Environmental monitoring device von Koenig Keith Alden, St. John David, Wimberly Graham Neal, Lyons Daniel Carson, Hampton Jenna Marie

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Environmental monitoring device von Koenig Keith Alden, St. John David, Wimberly Graham Neal, Lyons Daniel Carson, Hampton Jenna Marie

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COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records von Thygesen, Johan H, Mizani, Mehrdad A, Banerjee, Amitava, Cooper, Jennifer, Lai, Alvina G, Sudlow, Cathie, Abbasizanjani, Hoda, Ahmed, Nida, Akbari, Ashley, Allery, Freya, Ashworth, Mark, Bacon, Seb, Ball, Steve, Banerjee, Ami, Berry, Colin, Beveridge, Jennifer, Boyle, Jon, Briffa, Norman, Buch, Maya, Canoy, Dexter, Cheema, Kate, Crallan, Rebecca, Curcin, Vasa, Curry, Gwenetta, Denholm, Rachel, Dennis, John, Denniston, Alastair, Deo, Salil, Dhillon, Baljean, Dong, Tim, Downs, Johnny, Dregan, Alexandru, Elwenspoek, Martha, Falter, Florian, Firth, Joseph, Friebel, Rocco, Gilbert, Ruth, Goldacre, Ben, Goldacre, Raph, Grieco, Luca, Handy, Alex, Hardelid, Pia, Hardy, Flavien, Hemingway, Harry, Herz, Naomi, Heyl, Johannes, Hinchliffe, Rosie, Hippisley-Cox, Julia, Hocaoglu, Mevhibe, Hollings, Sam, Inouye, Mike, Jenkins, David, Kadam, Umesh, Kallis, Costas, Khawaja, Anthony, Killick, Richard, Kinnear, Deborah, Kolamunnage-Dona, Ruwanthi, Kurdi, Amanj, Lai, Alvina, Lambarth, Andrew, Larzjan, Milad Nazarzadeh, Li, Qiuju, Lyons, Ronan, Macleod, Mary Joan, Mamouei, Mohammad, Melville, Craig, Moncusi, Marta Pineda, Morales, Daniel, Morris, Carole, Nicholson, George, Norris, Tom, Oliver, Dominic, Oluyase, Adejoke, Pierotti, Livia, Priedon, Rouven, Proudfoot, Alastair, Roberts, Brian, Rossdale, Jennifer, Samani, Nilesh, Sattar, Naveed, Schwartz, Roy, Seminog, Olena, Sinha, Shubhra, Skrypak, Mirek, Sofat, Reecha, Sun, Luanluan, Suseeladevi, Arun Karthikeyan, Tilston, George, Toit, Clea du, Torabi, Fatemeh, Watkinson, Ruth, Whiteley, William, Williams, Michelle, Williams, Richard, Withnell, Eloise, Wright, Lucy, Wu, Jinge, Wu, Jianhua, Zaccardi, Francesco

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Machine learning models for predicting blood pressure phenotypes by combining multiple polygenic risk scores von Hrytsenko, Yana, Shea, Benjamin, Elgart, Michael, Kurniansyah, Nuzulul, Lyons, Genevieve, Morrison, Alanna C., Carson, April P., Haring, Bernhard, Mitchell, Braxton D., Psaty, Bruce M., Jaeger, Byron C., Gu, C. Charles, Kooperberg, Charles, Levy, Daniel, Lloyd-Jones, Donald, Choi, Eunhee, Brody, Jennifer A., Smith, Jennifer A., Rotter, Jerome I., Moll, Matthew, Fornage, Myriam, Simon, Noah, Castaldi, Peter, Casanova, Ramon, Chung, Ren-Hua, Kaplan, Robert, Loos, Ruth J. F., Kardia, Sharon L. R., Rich, Stephen S., Redline, Susan, Kelly, Tanika, O’Connor, Timothy, Zhao, Wei, Kim, Wonji, Guo, Xiuqing, Ida Chen, Yii-Der, Sofer, Tamar

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Activity enhances dopaminergic long-duration response in Parkinson disease von UN JUNG KANG, AUINGER, Peggy

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Heterozygosity for a mutation in the Parkin gene leads to later onset Parkinson disease von FOROUD, T, UNIACKE, S. K, LIU, L, PANKRATZ, N, RUDOLPH, A, HALTER, C, SHULTS, C, MARDER, K, CONNEALLY, P. M, NICHOLS, W. C

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Presence of an APOE4 allele results in significantly earlier onset of Parkinson's disease and a higher risk with dementia von Pankratz, Nathan, Byder, Lisa, Halter, Cheryl, Rudolph, Alice, Shults, Clifford W., Conneally, P. Michael, Foroud, Tatiana, Nichols, William C.

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Significant Linkage of Parkinson Disease to Chromosome 2q36-37 von Pankratz, Nathan, Nichols, William C., Uniacke, Sean K., Halter, Cheryl, Rudolph, Alice, Shults, Cliff, Conneally, P. Michael, Foroud, Tatiana

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Genome Screen to Identify Susceptibility Genes for Parkinson Disease in a Sample without parkin Mutations von Pankratz, Nathan, Nichols, William C., Uniacke, Sean K., Halter, Cheryl, Rudolph, Alice, Shults, Cliff, Conneally, P. Michael, Foroud, Tatiana

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Evaluation of the role of Nurr1 in a large sample of familial Parkinson's disease von Nichols, William C., Uniacke, Sean K., Pankratz, Nathan, Reed, Terry, Simon, David K., Halter, Cheryl, Rudolph, Alice, Shults, Clifford W., Conneally, P. Michael, Foroud, Tatiana

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COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records von Hollings, Sam, Handy, Alex, Akbari, Ashley, Lai, Alvina G, Torralbo, Ana, Whiteley, William N, Sudlow, Cathie, Denaxas, Spiros, Abbasizanjani, Hoda, Ahmed, Nida, Ahmed, Badar, Akinoso-Imran, Abdul Qadr, Allara, Elias, Babu-Narayan, Sonya, Banerjee, Ami, Barber, Mark, Beveridge, Jennifer, Bojanić, Lana, Braithwaite, Tasanee, Briffa, Norman, Carson, Alan, Chang, Jen-Yu Amy, Copland, Emma, Cripps, Rachel, Cromwell, David, Curcin, Vasa, Delmestri, Antonella, Deo, Salil, Dhillon, Baljean, Dong, Tim, Downs, Johnny, Firth, Joseph, Gavrieli, Amir, Gilbert, Ruth, Gillies, Clare, Goldacre, Ben, Green, Mark, Gurdasani, Deepti, Hama, Tuankasfee, Hardelid, Pia, Healey, Russell, Henderson, Angela, Heyl, Johannes, Hidajat, Mira, Hughes, David, Ip, Samantha, Jiang, Xiyun, Kadam, Umesh, Kallis, Costas, Karim, Zainab, Kasan, Jake, Kavanagh, Kim, Kee, Frank, Khunti, Kamlesh, Killick, Richard, Kinnear, Deborah, Kontopantelis, Evan, Llinares, Miguel Bernabeu, Macleod, John, Malgapo, Evaleen, Mamouei, Mohammad, Martos, David Moreno, Melville, Craig, Morales, Daniel, Mordi, Ify, Morris, Eva, Murdock, Lars, Nolan, John, North, Teri-Louise, Oliver, Dominic, Oluyase, Adejoke, Olvera-Barrios, Abraham, Pherwani, Arun, Pierotti, Livia, Quinn, Terry, Quint, Jennifer, Rao, Shishir, Roberts, Brian, Rossdale, Jennifer, Schnier, Christian, Shabnam, Sharmin, Sinha, Shubhra, Slapkova, Martina, Steeg, Sarah, Stoica, Serban, Sweeting, Michael, Sydes, Matt, Takhar, Rohan, Tufail, Adnan, Tungamirai, Tapiwa, Wang, Huan, Warwick, Alasdair, Watson, Harry, Whiteley, William, Wilkinson, Tim, Wu, Jinge, Wu, Jianhua, Zaccardi, Francesco, Zhang, Haoting, Zuccolo, Luisa

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