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556 results on '"Urban, Alexander"'

1. Integrative analyses highlight functional regulatory variants associated with neuropsychiatric diseases

Author

Guo, Margaret G., Reynolds, David L., Ang, Cheen E., Liu, Yingfei, Zhao, Yang, Donohue, Laura K. H., Siprashvili, Zurab, Yang, Xue, Yoo, Yongjin, Mondal, Smarajit, Hong, Audrey, Kain, Jessica, Meservey, Lindsey, Fabo, Tania, Elfaki, Ibtihal, Kellman, Laura N., Abell, Nathan S., Pershad, Yash, Bayat, Vafa, Etminani, Payam, Holodniy, Mark, Geschwind, Daniel H., Montgomery, Stephen B., Duncan, Laramie E., Urban, Alexander E., Altman, Russ B., Wernig, Marius, and Khavari, Paul A.

Published
2023
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2. Discovering melting temperature prediction models of inorganic solids by combining supervised and unsupervised learning.

Author

Gharakhanyan, Vahe, Wirth, Luke J., Garrido Torres, Jose A., Eisenberg, Ethan, Wang, Ting, Trinkle, Dallas R., Chatterjee, Snigdhansu, and Urban, Alexander

Subjects
SUPERVISED learning, MELTING points, PREDICTION models, IONIC crystals, FIX-point estimation, MELTING
Abstract

The melting temperature is important for materials design because of its relationship with thermal stability, synthesis, and processing conditions. Current empirical and computational melting point estimation techniques are limited in scope, computational feasibility, or interpretability. We report the development of a machine learning methodology for predicting melting temperatures of binary ionic solid materials. We evaluated different machine-learning models trained on a dataset of the melting points of 476 non-metallic crystalline binary compounds using materials embeddings constructed from elemental properties and density-functional theory calculations as model inputs. A direct supervised-learning approach yields a mean absolute error of around 180 K but suffers from low interpretability. We find that the fidelity of predictions can further be improved by introducing an additional unsupervised-learning step that first classifies the materials before the melting-point regression. Not only does this two-step model exhibit improved accuracy, but the approach also provides a level of interpretability with insights into feature importance and different types of melting that depend on the specific atomic bonding inside a material. Motivated by this finding, we used a symbolic learning approach to find interpretable physical models for the melting temperature, which recovered the best-performing features from both prior models and provided additional interpretability. [ABSTRACT FROM AUTHOR]

Published
2024
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4. Genomic data resources of the Brain Somatic Mosaicism Network for neuropsychiatric diseases

Author

Garrison, McKinzie A., Jang, Yeongjun, Bae, Taejeong, Cherskov, Adriana, Emery, Sarah B., Fasching, Liana, Jones, Attila, Moldovan, John B., Molitor, Cindy, Pochareddy, Sirisha, Peters, Mette A., Shin, Joo Heon, Wang, Yifan, Yang, Xiaoxu, Akbarian, Schahram, Chess, Andrew, Gage, Fred H., Gleeson, Joseph G., Kidd, Jeffrey M., McConnell, Michael, Mills, Ryan E., Moran, John V., Park, Peter J., Sestan, Nenad, Urban, Alexander E., Vaccarino, Flora M., Walsh, Christopher A., Weinberger, Daniel R., Wheelan, Sarah J., and Abyzov, Alexej

Published
2023
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5. Pan-conserved segment tags identify ultra-conserved sequences across assemblies in the human pangenome

Author

Liao, Wen-Wei, Asri, Mobin, Ebler, Jana, Doerr, Daniel, Haukness, Marina, Hickey, Glenn, Lu, Shuangjia, Lucas, Julian K., Monlong, Jean, Abel, Haley J., Buonaiuto, Silvia, Chang, Xian H., Cheng, Haoyu, Chu, Justin, Colonna, Vincenza, Eizenga, Jordan M., Feng, Xiaowen, Fischer, Christian, Fulton, Robert S., Garg, Shilpa, Groza, Cristian, Guarracino, Andrea, Harvey, William T., Heumos, Simon, Howe, Kerstin, Jain, Miten, Lu, Tsung-Yu, Markello, Charles, Martin, Fergal J., Mitchell, Matthew W., Munson, Katherine M., Mwaniki, Moses Njagi, Novak, Adam M., Olsen, Hugh E., Pesout, Trevor, Porubsky, David, Prins, Pjotr, Sibbesen, Jonas A., Tomlinson, Chad, Villani, Flavia, Vollger, Mitchell R., Antonacci-Fulton, Lucinda L., Baid, Gunjan, Baker, Carl A., Belyaeva, Anastasiya, Billis, Konstantinos, Carroll, Andrew, Chang, Pi-Chuan, Cody, Sarah, Cook, Daniel E., Cornejo, Omar E., Diekhans, Mark, Ebert, Peter, Fairley, Susan, Fedrigo, Olivier, Felsenfeld, Adam L., Formenti, Giulio, Frankish, Adam, Gao, Yan, Giron, Carlos Garcia, Green, Richard E., Haggerty, Leanne, Hoekzema, Kendra, Hourlier, Thibaut, Ji, Hanlee P., Kolesnikov, Alexey, Korbel, Jan O., Kordosky, Jennifer, Lee, HoJoon, Lewis, Alexandra P., Magalhães, Hugo, Marco-Sola, Santiago, Marijon, Pierre, McDaniel, Jennifer, Mountcastle, Jacquelyn, Nattestad, Maria, Olson, Nathan D., Puiu, Daniela, Regier, Allison A., Rhie, Arang, Sacco, Samuel, Sanders, Ashley D., Schneider, Valerie A., Schultz, Baergen I., Shafin, Kishwar, Sirén, Jouni, Smith, Michael W., Sofia, Heidi J., Abou Tayoun, Ahmad N., Thibaud-Nissen, Françoise, Tricomi, Francesca Floriana, Wagner, Justin, Wood, Jonathan M.D., Zimin, Aleksey V., Popejoy, Alice B., Bourque, Guillaume, Chaisson, Mark J.P., Flicek, Paul, Phillippy, Adam M., Zook, Justin M., Eichler, Evan E., Haussler, David, Jarvis, Erich D., Miga, Karen H., Wang, Ting, Garrison, Erik, Marschall, Tobias, Hall, Ira, Li, Heng, Paten, Benedict, Greer, Stephanie U., Pavlichin, Dmitri S., Zhou, Bo, Urban, Alexander E., and Weissman, Tsachy

Published
2023
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6. Schizophrenia-associated somatic copy-number variants from 12,834 cases reveal recurrent NRXN1 and ABCB11 disruptions

Author

Marshall, Christian R., Merico, Daniele, Thiruvahindrapuram, Bhooma, Wang, Zhouzhi, Scherer, Stephen W., Howrigan, Daniel P, Ripke, Stephan, Bulik-Sullivan, Brendan, Farh, Kai-How, Fromer, Menachem, Goldstein, Jacqueline I., Huang, Hailiang, Lee, Phil, Daly, Mark J., Neale, Benjamin M., Belliveau, Richard A., Jr., Bergen, Sarah E., Bevilacqua, Elizabeth, Chambert, Kimberley D., O'Dushlaine, Colm, Scolnick, Edward M., Smoller, Jordan W., Moran, Jennifer L., Palotie, Aarno, Petryshen, Tracey L., Wu, Wenting, Greer, Douglas S., Antaki, Danny, Shetty, Aniket, Gujral, Madhusudan, Brandler, William M., Malhotra, Dheeraj, Fuentes Fajarado, Karin V., Maile, Michelle S., Holmans, Peter A., Carrera, Noa, Craddock, Nick, Escott-Price, Valentina, Georgieva, Lyudmila, Hamshere, Marian L., Kavanagh, David, Legge, Sophie E., Pocklington, Andrew J., Richards, Alexander L., Ruderfer, Douglas M., Williams, Nigel M., Kirov, George, Owen, Michael J., Pinto, Dalila, Cai, Guiqing, Davis, Kenneth L., Drapeau, Elodie, Friedman, Joseph I, Haroutunian, Vahram, Parkhomenko, Elena, Reichenberg, Abraham, Silverman, Jeremy M., Buxbaum, Joseph D., Domenici, Enrico, Agartz, Ingrid, Djurovic, Srdjan, Mattingsdal, Morten, Melle, Ingrid, Andreassen, Ole A., Jönsson, Erik G., Söderman, Erik, Albus, Margot, Alexander, Madeline, Laurent, Claudine, Levinson, Douglas F., Amin, Farooq, Atkins, Joshua, Cairns, Murray J., Scott, Rodney J., Tooney, Paul A., Wu, Jing Qin, Bacanu, Silviu A., Bigdeli, Tim B., Reimers, Mark A., Webb, Bradley T., Wolen, Aaron R., Wormley, Brandon K., Kendler, Kenneth S., Riley, Brien P., Kähler, Anna K., Magnusson, Patrik K.E., Hultman, Christina M., Bertalan, Marcelo, Hansen, Thomas, Olsen, Line, Rasmussen, Henrik B., Werge, Thomas, Mattheisen, Manuel, Black, Donald W., Bruggeman, Richard, Buccola, Nancy G., Buckner, Randy L., Roffman, Joshua L., Byerley, William, Cahn, Wiepke, Kahn, René S, Strengman, Eric, Ophoff, Roel A., Carr, Vaughan J., Catts, Stanley V., Henskens, Frans A., Loughland, Carmel M., Michie, Patricia T., Pantelis, Christos, Schall, Ulrich, Jablensky, Assen V., Kelly, Brian J., Campion, Dominique, Cantor, Rita M., Cheng, Wei, Cloninger, C. Robert, Svrakic, Dragan M, Cohen, David, Cormican, Paul, Donohoe, Gary, Morris, Derek W., Corvin, Aiden, Gill, Michael, Crespo-Facorro, Benedicto, Crowley, James J., Farrell, Martilias S., Giusti-Rodríguez, Paola, Kim, Yunjung, Szatkiewicz, Jin P., Williams, Stephanie, Curtis, David, Pimm, Jonathan, Gurling, Hugh, McQuillin, Andrew, Davidson, Michael, Weiser, Mark, Degenhardt, Franziska, Forstner, Andreas J., Herms, Stefan, Hoffmann, Per, Hofman, Andrea, Cichon, Sven, Nöthen, Markus M., Del Favero, Jurgen, DeLisi, Lynn E., McCarley, Robert W., Levy, Deborah L., Mesholam-Gately, Raquelle I., Seidman, Larry J., Dikeos, Dimitris, Papadimitriou, George N., Dinan, Timothy, Duan, Jubao, Sanders, Alan R., Gejman, Pablo V., Gershon, Elliot S., Dudbridge, Frank, Eichhammer, Peter, Eriksson, Johan, Salomaa, Veikko, Essioux, Laurent, Fanous, Ayman H., Knowles, James A., Pato, Michele T., Pato, Carlos N., Frank, Josef, Meier, Sandra, Schulze, Thomas G., Strohmaier, Jana, Witt, Stephanie H., Rietschel, Marcella, Franke, Lude, Karjalainen, Juha, Freedman, Robert, Olincy, Ann, Freimer, Nelson B., Purcell, Shaun M., Roussos, Panos, Stahl, Eli A., Sklar, Pamela, Giegling, Ina, Hartmann, Annette M., Konte, Bettina, Rujescu, Dan, Godard, Stephanie, Hirschhorn, Joel N., Pers, Tune H., Price, Alkes, Esko, Tõnu, Gratten, Jacob, Lee, S. Hong, Visscher, Peter M., Wray, Naomi R., Mowry, Bryan J., de Haan, Lieuwe, Meijer, Carin J., Hansen, Mark, Ikeda, Masashi, Iwata, Nakao, Joa, Inge, Kalaydjieva, Luba, Keller, Matthew C., Kennedy, James L., Zai, Clement C., Knight, Jo, Lerer, Bernard, Liang, Kung-Yee, Lieberman, Jeffrey, Stroup, T. Scott, Lönnqvist, Jouko, Suvisaari, Jaana, Maher, Brion S., Maier, Wolfgang, Mallet, Jacques, McDonald, Colm, McIntosh, Andrew M., Blackwood, Douglas H.R., Metspalu, Andres, Milani, Lili, Milanova, Vihra, Mokrab, Younes, Collier, David A., Müller-Myhsok, Bertram, Murphy, Kieran C., Murray, Robin M., Powell, John, Myin-Germeys, Inez, Van Os, Jim, Nenadic, Igor, Nertney, Deborah A., Nestadt, Gerald, Pulver, Ann E., Nicodemus, Kristin K., Nisenbaum, Laura, Nordin, Annelie, Adolfsson, Rolf, O'Callaghan, Eadbhard, Oh, Sang-Yun, O'Neill, F. Anthony, Paunio, Tiina, Pietiläinen, Olli, Perkins, Diana O., Quested, Digby, Savitz, Adam, Li, Qingqin S., Schwab, Sibylle G., Shi, Jianxin, Spencer, Chris C.A., Thirumalai, Srinivas, Veijola, Juha, Waddington, John, Walsh, Dermot, Wildenauer, Dieter B., Bramon, Elvira, Darvasi, Ariel, Posthuma, Danielle, St. Clair, David, Shanta, Omar, Klein, Marieke, Park, Peter J., Weinberger, Daniel, Moran, John V., Gage, Fred H., Vaccarino, Flora M., Gleeson, Joseph, Mathern, Gary, Courchesne, Eric, Roy, Subhojit, Bizzotto, Sara, Coulter, Michael, Dias, Caroline, D'Gama, Alissa, Ganz, Javier, Hill, Robert, Huang, August Yue, Khoshkhoo, Sattar, Kim, Sonia, Lodato, Michael, Miller, Michael, Borges-Monroy, Rebeca, Rodin, Rachel, Zhou, Zinan, Bohrson, Craig, Chu, Chong, Cortes-Ciriano, Isidro, Dou, Yanmei, Galor, Alon, Gulhan, Doga, Kwon, Minseok, Luquette, Joe, Viswanadham, Vinay, Jones, Attila, Rosenbluh, Chaggai, Cho, Sean, Langmead, Ben, Thorpe, Jeremy, Erwin, Jennifer, Jaffe, Andrew, McConnell, Michael, Narurkar, Rujuta, Paquola, Apua, Shin, Jooheon, Straub, Richard, Abyzov, Alexej, Bae, Taejeong, Jang, Yeongjun, Wang, Yifan, Gage, Fred, Linker, Sara, Reed, Patrick, Wang, Meiyan, Urban, Alexander, Zhou, Bo, Zhu, Xiaowei, Pattni, Reenal, Amero, Aitor Serres, Juan, David, Lobon, Irene, Marques-Bonet, Tomas, Moruno, Manuel Solis, Perez, Raquel Garcia, Povolotskaya, Inna, Soriano, Eduardo, Averbuj, Dan, Ball, Laurel, Breuss, Martin, Yang, Xiaoxu, Chung, Changuk, Emery, Sarah B., Flasch, Diane A., Kidd, Jeffrey M., Kopera, Huira C., Kwan, Kenneth Y., Mills, Ryan E., Moldovan, John B., Sun, Chen, Zhao, Xuefang, Zhou, Weichen, Frisbie, Trenton J., Cherskov, Adriana, Fasching, Liana, Jourdon, Alexandre, Pochareddy, Sirisha, Scuderi, Soraya, Sestan, Nenad, Maury, Eduardo A., Sherman, Maxwell A., Genovese, Giulio, Gilgenast, Thomas G., Kamath, Tushar, Burris, S.J., Rajarajan, Prashanth, Flaherty, Erin, Akbarian, Schahram, Chess, Andrew, McCarroll, Steven A., Loh, Po-Ru, Phillips-Cremins, Jennifer E., Brennand, Kristen J., Macosko, Evan Z., Walters, James T.R., O’Donovan, Michael, Sullivan, Patrick, Sebat, Jonathan, Lee, Eunjung A., and Walsh, Christopher A.

Published
2023
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7. Author Correction: Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia

Author

Zhu, Xiaowei, Zhou, Bo, Pattni, Reenal, Gleason, Kelly, Tan, Chunfeng, Kalinowski, Agnieszka, Sloan, Steven, Fiston-Lavier, Anna-Sophie, Mariani, Jessica, Petrov, Dmitri, Barres, Ben A., Duncan, Laramie, Abyzov, Alexej, Vogel, Hannes, Moran, John V., Vaccarino, Flora M., Tamminga, Carol A., Levinson, Douglas F., and Urban, Alexander E.

Published
2023
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9. Cross-platform validation of neurotransmitter release impairments in schizophrenia patient-derived NRXN1 -mutant neurons

Author

Pak, ChangHui, Danko, Tamas, Mirabella, Vincent R., Wang, Jinzhao, Liu, Yingfei, Vangipuram, Madhuri, Grieder, Sarah, Zhang, Xianglong, Ward, Thomas, Huang, Yu-Wen Alvin, Jin, Kang, Dexheimer, Philip, Bardes, Eric, Mitelpunkt, Alexis, Ma, Junyi, McLachlan, Michael, Moore, Jennifer C., Qu, Pingping, Purmann, Carolin, Dage, Jeffrey L., Swanson, Bradley J., Urban, Alexander E., Aronow, Bruce J., Pang, Zhiping P., Levinson, Douglas F., Wernig, Marius, and Südhof, Thomas C.

Published
2021

11. Resolving the 22q11.2 deletion using CTLR-Seq reveals chromosomal rearrangement mechanisms and individual variance in breakpoints.

Author

Bo Zhou, Purmann, Carolin, Hanmin Guo, GiWon Shin, Yiling Huang, Pattni, Reenal, Qingxi Meng, Greer, Stephanie U., Roychowdhury, Tanmoy, Wood, Raegan N., Ho, Marcus, zu Dohna, Heinrich, Abyzov, Alexej, Hallmayer, Joachim F., Wong, Wing H., Ji, Hanlee P., and Urban, Alexander E.

Subjects
DIGEORGE syndrome, DNA analysis, CHROMOSOMAL rearrangement, 22Q11 deletion syndrome, HUMAN genome
Abstract

We developed a generally applicable method, CRISPR/Cas9-targeted long-read sequencing (CTLR-Seq), to resolve, haplotype-specifically, the large and complex regions in the human genome that had been previously impenetrable to sequencing analysis, such as large segmental duplications (SegDups) and their associated genome rearrangements. CTLR-Seq combines in vitro Cas9-mediated cutting of the genome and pulse-field gel electrophoresis to isolate intact large (i.e., up to 2,000 kb) genomic regions that encompass previously unresolvable genomic sequences. These targets are then sequenced (amplification-free) at high on-target coverage using long-read sequencing, allowing for their complete sequence assembly. We applied CTLR-Seq to the SegDup-mediated rearrangements that constitute the boundaries of, and give rise to, the 22q11.2 Deletion Syndrome (22q11DS), the most common human microdeletion disorder. We then performed de novo assembly to resolve, at base-pair resolution, the full sequence rearrangements and exact chromosomal breakpoints of 22q11.2DS (including all common subtypes). Across multiple patients, we found a high degree of variability for both the rearranged SegDup sequences and the exact chromosomal breakpoint locations, which coincide with various transposons within the 22q11.2 SegDups, suggesting that 22q11DS can be driven by transposon-mediated genome recombination. Guided by CTLR-Seq results from two 22q11DS patients, we performed three-dimensional chromosomal folding analysis for the 22q11.2 SegDups from patient-derived neurons and astrocytes and found chromosome interactions anchored within the SegDups to be both cell type-specific and patient-specific. Lastly, we demonstrated that CTLR-Seq enables cell-type specific analysis of DNA methylation patterns within the deletion haplotype of 22q11DS. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Fine‐Tuning Blue‐Emitting Halide Perovskite Nanocrystals.

Author

Martin, Stefan, Henke, Nina A., Lampe, Carola, Döblinger, Markus, Frank, Kilian, Ganswindt, Patrick, Nickel, Bert, and Urban, Alexander S.

Subjects
PEROVSKITE, LEAD halides, OPTICAL spectroscopy, HALIDES, ELECTRON microscopy, PHOTOLUMINESCENCE, NANOCRYSTALS
Abstract

Lead halide perovskite nanocrystals (NCs) with narrow, bright emission in the visible range are promising candidates for light‐emitting applications. Near‐unity quantum yields have been realized for green and red‐emitting perovskites, but efficient, stable blue‐emitting perovskite materials are scarce. Current methods to synthesize quantum‐confined CsPbBr3 NCs with blue emission are limited to specific wavelength ranges and still suffer from inhomogeneously broadened emission profiles. Herein, anisotropic blue‐green emitting CsPbBr3 NCs are synthesized in ambient atmosphere using a spontaneous crystallization method. Optical spectroscopy reveals a gradual, asymptotic photoluminescence (PL) redshift of pristine colloidal NCs after synthesis. During this process, the emission quality improves notably as the PL spectra become narrower and more symmetric, accompanied by a PL intensity increase. Electron microscopy indicates that the gradual redshift stems from an isotropic growth of the CsPbBr3 NCs in at least two dimensions, likely due to residual precursor ions in the dispersion. Most importantly, the growth process can be halted at any point by injecting an enhancement solution containing PbBr2 and organic capping ligands. Thus, excellent control over NC size is achieved, allowing for nanometer‐precise tunability of the respective emission wavelength in the range between 475 and 500 nm, enhancing the functionality of these already impressive NCs. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Dark‐Bright Exciton Splitting Dominates Low‐Temperature Diffusion in Halide Perovskite Nanocrystal Assemblies.

Author

Bornschlegl, Andreas J., Lichtenegger, Michael F., Luber, Leo, Lampe, Carola, Bodnarchuk, Maryna I., Kovalenko, Maksym V., and Urban, Alexander S.

Subjects
SEMICONDUCTOR nanocrystals, PEROVSKITE, OSCILLATOR strengths, HALIDES, BINDING energy, CHARGE carriers, NANOCRYSTALS, CHARGE carrier mobility, SUPERLATTICES
Abstract

Semiconductor nanocrystals can replace conventional bulk materials completely in displays and light‐emitting diodes. Exciton transport dominates over charge carrier transport for materials with high exciton binding energies and long ligands, such as halide perovskite nanocrystal films. Here, how beneficial superlattices – nearly perfect 3D assemblies of nanocrystals ‐ are to exciton transport is investigated. Surprisingly, the high degree of order is not as crucial as the individual nanocrystal size, which strongly influences the splitting of the excitonic manifold into bright and dark states. At very low temperatures, the energetic splitting is larger for the smallest nanocrystals, and dark levels with low oscillator strength effectively trap excitons inside individual nanocrystals, suppressing diffusion. The effect is reversed at elevated temperatures, and the larger nanocrystal size becomes detrimental to exciton transport due to enhanced exciton trapping and dissociation. The results reveal that the nanocrystal size must be strongly accounted for in design strategies of future optoelectronic applications. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Epigenetic signatures of attachment insecurity and childhood adversity provide evidence for role transition in the pathogenesis of perinatal depression

Author

Robakis, Thalia K., Zhang, Siming, Rasgon, Natalie L., Li, Tongbin, Wang, Tao, Roth, Marissa C., Humphreys, Kathryn L., Gotlib, Ian H., Ho, Marcus, Khechaduri, Arineh, Watson, Katherine, Roat-Shumway, Siena, Budhan, Vena V., Davis, Kasey N., Crowe, Susan D., Ellie Williams, Katherine, and Urban, Alexander E.

Published
2020
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29. Intersection of diverse neuronal genomes and neuropsychiatric disease : The Brain Somatic Mosaicism Network

Author

Brain Somatic Mosaicism Network, McConnell, Michael J., Moran, John V., Abyzov, Alexej, Akbarian, Schahram, Bae, Taejeong, Cortes-Ciriano, Isidro, Erwin, Jennifer A., Fasching, Liana, Flasch, Diane A., Freed, Donald, Ganz, Javier, Jaffe, Andrew E., Kwan, Kenneth Y., Kwon, Minseok, Lodato, Michael A., Mills, Ryan E., Paquola, Apua C. M., Rodin, Rachel E., Rosenbluh, Chaggai, Sestan, Nenad, Sherman, Maxwell A., Shin, Joo Heon, Song, Saera, Straub, Richard E., Thorpe, Jeremy, Weinberger, Daniel R., Urban, Alexander E., Zhou, Bo, Gage, Fred H., Lehner, Thomas, Senthil, Geetha, A. Walsh, Christopher, Chess, Andrew, Courchesne, Eric, Gleeson, Joseph G., Kidd, Jeffrey M., Park, Peter J., Pevsner, Jonathan, and Vaccarino, Flora M.

Published
2017

32. Evaluation of C4 Gene Copy Number in Pediatric Acute Neuropsychiatric Syndrome.

Author

Kalinowski, Agnieszka, Tian, Lu, Pattni, Reenal, Ollila, Hanna, Khan, Maroof, Manko, Cindy, Silverman, Melissa, Ma, Meiqian, Columbo, Laurie, Farhadian, Bahare, Swedo, Susan, Murphy, Tanya, Johnson, Mats, Fernell, Elisabeth, Gillberg, Christopher, Thienemann, Margo, Mellins, Elizabeth D, Levinson, Douglas F, Urban, Alexander E, and Frankovich, Jennifer

Abstract

Pediatric acute-onset neuropsychiatric syndrome (PANS) is an abrupt-onset neuropsychiatric disorder. PANS patients have an increased prevalence of comorbid autoimmune illness, most commonly arthritis. In addition, an estimated one-third of PANS patients present with low serum C4 protein, suggesting decreased production or increased consumption of C4 protein. To test the possibility that copy number (CN) variation contributes to risk of PANS illness, we compared mean total C4A and total C4B CN in ethnically matched subjects from PANS DNA samples and controls (192 cases and 182 controls). Longitudinal data from the Stanford PANS cohort (n = 121) were used to assess whether the time to juvenile idiopathic arthritis (JIA) or autoimmune disease (AI) onset was a function of total C4A or C4B CN. Lastly, we performed several hypothesis-generating analyses to explore the correlation between individual C4 gene variants, sex, specific genotypes, and age of PANS onset. Although the mean total C4A or C4B CN did not differ in PANS compared to controls, PANS patients with low C4B CN were at increased risk for subsequent JIA diagnosis (hazard ratio = 2.7, p value = 0.004). We also observed a possible increase in risk for AI in PANS patients and a possible correlation between lower C4B and PANS age of onset. An association between rheumatoid arthritis and low C4B CN has been reported previously. However, patients with PANS develop different types of JIA: enthesitis-related arthritis, spondyloarthritis, and psoriatic arthritis. This suggests that C4B plays a role that spans these arthritis types. [ABSTRACT FROM AUTHOR]

Published
2023
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34. Modeling ionic transport and disorder in crystalline electrodes using percolation theory

Author

Urban, Alexander

Subjects
Condensed Matter - Materials Science, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences
Abstract

Solid ionic conductors are essential components of batteries and fuel cells. In many cases, ionic conduction through crystalline materials with substitutional disorder can be modeled with atomic-scale lattice model percolation simulations. The ionic percolation theory reviewed in this chapter describes the percolation behavior of diffusion pathways, identifies the fraction of lattice sites that contributes to ionic conduction, and quantifies the tortuosity of diffusion networks. These quantities can be related to the bulk diffusivity and capacity of intercalation battery electrodes. We discuss applications to lithium-ion battery cathodes in the disordered rocksalt and related crystal structures, showing how the diffusion pathways and their tortuosity vary with the Li content short-range order. All examples are based on the free and open-source Dribble simulation software., book chapter, 20 pages, 6 figures

Published
2023

35. Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes

Author

Guo, Haoyue, Carbone, Matthew R., Cao, Chuntian, Qu, Jianzhou, Du, Yonghua, Bak, Seong-Min, Weiland, Conan, Wang, Feng, Yoo, Shinjae, Artrith, Nongnuch, Urban, Alexander, and Lu, Deyu

Subjects
Condensed Matter - Materials Science, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences
Abstract

X-ray absorption spectroscopy (XAS) is a premier technique for materials characterization, providing key information about the local chemical environment of the absorber atom. In this work, we develop a database of sulfur K-edge XAS spectra of crystalline and amorphous lithium thiophosphate materials based on the atomic structures reported in Chem. Mater., 34, 6702 (2022). The XAS database is based on simulations using the excited electron and core-hole pseudopotential approach implemented in the Vienna Ab initio Simulation Package. Our database contains 2681 S K-edge XAS spectra for 66 crystalline and glassy structure models, making it the largest collection of first-principles computational XAS spectra for glass/ceramic lithium thiophosphates to date. This database can be used to correlate S spectral features with distinct S species based on their local coordination and short-range ordering in sulfide-based solid electrolytes. The data is openly distributed via the Materials Cloud, allowing researchers to access it for free and use it for further analysis, such as spectral fingerprinting, matching with experiments, and developing machine learning models., 11 pages, 3 figures, 1 table

Published
2023

40. Machine-Learning-Optimized Perovskite Nanoplatelet Synthesis

Author

Lampe, Carola, Kouroudis, Ioannis, Harth, Milan, Martin, Stefan, Gagliardi, Alessio, and Urban, Alexander S.

Subjects
FOS: Computer and information sciences, Condensed Matter - Materials Science, Computer Science - Machine Learning, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, Applied Physics (physics.app-ph), Physics - Applied Physics, Machine Learning (cs.LG)
Abstract

With the demand for renewable energy and efficient devices rapidly increasing, a need arises to find and optimize novel (nano)materials. This can be an extremely tedious process, often relying significantly on trial and error. Machine learning has emerged recently as a powerful alternative; however, most approaches require a substantial amount of data points, i.e., syntheses. Here, we merge three machine-learning models with Bayesian Optimization and are able to dramatically improve the quality of CsPbBr3 nanoplatelets (NPLs) using only approximately 200 total syntheses. The algorithm can predict the resulting PL emission maxima of the NPL dispersions based on the precursor ratios, which lead to previously unobtainable 7 and 8 ML NPLs. Aided by heuristic knowledge, the algorithm should be easily applicable to other nanocrystal syntheses and significantly help to identify interesting compositions and rapidly improve their quality.

Published
2022

42. An approach to the optimal timber transport scheduling

Author

Shabaev Anton, Sokolov Anton, Urban Alexander, and Pyatin Dmitry

Subjects
Environmental sciences, GE1-350
Abstract

An approach to the optimal timber transport scheduling is described in the paper. A description of this problem is given, a multi-criteria mathematical model is created. It is noted that the problem belongs to the class of General vehicle routing problems (GVRP) associated with the job-shop scheduling. A hybrid algorithm for solving this problem based on the decomposition method using the simplex method and the genetic algorithm is developed. Testing of the proposed approach using real data from wood harvesting enterprises showed its effectiveness. The algorithm was implemented in “Opti-Wood” decision support system for wood harvesting planning and management, developed by Opti-Soft company (Russia).

Published
2020
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45. Artificial Intelligence-Aided Mapping of the Structure-Composition-Conductivity Relationships of Glass-Ceramic Lithium Thiophosphate Electrolytes

Author

Guo, Haoyue, Wang, Qian, Urban, Alexander, Artrith, Nongnuch, Sub Materials Chemistry and Catalysis, and Materials Chemistry and Catalysis

Subjects
General Chemical Engineering, Materials Chemistry, General Chemistry
Abstract

Lithium thiophosphates (LPSs) with the composition (Li2S)x(P2S5)1-x are among the most promising prospective electrolyte materials for solid-state batteries (SSBs), owing to their superionic conductivity at room temperature (>10-3 S cm-1), soft mechanical properties, and low grain boundary resistance. Several glass-ceramic (gc) LPSs with different compositions and good Li conductivity have been previously reported, but the relationship among composition, atomic structure, stability, and Li conductivity remains unclear due to the challenges in characterizing noncrystalline phases in experiments or simulations. Here, we mapped the LPS phase diagram by combining first-principles and artificial intelligence (AI) methods, integrating density functional theory, artificial neural network potentials, genetic-algorithm sampling, and ab initio molecular dynamics simulations. By means of an unsupervised structure-similarity analysis, the glassy/ceramic phases were correlated with the local structural motifs in the known LPS crystal structures, showing that the energetically most favorable Li environment varies with the composition. Based on the discovered trends in the LPS phase diagram, we propose a candidate solid-state electrolyte composition, (Li2S)x(P2S5)1-x (x ∼0.725), that exhibits high ionic conductivity (>10-2 S cm-1) in our simulations, thereby demonstrating a general design strategy for amorphous or glassy/ceramic solid electrolytes with enhanced conductivity and stability.

Published
2022

49. Understanding the Onset of Surface Degradation in LiNiO2Cathodes

Author

Li, Xinhao, Wang, Qian, Guo, Haoyue, Artrith, Nong, Urban, Alexander, Sub Materials Chemistry and Catalysis, and Materials Chemistry and Catalysis

Subjects
LiNiO, surface phase diagrams, Electrochemistry, Materials Chemistry, Li-ion batteries, Chemical Engineering (miscellaneous), Energy Engineering and Power Technology, Electrical and Electronic Engineering, density functional theory, degradation
Abstract

Nickel-based layered oxides offer an attractive platform for the development of energy-dense cobalt-free cathodes for lithium-ion batteries but suffer from degradation via oxygen gas release during electrochemical cycling. While such degradation has previously been characterized phenomenologically with experiments, an atomic-scale understanding of the reactions that take place at the cathode surface has been lacking. Here, we develop a first-principles methodology for the prediction of the surface reconstructions of intercalation electrode particles as a function of the temperature and state of charge. We report the surface phase diagrams of the LiNiO2 (001) and (104) surfaces and identify surface structures that are likely visited during the first charge and discharge. Our calculations indicate that both surfaces experience oxygen loss during the first charge, resulting in irreversible changes to the surface structures. At the end of charge, the surface Ni atoms migrate into tetrahedral sites, from which they further migrate into Li vacancies during discharge, leading to Li/Ni mixed discharged surface phases. Further, the impact of the temperature and voltage range during cycling on the charge/discharge mechanism is discussed. The present study thus provides insight into the initial stages of cathode surface degradation and lays the foundation for the computational design of cathode materials that are stable against oxygen release.

Published
2022

50. Annual Research Review: The Promise of Stem Cell Research for Neuropsychiatric Disorders

Author

Vaccarino, Flora M., Urban, Alexander Eckehart, and Stevens, Hanna E.

Abstract

The study of the developing brain has begun to shed light on the underpinnings of both early and adult onset neuropsychiatric disorders. Neuroimaging of the human brain across developmental time points and the use of model animal systems have combined to reveal brain systems and gene products that may play a role in autism spectrum disorders, attention deficit hyperactivity disorder, obsessive compulsive disorder and many other neurodevelopmental conditions. However, precisely how genes may function in human brain development and how they interact with each other leading to psychiatric disorders is unknown. Because of an increasing understanding of neural stem cells and how the nervous system subsequently develops from these cells, we have now the ability to study disorders of the nervous system in a new way--by rewinding and reviewing the development of human neural cells. Induced pluripotent stem cells (iPSCs), developed from mature somatic cells, have allowed the development of specific cells in patients to be observed in real time. Moreover, they have allowed some neuronal-specific abnormalities to be corrected with pharmacological intervention in tissue culture. These exciting advances based on the use of iPSCs hold great promise for understanding, diagnosing and, possibly, treating psychiatric disorders. Specifically, examination of iPSCs from typically developing individuals will reveal how basic cellular processes and genetic differences contribute to individually unique nervous systems. Moreover, by comparing iPSCs from typically developing individuals and patients, differences at stem cell stages, through neural differentiation, and into the development of functional neurons may be identified that will reveal opportunities for intervention. The application of such techniques to early onset neuropsychiatric disorders is still on the horizon but has become a reality of current research efforts as a consequence of the revelations of many years of basic developmental neurobiological science.

Published
2011
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