, Z, Tarres-Deulofeu, M, Tegner, J, Thommesen, L, Tonekaboni, S, Tran, H, Troyer, E, Truong, A, Tsunoda, T, Turu, G, Tzeng, G, Verbeke, L, Videla, S, Vis, D, Voronkov, A, Votis, K, Wang, A, Wang, H, Wang, P, Wang, S, Wang, W, Wang, X, Wennerberg, K, Wernisch, L, Wessels, L, van Westen, G, Westerman, B, White, S, Willighagen, E, Wurdinger, T, Xie, L, Xie, S, Xu, H, Yadav, B, Yau, C, Yeerna, H, Yin, J, Yu, M, Yun, S, Zakharov, A, Zamichos, A, Zanin, M, Zeng, L, Zenil, H, Zhang, F, Zhang, P, Zhang, W, Zhao, H, Zhao, L, Zheng, W, Zoufir, A, Zucknick, M, Jang, I, Ghazoui, Z, Ahsen, M, Vogel, R, Neto, E, Norman, T, Tang, E, Garnett, M, Veroli, G, Fawell, S, Stolovitzky, G, Guinney, J, Dry, J, Saez-Rodriguez, J, Menden M. P., Wang D., Mason M. J., Szalai B., Bulusu K. C., Guan Y., Yu T., Kang J., Jeon M., Wolfinger R., Nguyen T., Zaslavskiy M., Abante J., Abecassis B. S., Aben N., Aghamirzaie D., Aittokallio T., Akhtari F. S., Al-lazikani B., Alam T., Allam A., Allen C., de Almeida M. P., Altarawy D., Alves V., Amadoz A., Anchang B., Antolin A. A., Ash J. R., Aznar V. R., Ba-alawi W., Bagheri M., Bajic V., Ball G., Ballester P. J., Baptista D., Bare C., Bateson M., Bender A., Bertrand D., Wijayawardena B., Boroevich K. A., Bosdriesz E., Bougouffa S., Bounova G., Brouwer T., Bryant B., Calaza M., Calderone A., Calza S., Capuzzi S., Carbonell-Caballero J., Carlin D., Carter H., Castagnoli L., Celebi R., Cesareni G., Chang H., Chen G., Chen H., Cheng L., Chernomoretz A., Chicco D., Cho K. -H., Cho S., Choi D., Choi J., Choi K., Choi M., Cock M. D., Coker E., Cortes-Ciriano I., Cserzo M., Cubuk C., Curtis C., Daele D. V., Dang C. C., Dijkstra T., Dopazo J., Draghici S., Drosou A., Dumontier M., Ehrhart F., Eid F. -E., ElHefnawi M., Elmarakeby H., van Engelen B., Engin H. B., de Esch I., Evelo C., Falcao A. O., Farag S., Fernandez-Lozano C., Fisch K., Flobak A., Fornari C., Foroushani A. B. K., Fotso D. C., Fourches D., Friend S., Frigessi A., Gao F., Gao X., Gerold J. M., Gestraud P., Ghosh S., Gillberg J., Godoy-Lorite A., Godynyuk L., Godzik A., Goldenberg A., Gomez-Cabrero D., Gonen M., de Graaf C., Gray H., Grechkin M., Guimera R., Guney E., Haibe-Kains B., Han Y., Hase T., He D., He L., Heath L. S., Hellton K. H., Helmer-Citterich M., Hidalgo M. R., Hidru D., Hill S. M., Hochreiter S., Hong S., Hovig E., Hsueh Y. -C., Hu Z., Huang J. K., Huang R. S., Hunyady L., Hwang J., Hwang T. H., Hwang W., Hwang Y., Isayev O., Don't Walk O. B., Jack J., Jahandideh S., Ji J., Jo Y., Kamola P. J., Kanev G. K., Karacosta L., Karimi M., Kaski S., Kazanov M., Khamis A. M., Khan S. A., Kiani N. A., Kim A., Kim J., Kim K., Kim S., Kim Y., Kirk P. D. W., Kitano H., Klambauer G., Knowles D., Ko M., Kohn-Luque A., Kooistra A. J., Kuenemann M. A., Kuiper M., Kurz C., Kwon M., van Laarhoven T., Laegreid A., Lederer S., Lee H., Lee J., Lee Y. W., Lepp_aho E., Lewis R., Li J., Li L., Liley J., Lim W. K., Lin C., Liu Y., Lopez Y., Low J., Lysenko A., Machado D., Madhukar N., Maeyer D. D., Malpartida A. B., Mamitsuka H., Marabita F., Marchal K., Marttinen P., Mason D., Mazaheri A., Mehmood A., Mehreen A., Michaut M., Miller R. A., Mitsopoulos C., Modos D., Moerbeke M. V., Moo K., Motsinger-Reif A., Movva R., Muraru S., Muratov E., Mushthofa M., Nagarajan N., Nakken S., Nath A., Neuvial P., Newton R., Ning Z., Niz C. D., Oliva B., Olsen C., Palmeri A., Panesar B., Papadopoulos S., Park J., Park S., Pawitan Y., Peluso D., Pendyala S., Peng J., Perfetto L., Pirro S., Plevritis S., Politi R., Poon H., Porta E., Prellner I., Preuer K., Pujana M. A., Ramnarine R., Reid J. E., Reyal F., Richardson S., Ricketts C., Rieswijk L., Rocha M., Rodriguez-Gonzalvez C., Roell K., Rotroff D., de Ruiter J. R., Rukawa P., Sadacca B., Safikhani Z., Safitri F., Sales-Pardo M., Sauer S., Schlichting M., Seoane J. A., Serra J., Shang M. -M., Sharma A., Sharma H., Shen Y., Shiga M., Shin M., Shkedy Z., Shopsowitz K., Sinai S., Skola D., Smirnov P., Soerensen I. F., Soerensen P., Song J. -H., Song S. O., Soufan O., Spitzmueller A., Steipe B., Suphavilai C., Tamayo S. P., Tamborero D., Tang J., Tanoli Z. -U. -R., Tarres-Deulofeu M., Tegner J., Thommesen L., Tonekaboni S. A. M., Tran H., Troyer E. D., Truong A., Tsunoda T., Turu G., Tzeng G. -Y., Verbeke L., Videla S., Vis D., Voronkov A., Votis K., Wang A., Wang H. -Q. H., Wang P. -W., Wang S., Wang W., Wang X., Wennerberg K., Wernisch L., Wessels L., van Westen G. J. P., Westerman B. A., White S. R., Willighagen E., Wurdinger T., Xie L., Xie S., Xu H., Yadav B., Yau C., Yeerna H., Yin J. W., Yu M., Yu M. H., Yun S. J., Zakharov A., Zamichos A., Zanin M., Zeng L., Zenil H., Zhang F., Zhang P., Zhang W., Zhao H., Zhao L., Zheng W., Zoufir A., Zucknick M., Jang I. S., Ghazoui Z., Ahsen M. E., Vogel R., Neto E. C., Norman T., Tang E. K. Y., Garnett M. J., Veroli G. Y. D., Fawell S., Stolovitzky G., Guinney J., Dry J. R., Saez-Rodriguez J., Menden, M, Wang, D, Mason, M, Szalai, B, Bulusu, K, Guan, Y, Yu, T, Kang, J, Jeon, M, Wolfinger, R, Nguyen, T, Zaslavskiy, M, Abante, J, Abecassis, B, Aben, N, Aghamirzaie, D, Aittokallio, T, Akhtari, F, Al-lazikani, B, Alam, T, Allam, A, Allen, C, de Almeida, M, Altarawy, D, Alves, V, Amadoz, A, Anchang, B, Antolin, A, Ash, J, Aznar, V, Ba-alawi, W, Bagheri, M, Bajic, V, Ball, G, Ballester, P, Baptista, D, Bare, C, Bateson, M, Bender, A, Bertrand, D, Wijayawardena, B, Boroevich, K, Bosdriesz, E, Bougouffa, S, Bounova, G, Brouwer, T, Bryant, B, Calaza, M, Calderone, A, Calza, S, Capuzzi, S, Carbonell-Caballero, J, Carlin, D, Carter, H, Castagnoli, L, Celebi, R, Cesareni, G, Chang, H, Chen, G, Chen, H, Cheng, L, Chernomoretz, A, Chicco, D, Cho, K, Cho, S, Choi, D, Choi, J, Choi, K, Choi, M, Cock, M, Coker, E, Cortes-Ciriano, I, Cserzo, M, Cubuk, C, Curtis, C, Daele, D, Dang, C, Dijkstra, T, Dopazo, J, Draghici, S, Drosou, A, Dumontier, M, Ehrhart, F, Eid, F, Elhefnawi, M, Elmarakeby, H, van Engelen, B, Engin, H, de Esch, I, Evelo, C, Falcao, A, Farag, S, Fernandez-Lozano, C, Fisch, K, Flobak, A, Fornari, C, Foroushani, A, Fotso, D, Fourches, D, Friend, S, Frigessi, A, Gao, F, Gao, X, Gerold, J, Gestraud, P, Ghosh, S, Gillberg, J, Godoy-Lorite, A, Godynyuk, L, Godzik, A, Goldenberg, A, Gomez-Cabrero, D, Gonen, M, de Graaf, C, Gray, H, Grechkin, M, Guimera, R, Guney, E, Haibe-Kains, B, Han, Y, Hase, T, He, D, He, L, Heath, L, Hellton, K, Helmer-Citterich, M, Hidalgo, M, Hidru, D, Hill, S, Hochreiter, S, Hong, S, Hovig, E, Hsueh, Y, Hu, Z, Huang, J, Huang, R, Hunyady, L, Hwang, J, Hwang, T, Hwang, W, Hwang, Y, Isayev, O, Don't Walk, O, Jack, J, Jahandideh, S, Ji, J, Jo, Y, Kamola, P, Kanev, G, Karacosta, L, Karimi, M, Kaski, S, Kazanov, M, Khamis, A, Khan, S, Kiani, N, Kim, A, Kim, J, Kim, K, Kim, S, Kim, Y, Kirk, P, Kitano, H, Klambauer, G, Knowles, D, Ko, M, Kohn-Luque, A, Kooistra, A, Kuenemann, M, Kuiper, M, Kurz, C, Kwon, M, van Laarhoven, T, Laegreid, A, Lederer, S, Lee, H, Lee, J, Lee, Y, Lepp_aho, E, Lewis, R, Li, J, Li, L, Liley, J, Lim, W, Lin, C, Liu, Y, Lopez, Y, Low, J, Lysenko, A, Machado, D, Madhukar, N, Maeyer, D, Malpartida, A, Mamitsuka, H, Marabita, F, Marchal, K, Marttinen, P, Mason, D, Mazaheri, A, Mehmood, A, Mehreen, A, Michaut, M, Miller, R, Mitsopoulos, C, Modos, D, Moerbeke, M, Moo, K, Motsinger-Reif, A, Movva, R, Muraru, S, Muratov, E, Mushthofa, M, Nagarajan, N, Nakken, S, Nath, A, Neuvial, P, Newton, R, Ning, Z, Niz, C, Oliva, B, Olsen, C, Palmeri, A, Panesar, B, Papadopoulos, S, Park, J, Park, S, Pawitan, Y, Peluso, D, Pendyala, S, Peng, J, Perfetto, L, Pirro, S, Plevritis, S, Politi, R, Poon, H, Porta, E, Prellner, I, Preuer, K, Pujana, M, Ramnarine, R, Reid, J, Reyal, F, Richardson, S, Ricketts, C, Rieswijk, L, Rocha, M, Rodriguez-Gonzalvez, C, Roell, K, Rotroff, D, de Ruiter, J, Rukawa, P, Sadacca, B, Safikhani, Z, Safitri, F, Sales-Pardo, M, Sauer, S, Schlichting, M, Seoane, J, Serra, J, Shang, M, Sharma, A, Sharma, H, Shen, Y, Shiga, M, Shin, M, Shkedy, Z, Shopsowitz, K, Sinai, S, Skola, D, Smirnov, P, Soerensen, I, Soerensen, P, Song, J, Song, S, Soufan, O, Spitzmueller, A, Steipe, B, Suphavilai, C, Tamayo, S, Tamborero, D, Tang, J, Tanoli, Z, Tarres-Deulofeu, M, Tegner, J, Thommesen, L, Tonekaboni, S, Tran, H, Troyer, E, Truong, A, Tsunoda, T, Turu, G, Tzeng, G, Verbeke, L, Videla, S, Vis, D, Voronkov, A, Votis, K, Wang, A, Wang, H, Wang, P, Wang, S, Wang, W, Wang, X, Wennerberg, K, Wernisch, L, Wessels, L, van Westen, G, Westerman, B, White, S, Willighagen, E, Wurdinger, T, Xie, L, Xie, S, Xu, H, Yadav, B, Yau, C, Yeerna, H, Yin, J, Yu, M, Yun, S, Zakharov, A, Zamichos, A, Zanin, M, Zeng, L, Zenil, H, Zhang, F, Zhang, P, Zhang, W, Zhao, H, Zhao, L, Zheng, W, Zoufir, A, Zucknick, M, Jang, I, Ghazoui, Z, Ahsen, M, Vogel, R, Neto, E, Norman, T, Tang, E, Garnett, M, Veroli, G, Fawell, S, Stolovitzky, G, Guinney, J, Dry, J, Saez-Rodriguez, J, Menden M. P., Wang D., Mason M. J., Szalai B., Bulusu K. C., Guan Y., Yu T., Kang J., Jeon M., Wolfinger R., Nguyen T., Zaslavskiy M., Abante J., Abecassis B. S., Aben N., Aghamirzaie D., Aittokallio T., Akhtari F. S., Al-lazikani B., Alam T., Allam A., Allen C., de Almeida M. P., Altarawy D., Alves V., Amadoz A., Anchang B., Antolin A. A., Ash J. R., Aznar V. R., Ba-alawi W., Bagheri M., Bajic V., Ball G., Ballester P. J., Baptista D., Bare C., Bateson M., Bender A., Bertrand D., Wijayawardena B., Boroevich K. A., Bosdriesz E., Bougouffa S., Bounova G., Brouwer T., Bryant B., Calaza M., Calderone A., Calza S., Capuzzi S., Carbonell-Caballero J., Carlin D., Carter H., Castagnoli L., Celebi R., Cesareni G., Chang H., Chen G., Chen H., Cheng L., Chernomoretz A., Chicco D., Cho K. -H., Cho S., Choi D., Choi J., Choi K., Choi M., Cock M. D., Coker E., Cortes-Ciriano I., Cserzo M., Cubuk C., Curtis C., Daele D. V., Dang C. C., Dijkstra T., Dopazo J., Draghici S., Drosou A., Dumontier M., Ehrhart F., Eid F. -E., ElHefnawi M., Elmarakeby H., van Engelen B., Engin H. B., de Esch I., Evelo C., Falcao A. O., Farag S., Fernandez-Lozano C., Fisch K., Flobak A., Fornari C., Foroushani A. B. K., Fotso D. C., Fourches D., Friend S., Frigessi A., Gao F., Gao X., Gerold J. M., Gestraud P., Ghosh S., Gillberg J., Godoy-Lorite A., Godynyuk L., Godzik A., Goldenberg A., Gomez-Cabrero D., Gonen M., de Graaf C., Gray H., Grechkin M., Guimera R., Guney E., Haibe-Kains B., Han Y., Hase T., He D., He L., Heath L. S., Hellton K. H., Helmer-Citterich M., Hidalgo M. R., Hidru D., Hill S. M., Hochreiter S., Hong S., Hovig E., Hsueh Y. -C., Hu Z., Huang J. K., Huang R. S., Hunyady L., Hwang J., Hwang T. H., Hwang W., Hwang Y., Isayev O., Don't Walk O. B., Jack J., Jahandideh S., Ji J., Jo Y., Kamola P. J., Kanev G. K., Karacosta L., Karimi M., Kaski S., Kazanov M., Khamis A. M., Khan S. A., Kiani N. A., Kim A., Kim J., Kim K., Kim S., Kim Y., Kirk P. D. W., Kitano H., Klambauer G., Knowles D., Ko M., Kohn-Luque A., Kooistra A. J., Kuenemann M. A., Kuiper M., Kurz C., Kwon M., van Laarhoven T., Laegreid A., Lederer S., Lee H., Lee J., Lee Y. W., Lepp_aho E., Lewis R., Li J., Li L., Liley J., Lim W. K., Lin C., Liu Y., Lopez Y., Low J., Lysenko A., Machado D., Madhukar N., Maeyer D. D., Malpartida A. B., Mamitsuka H., Marabita F., Marchal K., Marttinen P., Mason D., Mazaheri A., Mehmood A., Mehreen A., Michaut M., Miller R. A., Mitsopoulos C., Modos D., Moerbeke M. V., Moo K., Motsinger-Reif A., Movva R., Muraru S., Muratov E., Mushthofa M., Nagarajan N., Nakken S., Nath A., Neuvial P., Newton R., Ning Z., Niz C. D., Oliva B., Olsen C., Palmeri A., Panesar B., Papadopoulos S., Park J., Park S., Pawitan Y., Peluso D., Pendyala S., Peng J., Perfetto L., Pirro S., Plevritis S., Politi R., Poon H., Porta E., Prellner I., Preuer K., Pujana M. A., Ramnarine R., Reid J. E., Reyal F., Richardson S., Ricketts C., Rieswijk L., Rocha M., Rodriguez-Gonzalvez C., Roell K., Rotroff D., de Ruiter J. R., Rukawa P., Sadacca B., Safikhani Z., Safitri F., Sales-Pardo M., Sauer S., Schlichting M., Seoane J. A., Serra J., Shang M. -M., Sharma A., Sharma H., Shen Y., Shiga M., Shin M., Shkedy Z., Shopsowitz K., Sinai S., Skola D., Smirnov P., Soerensen I. F., Soerensen P., Song J. -H., Song S. O., Soufan O., Spitzmueller A., Steipe B., Suphavilai C., Tamayo S. P., Tamborero D., Tang J., Tanoli Z. -U. -R., Tarres-Deulofeu M., Tegner J., Thommesen L., Tonekaboni S. A. M., Tran H., Troyer E. D., Truong A., Tsunoda T., Turu G., Tzeng G. -Y., Verbeke L., Videla S., Vis D., Voronkov A., Votis K., Wang A., Wang H. -Q. H., Wang P. -W., Wang S., Wang W., Wang X., Wennerberg K., Wernisch L., Wessels L., van Westen G. J. P., Westerman B. A., White S. R., Willighagen E., Wurdinger T., Xie L., Xie S., Xu H., Yadav B., Yau C., Yeerna H., Yin J. W., Yu M., Yu M. H., Yun S. J., Zakharov A., Zamichos A., Zanin M., Zeng L., Zenil H., Zhang F., Zhang P., Zhang W., Zhao H., Zhao L., Zheng W., Zoufir A., Zucknick M., Jang I. S., Ghazoui Z., Ahsen M. E., Vogel R., Neto E. C., Norman T., Tang E. K. Y., Garnett M. J., Veroli G. Y. D., Fawell S., Stolovitzky G., Guinney J., Dry J. R., and Saez-Rodriguez J.

Abstract

The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.

Published
2019

19. SCLC subtype-enriched biomarkers define positioning of Aurora B inhibitor combination with venetoclax

Author

Della Corte, C., primary, Gay, C., additional, Urosevic, J., additional, Polanska, U., additional, Ajpacaja, L., additional, Wijnhoven, P., additional, Wang, J., additional, Coker, E., additional, Fabbri, G., additional, Jaaks, P., additional, Jerome, M., additional, Cosaert, J., additional, Garnett, M., additional, Cardnell, R., additional, Pease, J.E., additional, Travers, J., additional, and Byers, L.A., additional

Published
2020
Full Text
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20. Conversion of a flood control system to a sustainable system: the energy requirements for pipeline transport of silt

Author

Coker, E. Howard

Subjects
Environmental issues, Science and technology, The University of South Dakota -- Research
Abstract

E. Howard Coker, a researcher from the chemistry department of University of South Dakota studied the energy required to transport reservoir sediments back to the river channel. The Missouri River has been used as a model system for the experiment.

Published
2000

22. The Effects of Air Pollution on COVID-19 Related Mortality in Northern Italy

Author

Coker, E. S., Cavalli, L., Fabrizi, E., Guastella, G., Lippo, E., Parisi, M. L., Pontarollo, N., Rizzati, M., Varacca, A., Vergalli, S., Cavalli L. (ORCID:0000-0003-4180-9108), Fabrizi E. (ORCID:0000-0003-2504-7043), Guastella G. (ORCID:0000-0002-1333-4718), Lippo E., Rizzati M., Varacca A. (ORCID:0000-0003-4362-0325), Coker, E. S., Cavalli, L., Fabrizi, E., Guastella, G., Lippo, E., Parisi, M. L., Pontarollo, N., Rizzati, M., Varacca, A., Vergalli, S., Cavalli L. (ORCID:0000-0003-4180-9108), Fabrizi E. (ORCID:0000-0003-2504-7043), Guastella G. (ORCID:0000-0002-1333-4718), Lippo E., Rizzati M., and Varacca A. (ORCID:0000-0003-4362-0325)

Abstract

Long-term exposure to ambient air pollutant concentrations is known to cause chronic lung inflammation, a condition that may promote increased severity of COVID-19 syndrome caused by the novel coronavirus (SARS-CoV-2). In this paper, we empirically investigate the ecologic association between long-term concentrations of area-level fine particulate matter (PM2.5) and excess deaths in the first quarter of 2020 in municipalities of Northern Italy. The study accounts for potentially spatial confounding factors related to urbanization that may have influenced the spreading of SARS-CoV-2 and related COVID-19 mortality. Our epidemiological analysis uses geographical information (e.g., municipalities) and negative binomial regression to assess whether both ambient PM2.5 concentration and excess mortality have a similar spatial distribution. Our analysis suggests a positive association of ambient PM2.5 concentration on excess mortality in Northern Italy related to the COVID-19 epidemic. Our estimates suggest that a one-unit increase in PM2.5 concentration (µg/m3) is associated with a 9% (95% confidence interval: 6–12%) increase in COVID-19 related mortality.

Published
2020

25. Simulated ablation for detection of cells impacting paracrine signalling in histology analysis

Author

Taylor-King, J, Baratchart, E, Dhawan, A, Coker, E, Rye, I, Russnes, H, Chapman, S, Basanta, D, and Marusyk, A

Subjects
FOS: Biological sciences, image analysis, paracrine, signalling, histology, cancer, Cell Behavior (q-bio.CB), Quantitative Biology - Cell Behavior, Quantitative Biology - Tissues and Organs, Tissues and Organs (q-bio.TO), Quantitative Biology - Quantitative Methods, Quantitative Methods (q-bio.QM)
Abstract

Intra-tumour phenotypic heterogeneity limits accuracy of clinical diagnostics and hampers the efficiency of anti-cancer therapies. Dealing with this cellular heterogeneity requires adequate understanding of its sources, which is extremely difficult, as phenotypes of tumour cells integrate hardwired (epi)mutational differences with the dynamic responses to microenvironmental cues. The later come in form of both direct physical interactions, as well as inputs from gradients of secreted signalling molecules. Furthermore, tumour cells can not only receive microenvironmental cues, but also produce them. Despite high biological and clinical importance of understanding spatial aspects of paracrine signaling, adequate research tools are largely lacking. Here, a partial differential equation (PDE) based mathematical model is developed that mimics the process of cell ablation. This model suggests how each cell might contribute to the microenvironment by either absorbing or secreting diffusible factors, and quantifies the extent to which observed intensities can be explained via diffusion mediated signalling. The model allows for the separation of phenotypic responses to signalling gradients within tumour microenvironments from the combined influence of responses mediated by direct physical contact and hardwired (epi)genetic differences. The differential equation is solved around cell membrane outlines using a finite element method (FEM). The method is applied to a multi-channel immunofluorescence in situ hybridization (iFISH) stained breast cancer histological specimen and correlations are investigated between: HER2 gene amplification; HER2 protein expression; and cell interaction with the diffusible microenvironment. This approach allows partial deconvolution of the complex inputs..., 17 pages, 5 figures

Published
2018

27. Modular Metal-Organic Polyhedra Superassembly: From Molecular-Level Design to Targeted Drug Delivery

Author

Zhu, W, Guo, J, Ju, Y, Serda, RE, Croissant, JG, Shang, J, Coker, E, Agola, JO, Zhong, Q-Z, Ping, Y, Caruso, F, Brinker, CJ, Zhu, W, Guo, J, Ju, Y, Serda, RE, Croissant, JG, Shang, J, Coker, E, Agola, JO, Zhong, Q-Z, Ping, Y, Caruso, F, and Brinker, CJ

Abstract

Targeted drug delivery remains at the forefront of biomedical research but remains a challenge to date. Herein, the first superassembly of nanosized metal-organic polyhedra (MOP) and their biomimetic coatings of lipid bilayers are described to synergistically combine the advantages of micelles and supramolecular coordination cages for targeted drug delivery. The superassembly technique affords unique hydrophobic features that endow individual MOP to act as nanobuilding blocks and enable their superassembly into larger and well-defined nanocarriers with homogeneous sizes over a broad range of diameters. Various cargos are controllably loaded into the MOP with high payloads, and the nanocages are then superassembled to form multidrug delivery systems. Additionally, functional nanoparticles are introduced into the superassemblies via a one-pot process for versatile bioapplications. The MOP superassemblies are surface-engineered with epidermal growth factor receptors and can be targeted to cancer cells. In vivo studies indicated the assemblies to have a substantial circulation half-life of 5.6 h and to undergo renal clearance-characteristics needed for nanomedicines.

Published
2019

28. The growth of zeolites A, X and mordenite in space

Author

Sacco, Albert, Jr, Bac, N, Coker, E. N, Dixon, A. G, Warzywoda, J, and Thompson, R. W

Subjects
Materials Processing
Abstract

Zeolites are a class of crystalline aluminosilicate materials that form the backbone of the chemical process industry worldwide. They are used primarily as adsorbents and catalysts and support to a significant extent the positive balance of trade realized by the chemical industry in the United States (around $19 billion in 1991). The magnitude of their efforts can be appreciated when one realizes that since their introduction as 'cracking catalysts' in the early 1960's, they have saved the equivalent of 60 percent of the total oil production from Alaska's North Slope. Thus the performance of zeolite catalysts can have a profound effect on the U.S. economy. It is estimated that a 1 percent increase in yield of the gasoline fraction per barrel of oil would represent a savings of 22 million barrels of crude oil per year, representing a reduction of $400 million in the United States' balance of payments. Thus any activity that results in improvement in zeolite catalyst performance is of significant scientific and industrial interest. In addition, due to their 'stability,' uniformity, and, within limits, their 'engineerable' structures, zeolites are being tested as potential adsorbents to purify gases and liquids at the parts-per-billion levels needed in today's electronic, biomedical, and biotechnology industries and for the environment. Other exotic applications, such as host materials for quantum-confined semiconductor atomic arrays, are also being investigated. Because of the importance of this class of material, extensive efforts have been made to characterize their structures and to understand their nucleation and growth mechanisms, so as to be able to custom-make zeolites for a desired application. To date, both the nucleation mechanics and chemistry (such as what are the 'key' nutrients) are, as yet, still unknown for many, if not all, systems. The problem is compounded because there is usually a 'gel' phase present that is assumed to control the degree of supersaturation, and this gel undergoes a continuous 'polymerization' type reaction during nucleation and growth. Generally, for structure characterization and diffusion studies, which are useful in evaluating zeolites for improving yield in petroleum refining as well as for many of the proposed new applications (e.g., catalytic membranes, molecular electronics, chemical sensors) large zeolites (greater than 100 to 1000 times normal size) with minimum lattice defects are desired. Presently, the lack of understanding of zeolite nucleation and growth precludes the custom design of zeolites for these or other uses. It was hypothesized that the microgravity levels achieved in an orbiting spacecraft could help to isolate the possible effects of natural convection (which affects defect formation) and minimize sedimentation, which occurs since zeolites are twice as dense as the solution from which they are formed. This was expected to promote larger crystals by allowing growing crystals a longer residence time in a high-concentration nutrient field. Thus it was hypothesized that the microgravity environment of Earth orbit would allow the growth of large, more defect-free zeolite crystals in high yield.

Published
1994

32. Magnetic And Low Dc Field Sensing Analysis Of Cobalt-Doped Ybco Superconductors As The Core Of Fluxgate-Type Sensors

Author

Coker, E. Gulce, Can, Hava, and Topal, Ugur

Subjects
Condensed Matter::Superconductivity
Abstract

In this study, the critical factors affecting the sensitivity of a magnetic field sensor, based on linear DC field dependence of second harmonic signals generated by co-application of AC and DC fields to polycrystalline type II superconductors, were handled. For this purpose, the Y-123 superconducting samples with different amounts of cobalt ion, as a core material, were synthesized in order to get the best sensing performance. From the M-T and M-H measurements, we have tried to understand the relation between the 2f signal strength (used as the sensor signal) and the characteristic magnetic properties of these superconductors, such as the T-c (on), the T-c (off), and the H-clg. Finally, we could achieve to sense 0.5 mu Oe DC fields by using the Y-123 sample doped with 0.06 wt% of cobalt.

Published
2017

36. Monitoring of FES2 reactions using high-temperature XRD coupled with gas chromatography.

Author

Stirrup, K.-A. M., Rodriguez, M. A., Coker, E. N., Griego, J. J. M., and Anderson, T. M.

Abstract

High-temperature X-ray diffraction with concurrent gas chromatography (GC) was employed in the study of iron disulfide (FeS2) cathode pellets disassembled from thermal batteries. When FeS2 cathode materials were analyzed in an air environment, reaction of the KCl and LiCl salt phases led to the formation of Li2(SO4) and KFe2S3 phases beginning at ~230 °C. These phases subsequently reacted to generate various forms of potassium iron sulfates in the 280–500 °C range, with the final products resulting in a β -Fe2O3 phase and K2(SO4). Independent simultaneous thermal analysis coupled with mass spectroscopy (MS) augmented the diffraction results and supported the overall picture of FeS2 decomposition. Both gas analysis measurements (i.e. GC and MS) from the independent experiments confirmed the formation of SO2 off-gas species during the breakdown of the FeS2. In contrast, characterization of the same cathode material under inert conditions showed the persistence of the initial FeS2 phase throughout the entire temperature range of analysis. [ABSTRACT FROM AUTHOR]

Published
2019
Full Text
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37. Measuring DC fields as low as 0.5 nT by using Bi-2223 polycrystalline superconductors

Author

Topal, U., Alıkma, F., Gulce Coker, E., Topal, U., Alıkma, F., Gulce Coker, E., and Yeditepe Üniversitesi

Subjects
Magnetic field sensor, Ultra-low DC field measurements, DC-magnetometer, 2nd harmonic signal, High-Tc superconductor
Abstract

In this study a novel type of magnetometer capable of direct measurement of DC fields as low as 0.5 nT was described. The second harmonic voltage generated by polycrystalline superconductors inserted in AC and DC fields was used as sensor signal. The experiments have shown that a 0.5 nT DC field can be detectable by using Bi-2223 superconductors as the core material. The Bi-2223 reveals better sensitivity compared to the other high-Tc cuprates. Besides, the sensor works in a wide dynamical range (105 orders in magnitude), which increases its potential application areas. © Springer Science+Business Media New York 2012. Türkiye Bilimsel ve Teknolojik AraÅ?tirma Kurumu: 109T715 Acknowledgements This work was supported by the Scientific and Technological Research Council of Turkey (TÜB'TAK) grant no. 109T715.

Published
2013

38. Abstracts of the Eighth EDCTP Forum, 6-9 November 2016.

Author

Makanga, M, Beattie, P, Breugelmans, G, Nyirenda, T, Bockarie, M, Tanner, M, Volmink, J, Hankins, C, Walzl, G, Chegou, N, Malherbe, S, Hatherill, M, Scriba, TJ, Zak, DE, Barry, CE, Kaufmann, SHE, Noor, A, Strub-Wourgaft, N, Phillips, P, Munguambe, K, Ravinetto, R, Tinto, H, Diro, E, Mahendrahata, Y, Okebe, J, Rijal, S, Garcia, C, Sundar, S, Ndayisaba, G, Sopheak, T, Ngoduc, T, Van Loen, H, Jacobs, J, D'Alessandro, U, Boelaert, M, Buvé, A, Kamalo, P, Manda-Taylor, L, Rennie, S, Mokgatla, B, Bahati, Ijsselmuiden, C, Afolabi, M, Mcgrath, N, Kampmann, B, Imoukhuede, E, Alexander, N, Larson, H, Chandramohan, D, Bojang, K, Kasaro, MP, Muluka, B, Kaunda, K, Morse, J, Westfall, A, Kapata, N, Kruuner, A, Henostroza, G, Reid, S, Alabi, A, Foguim, F, Sankarganesh, J, Bruske, E, Mfoumbi, A, Mevyann, C, Adegnika, A, Lell, B, Kranzer, K, Kremsner, P, Grobusch, M, Sabiiti, W, Ntinginya, N, Kuchaka, D, Azam, K, Kampira, E, Mtafya, B, Bowness, R, Bhatt, N, Davies, G, Kibiki, G, Gillespie, S, Lejon, V, Ilboudo, H, Mumba, D, Camara, M, Kaba, D, Lumbala, C, Fèvre, E, Jamonneau, V, Bucheton, B, Büscher, P, Chisenga, C, Sinkala, E, Chilengi, R, Chitundu, H, Zyambo, Z, Wandeler, G, Vinikoor, M, Emilie, D, Camara, O, Mathurin, K, Guiguigbaza-Kossigan, D, Philippe, B, Regassa, F, Hassane, S, Bienvenu, SM, Fabrice, C, Ouédraogo, E, Kouakou, L, Owusu, M, Mensah, E, Enimil, A, Mutocheluh, M, Ndongo, FA, Tejiokem, MC, Texier, G, Penda, C, Ndiang, S, Ndongo, J-A, Guemkam, G, Sofeu, CL, Afumbom, K, Faye, A, Msellati, P, Warszawski, J, Vos, A, Devillé, W, Barth, R, Klipstein-Grobusch, K, Tempelman, H, Venter, F, Coutinho, R, Grobbee, D, Ssemwanga, D, Lyagoba, F, Magambo, B, Kapaata, A, Kirangwa, J, Nannyonjo, M, Nassolo, F, Nsubuga, R, Yebra, G, Brown, A, Kaleebu, P, Nylén, H, Habtewold, A, Makonnen, E, Yimer, G, Burhenne, J, Diczfalusy, U, Aklillu, E, Steele, D, Walker, R, Simuyandi, M, Beres, L, Bosomprah, S, Ansumana, R, Taitt, C, Lamin, JM, Jacobsen, KH, Mulvaney, SP, Leski, T, Bangura, U, Stenger, D, De Vries, S, Zinsou, FJ, Honkpehedji, J, Dejon, JC, Loembe, MM, Bache, B, Pakker, N, Van Leeuwen, R, Hounkpatin, AB, Yazdanbakhsh, M, Bethony, J, Hotez, P, Diemert, D, Bache, BE, Fernandes, JF, Obiang, RM, Kabwende, AL, Grobusch, MP, Krishna, S, Kremsner, PG, Todagbe, AS, Nambozi, M, Kabuya, J-B, Hachizovu, S, Mwakazanga, D, Kasongo, W, Buyze, J, Mulenga, M, Geertruyden, J-P, Gitaka, J, Chan, C, Kongere, J, Kagaya, W, Kaneko, A, Kabore, N, Barry, N, Kabre, Z, Werme, K, Fofana, A, Compaore, D, Nikiema, F, Some, F, Djimde, A, Zongo, I, Ouedraogo, B, Kone, A, Sagara, I, Björkman, A, Gil, JP, Nchinda, G, Bopda, A, Nji, N, Ambada, G, Ngu, L, Tchadji, J, Sake, C, Magagoum, S, Njambe, GD, Lisom, A, Park, CG, Tait, D, Sibusiso, H, Manda, O, Croucher, K, Van Der Westhuizen, A, Mshanga, I, Levin, J, Nanvubya, A, Kibengo, F, Jaoko, W, Pala, P, Perreau, M, Namuniina, A, Kitandwe, P, Tapia, G, Serwanga, J, Yates, N, Fast, P, Mayer, B, Montefiori, D, Tomaras, G, Robb, M, Lee, C, Wagner, R, Sanders, E, Kilembe, W, Kiwanuka, N, Gilmour, J, Kuipers, H, Vooij, D, Chinyenze, K, Priddy, F, Ding, S, Hanke, T, Pantaleo, G, Ngasala, B, Jovel, I, Malmberg, M, Mmbando, B, Premji, Z, Mårtensson, A, Mwaiswelo, R, Agbor, L, Apinjoh, T, Mwanza, S, Chileshe, J, Joshi, S, Malunga, P, Manyando, C, Laufer, M, Dara, A, Niangaly, A, Sinha, I, Brodin, D, Fofana, B, Dama, S, Dembele, D, Sidibe, B, Diallo, N, Thera, M, Wright, K, Gil, J, Doumbo, O, Baraka, V, Nabasumba, C, Francis, F, Lutumba, P, Mavoko, H, Alifrangis, M, Van Geertruyden, J-P, Sissoko, S, Sangaré, C, Toure, S, Sanogo, K, Diakite, H, Doumbia, D, Haidara, K, Julé, A, Ashurst, H, Merson, L, Olliaro, P, Marsh, V, Lang, T, Guérin, P, Awuondo, K, Njenga, D, Nyakarungu, E, Titus, P, Sutamihardja, A, Lowe, B, Ogutu, B, Billingsley, P, Soulama, I, Kaboré, M, Coulibaly, A, Ouattara, M, Sanon, S, Diarra, A, Bougouma, E, Ouedraogo, A, Sombie, B, Kargougou, D, Ouattara, D, Issa, N, Tiono, A, Sirima, S, Chaponda, M, Dabira, E, Dao, F, Dara, N, Coulibaly, M, Tolo, A, Maiga, H, Ouologuem, N, Niangaly, H, Botchway, F, Wilson, N, Dickinson-Copeland, CM, Adjei, AA, Wilson, M, Stiles, JK, Hamid, MA, Awad-Elgeid, M, Nasr, A, Netongo, P, Kamdem, S, Velavan, T, Lasry, E, Diarra, M, Bamadio, A, Traore, A, Coumare, S, Soma, B, Dicko, Y, Sangare, B, Tembely, A, Traore, D, Haidara, A, Dicko, A, Diawara, E, Beavogui, A, Camara, D, Sylla, M, Yattara, M, Sow, A, Camara, GC, Diallo, S, Mombo-Ngoma, G, Remppis, J, Sievers, M, Manego, RZ, Endamne, L, Hutchinson, D, Held, J, Supan, C, Salazar, CLO, Bonkian, LN, Nahum, A, Sié, A, Abdulla, S, Cantalloube, C, Djeriou, E, Bouyou-Akotet, M, Mordmüller, B, Siribie, M, Sirima, SB, Ouattara, SM, Coulibaly, S, Kabore, JM, Amidou, D, Tekete, M, Traore, O, Haefeli, W, Borrmann, S, Kaboré, N, Kabré, Z, Nikèma, F, Compaoré, D, Somé, F, Djimdé, A, Ouédraogo, J, Chalwe, V, Miller, J, Diakité, H, Greco, B, Spangenberg, T, Kourany-Lefoll, E, Oeuvray, C, Mulry, J, Tyagarajan, K, Magsaam, B, Barnes, K, Hodel, EM, Humphreys, G, Pace, C, Banda, CG, Denti, P, Allen, E, Lalloo, D, Mwapasa, V, Terlouw, A, Mwesigwa, J, Achan, J, Jawara, M, Ditanna, G, Worwui, A, Affara, M, Koukouikila-Koussounda, F, Kombo, M, Vouvoungui, C, Ntoumi, F, Etoka-Beka, MK, Deibert, J, Poulain, P, Kobawila, S, Gueye, NG, Seda, B, Kwambai, T, Jangu, P, Samuels, A, Kuile, FT, Kariuki, S, Barry, A, Bousema, T, Okech, B, Egwang, T, Corran, P, Riley, E, Ezennia, I, Ekwunife, O, Muleba, M, Stevenson, J, Mbata, K, Coetzee, M, Norris, D, Moneke-Anyanwoke, N, Momodou, J, Clarke, E, Scott, S, Tijani, A, Djimde, M, Vaillant, M, Samouda, H, Mensah, V, Roetynck, S, Kanteh, E, Bowyer, G, Ndaw, A, Oko, F, Bliss, C, Jagne, YJ, Cortese, R, Nicosia, A, Roberts, R, D'Alessio, F, Leroy, O, Faye, B, Cisse, B, Gerry, S, Viebig, N, Lawrie, A, Ewer, K, Hill, A, Nebie, I, Tiono, AB, Sanou, G, Konate, AT, Yaro, BJ, Sodiomon, S, Honkpehedji, Y, Agobe, JCD, Zinsou, F, Mengue, J, Richie, T, Hoffman, S, Nouatin, O, Ngoa, UA, Edoa, JR, Homoet, A, Engelhon, JE, Massinga-Louembe, M, Esen, M, Theisen, M, Sim, KL, Luty, AJ, Moutairou, K, Dinko, B, King, E, Targett, G, Sutherland, C, Likhovole, C, Ouma, C, Vulule, J, Musau, S, Khayumbi, J, Okumu, A, Murithi, W, Otu, J, Gehre, F, Zingue, D, Kudzawu, S, Forson, A, Mane, M, Rabna, P, Diarra, B, Kayede, S, Adebiyi, E, Kehinde, A, Onyejepu, N, Onubogu, C, Idigbe, E, Ba, A, Diallo, A, Mboup, S, Disse, K, Kadanga, G, Dagnra, Y, Baldeh, I, Corrah, T, De Jong, B, Antonio, M, Musanabaganwa, C, Musabyimana, JP, Karita, E, Diop, B, Nambajimana, A, Dushimiyimana, V, Karame, P, Russell, J, Ndoli, J, Hategekimana, T, Sendegeya, A, Condo, J, Binagwaho, A, Okonko, I, Okerentugba, P, Opaleye, O, Awujo, E, Frank-Peterside, N, Moyo, S, Kotokwe, K, Mohammed, T, Boleo, C, Mupfumi, L, Chishala, S, Gaseitsiwe, S, Tsalaile, L, Bussmann, H, Makhema, J, Baum, M, Marlink, R, Engelbretch, S, Essex, M, Novitsky, V, Saka, E, Kalipalire, Z, Bhairavabhotla, R, Midiani, D, Sherman, J, Mgode, G, Cox, C, Bwana, D, Mtui, L, Magesa, D, Kahwa, A, Mfinanga, G, Mulder, C, Borain, N, Petersen, L, Du Plessis, J, Theron, G, Holm-Hansen, C, Tekwu, EM, Sidze, LK, Assam, JPA, Eyangoh, S, Niemann, S, Beng, VP, Frank, M, Atiadeve, S, Hilmann, D, Awoniyi, D, Baumann, R, Kriel, B, Jacobs, R, Kidd, M, Loxton, A, Kaempfer, S, Singh, M, Mwanza, W, Milimo, D, Moyo, M, Kasese, N, Cheeba-Lengwe, M, Munkondya, S, Ayles, H, De Haas, P, Muyoyeta, M, Namuganga, AR, Kizza, HM, Mendy, A, Tientcheu, L, Ayorinde, A, Coker, E, Egere, U, Coussens, A, Naude, C, Chaplin, G, Noursadeghi, M, Martineau, A, Jablonski, N, Wilkinson, R, Ouedraogo, HG, Matteelli, A, Regazzi, M, Tarnagda, G, Villani, P, Sulis, G, Diagbouga, S, Roggi, A, Giorgetti, F, Kouanda, S, Bidias, A, Ndjonka, D, Olemba, C, Souleymanou, A, Mukonzo, J, Kuteesa, R, Ogwal-Okeng, J, Gustafsson, LL, Owen, J, Bassi, P, Gashau, W, Olaf, K, Dodoo, A, Okonkwo, P, Kanki, P, Maruapula, D, Seraise, B, Einkauf, K, Reilly, A, Rowley, C, Musonda, R, Framhein, A, Mpagama, S, Semvua, H, Maboko, L, Hoelscher, M, Heinrich, N, Mulenga, L, Kaayunga, C, Davies, M-A, Egger, M, Musukuma, K, Dambe, R, Usadi, B, Ngari, M, Thitiri, J, Mwalekwa, L, Fegan, G, Berkley, J, Nsagha, D, Munamunungu, V, Bolton, C, Siyunda, A, Shilimi, J, Bucciardini, R, Fragola, V, Abegaz, T, Lucattini, S, Halifom, A, Tadesse, E, Berhe, M, Pugliese, K, De Castro, P, Terlizzi, R, Fucili, L, Di Gregorio, M, Mirra, M, Zegeye, T, Binelli, A, Vella, S, Abraham, L, Godefay, H, Rakotoarivelo, R, Raberahona, M, Randriamampionona, N, Andriamihaja, R, Rasamoelina, T, Cornet, M, De Dieu Randria, MJ, Benet, T, Vanhems, P, Andrianarivelo, MR, Chirwa, U, Michelo, C, Hamoonga, R, Wandiga, S, Oduor, P, Agaya, J, Sharma, A, Cavanaugh, S, Cain, K, Mukisa, J, Mupere, E, Worodria, W, Ngom, JT, Koro, F, Godwe, C, Adande, C, Ateugieu, R, Onana, T, Ngono, A, Kamdem, Y, Ngo-Niobe, S, Etoa, F-X, Kanengoni, M, Ruzario, S, Ndebele, P, Shana, M, Tarumbiswa, F, Musesengwa, R, Gutsire, R, Fisher, K, Thyagarajan, B, Akanbi, O, Binuyo, M, Ssengooba, W, Respeito, D, Mambuque, E, Blanco, S, Mandomando, I, Cobelens, F, Garcia-Basteiro, A, Tamene, A, Topp, S, Mwamba, C, Padian, N, Sikazwe, I, Geng, E, Holmes, C, Sikombe, K, Hantuba, Czaicki, N, Simbeza, S, Somwe, P, Umulisa, M, Ilo, J, Kestelyn, E, Uwineza, M, Agaba, S, Delvaux, T, Wijgert, J, Gethi, D, Odeny, L, Tamandjou, C, Kaindjee-Tjituka, F, Brandt, L, Cotton, M, Nel, E, Preiser, W, Andersson, M, Adepoju, A, Magana, M, Etsetowaghan, A, Chilikwazi, M, Sutcliffe, C, Thuma, P, Sinywimaanzi, K, Matakala, H, Munachoonga, P, Moss, W, Masenza, IS, Geisenberger, O, Agrea, P, Rwegoshora, F, Mahiga, H, Olomi, W, Kroidl, A, Kayode, G, Amoakoh-Coleman, M, Ansah, E, Uthman, O, Fokam, J, Santoro, M-M, Musolo, C, Chimbiri, I, Chikwenga, G, Deula, R, Massari, R, Lungu, A, Perno, C-F, Ndzengue, G, Loveline, N, Lissom, A, Flaurent, T, Sosso, S, Essomba, C, Kpeli, G, Otchere, I, Lamelas, A, Buultjens, A, Bulach, D, Baines, S, Seemann, T, Giulieri, S, Nakobu, Z, 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Sinywimaanzi, K, Matakala, H, Munachoonga, P, Moss, W, Masenza, IS, Geisenberger, O, Agrea, P, Rwegoshora, F, Mahiga, H, Olomi, W, Kroidl, A, Kayode, G, Amoakoh-Coleman, M, Ansah, E, Uthman, O, Fokam, J, Santoro, M-M, Musolo, C, Chimbiri, I, Chikwenga, G, Deula, R, Massari, R, Lungu, A, Perno, C-F, Ndzengue, G, Loveline, N, Lissom, A, Flaurent, T, Sosso, S, Essomba, C, Kpeli, G, Otchere, I, Lamelas, A, Buultjens, A, Bulach, D, Baines, S, Seemann, T, Giulieri, S, Nakobu, Z, Aboagye, S, Owusu-Mireku, E, Danso, E, Hauser, J, Hinic, V, Pluschke, G, Stinear, T, Yeboah-Manu, D, Elshayeb, A, Siddig, ME, Ahmed, AA, Hussien, AE, Kabwe, M, Tembo, J, Chilukutu, L, Chilufya, M, Ngulube, F, Lukwesa, C, Enne, V, Wexner, H, Mwananyanda, L, Hamer, D, Sinyangwe, S, Ahmed, Y, Klein, N, Maeurer, M, Zumla, A, Bates, M, Beyala, L, Etienne, G, Anthony, N, Benjamin, A, Ateudjieu, J, Chibwe, B, Ojok, D, Tarr, CA, Perez, GM, Omeonga, S, Kibungu, F, Meyer, A, Lansana, P, Mayor, A, Onyango, P, Van Loggerenberg, 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Muñoz, J, Nikiema, M, Ky-Ba, A, Comapore, KAM, Sangare, L, Oluremi, A, Michel, M, Camara, Y, Sanneh, B, Cuamba, I, Gutiérrez, J, Lázaro, C, Mejia, R, Adedeji, A, Folorunsho, S, Demehin, P, Akinsanya, B, Cowley, G, Da Silva, ET, Nabicassa, M, De Barros, PDP, Blif, MM, Bailey, R, Last, A, Mahendradhata, Y, Gotuzzo, E, De Nys, K, Casteels, M, Nona, SK, Lumeka, K, Todagbe, A, Djima, MM, Ukpong, M, Sagay, A, Khamofu, H, Torpey, K, Afiadigwe, E, Anenih, J, Ezechi, O, Nweneka, C, Idoko, J, Muhumuza, S, Katahoire, A, Nuwaha, F, Olsen, A, Okeyo, S, Omollo, R, Kimutai, R, Ochieng, M, Egondi, T, Moonga, C, Chileshe, C, Magwende, G, Anumudu, C, Onile, O, Oladele, V, Adebayo, A, Awobode, H, Oyeyemi, O, Odaibo, A, Kabuye, E, Lutalo, T, Njua-Yafi, C, Nkuo-Akenji, T, Anchang-Kimbi, J, Mugri, R, Chi, H, Tata, R, Njumkeng, C, Dodoo, D, Achidi, E, Fernandes, J, Bache, EB, Matakala, K, Searle, K, Greenman, M, and Rainwater-Lovett, K

Published
2017

42. Physical And Mechanical Properties Of B2O3 Doped Ybacuo Superconductors: Applicability As A Low Dc Magnetometer

Author

Coker, E. Gulce, Kolemen, U., and Topal, U.

Subjects
Condensed Matter::Superconductivity
Abstract

The effect of the intergranular couplings on the second harmonic of the fundamental signal, which is generated by co-application of DC and AC fields to a magnetic material having nonlinear magnetization, was investigated on B (2) O (3) doped YBaCuO superconductors. Physical and mechanical properties of B (2) O (3) doped YBaCuO superconductors were also analyzed to support electrical measurements.

Published
2015

44. Monitoring of FES2reactions using high-temperature XRD coupled with gas chromatography

Author

Stirrup, K.-A. M., Rodriguez, M. A., Coker, E. N., Griego, J. J. M., and Anderson, T. M.

Abstract

High-temperature X-ray diffraction with concurrent gas chromatography (GC) was employed in the study of iron disulfide (FeS2) cathode pellets disassembled from thermal batteries. When FeS2cathode materials were analyzed in an air environment, reaction of the KCl and LiCl salt phases led to the formation of Li2(SO4) and KFe2S3phases beginning at ~230 °C. These phases subsequently reacted to generate various forms of potassium iron sulfates in the 280–500 °C range, with the final products resulting in a β-Fe2O3phase and K2(SO4). Independent simultaneous thermal analysis coupled with mass spectroscopy (MS) augmented the diffraction results and supported the overall picture of FeS2decomposition. Both gas analysis measurements (i.e. GC and MS) from the independent experiments confirmed the formation of SO2off-gas species during the breakdown of the FeS2. In contrast, characterization of the same cathode material under inert conditions showed the persistence of the initial FeS2phase throughout the entire temperature range of analysis.

Published
2019
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48. STUDY OF THE STRENGTH CHARACTERISTICS OF PROTEIN-BASED LIGHTWEIGHT FOAMED CONCRETE WITH CEMENT PARTIALLY REPLACED WITH RICE HUSK ASH.

Author

Coker, E. B., Sadiku, S., Aguwa, J. I., and Abdullahi, M.

Subjects
CEMENT, STRENGTH of materials, CONCRETE industry, REINFORCED concrete, CONSTRUCTION materials
Abstract

Compressive strength test was carried out on the protein-based lightweight foamed concrete produced with cement partially replaced by rice husk ash to ascertain its strength characteristics. Standard concrete cubes of 150 x 150 x 150 mm were produced using ordinary Portland cement (OPC), fine aggregate, aqueous protein-based foaming agent and rice husk ash (RHA). The RHA was used to replace cement at 5 %, 10 %, 15 %, 20 %, 25 %, 30 %, 35%, 40 %, 45 % and 50 % by weight of cement. Control cubes with no cement replacement (0 %), were also produced and used as reference points for comparing the compressive strength of the lightweight foamed concrete at 28 days and 56 days respectively. The mix proportion of 1:1.5 was used as binder/fine aggregate proportions with the foam occupying 20 % of the volume of the concrete and the other constituents occupying the remaining 80 %. The compressive strengths of the lightweight foamed concrete at both 28 days and 56 days, increased for cement replacement levels of 5 - 30 % and gradually decreased for cement replacement levels of 35 - 50 % respectively for the mix proportion of 1:1.5 and for the water/binder ratio of 0.4. The minimum 28 days compressive strength for the mix proportion of 1:1.5 at cement replacement level of 30 % and water/binder ratio of 0.4 was 15.52 N/mm² while that at 56 days was 18.51 N/mm². The rice husk ash is a pozzolanic material with a capability of contributing up to 80 % and above to the compressive strength of lightweight foamed concrete, if the percentage replacement does not exceed 30 %. The mix proportion of 1:1.5 at water/binder ratio of 0.4 produces a structural lightweight concrete at 28 days. [ABSTRACT FROM AUTHOR]

Published
2016
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