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3. Reacting to wrongdoers : victims, intentionality and partner management

Author

Myers, Simon

Subjects
BF Psychology, BJ Ethics
Abstract

With regards to the behaviours of our social partners, how do we make judgments of moral relevance? For example, under what conditions do we assign responsibility, level blame, and determine and institute the appropriate responses? How do we determine what constitutes a moral transgression, who the valid victim is and what responses are the most appropriate? These questions lie in the gaps between the conceptual frameworks provided by philosophical ethics, philosophy of mind, and the empirical investigations of the cognitive and social sciences. Leveraging the stereotypical structure of everyday moral judgement (discussed below), this thesis highlights each specific element of that structure and aims to consolidate the most recent research on each element whilst also, across three papers, establishing novel findings for each element. Kurt Gray and colleagues (2011; 2012; 2014; 2015; 2018) outline what they consider to be the fundamental structure of moral judgement. One [reacts] to an [agent] who [intentionally] [violates/harms] a moral [patient]. This cognitive template forms part of the Theory of Dyadic Morality (TDM). Although the theory is more extensive, for now, this structure will form the basis for this chapter of this thesis. As written, there are five elements in this structure. 1. Harming/Violating, 2. Moral agents (the principal transgressors), 3. Reactions to those agents, 4. Ascriptions of intentionality, and 5. Moral patients. These five elements are discussed, respectively, as the five sections of the Introduction. Chapters 2, 3 and 4 contain the three papers that form the empirical work for this thesis. Finally Chapter 5 summarises how this novel work fits into the overview established in Chapter 1. 1.1 covers what kind of actions constitute moral harms, how psychologists have disagreed about the centrality of harm over other kinds of violation (e.g., violations that appear to not contain actual physical or emotional harm to a victim) and discusses current pluralist accounts of moral psychology that argue for a range of different kinds of moral violation. 1.2 focuses on judgments that go beyond the act to inferences over the moral agents themselves. Recent work has discovered that a great deal of moral psychology entails character-based rather than act-based judgments and this section discusses how this is important for the understanding of different kinds of moral transgression. 1.3 covers how we react to transgressors including emotional responses, ascriptions of blame and wrongness and how these emotions and judgments drive our different behaviours towards the transgressor. There is a specific focus on the behaviours of Partner Choice (avoidance and ostracization) and Partner Control (punishment). These first sections of Chapter 1 then guide the hypotheses of the first paper, 2.1, Reacting to Wrongdoers: Harm Leads to Partner Control and Impurity to Partner Choice. 1.4 covers our current understanding of how people ascribe intentionality, especially how cognitive psychology has highlighted significant deviations from the most prominent normative theories of intentionality ascription. This lays the foundation for the second paper, 2.2, Does Counterfactual Requirement Explain the Side-Effect Effect? Finally, 1.5 covers judgments with regard to the victims of moral transgressions. For example, how do we perceive the minds of moral patients and why does this matter for moral judgement and also whether we are especially sensitive to human moral patients compared to our cousins in the animal kingdom. This establishes the open questions explored in the third paper, 2.3, Suffering and Dying: How Speciesism Matters for Assessing Extreme Harms.

Published
2022

4. Contributors

Author

Aldana, Ana A., primary, Alexander, Morgan R., additional, Atala, Anthony, additional, Badylak, Stephen F., additional, Baker, Matthew B., additional, Bauer, Jurica, additional, Black, Cameron, additional, Bobbala, Sharan, additional, Brittberg, Mats, additional, Brook, Gary A., additional, Buchanan, Fraser, additional, Carlier, Aurélie, additional, Chen, Saray, additional, Claes, Evan, additional, Cohen, Smadar, additional, Connelly, John, additional, Dalby, Matthew J., additional, Dalton, Paul D., additional, Dawson, Jonathan I., additional, de Boer, Jan, additional, Desmet, Tim, additional, Donnelly, Hannah, additional, Donvil, Filip, additional, Dziki, Jenna L., additional, Egger, Dominik, additional, Filippi, Miriam, additional, Gensler, Marius, additional, Gibbs, David, additional, Gibbs, Susan, additional, Hannen, Rosalind, additional, Hansmann, Jan, additional, Harvey, Alan R., additional, Heck, Tommy, additional, Herrmann, Marietta, additional, Hook, Andrew L., additional, Hubbell, Jeffrey A., additional, Hutmacher, Dietmar W., additional, Hynes, Clara Grace, additional, Joly, Johan, additional, Jorgensen, Adam M., additional, Kanczler, Janos, additional, Karperien, Marcel, additional, Kasper, Cornelia, additional, Kerr, Candace L., additional, Kilian, Kristopher A., additional, Kreß, Sebastian, additional, LaPointe, Vanessa, additional, Laschke, Matthias W., additional, Lindahl, Anders, additional, Londono, Ricardo, additional, Luyten, Frank P., additional, Marechal, Marina, additional, Martino, Mikaël M., additional, Moos, Malcolm, additional, Moroni, Lorenzo, additional, Morra, Emily, additional, Myers, Simon, additional, Nebel, Sabrina, additional, Nie, Minghao, additional, Nisbet, David R., additional, O'Neill, Kelly L., additional, Ojeh, Nkemcho, additional, Oreffo, Richard OC., additional, Oudega, Martin, additional, Passier, Robert, additional, Pêgo, Ana Paula, additional, Pittenger, Mark F., additional, Plant, Giles W., additional, Rice, Jeffrey J., additional, Roelen, Bernard A.J., additional, Schaschkow, Anaïs, additional, Scherberich, Arnaud, additional, Schrooten, Jan, additional, Scott, Evan A., additional, Sicari, Brian M., additional, Sonnaert, Maarten, additional, Später, Thomas, additional, Takeuchi, Shoji, additional, Tandon, Biranche, additional, Tare, Rahul, additional, Truckenmüller, Roman, additional, Tsimbouri, Monica, additional, Uquillas, Jorge Alfredo, additional, Van Assche, Dieter, additional, Vermeulen, Steven, additional, Verrier, Sophie, additional, Walsh, Pamela, additional, and Winkler, David A., additional

Published
2023
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6. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Author

Mahajan, Anubha, Spracklen, Cassandra N., Zhang, Weihua, Ng, Maggie C. Y., Petty, Lauren E., Kitajima, Hidetoshi, Yu, Grace Z., Rüeger, Sina, Speidel, Leo, Kim, Young Jin, Horikoshi, Momoko, Mercader, Josep M., Taliun, Daniel, Moon, Sanghoon, Kwak, Soo-Heon, Robertson, Neil R., Rayner, Nigel W., Loh, Marie, Kim, Bong-Jo, Chiou, Joshua, Miguel-Escalada, Irene, della Briotta Parolo, Pietro, Lin, Kuang, Bragg, Fiona, Preuss, Michael H., Takeuchi, Fumihiko, Nano, Jana, Guo, Xiuqing, Lamri, Amel, Nakatochi, Masahiro, Scott, Robert A., Lee, Jung-Jin, Huerta-Chagoya, Alicia, Graff, Mariaelisa, Chai, Jin-Fang, Parra, Esteban J., Yao, Jie, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Steinthorsdottir, Valgerdur, Cook, James P., Kals, Mart, Grarup, Niels, Schmidt, Ellen M., Pan, Ian, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloe, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Ahmad, Meraj, Noordam, Raymond, Lim, Victor J. Y., Tam, Claudia H. T., Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M., Lecoeur, Cécile, Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R., Chen, Guanjie, Jensen, Richard A., Tajuddin, Salman, Kabagambe, Edmond K., An, Ping, Xiang, Anny H., Choi, Hyeok Sun, Cade, Brian E., Tan, Jingyi, Flanagan, Jack, Abaitua, Fernando, Adair, Linda S., Adeyemo, Adebowale, Aguilar-Salinas, Carlos A., Akiyama, Masato, Anand, Sonia S., Bertoni, Alain, Bian, Zheng, Bork-Jensen, Jette, Brandslund, Ivan, Brody, Jennifer A., Brummett, Chad M., Buchanan, Thomas A., Canouil, Mickaël, Chan, Juliana C. N., Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Das, Swapan K., de Silva, H. Janaka, Dedoussis, George, Dimitrov, Latchezar, Doumatey, Ayo P., Du, Shufa, Duan, Qing, Eckardt, Kai-Uwe, Emery, Leslie S., Evans, Daniel S., Evans, Michele K., Fischer, Krista, Floyd, James S., Ford, Ian, Fornage, Myriam, Franco, Oscar H., Frayling, Timothy M., Freedman, Barry I., Fuchsberger, Christian, Genter, Pauline, Gerstein, Hertzel C., Giedraitis, Vilmantas, González-Villalpando, Clicerio, González-Villalpando, Maria Elena, Goodarzi, Mark O., Gordon-Larsen, Penny, Gorkin, David, Gross, Myron, Guo, Yu, Hackinger, Sophie, Han, Sohee, Hattersley, Andrew T., Herder, Christian, Howard, Annie-Green, Hsueh, Willa, Huang, Mengna, Huang, Wei, Hung, Yi-Jen, Hwang, Mi Yeong, Hwu, Chii-Min, Ichihara, Sahoko, Ikram, Mohammad Arfan, Ingelsson, Martin, Islam, Md Tariqul, Isono, Masato, Jang, Hye-Mi, Jasmine, Farzana, Jiang, Guozhi, Jonas, Jost B., Jørgensen, Marit E., Jørgensen, Torben, Kamatani, Yoichiro, Kandeel, Fouad R., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kaur, Varinderpal, Kawaguchi, Takahisa, Keaton, Jacob M., Kho, Abel N., Khor, Chiea-Chuen, Kibriya, Muhammad G., Kim, Duk-Hwan, Kohara, Katsuhiko, Kriebel, Jennifer, Kronenberg, Florian, Kuusisto, Johanna, Läll, Kristi, Lange, Leslie A., Lee, Myung-Shik, Lee, Nanette R., Leong, Aaron, Li, Liming, Li, Yun, Li-Gao, Ruifang, Ligthart, Symen, Lindgren, Cecilia M., Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Locke, Adam E., Louie, Tin, Luan, Jian’an, Luk, Andrea O., Luo, Xi, Lv, Jun, Lyssenko, Valeriya, Mamakou, Vasiliki, Mani, K. Radha, Meitinger, Thomas, Metspalu, Andres, Morris, Andrew D., Nadkarni, Girish N., Nadler, Jerry L., Nalls, Michael A., Nayak, Uma, Nongmaithem, Suraj S., Ntalla, Ioanna, Okada, Yukinori, Orozco, Lorena, Patel, Sanjay R., Pereira, Mark A., Peters, Annette, Pirie, Fraser J., Porneala, Bianca, Prasad, Gauri, Preissl, Sebastian, Rasmussen-Torvik, Laura J., Reiner, Alexander P., Roden, Michael, Rohde, Rebecca, Roll, Kathryn, Sabanayagam, Charumathi, Sander, Maike, Sandow, Kevin, Sattar, Naveed, Schönherr, Sebastian, Schurmann, Claudia, Shahriar, Mohammad, Shi, Jinxiu, Shin, Dong Mun, Shriner, Daniel, Smith, Jennifer A., So, Wing Yee, Stančáková, Alena, Stilp, Adrienne M., Strauch, Konstantin, Suzuki, Ken, Takahashi, Atsushi, Taylor, Kent D., Thorand, Barbara, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Tomlinson, Brian, Torres, Jason M., Tsai, Fuu-Jen, Tuomilehto, Jaakko, Tusie-Luna, Teresa, Udler, Miriam S., Valladares-Salgado, Adan, van Dam, Rob M., van Klinken, Jan B., Varma, Rohit, Vujkovic, Marijana, Wacher-Rodarte, Niels, Wheeler, Eleanor, Whitsel, Eric A., Wickremasinghe, Ananda R., van Dijk, Ko Willems, Witte, Daniel R., Yajnik, Chittaranjan S., Yamamoto, Ken, Yamauchi, Toshimasa, Yengo, Loïc, Yoon, Kyungheon, Yu, Canqing, Yuan, Jian-Min, Yusuf, Salim, Zhang, Liang, Zheng, Wei, Raffel, Leslie J., Igase, Michiya, Ipp, Eli, Redline, Susan, Cho, Yoon Shin, Lind, Lars, Province, Michael A., Hanis, Craig L., Peyser, Patricia A., Ingelsson, Erik, Zonderman, Alan B., Psaty, Bruce M., Wang, Ya-Xing, Rotimi, Charles N., Becker, Diane M., Matsuda, Fumihiko, Liu, Yongmei, Zeggini, Eleftheria, Yokota, Mitsuhiro, Rich, Stephen S., Kooperberg, Charles, Pankow, James S., Engert, James C., Chen, Yii-Der Ida, Froguel, Philippe, Wilson, James G., Sheu, Wayne H. H., Kardia, Sharon L. R., Wu, Jer-Yuarn, Hayes, M. Geoffrey, Ma, Ronald C. W., Wong, Tien-Yin, Groop, Leif, Mook-Kanamori, Dennis O., Chandak, Giriraj R., Collins, Francis S., Bharadwaj, Dwaipayan, Paré, Guillaume, Sale, Michèle M., Ahsan, Habibul, Motala, Ayesha A., Shu, Xiao-Ou, Park, Kyong-Soo, Jukema, J. Wouter, Cruz, Miguel, McKean-Cowdin, Roberta, Grallert, Harald, Cheng, Ching-Yu, Bottinger, Erwin P., Dehghan, Abbas, Tai, E-Shyong, Dupuis, Josée, Kato, Norihiro, Laakso, Markku, Köttgen, Anna, Koh, Woon-Puay, Palmer, Colin N. A., Liu, Simin, Abecasis, Goncalo, Kooner, Jaspal S., Loos, Ruth J. F., North, Kari E., Haiman, Christopher A., Florez, Jose C., Saleheen, Danish, Hansen, Torben, Pedersen, Oluf, Mägi, Reedik, Langenberg, Claudia, Wareham, Nicholas J., Maeda, Shiro, Kadowaki, Takashi, Lee, Juyoung, Millwood, Iona Y., Walters, Robin G., Stefansson, Kari, Myers, Simon R., Ferrer, Jorge, Gaulton, Kyle J., Meigs, James B., Mohlke, Karen L., Gloyn, Anna L., Bowden, Donald W., Below, Jennifer E., Chambers, John C., Sim, Xueling, Boehnke, Michael, Rotter, Jerome I., McCarthy, Mark I., and Morris, Andrew P.

Published
2022
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7. A high-resolution map of non-crossover events reveals impacts of genetic diversity on mammalian meiotic recombination

Author

Li, Ran, Bitoun, Emmanuelle, Altemose, Nicolas, Davies, Robert W, Davies, Benjamin, and Myers, Simon R

Subjects
Human Genome, Biotechnology, Genetics, Contraception/Reproduction, 1.1 Normal biological development and functioning, Underpinning research, Generic health relevance, Alleles, Animals, Cell Cycle Proteins, Chromosomes, Crossing Over, Genetic, DNA Breaks, Double-Stranded, DNA Damage, DNA Mismatch Repair, Female, Gene Conversion, Genetic Variation, Histone-Lysine N-Methyltransferase, Histones, Homologous Recombination, Humans, Hybridization, Genetic, Male, Mice, Mice, Inbred C57BL, Models, Genetic, Phosphate-Binding Proteins, Polymorphism, Single Nucleotide, Recombinational DNA Repair
Abstract

During meiotic recombination, homologue-templated repair of programmed DNA double-strand breaks (DSBs) produces relatively few crossovers and many difficult-to-detect non-crossovers. By intercrossing two diverged mouse subspecies over five generations and deep-sequencing 119 offspring, we detect thousands of crossover and non-crossover events genome-wide with unprecedented power and spatial resolution. We find that both crossovers and non-crossovers are strongly depleted at DSB hotspots where the DSB-positioning protein PRDM9 fails to bind to the unbroken homologous chromosome, revealing that PRDM9 also functions to promote homologue-templated repair. Our results show that complex non-crossovers are much rarer in mice than humans, consistent with complex events arising from accumulated non-programmed DNA damage. Unexpectedly, we also find that GC-biased gene conversion is restricted to non-crossover tracts containing only one mismatch. These results demonstrate that local genetic diversity profoundly alters meiotic repair pathway decisions via at least two distinct mechanisms, impacting genome evolution and Prdm9-related hybrid infertility.

Published
2019

11. List of Contributors

Author

Adamthwaite, Jonathan, primary, Deek, Nidal Farhan AL, additional, Alhusainan, Hanan, additional, Allen, Robert J., additional, Ayers, Rebecca, additional, Azad, Gurdip, additional, Azzi, Alain J., additional, Barnacle, Alex, additional, Bartlett, Scott P., additional, Belinsky, Irina, additional, Ben-Amotz, Oded, additional, Blecher, Nathaniel A., additional, Boyd, Kirsty, additional, Bruckman, Karl C., additional, Buck, Donald W., additional, Bulstrode, Neil W., additional, Burr, Nicola, additional, Butler, Daniel P., additional, Cohen, Marc A., additional, Coleman, Sydney R., additional, Constantine, Ryan, additional, Coriddi, Michelle, additional, Cugno, Sabrina, additional, David, David J., additional, Davidge, Kristen M., additional, Dayan, Joseph, additional, Degreef, Ilse, additional, Dunaway, David J., additional, Egro, Francesco M., additional, Elahi, Ebby, additional, Elyassnia, Dino, additional, Evans, Kathryn, additional, Farhadieh, Rostam D., additional, Findlay, Michael W., additional, Firmin, Françoise, additional, Fisher, David M., additional, Flood, Stephen, additional, Forte, Antonio J., additional, Gascoigne, Adam C., additional, Gilardino, Mirko S., additional, Greig, Aina V.H., additional, Grobbelaar, Adriaan O., additional, Gurtner, Geoffrey C., additional, Gunn, Lucinda, additional, Guyuron, Bahman, additional, Hall-Findlay, Elizabeth J., additional, Hanasono, Matthew M., additional, Harper, John, additional, Hassan, Kareem, additional, Henderson, Michael A., additional, Hespe, Geoffrey E., additional, Heuft, Tobias, additional, Hofer, Stefan O.P., additional, Hovius, Steven E.R., additional, Howes, Benjamin H.L., additional, Hsieh, Yun-Huan (Barry), additional, Jallali, Navid, additional, Jemec, Barbara, additional, Joji, Nikita, additional, Kanani, Mazyar, additional, Kataru, Raghu P., additional, Kerolus, Julia L., additional, Kinsler, Veronica, additional, Krauss, Emily M., additional, Leckenby, Jonathan I., additional, Lee, Gordon K., additional, Levi, Ben, additional, Levin, L. Scott, additional, Liew, Se Hwang, additional, Loh, Charles Y.Y., additional, Mackinnon, Susan E., additional, Marten, Timothy J., additional, Mathes, David W., additional, McCarten, Gregory, additional, McNab, Alan A., additional, Mehrara, Babak J., additional, Mendelson, Bryan, additional, Mendenhall, Shaun D., additional, Mericli, Alexander F., additional, Mimica, Ximena, additional, Morrison, Edwin, additional, Morrison, Wayne A.J., additional, Morritt, Andrew, additional, Mosahebi, Afshin, additional, Murray, Peter M., additional, Mushtaq, Imran, additional, Muthialu, Nagarajan, additional, Myers, Simon, additional, Nassif, Paul S., additional, Nijhuis, Tim H.J., additional, Nikkhah, Dariush, additional, Niranjan, Niri S., additional, Noland, Shelley S., additional, Nutting, Chris, additional, Ogunleye, Adeyemi A., additional, O’Neill, Anne C., additional, Pearl, Robert, additional, Lee Peng, Grace, additional, Perotti, Olivia M., additional, Pickford, Mark, additional, Power, Hollie A., additional, Rao, Krishna, additional, Rau, Aline, additional, Reavey, Patrick L., additional, Richter, Dirk F., additional, Rodriguez, Abigail M., additional, Rossi, Carlo Riccardo, additional, Rubin, J. Peter, additional, Saint-Cyr, Michel, additional, Sammut, Donald, additional, See, Marlene, additional, Siemionow, Maria Z., additional, Sivakumar, Bran, additional, Smith, Oliver J., additional, Smith, Paul, additional, Sommariva, Antonio, additional, Sommerlad, Brian C., additional, Soufan, Catherine, additional, Steinbacher, Derek M., additional, Sud, Ajay R., additional, Sullivan, Justine Victoria, additional, Swan, Marc C., additional, Tang, Jin Bo, additional, Totonchi, Ali, additional, Townley, William A., additional, van de Lande, Lara S., additional, Weber, Renata V., additional, Wei, Fu-Chan, additional, Werker, Paul M.N., additional, Wink, Jason, additional, Withey, Simon, additional, Wong, Chin Ho, additional, Wong, Stacy, additional, Ziabari, Yasamin, additional, Zoltan, Susan, additional, and Zor, Fatih, additional

Published
2022
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12. International microsurgery simulation society (IMSS) consensus statement on the minimum standards for a basic microsurgery course, requirements for a microsurgical anastomosis global rating scale and minimum thresholds for training

Author

Ghanem, Ali, Kearns, Marie, Ballestín, Alberto, Froschauer, Stefan, Akelina, Yelena, Shurey, Sandra, Legagneux, Josette, Ramachandran, Savitha, Cozzolino, Santolo, Ramakrishnan, Venkat, Pafitanis, Georgios, Zakaria, Yehya, Al-Maaytah, Kalid, Komatsu, Seiji, Kimata, Yoshihori, Cifuentes, Ignacio, Soucacos, Panayotis N., Tos, Pierluigi, and Myers, Simon

Published
2020
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14. A map of human PRDM9 binding provides evidence for novel behaviors of PRDM9 and other zinc-finger proteins in meiosis

Author

Altemose, Nicolas, Noor, Nudrat, Bitoun, Emmanuelle, Tumian, Afidalina, Imbeault, Michael, Chapman, J Ross, Aricescu, A Radu, and Myers, Simon R

Subjects
Biochemistry and Cell Biology, Bioinformatics and Computational Biology, Biological Sciences, Genetics, Human Genome, Biotechnology, 1.1 Normal biological development and functioning, Underpinning research, Generic health relevance, Binding Sites, Chromosome Mapping, DNA, HEK293 Cells, Histone-Lysine N-Methyltransferase, Homologous Recombination, Humans, Meiosis, Protein Binding, Protein Multimerization, KRAB, PRDM9, chromosomes, evolutionary biology, genes, genomics, human, meiosis, recombination, transposable elements, zinc finger protein, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

PRDM9 binding localizes almost all meiotic recombination sites in humans and mice. However, most PRDM9-bound loci do not become recombination hotspots. To explore factors that affect binding and subsequent recombination outcomes, we mapped human PRDM9 binding sites in a transfected human cell line and measured PRDM9-induced histone modifications. These data reveal varied DNA-binding modalities of PRDM9. We also find that human PRDM9 frequently binds promoters, despite their low recombination rates, and it can activate expression of a small number of genes including CTCFL and VCX. Furthermore, we identify specific sequence motifs that predict consistent, localized meiotic recombination suppression around a subset of PRDM9 binding sites. These motifs strongly associate with KRAB-ZNF protein binding, TRIM28 recruitment, and specific histone modifications. Finally, we demonstrate that, in addition to binding DNA, PRDM9's zinc fingers also mediate its multimerization, and we show that a pair of highly diverged alleles preferentially form homo-multimers.

Published
2017

16. Re-engineering the zinc fingers of PRDM9 reverses hybrid sterility in mice

Author

Davies, Benjamin, Hatton, Edouard, Altemose, Nicolas, Hussin, Julie G, Pratto, Florencia, Zhang, Gang, Hinch, Anjali Gupta, Moralli, Daniela, Biggs, Daniel, Diaz, Rebeca, Preece, Chris, Li, Ran, Bitoun, Emmanuelle, Brick, Kevin, Green, Catherine M, Camerini-Otero, R Daniel, Myers, Simon R, and Donnelly, Peter

Subjects
Biochemistry and Cell Biology, Biological Sciences, Infertility, Biotechnology, Human Genome, Genetics, Contraception/Reproduction, Underpinning research, 1.1 Normal biological development and functioning, Generic health relevance, Alleles, Animals, Binding Sites, Chromosome Pairing, Chromosomes, Mammalian, DNA Breaks, Double-Stranded, Female, Genetic Speciation, Histone-Lysine N-Methyltransferase, Humans, Hybridization, Genetic, Male, Meiosis, Mice, Mice, Inbred C57BL, Protein Binding, Protein Engineering, Protein Structure, Tertiary, Recombination, Genetic, Zinc Fingers, General Science & Technology
Abstract

The DNA-binding protein PRDM9 directs positioning of the double-strand breaks (DSBs) that initiate meiotic recombination in mice and humans. Prdm9 is the only mammalian speciation gene yet identified and is responsible for sterility phenotypes in male hybrids of certain mouse subspecies. To investigate PRDM9 binding and its role in fertility and meiotic recombination, we humanized the DNA-binding domain of PRDM9 in C57BL/6 mice. This change repositions DSB hotspots and completely restores fertility in male hybrids. Here we show that alteration of one Prdm9 allele impacts the behaviour of DSBs controlled by the other allele at chromosome-wide scales. These effects correlate strongly with the degree to which each PRDM9 variant binds both homologues at the DSB sites it controls. Furthermore, higher genome-wide levels of such 'symmetric' PRDM9 binding associate with increasing fertility measures, and comparisons of individual hotspots suggest binding symmetry plays a downstream role in the recombination process. These findings reveal that subspecies-specific degradation of PRDM9 binding sites by meiotic drive, which steadily increases asymmetric PRDM9 binding, has impacts beyond simply changing hotspot positions, and strongly support a direct involvement in hybrid infertility. Because such meiotic drive occurs across mammals, PRDM9 may play a wider, yet transient, role in the early stages of speciation.

Published
2016

17. Identifying recombination hotspots using population genetic data

Author

Auton, Adam, Myers, Simon, and McVean, Gil

Subjects
Quantitative Biology - Quantitative Methods, Quantitative Biology - Populations and Evolution
Abstract

Motivation: Recombination rates vary considerably at the fine scale within mammalian genomes, with the majority of recombination occurring within hotspots of ~2 kb in width. We present a method for inferring the location of recombination hotspots from patterns of linkage disequilibrium within samples of population genetic data. Results: Using simulations, we show that our method has hotspot detection power of approximately 50-60%, but depending on the magnitude of the hotspot. The false positive rate is between 0.24 and 0.56 false positives per Mb for data typical of humans. Availability: http://github.com/auton1/LDhot, Comment: 3 pages, 1 figure

Published
2014

20. Extreme selective sweeps independently targeted the X chromosomes of the great apes

Author

Nam, Kiwoong, Munch, Kasper, Hobolth, Asger, Dutheil, Julien Yann, Veeramah, Krishna R, Woerner, August E, Hammer, Michael F, Mailund, Thomas, Schierup, Mikkel Heide, Prado-Martinez, Javier, Sudmant, Peter H, Kidd, Jeffrey M, Li, Heng, Kelley, Joanna L, Lorente-Galdos, Belen, O’Connor, Timothy D, Santpere, Gabriel, Cagan, Alexander, Theunert, Christoph, Casals, Ferran, Laayouni, Hafid, Halager, Anders E, Malig, Maika, Hernandez-Rodriguez, Jessica, Hernando-Herraez, Irene, Prüfer, Kay, Pybus, Marc, Johnstone, Laurel, Lachmann, Michael, Alkan, Can, Twigg, Dorina, Petit, Natalia, Baker, Carl, Hormozdiari, Fereydoun, Fernandez-Callejo, Marcos, Dabad, Marc, Wilson, Michael L, Stevison, Laurie, Camprubí, Cristina, Carvalho, Tiago, Ruiz-Herrera, Aurora, Vives, Laura, Mele, Marta, Abello, Teresa, Kondova, Ivanela, Bontrop, Ronald E, Pusey, Anne, Lankester, Felix, Kiyang, John A, Bergl, Richard A, Lonsdorf, Elizabeth, Myers, Simon, Ventura, Mario, Gagneux, Pascal, Comas, David, Siegismund, Hans, Blanc, Julie, Agueda-Calpena, Lidia, Gut, Marta, Fulton, Lucinda, Tishkoff, Sarah A, Mullikin, James C, Wilson, Richard K, Gut, Ivo G, Gonder, Mary Katherine, Ryder, Oliver A, Hahn, Beatrice H, Navarro, Arcadi, Akey, Joshua M, Bertranpetit, Jaume, Reich, David, Schierup, Mikkel H, Hvilsom, Christina, Andrés, Aida M, Wall, Jeffrey D, Bustamante, Carlos D, Eichler, Evan E, and Marques-Bonet, Tomas

Subjects
Human Genome, Genetics, Animals, Computational Biology, Databases, Genetic, Genetic Variation, Genetics, Population, Hominidae, Models, Genetic, Polymorphism, Genetic, Selection, Genetic, Species Specificity, X Chromosome, Great Ape Genome Diversity Project, X-chromosome evolution, ampliconic genes, great apes, meiotic drive, selective sweeps
Abstract

The unique inheritance pattern of the X chromosome exposes it to natural selection in a way that is different from that of the autosomes, potentially resulting in accelerated evolution. We perform a comparative analysis of X chromosome polymorphism in 10 great ape species, including humans. In most species, we identify striking megabase-wide regions, where nucleotide diversity is less than 20% of the chromosomal average. Such regions are found exclusively on the X chromosome. The regions overlap partially among species, suggesting that the underlying targets are partly shared among species. The regions have higher proportions of singleton SNPs, higher levels of population differentiation, and a higher nonsynonymous-to-synonymous substitution ratio than the rest of the X chromosome. We show that the extent to which diversity is reduced is incompatible with direct selection or the action of background selection and soft selective sweeps alone, and therefore, we suggest that very strong selective sweeps have independently targeted these specific regions in several species. The only genomic feature that we can identify as strongly associated with loss of diversity is the location of testis-expressed ampliconic genes, which also have reduced diversity around them. We hypothesize that these genes may be responsible for selective sweeps in the form of meiotic drive caused by an intragenomic conflict in male meiosis.

Published
2015

25. Great ape genetic diversity and population history.

Author

Prado-Martinez, Javier, Sudmant, Peter H, Kidd, Jeffrey M, Li, Heng, Kelley, Joanna L, Lorente-Galdos, Belen, Veeramah, Krishna R, Woerner, August E, O'Connor, Timothy D, Santpere, Gabriel, Cagan, Alexander, Theunert, Christoph, Casals, Ferran, Laayouni, Hafid, Munch, Kasper, Hobolth, Asger, Halager, Anders E, Malig, Maika, Hernandez-Rodriguez, Jessica, Hernando-Herraez, Irene, Prüfer, Kay, Pybus, Marc, Johnstone, Laurel, Lachmann, Michael, Alkan, Can, Twigg, Dorina, Petit, Natalia, Baker, Carl, Hormozdiari, Fereydoun, Fernandez-Callejo, Marcos, Dabad, Marc, Wilson, Michael L, Stevison, Laurie, Camprubí, Cristina, Carvalho, Tiago, Ruiz-Herrera, Aurora, Vives, Laura, Mele, Marta, Abello, Teresa, Kondova, Ivanela, Bontrop, Ronald E, Pusey, Anne, Lankester, Felix, Kiyang, John A, Bergl, Richard A, Lonsdorf, Elizabeth, Myers, Simon, Ventura, Mario, Gagneux, Pascal, Comas, David, Siegismund, Hans, Blanc, Julie, Agueda-Calpena, Lidia, Gut, Marta, Fulton, Lucinda, Tishkoff, Sarah A, Mullikin, James C, Wilson, Richard K, Gut, Ivo G, Gonder, Mary Katherine, Ryder, Oliver A, Hahn, Beatrice H, Navarro, Arcadi, Akey, Joshua M, Bertranpetit, Jaume, Reich, David, Mailund, Thomas, Schierup, Mikkel H, Hvilsom, Christina, Andrés, Aida M, Wall, Jeffrey D, Bustamante, Carlos D, Hammer, Michael F, Eichler, Evan E, and Marques-Bonet, Tomas

Subjects
Animals, Animals, Wild, Animals, Zoo, Hominidae, Gorilla gorilla, Humans, Pan paniscus, Pan troglodytes, Inbreeding, Genetics, Population, Population Density, Evolution, Molecular, Phylogeny, Polymorphism, Single Nucleotide, Genome, Africa, Asia, Southeastern, Gene Flow, Genetic Variation, General Science & Technology
Abstract

Most great ape genetic variation remains uncharacterized; however, its study is critical for understanding population history, recombination, selection and susceptibility to disease. Here we sequence to high coverage a total of 79 wild- and captive-born individuals representing all six great ape species and seven subspecies and report 88.8 million single nucleotide polymorphisms. Our analysis provides support for genetically distinct populations within each species, signals of gene flow, and the split of common chimpanzees into two distinct groups: Nigeria-Cameroon/western and central/eastern populations. We find extensive inbreeding in almost all wild populations, with eastern gorillas being the most extreme. Inferred effective population sizes have varied radically over time in different lineages and this appears to have a profound effect on the genetic diversity at, or close to, genes in almost all species. We discover and assign 1,982 loss-of-function variants throughout the human and great ape lineages, determining that the rate of gene loss has not been different in the human branch compared to other internal branches in the great ape phylogeny. This comprehensive catalogue of great ape genome diversity provides a framework for understanding evolution and a resource for more effective management of wild and captive great ape populations.

Published
2013

27. The landscape of recombination in African Americans

Author

Hinch, Anjali G, Tandon, Arti, Patterson, Nick, Song, Yunli, Rohland, Nadin, Palmer, Cameron D, Chen, Gary K, Wang, Kai, Buxbaum, Sarah G, Akylbekova, Ermeg L, Aldrich, Melinda C, Ambrosone, Christine B, Amos, Christopher, Bandera, Elisa V, Berndt, Sonja I, Bernstein, Leslie, Blot, William J, Bock, Cathryn H, Boerwinkle, Eric, Cai, Qiuyin, Caporaso, Neil, Casey, Graham, Adrienne Cupples, L, Deming, Sandra L, Ryan Diver, W, Divers, Jasmin, Fornage, Myriam, Gillanders, Elizabeth M, Glessner, Joseph, Harris, Curtis C, Hu, Jennifer J, Ingles, Sue A, Isaacs, William, John, Esther M, Linda Kao, WH, Keating, Brendan, Kittles, Rick A, Kolonel, Laurence N, Larkin, Emma, Le Marchand, Loic, McNeill, Lorna H, Millikan, Robert C, Murphy, Musani, Solomon, Neslund-Dudas, Christine, Nyante, Sarah, Papanicolaou, George J, Press, Michael F, Psaty, Bruce M, Reiner, Alex P, Rich, Stephen S, Rodriguez-Gil, Jorge L, Rotter, Jerome I, Rybicki, Benjamin A, Schwartz, Ann G, Signorello, Lisa B, Spitz, Margaret, Strom, Sara S, Thun, Michael J, Tucker, Margaret A, Wang, Zhaoming, Wiencke, John K, Witte, John S, Wrensch, Margaret, Wu, Xifeng, Yamamura, Yuko, Zanetti, Krista A, Zheng, Wei, Ziegler, Regina G, Zhu, Xiaofeng, Redline, Susan, Hirschhorn, Joel N, Henderson, Brian E, Taylor Jr, Herman A, Price, Alkes L, Hakonarson, Hakon, Chanock, Stephen J, Haiman, Christopher A, Wilson, James G, Reich, David, and Myers, Simon R

Subjects
Biological Sciences, Genetics, Biotechnology, Human Genome, Africa, Western, Black or African American, Alleles, Amino Acid Motifs, Base Sequence, Chromosome Mapping, Crossing Over, Genetic, Europe, Evolution, Molecular, Female, Gene Frequency, Genetics, Population, Genome, Human, Genomics, Haplotypes, Histone-Lysine N-Methyltransferase, Humans, Male, Molecular Sequence Data, Pedigree, Polymorphism, Single Nucleotide, Probability, White People, General Science & Technology
Abstract

Recombination, together with mutation, gives rise to genetic variation in populations. Here we leverage the recent mixture of people of African and European ancestry in the Americas to build a genetic map measuring the probability of crossing over at each position in the genome, based on about 2.1 million crossovers in 30,000 unrelated African Americans. At intervals of more than three megabases it is nearly identical to a map built in Europeans. At finer scales it differs significantly, and we identify about 2,500 recombination hotspots that are active in people of West African ancestry but nearly inactive in Europeans. The probability of a crossover at these hotspots is almost fully controlled by the alleles an individual carries at PRDM9 (P value

Published
2011

28. Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.

Author

Pasaniuc, Bogdan, Zaitlen, Noah, Lettre, Guillaume, Chen, Gary K, Tandon, Arti, Kao, WH Linda, Ruczinski, Ingo, Fornage, Myriam, Siscovick, David S, Zhu, Xiaofeng, Larkin, Emma, Lange, Leslie A, Cupples, L Adrienne, Yang, Qiong, Akylbekova, Ermeg L, Musani, Solomon K, Divers, Jasmin, Mychaleckyj, Joe, Li, Mingyao, Papanicolaou, George J, Millikan, Robert C, Ambrosone, Christine B, John, Esther M, Bernstein, Leslie, Zheng, Wei, Hu, Jennifer J, Ziegler, Regina G, Nyante, Sarah J, Bandera, Elisa V, Ingles, Sue A, Press, Michael F, Chanock, Stephen J, Deming, Sandra L, Rodriguez-Gil, Jorge L, Palmer, Cameron D, Buxbaum, Sarah, Ekunwe, Lynette, Hirschhorn, Joel N, Henderson, Brian E, Myers, Simon, Haiman, Christopher A, Reich, David, Patterson, Nick, Wilson, James G, and Price, Alkes L

Subjects
Humans, Breast Neoplasms, Coronary Disease, Diabetes Mellitus, Type 2, Odds Ratio, Chromosome Mapping, Genetics, Population, Gene Frequency, Genotype, Linkage Disequilibrium, Phenotype, Polymorphism, Single Nucleotide, Genome, Human, Algorithms, Principal Component Analysis, Software, African Americans, Female, Male, Receptor, Fibroblast Growth Factor, Type 2, Genetic Variation, Genome-Wide Association Study, Diabetes Mellitus, Type 2, Genetics, Population, Polymorphism, Single Nucleotide, Genome, Human, Receptor, Fibroblast Growth Factor, Developmental Biology
Abstract

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.

Published
2011

34. Discussion on the Meeting on 'Statistical Modelling and Analysis of Genetic Data'

Author

Balding, David J., Carothers, Andrew D., Marchini, Jonathan L., Cardon, Lon R., Vetta, Atam, Griffiths, Bob, Weir, B. S., Hill, W. G., Goldstein, Darlene, Strimmer, Korbinian, Myers, Simon, Beaumont, Mark A., Glasbey, C. A., Mayer, C. D., Durrett, Richard, Nielsen, Rasmus, Visscher, P. M., Knott, S. A., Haley, C. S., Ball, Roderick D., Hackett, Christine A., Holmes, Susan, Husmeier, Dirk, Jansen, Ritsert C., Maliepaard, Chris A., Boer, Martin P., Joyce, Paul, Li, Na, Stephens, Matthew, Marcoulides, George A., Drezner, Zvi, Mardia, Kanti, McVean, Gilean, Meng, Xiao-Li, Ochs, Michael F., Pagel, Mark, Sha, Naijun, Vannucci, Marina, Sillanpää, Mikko J., Sisson, Scott, Yandell, Brian S., Jin, Chunfang, Satagopan, Jaya M., Gaffney, Patrick J., Zeng, Zhao-Bang, Broman, Karl W., Speed, Terence P., Fearnhead, Paul, Donnelly, Peter, Larget, Bret, Simon, Donald L., Kadane, Joseph B., Nicholson, George, Smith, Albert V., Jónsson, Frosti, Gústafsson, Ómar, Stefánsson, Kárl, Donnelly, Peter, Parmigiani, Giovanni, Garrett, Elizabeth S., Anbazhagan, Ramaswamy, and Gabrielson, Edward

Published
2002

39. Rose bengal–encapsulated chitosan nanoparticles for the photodynamic treatment of Trichophyton species

Author

Bekmukhametova, Alina, primary, Antony, Anu, additional, Halliday, Catriona, additional, Chen, Sharon, additional, Ho, Chun‐Hoong, additional, Uddin, Mir Muhammad Nasir, additional, Longo, Leonardo, additional, Pedrinazzi, Christian, additional, George, Laurel, additional, Wuhrer, Richard, additional, Myers, Simon, additional, Mawad, Damia, additional, Houang, Jessica, additional, and Lauto, Antonio, additional

Published
2023
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42. A Method to Exploit the Structure of Genetic Ancestry Space to Enhance Case-Control Studies

Author

Barclay, Murray, Peyrin-Biroulet, Laurent, Chamaillard, Mathias, Colombel, Jean-Frederick, Cottone, Mario, Croft, Anthony, D’Incà, Renata, Halfvarson, Jonas, Hanigan, Katherine, Henderson, Paul, Hugot, Jean-Pierre, Karban, Amir, Kennedy, Nicholas A., Khan, Mohammed Azam, Lémann, Marc, Levine, Arie, Massey, Dunecan, Milla, Monica, Montgomery, Grant W., Ng, Sok Meng Evelyn, Oikonomou, Ioannis, Peeters, Harald, Proctor, Deborah D., Rahier, Jean-Francois, Roberts, Rebecca, Rutgeerts, Paul, Seibold, Frank, Stronati, Laura, Taylor, Kirstin M., Törkvist, Leif, Ublick, Kullak, Van Limbergen, Johan, Van Gossum, Andre, Vatn, Morten H., Zhang, Hu, Zhang, Wei, Andrews, Jane M., Bampton, Peter A., Florin, Timothy H., Gearry, Richard, Krishnaprasad, Krupa, Lawrance, Ian C., Mahy, Gillian, Radford-Smith, Graham, Roberts, Rebecca L., Simms, Lisa A., Amininijad, Leila, Cleynen, Isabelle, Dewit, Olivier, Franchimont, Denis, Georges, Michel, Laukens, Debby, Theatre, Emilie, Van Gossum, André, Vermeire, Severine, Aumais, Guy, Baidoo, Leonard, Barrie, Arthur M., III, Beck, Karen, Bernard, Edmond-Jean, Binion, David G., Bitton, Alain, Brant, Steve R., Cho, Judy H., Cohen, Albert, Croitoru, Kenneth, Daly, Mark J., Datta, Lisa W., Deslandres, Colette, Duerr, Richard H., Dutridge, Debra, Ferguson, John, Fultz, Joann, Goyette, Philippe, Greenberg, Gordon R., Haritunians, Talin, Jobin, Gilles, Katz, Seymour, Lahaie, Raymond G., McGovern, Dermot P., Nelson, Linda, Ng, Sok Meng, Ning, Kaida, Paré, Pierre, Regueiro, Miguel D., Rioux, John D., Ruggiero, Elizabeth, Schumm, L. Philip, Schwartz, Marc, Scott, Regan, Sharma, Yashoda, Silverberg, Mark S., Spears, Denise, Steinhart, A. Hillary, Stempak, Joanne M., Swoger, Jason M., Tsagarelis, Constantina, Zhang, Clarence, Zhao, Hongyu, Aerts, Jan, Ahmad, Tariq, Arbury, Hazel, Attwood, Anthony, Auton, Adam, Ball, Stephen G., Balmforth, Anthony J., Barnes, Chris, Barrett, Jeffrey C., Barroso, Inês, Barton, Anne, Bennett, Amanda J., Bhaskar, Sanjeev, Blaszczyk, Katarzyna, Bowes, John, Brand, Oliver J., Braund, Peter S., Bredin, Francesca, Breen, Gerome, Brown, Morris J., Bruce, Ian N., Bull, Jaswinder, Burren, Oliver S., Burton, John, Byrnes, Jake, Caesar, Sian, Cardin, Niall, Clee, Chris M., Coffey, Alison J., Connell, John M.C., Conrad, Donald F., Cooper, Jason D., Dominiczak, Anna F., Downes, Kate, Drummond, Hazel E., Dudakia, Darshna, Dunham, Andrew, Ebbs, Bernadette, Eccles, Diana, Edkins, Sarah, Edwards, Cathryn, Elliot, Anna, Emery, Paul, Evans, David M., Evans, Gareth, Eyre, Steve, Farmer, Anne, I, Ferrier, Nicol, Flynn, Edward, Forbes, Alistair, Forty, Liz, Franklyn, Jayne A., Frayling, Timothy M., Freathy, Rachel M., Giannoulatou, Eleni, Gibbs, Polly, Gilbert, Paul, Gordon-Smith, Katherine, Gray, Emma, Green, Elaine, Groves, Chris J., Grozeva, Detelina, Gwilliam, Rhian, Hall, Anita, Hammond, Naomi, Hardy, Matt, Harrison, Pile, Hassanali, Neelam, Hebaishi, Husam, Hines, Sarah, Hinks, Anne, Hitman, Graham A., Hocking, Lynne, Holmes, Chris, Howard, Eleanor, Howard, Philip, Howson, Joanna M.M., Hughes, Debbie, Hunt, Sarah, Isaacs, John D., Jain, Mahim, Jewell, Derek P., Johnson, Toby, Jolley, Jennifer D., Jones, Ian R., Jones, Lisa A., Kirov, George, Langford, Cordelia F., Lango-Allen, Hana, Lathrop, G. Mark, Lee, James, Lee, Kate L., Lees, Charlie, Lewis, Kevin, Lindgren, Cecilia M., Maisuria-Armer, Meeta, Maller, Julian, Mansfield, John, Marchini, Jonathan L., Martin, Paul, Massey, Dunecan C.O., McArdle, Wendy L., McGuffin, Peter, McLay, Kirsten E., McVean, Gil, Mentzer, Alex, Mimmack, Michael L., Morgan, Ann E., Morris, Andrew P., Mowat, Craig, Munroe, Patricia B., Myers, Simon, Newman, William, Nimmo, Elaine R., O’Donovan, Michael C., Onipinla, Abiodun, Ovington, Nigel R., Owen, Michael J., Palin, Kimmo, Palotie, Aarno, Parnell, Kirstie, Pearson, Richard, Pernet, David, Perry, John R.B., Phillips, Anne, Plagnol, Vincent, Prescott, Natalie J., Prokopenko, Inga, Quail, Michael A., Rafelt, Suzanne, Rayner, Nigel W., Reid, David M., Renwick, Anthony, Ring, Susan M., Robertson, Neil, Robson, Samuel, Russell, Ellie, St Clair, David, Sambrook, Jennifer G., Sanderson, Jeremy D., Sawcer, Stephen J., Schuilenburg, Helen, Scott, Carol E., Scott, Richard, Seal, Sheila, Shaw-Hawkins, Sue, Shields, Beverley M., Simmonds, Matthew J., Smyth, Debbie J., Somaskantharajah, Elilan, Spanova, Katarina, Steer, Sophia, Stephens, Jonathan, Stevens, Helen E., Stirrups, Kathy, Stone, Millicent A., Strachan, David P., Su, Zhan, Symmons, Deborah P.M., Thompson, John R., Thomson, Wendy, Tobin, Martin D., Travers, Mary E., Turnbull, Clare, Vukcevic, Damjan, Wain, Louise V., Walker, Mark, Walker, Neil M., Wallace, Chris, Warren-Perry, Margaret, Watkins, Nicholas A., Webster, John, Weedon, Michael N., Wilson, Anthony G., Woodburn, Matthew, Wordsworth, B. Paul, Yau, Chris, Young, Allan H., Zeggini, Eleftheria, Brown, Matthew A., Burton, Paul R., Caulfield, Mark J., Compston, Alastair, Farrall, Martin, Gough, Stephen C.L., Hall, Alistair S., Hattersley, Andrew T., Hill, Adrian V.S., Mathew, Christopher G., Pembrey, Marcus, Satsangi, Jack, Stratton, Michael R., Worthington, Jane, Hurles, Matthew E., Duncanson, Audrey, Ouwehand, Willem H., Parkes, Miles, Rahman, Nazneen, Todd, John A., Samani, Nilesh J., Kwiatkowski, Dominic P., McCarthy, Mark I., Craddock, Nick, Deloukas, Panos, Donnelly, Peter, Blackwell, Jenefer M., Bramon, Elvira, Casas, Juan P., Corvin, Aiden, Jankowski, Janusz, Markus, Hugh S., Palmer, Colin N.A., Plomin, Robert, Rautanen, Anna, Trembath, Richard C., Viswanathan, Ananth C., Wood, Nicholas W., Spencer, Chris C.A., Band, Gavin, Bellenguez, Céline, Freeman, Colin, Hellenthal, Garrett, Pirinen, Matti, Strange, Amy, Blackburn, Hannah, Bumpstead, Suzannah J., Dronov, Serge, Gillman, Matthew, Jayakumar, Alagurevathi, McCann, Owen T., Liddle, Jennifer, Potter, Simon C., Ravindrarajah, Radhi, Ricketts, Michelle, Waller, Matthew, Weston, Paul, Widaa, Sara, Whittaker, Pamela, Bodea, Corneliu A., Neale, Benjamin M., Ripke, Stephan, Devlin, Bernie, and Roeder, Kathryn

Published
2016
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45. Rose bengal–encapsulated chitosan nanoparticles for the photodynamic treatment of Trichophyton species.

Author

Bekmukhametova, Alina, Antony, Anu, Halliday, Catriona, Chen, Sharon, Ho, Chun‐Hoong, Uddin, Mir Muhammad Nasir, Longo, Leonardo, Pedrinazzi, Christian, George, Laurel, Wuhrer, Richard, Myers, Simon, Mawad, Damia, Houang, Jessica, and Lauto, Antonio

Subjects
PHOTODYNAMIC therapy, TRICHOPHYTON, CHITOSAN, ROSE bengal, NANOPARTICLES
Abstract

Rose bengal (RB) solutions coupled with a green laser have proven to be efficient in clearing resilient nail infections caused by Trichophyton rubrum in a human pilot study and in extensive in vitro experiments. Nonetheless, the RB solution can become diluted or dispersed over the tissue and prevented from penetrating the nail plate to reach the subungual area where fungal infection proliferates. Nanoparticles carrying RB can mitigate the problem of dilution and are reported to effectively penetrate through the nail. For this reason, we have synthesized RB‐encapsulated chitosan nanoparticles with a peak distribution size of ~200 nm and high reactive oxygen species (ROS) production. The RB‐encapsulated chitosan nanoparticles aPDT were shown to kill more than 99% of T. rubrum, T. mentagrophytes, and T. interdigitale spores, which are the common clinically relevant pathogens in onychomycosis. These nanoparticles are not cytotoxic against human fibroblasts, which promotes their safe application in clinical translation. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Advice-taking under Moral Uncertainty: The Role of Ethical Justifications on Moral Advice-taking

Author

Okoroafor, Junior, Myers, Simon, and Everett, Jim AC

Subjects
Artificial Intelligence and Robotics, Ethical Justifications, Moral Advice-taking, Computer Sciences, Physical Sciences and Mathematics, Artificial Moral Advisors, Trust in AI, Social and Behavioral Sciences, AI Ethics, Moral Psychology
Abstract

The purpose of this study is to investigate under what conditions people are more likely to adopt moral advice. In particular, we are investigating how a) different moral frameworks of the advisor and b) moral uncertainty of the moral decision-maker, might influence advice adoption in c) AI compared to human moral advisors.

Published
2023
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