Author: "ZHENG Wei" / Publication Type: Electronic Resources - Searchworks@Jio Institute Digital Library Search Results

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1,692 results on '"ZHENG Wei"'

1. Design and development of DNA biosensors based on silver nanoclusters and hybridisation chain reaction

Author: Wong, Zheng Wei
Subjects: RS Pharmacy and materia medica
Abstract: Biosensors that couple hybridisation chain reaction amplification and fluorogenic silver nanoclusters (HCR-AgNCs) have the potential to enable simple and cost-effective detection of target analytes. These biosensors feature non-enzymatic amplification at mild conditions with a strong label-free fluorescence response. Whilst the proof-of-concept of these sensors have been promising, the design and developmental stages of HCR-AgNCs biosensors remain a challenge due to the lack of studies within the field itself. The primary aim of this thesis was to design and develop new HCR-AgNCs biosensors for specific detection of short nucleic acid sequences (i.e., DNA and microRNA (miR)). To achieve this, three novel HCR-AgNCs biosensors were developed by designing DNA probes with assistance of computational software, then validated via lab-based experiments such as feasibility tests, condition optimisation, as well as performance analysis in both buffer and complex samples. A ratiometric fluorescence HCR-AgNCs biosensor was first developed for miR detection, where emission of AgNCs changed from red to yellow in the absence and presence of miR-155. The ratiometric analysis has reduced the possibility of false measurement and increased the sensitivity of the assay, with limit of detection (LOD) measured at 1.18 fM. In the next study, a HCR biosensor was integrated with an externalised AgNCs probes via an 'end-to-end cluster transfer' mechanism, for DNA detection. This strategy simplified the designing process of DNA hairpins, ensured HCR predictability, and formed specific AgNCs species. In addition, the HCR-AgNCs biosensor exhibited high sensitivity towards the DNA target, with qualitative LOD at 1 pM and quantitative LOD at 3.35 fM. In the final study, magnetic-assistance was integrated into a ratiometric fluorescence HCR-AgNCs biosensor for the detection of miR-144-3p. The addition of magnetic beads (MBs) into the HCR-AgNCs biosensor facilitated a quick extraction and direct analysis of miR-144-3p, with LOD measured at 4.88 fM and satisfactory detection in raw human serum sample. The overall findings from these works conclude that by carefully designing the DNA probes used to construct HCR-AgNCs, one can develop a functional and stable HCRAgNCs biosensor without overcomplicating the detection process. Besides that, the concept of proximity-dependent AgNCs, introduced in each of the proposed biosensors, addressed some of the practical limitations posed by conventional HCR-AgNCs biosensors. Moreover, the implementation of different sensing mechanism and modifications (i.e., externalisation of AgNCs and MBs addition) in these studies highlight the versatility of HCR-AgNCs assays for different applications. Ultimately, the design and development efforts of HCR-AgNCs biosensors in this work can inspire further insights and research into this class of biosensors and facilitate extensive biosensing applications in the field of clinical diagnostics and beyond.
Published: 2023

2. Control strategies enabling seamless switching to islanded operation

Author: Zheng, Wei and Liu, Qiang
Subjects: 621.31, Power System Islanding, Islanding Switching, Power System Modelling, Transient Analysis, Load Shedding, Distributed Generator
Abstract: Significant penetration of distributed generation (DG) and the increasing automation level available for distribution networks have opened an option of splitting a network into subsystems and operating each as an "autonomous island". This is particularly important when a major contingency occurs. However, there are issues and challenges that must be addressed before islanded operation becomes viable, among which, ensuring seamless switching of a distribution subsystem from grid-connected to islanded mode is critically important. Unless the subsystem is a predesigned microgrid, it is highly possible that the subsystem load demand will exceed the generation capacity of island DGs. Therefore, an appropriate load shedding scheme must be implemented to ensure the islanded subsystem is power balanced. In this thesis, a switching control strategy is designed to deliver seamless islanding switching. This strategy comprises a multiple-DG coordination method and a single-step load shedding scheme. Mathematical studies and time-domain simulations that investigate the transients observed during the islanding switching process are both conducted, and together, they are used to address the transient stability issues of an islanded subsystem. This thesis focuses on a distribution subsystem consisting of a mix of synchronous and inverter-based DGs and a combination of static and dynamic loads. DG modelling and control is first introduced, and based on that, various types of method to achieve multiple-DG coordination, including an innovative multiple-master strategy, are investigated. The widely accepted master-slave strategy is used to coordinate DGs when the subsystem is islanded. The strategy demands a single dispatchable and controllable DG, such as a synchronous generator, to be the master, whilst requires the others, such as intermittent renewable-based DGs, to be the slaves. Dynamic load modelling is another critical part of this thesis. The transient stability of dynamic loads after major disturbances is investigated and then used to design the stability-oriented load shedding priority. The single-step load shedding scheme calculates the load shedding amount based on the power flow at the point of common coupling (PCC) and the spinning reserve available in the island. This scheme is activated by the tripping event of the PCC circuit breaker between the grid and the island, and then priorities the load to be shed according to the priority predetermined from the stability perspective. Mathematical analysis is first conducted on a simple subsystem to investigate the impact of DG settings on the islanding transients. A full-scale subsystem is also simulated in PSCAD/EMTDC and used to verify the effectiveness of the switching control strategy. In time-domain simulations, the subsystem is islanded following either a routine switching event or a permanent grid fault. Various factors that may affect the transient performance are analysed, such as the severity of the fault, the DG penetration level, the fault clearance time and the switching control delay. This thesis concludes that based on the proposed switching control strategy, the concept of seamless switching from grid-connected to islanded operation is technically viable.
Published: 2018

3. Quantum Simulation with Gauge Fixing: from Ising Lattice Gauge Theory to Dynamical Flux Model

Author: Wang, Junsen, Sun, Xiangxiang, Zheng, Wei, Wang, Junsen, Sun, Xiangxiang, and Zheng, Wei
Abstract: Quantum simulation of synthetic dynamic gauge field has attracted much attentions in recent years. There are two traditional ways to simulate gauge theories. One is to directly simulate the full Hamiltonian of gauge theories with local gauge symmetries. And the other is to engineer the projected Hamiltonian in one gauge subsector. In this work, we provide the third way towards the simulation of gauge theories based on \emph{gauge fixing}. To demonstrate this concept, we fix the gauge of an Ising lattice gauge field coupled with spinless fermions on a ladder geometry. After the gauge fixing, this gauge theory is reduced to a simpler model, in which fermions hop on a ladder with a fluctuating dynamical $\mathbb{Z}_{2}$ flux. Then we shows that this model can be realized via Floquet engineering in ultracold atomic gases. By analytical and numerical studies of this dynamical flux model, we deduce that there is confinement to deconfinement phase transition in the original unfixed gauge theory. This work paves the way to quantum simulate lattice gauge theory using the concept of gauge fixing, relevant both for condensed matter and high energy physics., Comment: 12 pages, 9 figures
Published: 2024

4. International Pooled Analysis of Leisure-Time Physical Activity and Premenopausal Breast Cancer in Women From 19 Cohorts

Author: Epi Kanker, JC onderzoeksprogramma Cancer, Cancer, Timmins, Iain R, Jones, Michael E, O'Brien, Katie M, Adami, Hans-Olov, Aune, Dagfinn, Baglietto, Laura, Bertrand, Kimberly A, Brantley, Kristen D, Chen, Yu, Clague DeHart, Jessica, Clendenen, Tess V, Dossus, Laure, Eliassen, A Heather, Fletcher, Olivia, Fournier, Agnès, Håkansson, Niclas, Hankinson, Susan E, Houlston, Richard S, Joshu, Corinne E, Kirsh, Victoria A, Kitahara, Cari M, Koh, Woon-Puay, Linet, Martha S, Park, Hannah Lui, Lynch, Brigid M, May, Anne M, Mellemkjær, Lene, Milne, Roger L, Palmer, Julie R, Ricceri, Fulvio, Rohan, Thomas E, Ruddy, Kathryn J, Sánchez, Maria-Jose, Shu, Xiao-Ou, Smith-Byrne, Karl, Steindorf, Karen, Sund, Malin, Vachon, Celine M, Vatten, Lars J, Visvanathan, Kala, Weiderpass, Elisabete, Willett, Walter C, Wolk, Alicja, Yuan, Jian-Min, Zheng, Wei, Nichols, Hazel B, Sandler, Dale P, Swerdlow, Anthony J, Schoemaker, Minouk J, Epi Kanker, JC onderzoeksprogramma Cancer, Cancer, Timmins, Iain R, Jones, Michael E, O'Brien, Katie M, Adami, Hans-Olov, Aune, Dagfinn, Baglietto, Laura, Bertrand, Kimberly A, Brantley, Kristen D, Chen, Yu, Clague DeHart, Jessica, Clendenen, Tess V, Dossus, Laure, Eliassen, A Heather, Fletcher, Olivia, Fournier, Agnès, Håkansson, Niclas, Hankinson, Susan E, Houlston, Richard S, Joshu, Corinne E, Kirsh, Victoria A, Kitahara, Cari M, Koh, Woon-Puay, Linet, Martha S, Park, Hannah Lui, Lynch, Brigid M, May, Anne M, Mellemkjær, Lene, Milne, Roger L, Palmer, Julie R, Ricceri, Fulvio, Rohan, Thomas E, Ruddy, Kathryn J, Sánchez, Maria-Jose, Shu, Xiao-Ou, Smith-Byrne, Karl, Steindorf, Karen, Sund, Malin, Vachon, Celine M, Vatten, Lars J, Visvanathan, Kala, Weiderpass, Elisabete, Willett, Walter C, Wolk, Alicja, Yuan, Jian-Min, Zheng, Wei, Nichols, Hazel B, Sandler, Dale P, Swerdlow, Anthony J, and Schoemaker, Minouk J
Published: 2024

5. Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

Author: Chen, Zhishan, Guo, Xingyi, Tao, Ran, Huyghe, Jeroen R., Law, Philip J., Fernandez-Rozadilla, Ceres, Ping, Jie, Jia, Guochong, Long, Jirong, Li, Chao, Shen, Quanhu, Xie, Yuhan, Timofeeva, Maria N., Thomas, Minta, Schmit, Stephanie L., Díez-Obrero, Virginia, Devall, Matthew, Moratalla-Navarro, Ferran, Fernandez-Tajes, Juan, Palles, Claire, Sherwood, Kitty, Briggs, Sarah E.W., Svinti, Victoria, Donnelly, Kevin, Farrington, Susan M., Blackmur, James, Vaughan-Shaw, Peter G., Shu, Xiao Ou, Lu, Yingchang, Broderick, Peter, Studd, James, Harrison, Tabitha A., Conti, David V., Schumacher, Fredrick R., Melas, Marilena, Rennert, Gad, Obón-Santacana, Mireia, Martín-Sánchez, Vicente, Oh, Jae Hwan, Kim, Jeongseon, Jee, Sun Ha, Jung, Keum Ji, Kweon, Sun Seog, Shin, Min Ho, Shin, Aesun, Ahn, Yoon Ok, Kim, Dong Hyun, Oze, Isao, Wen, Wanqing, Matsuo, Keitaro, Matsuda, Koichi, Tanikawa, Chizu, Ren, Zefang, Gao, Yu Tang, Jia, Wei Hua, Hopper, John L., Jenkins, Mark A., Win, Aung Ko, Pai, Rish K., Figueiredo, Jane C., Haile, Robert W., Gallinger, Steven, Woods, Michael O., Newcomb, Polly A., Duggan, David, Cheadle, Jeremy P., Kaplan, Richard, Kerr, Rachel, Kerr, David, Kirac, Iva, Böhm, Jan, Mecklin, Jukka Pekka, Jousilahti, Pekka, Knekt, Paul, Aaltonen, Lauri A., Rissanen, Harri, Pukkala, Eero, Eriksson, Johan G., Cajuso, Tatiana, Hänninen, Ulrika, Kondelin, Johanna, Palin, Kimmo, Tanskanen, Tomas, Renkonen-Sinisalo, Laura, Männistö, Satu, Albanes, Demetrius, Weinstein, Stephanie J., Ruiz-Narvaez, Edward, Palmer, Julie R., Buchanan, Daniel D., Platz, Elizabeth A., Visvanathan, Kala, Ulrich, Cornelia M., Siegel, Erin, Brezina, Stefanie, Gsur, Andrea, Campbell, Peter T., Chang-Claude, Jenny, Hoffmeister, Michael, Brenner, Hermann, Slattery, Martha L., Potter, John D., Tsilidis, Kostas K., Schulze, Matthias B., Gunter, Marc J., Murphy, Neil, Castells, Antoni, Castellví-Bel, Sergi, Moreira, Leticia, Arndt, Volker, Shcherbina, Anna, Bishop, Timothy, Giles, Graham G., Southey, Melissa C., Idos, Gregory E., McDonnell, Kevin J., Abu-Ful, Zomoroda, Greenson, Joel K., Shulman, Katerina, Lejbkowicz, Flavio, Offit, Kenneth, Su, Yu Ru, Steinfelder, Robert, Keku, Temitope O., van Guelpen, Bethany, Hudson, Thomas J., Hampel, Heather, Pearlman, Rachel, Berndt, Sonja I., Hayes, Richard B., Martinez, Marie Elena, Thomas, Sushma S., Pharoah, Paul D.P., Larsson, Susanna C., Yen, Yun, Lenz, Heinz Josef, White, Emily, Li, Li, Doheny, Kimberly F., Pugh, Elizabeth, Shelford, Tameka, Chan, Andrew T., Cruz-Correa, Marcia, Lindblom, Annika, Hunter, David J., Joshi, Amit D., Schafmayer, Clemens, Scacheri, Peter C., Kundaje, Anshul, Schoen, Robert E., Hampe, Jochen, Stadler, Zsofia K., Vodicka, Pavel, Vodickova, Ludmila, Vymetalkova, Veronika, Edlund, Christopher K., Gauderman, James, Shibata, David, Toland, Amanda, Markowitz, Sanford, Kim, Andre, Chanock, Stephen J., van Duijnhoven, Franzel, Feskens, Edith J.M., Sakoda, Lori C., Gago-Dominguez, Manuela, Wolk, Alicja, Pardini, Barbara, FitzGerald, Liesel M., Lee, Soo Chin, Ogino, Shuji, Bien, Stephanie A., Kooperberg, Charles, Li, Christopher I., Lin, Yi, Prentice, Ross, Qu, Conghui, Bézieau, Stéphane, Yamaji, Taiki, Sawada, Norie, Iwasaki, Motoki, Le Marchand, Loic, Wu, Anna H., Qu, Chenxu, McNeil, Caroline E., Coetzee, Gerhard, Hayward, Caroline, Deary, Ian J., Harris, Sarah E., Theodoratou, Evropi, Reid, Stuart, Walker, Marion, Ooi, Li Yin, Lau, Ken S., Zhao, Hongyu, Hsu, Li, Cai, Qiuyin, Dunlop, Malcolm G., Gruber, Stephen B., Houlston, Richard S., Moreno, Victor, Casey, Graham, Peters, Ulrike, Tomlinson, Ian, Zheng, Wei, Chen, Zhishan, Guo, Xingyi, Tao, Ran, Huyghe, Jeroen R., Law, Philip J., Fernandez-Rozadilla, Ceres, Ping, Jie, Jia, Guochong, Long, Jirong, Li, Chao, Shen, Quanhu, Xie, Yuhan, Timofeeva, Maria N., Thomas, Minta, Schmit, Stephanie L., Díez-Obrero, Virginia, Devall, Matthew, Moratalla-Navarro, Ferran, Fernandez-Tajes, Juan, Palles, Claire, Sherwood, Kitty, Briggs, Sarah E.W., Svinti, Victoria, Donnelly, Kevin, Farrington, Susan M., Blackmur, James, Vaughan-Shaw, Peter G., Shu, Xiao Ou, Lu, Yingchang, Broderick, Peter, Studd, James, Harrison, Tabitha A., Conti, David V., Schumacher, Fredrick R., Melas, Marilena, Rennert, Gad, Obón-Santacana, Mireia, Martín-Sánchez, Vicente, Oh, Jae Hwan, Kim, Jeongseon, Jee, Sun Ha, Jung, Keum Ji, Kweon, Sun Seog, Shin, Min Ho, Shin, Aesun, Ahn, Yoon Ok, Kim, Dong Hyun, Oze, Isao, Wen, Wanqing, Matsuo, Keitaro, Matsuda, Koichi, Tanikawa, Chizu, Ren, Zefang, Gao, Yu Tang, Jia, Wei Hua, Hopper, John L., Jenkins, Mark A., Win, Aung Ko, Pai, Rish K., Figueiredo, Jane C., Haile, Robert W., Gallinger, Steven, Woods, Michael O., Newcomb, Polly A., Duggan, David, Cheadle, Jeremy P., Kaplan, Richard, Kerr, Rachel, Kerr, David, Kirac, Iva, Böhm, Jan, Mecklin, Jukka Pekka, Jousilahti, Pekka, Knekt, Paul, Aaltonen, Lauri A., Rissanen, Harri, Pukkala, Eero, Eriksson, Johan G., Cajuso, Tatiana, Hänninen, Ulrika, Kondelin, Johanna, Palin, Kimmo, Tanskanen, Tomas, Renkonen-Sinisalo, Laura, Männistö, Satu, Albanes, Demetrius, Weinstein, Stephanie J., Ruiz-Narvaez, Edward, Palmer, Julie R., Buchanan, Daniel D., Platz, Elizabeth A., Visvanathan, Kala, Ulrich, Cornelia M., Siegel, Erin, Brezina, Stefanie, Gsur, Andrea, Campbell, Peter T., Chang-Claude, Jenny, Hoffmeister, Michael, Brenner, Hermann, Slattery, Martha L., Potter, John D., Tsilidis, Kostas K., Schulze, Matthias B., Gunter, Marc J., Murphy, Neil, Castells, Antoni, Castellví-Bel, Sergi, Moreira, Leticia, Arndt, Volker, Shcherbina, Anna, Bishop, Timothy, Giles, Graham G., Southey, Melissa C., Idos, Gregory E., McDonnell, Kevin J., Abu-Ful, Zomoroda, Greenson, Joel K., Shulman, Katerina, Lejbkowicz, Flavio, Offit, Kenneth, Su, Yu Ru, Steinfelder, Robert, Keku, Temitope O., van Guelpen, Bethany, Hudson, Thomas J., Hampel, Heather, Pearlman, Rachel, Berndt, Sonja I., Hayes, Richard B., Martinez, Marie Elena, Thomas, Sushma S., Pharoah, Paul D.P., Larsson, Susanna C., Yen, Yun, Lenz, Heinz Josef, White, Emily, Li, Li, Doheny, Kimberly F., Pugh, Elizabeth, Shelford, Tameka, Chan, Andrew T., Cruz-Correa, Marcia, Lindblom, Annika, Hunter, David J., Joshi, Amit D., Schafmayer, Clemens, Scacheri, Peter C., Kundaje, Anshul, Schoen, Robert E., Hampe, Jochen, Stadler, Zsofia K., Vodicka, Pavel, Vodickova, Ludmila, Vymetalkova, Veronika, Edlund, Christopher K., Gauderman, James, Shibata, David, Toland, Amanda, Markowitz, Sanford, Kim, Andre, Chanock, Stephen J., van Duijnhoven, Franzel, Feskens, Edith J.M., Sakoda, Lori C., Gago-Dominguez, Manuela, Wolk, Alicja, Pardini, Barbara, FitzGerald, Liesel M., Lee, Soo Chin, Ogino, Shuji, Bien, Stephanie A., Kooperberg, Charles, Li, Christopher I., Lin, Yi, Prentice, Ross, Qu, Conghui, Bézieau, Stéphane, Yamaji, Taiki, Sawada, Norie, Iwasaki, Motoki, Le Marchand, Loic, Wu, Anna H., Qu, Chenxu, McNeil, Caroline E., Coetzee, Gerhard, Hayward, Caroline, Deary, Ian J., Harris, Sarah E., Theodoratou, Evropi, Reid, Stuart, Walker, Marion, Ooi, Li Yin, Lau, Ken S., Zhao, Hongyu, Hsu, Li, Cai, Qiuyin, Dunlop, Malcolm G., Gruber, Stephen B., Houlston, Richard S., Moreno, Victor, Casey, Graham, Peters, Ulrike, Tomlinson, Ian, and Zheng, Wei
Abstract: Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.
Published: 2024

6. Simulation and parameter identification of linear shear wave equation using physics-informed neural networks: a feasibility study

Author: Zheng, Wei and Zheng, Wei
Published: 2024

7. Engineering and Revealing Dirac Strings in Spinor Condensates

Author: Xu, Gui-Sheng, Jain, Mudit, Zhou, Xiang-Fa, Guo, Guang-Can, Amin, Mustafa A., Pu, Han, Zhou, Zheng-Wei, Xu, Gui-Sheng, Jain, Mudit, Zhou, Xiang-Fa, Guo, Guang-Can, Amin, Mustafa A., Pu, Han, and Zhou, Zheng-Wei
Abstract: Artificial monopoles have been engineered in various systems, yet there has been no systematic study of the singular vector potentials associated with the monopole field. We show that the Dirac string, the line singularity of the vector potential, can be engineered, manipulated, and made manifest in a spinor atomic condensate. We elucidate the connection among spin, orbital degrees of freedom, and the artificial gauge, and show that there exists a mapping between the vortex filament and the Dirac string. We also devise a proposal where preparing initial spin states with relevant symmetries can result in different vortex patterns, revealing an underlying correspondence between the internal spin states and the spherical vortex structures. Such a mapping also leads to a new way of constructing spherical Landau levels, and monopole harmonics. Our observation provides insights into the behavior of quantum matter possessing internal symmetries in curved spaces., Comment: 5 pages + 5 figures + 5 appendices. In comparison with the previous version, we have (1) added supplementary material as appendices, and (2) made some minor revisions in the main text. Also, a simulation video for creating two artificial Dirac Strings with a mixed spin-1 state, is available at https://youtu.be/PCQGMqd-DfQ
Published: 2024

8. Fine-mapping analysis including over 254 000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

Author: Chen, Zhishan, Guo, Xingyi, Tao, Ran, Huyghe, Jeroen R., Law, Philip J., Fernandez-Rozadilla, Ceres, Ping, Jie, Jia, Guochong, Long, Jirong, Li, Chao, Shen, Quanhu, Xie, Yuhan, Timofeeva, Maria N., Thomas, Minta, Schmit, Stephanie L., Díez-Obrero, Virginia, Devall, Matthew, Moratalla-Navarro, Ferran, Fernandez-Tajes, Juan, Palles, Claire, Sherwood, Kitty, Briggs, Sarah E. W., Svinti, Victoria, Donnelly, Kevin, Farrington, Susan M., Blackmur, James, Vaughan-Shaw, Peter G., Shu, Xiao-Ou, Lu, Yingchang, Broderick, Peter, Studd, James, Harrison, Tabitha A., Conti, David V., Schumacher, Fredrick R., Melas, Marilena, Rennert, Gad, Obón-Santacana, Mireia, Martín-Sánchez, Vicente, Oh, Jae Hwan, Kim, Jeongseon, Jee, Sun Ha, Jung, Keum Ji, Kweon, Sun-Seog, Shin, Min-Ho, Shin, Aesun, Ahn, Yoon-Ok, Kim, Dong-Hyun, Oze, Isao, Wen, Wanqing, Matsuo, Keitaro, Matsuda, Koichi, Tanikawa, Chizu, Ren, Zefang, Gao, Yu-Tang, Jia, Wei-Hua, Hopper, John L., Jenkins, Mark A., Win, Aung Ko, Pai, Rish K., Figueiredo, Jane C., Haile, Robert W., Gallinger, Steven, Woods, Michael O., Newcomb, Polly A., Duggan, David, Cheadle, Jeremy P., Kaplan, Richard, Kerr, Rachel, Kerr, David, Kirac, Iva, Böhm, Jan, Mecklin, Jukka-Pekka, Jousilahti, Pekka, Knekt, Paul, Aaltonen, Lauri A., Rissanen, Harri, Pukkala, Eero, Eriksson, Johan G., Cajuso, Tatiana, Hänninen, Ulrika, Kondelin, Johanna, Palin, Kimmo, Tanskanen, Tomas, Renkonen-Sinisalo, Laura, Männistö, Satu, Albanes, Demetrius, Weinstein, Stephanie J., Ruiz-Narvaez, Edward, Palmer, Julie R., Buchanan, Daniel D., Platz, Elizabeth A., Visvanathan, Kala, Ulrich, Cornelia M., Siegel, Erin, Brezina, Stefanie, Gsur, Andrea, Campbell, Peter T., Chang-Claude, Jenny, Hoffmeister, Michael, Brenner, Hermann, Slattery, Martha L., Potter, John D., Tsilidis, Kostas K., Schulze, Matthias B., Gunter, Marc J., Murphy, Neil, Castells, Antoni, Castellví-Bel, Sergi, Moreira, Leticia, Arndt, Volker, Shcherbina, Anna, Bishop, D. Timothy, Giles, Graham G., Southey, Melissa C., Idos, Gregory E., McDonnell, Kevin J., Abu-Ful, Zomoroda, Greenson, Joel K., Shulman, Katerina, Lejbkowicz, Flavio, Offit, Kenneth, Su, Yu-Ru, Steinfelder, Robert, Keku, Temitope O., van Guelpen, Bethany, Hudson, Thomas J., Hampel, Heather, Pearlman, Rachel, Berndt, Sonja I., Hayes, Richard B., Martinez, Marie Elena, Thomas, Sushma S., Pharoah, Paul D. P., Larsson, Susanna C., Yen, Yun, Lenz, Heinz-Josef, White, Emily, Li, Li, Doheny, Kimberly F., Pugh, Elizabeth, Shelford, Tameka, Chan, Andrew T., Cruz-Correa, Marcia, Lindblom, Annika, Hunter, David J., Joshi, Amit D., Schafmayer, Clemens, Scacheri, Peter C., Kundaje, Anshul, Schoen, Robert E., Hampe, Jochen, Stadler, Zsofia K., Vodicka, Pavel, Vodickova, Ludmila, Vymetalkova, Veronika, Edlund, Christopher K., Gauderman, W. James, Shibata, David, Toland, Amanda, Markowitz, Sanford, Kim, Andre, Chanock, Stephen J., van Duijnhoven, Franzel, Feskens, Edith J. M., Sakoda, Lori C., Gago-Dominguez, Manuela, Wolk, Alicja, Pardini, Barbara, FitzGerald, Liesel M., Lee, Soo Chin, Ogino, Shuji, Bien, Stephanie A., Kooperberg, Charles, Li, Christopher I., Lin, Yi, Prentice, Ross, Qu, Conghui, Bézieau, Stéphane, Yamaji, Taiki, Sawada, Norie, Iwasaki, Motoki, Le Marchand, Loic, Wu, Anna H., Qu, Chenxu, McNeil, Caroline E., Coetzee, Gerhard, Hayward, Caroline, Deary, Ian J., Harris, Sarah E., Theodoratou, Evropi, Reid, Stuart, Walker, Marion, Ooi, Li Yin, Lau, Ken S., Zhao, Hongyu, Hsu, Li, Cai, Qiuyin, Dunlop, Malcolm G., Gruber, Stephen B., Houlston, Richard S., Moreno, Victor, Casey, Graham, Peters, Ulrike, Tomlinson, Ian, Zheng, Wei, Chen, Zhishan, Guo, Xingyi, Tao, Ran, Huyghe, Jeroen R., Law, Philip J., Fernandez-Rozadilla, Ceres, Ping, Jie, Jia, Guochong, Long, Jirong, Li, Chao, Shen, Quanhu, Xie, Yuhan, Timofeeva, Maria N., Thomas, Minta, Schmit, Stephanie L., Díez-Obrero, Virginia, Devall, Matthew, Moratalla-Navarro, Ferran, Fernandez-Tajes, Juan, Palles, Claire, Sherwood, Kitty, Briggs, Sarah E. W., Svinti, Victoria, Donnelly, Kevin, Farrington, Susan M., Blackmur, James, Vaughan-Shaw, Peter G., Shu, Xiao-Ou, Lu, Yingchang, Broderick, Peter, Studd, James, Harrison, Tabitha A., Conti, David V., Schumacher, Fredrick R., Melas, Marilena, Rennert, Gad, Obón-Santacana, Mireia, Martín-Sánchez, Vicente, Oh, Jae Hwan, Kim, Jeongseon, Jee, Sun Ha, Jung, Keum Ji, Kweon, Sun-Seog, Shin, Min-Ho, Shin, Aesun, Ahn, Yoon-Ok, Kim, Dong-Hyun, Oze, Isao, Wen, Wanqing, Matsuo, Keitaro, Matsuda, Koichi, Tanikawa, Chizu, Ren, Zefang, Gao, Yu-Tang, Jia, Wei-Hua, Hopper, John L., Jenkins, Mark A., Win, Aung Ko, Pai, Rish K., Figueiredo, Jane C., Haile, Robert W., Gallinger, Steven, Woods, Michael O., Newcomb, Polly A., Duggan, David, Cheadle, Jeremy P., Kaplan, Richard, Kerr, Rachel, Kerr, David, Kirac, Iva, Böhm, Jan, Mecklin, Jukka-Pekka, Jousilahti, Pekka, Knekt, Paul, Aaltonen, Lauri A., Rissanen, Harri, Pukkala, Eero, Eriksson, Johan G., Cajuso, Tatiana, Hänninen, Ulrika, Kondelin, Johanna, Palin, Kimmo, Tanskanen, Tomas, Renkonen-Sinisalo, Laura, Männistö, Satu, Albanes, Demetrius, Weinstein, Stephanie J., Ruiz-Narvaez, Edward, Palmer, Julie R., Buchanan, Daniel D., Platz, Elizabeth A., Visvanathan, Kala, Ulrich, Cornelia M., Siegel, Erin, Brezina, Stefanie, Gsur, Andrea, Campbell, Peter T., Chang-Claude, Jenny, Hoffmeister, Michael, Brenner, Hermann, Slattery, Martha L., Potter, John D., Tsilidis, Kostas K., Schulze, Matthias B., Gunter, Marc J., Murphy, Neil, Castells, Antoni, Castellví-Bel, Sergi, Moreira, Leticia, Arndt, Volker, Shcherbina, Anna, Bishop, D. Timothy, Giles, Graham G., Southey, Melissa C., Idos, Gregory E., McDonnell, Kevin J., Abu-Ful, Zomoroda, Greenson, Joel K., Shulman, Katerina, Lejbkowicz, Flavio, Offit, Kenneth, Su, Yu-Ru, Steinfelder, Robert, Keku, Temitope O., van Guelpen, Bethany, Hudson, Thomas J., Hampel, Heather, Pearlman, Rachel, Berndt, Sonja I., Hayes, Richard B., Martinez, Marie Elena, Thomas, Sushma S., Pharoah, Paul D. P., Larsson, Susanna C., Yen, Yun, Lenz, Heinz-Josef, White, Emily, Li, Li, Doheny, Kimberly F., Pugh, Elizabeth, Shelford, Tameka, Chan, Andrew T., Cruz-Correa, Marcia, Lindblom, Annika, Hunter, David J., Joshi, Amit D., Schafmayer, Clemens, Scacheri, Peter C., Kundaje, Anshul, Schoen, Robert E., Hampe, Jochen, Stadler, Zsofia K., Vodicka, Pavel, Vodickova, Ludmila, Vymetalkova, Veronika, Edlund, Christopher K., Gauderman, W. James, Shibata, David, Toland, Amanda, Markowitz, Sanford, Kim, Andre, Chanock, Stephen J., van Duijnhoven, Franzel, Feskens, Edith J. M., Sakoda, Lori C., Gago-Dominguez, Manuela, Wolk, Alicja, Pardini, Barbara, FitzGerald, Liesel M., Lee, Soo Chin, Ogino, Shuji, Bien, Stephanie A., Kooperberg, Charles, Li, Christopher I., Lin, Yi, Prentice, Ross, Qu, Conghui, Bézieau, Stéphane, Yamaji, Taiki, Sawada, Norie, Iwasaki, Motoki, Le Marchand, Loic, Wu, Anna H., Qu, Chenxu, McNeil, Caroline E., Coetzee, Gerhard, Hayward, Caroline, Deary, Ian J., Harris, Sarah E., Theodoratou, Evropi, Reid, Stuart, Walker, Marion, Ooi, Li Yin, Lau, Ken S., Zhao, Hongyu, Hsu, Li, Cai, Qiuyin, Dunlop, Malcolm G., Gruber, Stephen B., Houlston, Richard S., Moreno, Victor, Casey, Graham, Peters, Ulrike, Tomlinson, Ian, and Zheng, Wei
Abstract: Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.
Published: 2024
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9. On the surface helium abundance of B-type hot subdwarf stars from the WD+MS channel of Type Ia supernovae

Author: Ji, Rui-Jie, Meng, Xiang-Cun, Liu, Zheng-Wei, Ji, Rui-Jie, Meng, Xiang-Cun, and Liu, Zheng-Wei
Abstract: The origin of intermediate helium (He)-rich hot subdwarfs are still unclear. Previous studies have suggested that some surviving Type Ia supernovae (SNe Ia) companions from the white dwarf~+~main-sequence (WD+MS) channel may contribute to the intermediate He-rich hot subdwarfs. However, previous studies ignored the impact of atomic diffusion on the post-explosion evolution of surviving companion stars of SNe Ia, leading to that they could not explain the observed surface He abundance of intermediate He-rich hot subdwarfs. In this work, by taking the atomic diffusion and stellar wind into account, we trace the surviving companions of SNe Ia from the WD+MS channel using the one-dimensional stellar evolution code \textsc{MESA} until they evolve into hot subdwarfs. We find that the surface He-abundances of our surviving companion models during their core He-burning phases are in a range of $-1 \lesssim {\rm log}(N_{\rm He}/N_{\rm H}) \lesssim 0$, which are consistent with those observed in intermediate He-rich hot subdwarfs. This seems to further support that surviving companions of SNe Ia in the WD+MS channel are possible to form some intermediate He-rich hot subdwarfs., Comment: 10 pages, 5 figures
Published: 2024

10. Polarization and Multiwavelength Observations of Mrk 501 Reveal Polarization Variability across Different Energies and Fluxes

Author: Hu, Xin-Ke, Yu, Yu-Wei, Zhang, Jin, Wang, Xiang-Gao, Patra, Kishore C., Brink, Thomas G., Zheng, Wei-Kang, Wang, Qi, Kong, De-Feng, Chen, Liang-Jun, Zhou, Ji-Wang, Cao, Jia-Xin, Lu, Ming-Xuan, Zhou, Zi-Min, Wei, Yi-Ning, Huang, Xin-Bo, Li, Xing-Lin, Lou, Hao, Mao, Ji-Rong, Liang, En-Wei, Filippenko, Alexei V., Hu, Xin-Ke, Yu, Yu-Wei, Zhang, Jin, Wang, Xiang-Gao, Patra, Kishore C., Brink, Thomas G., Zheng, Wei-Kang, Wang, Qi, Kong, De-Feng, Chen, Liang-Jun, Zhou, Ji-Wang, Cao, Jia-Xin, Lu, Ming-Xuan, Zhou, Zi-Min, Wei, Yi-Ning, Huang, Xin-Bo, Li, Xing-Lin, Lou, Hao, Mao, Ji-Rong, Liang, En-Wei, and Filippenko, Alexei V.
Abstract: Mrk 501 is a prototypical high-synchrotron-peaked blazar (HBL) and serves as one of the primary targets for the Imaging X-ray Polarimetry Explorer (IXPE). In this study, we report X-ray polarization measurements of Mrk 501 based on six IXPE observations. The $>99\%$ confidence detection of X-ray polarization is obtained in four out of six observations in the entire energy band (2--8 keV) of IXPE, with a maximum polarization degree ($\Pi_{\rm X}$) of $15.8\%\pm2.8\%$ and a polarization angle ($\psi_{\rm X}$) of $98.0^{\circ}\pm5.1^{\circ}$ at a confidence level of $5.2\sigma$. During the other two observations, the source only exhibits the $>99\%$ confidence detection of X-ray polarization within an energy bin of 1 keV. Interestingly, both the second and sixth IXPE observations present energy-dependent variability in X-ray polarization, which is also observed in our optical spectropolarimetry. The chromatic behavior of $\Pi$ and the consistent values of $\psi$ across different frequencies, along with the agreement between $\psi$ and jet position angle, strongly support the interpretation of the energy-stratified model with shock-accelerated particles in the jet of Mrk 501. Additionally, the possibility of the presence of a global helical magnetic field in the jet of Mrk 501 is discussed., Comment: 19 pages, 8 figures, 5 tables, submitted
Published: 2024

11. Cold Air Plasma Inhibiting Tumor-Like Biological Behavior of Rheumatoid Arthritis Fibroblast-Like Synovial Cells via G2/M Cell Cycle Arrest

Author: Ni,Le-Ying, Ding,Cheng-Biao, Deng,Ji-Min, Wu,Zheng-Wei, Zhou,Yun, Ni,Le-Ying, Ding,Cheng-Biao, Deng,Ji-Min, Wu,Zheng-Wei, and Zhou,Yun
Abstract: Le-Ying Ni,1– 3,* Cheng-Biao Ding,1,2,4,* Ji-Min Deng,5 Zheng-Wei Wu,4,6,7 Yun Zhou1,2 1Department of Rehabilitation Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, People’s Republic of China; 2Research Center for Translational Medicine, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230601, People’s Republic of China; 3Department of Rehabilitation Medicine, Maanshan People’s Hospital, Maanshan, Anhui, People’s Republic of China; 4School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, People’s Republic of China; 5Anhui institute for Food and Drug Control, Hefei, People’s Republic of China; 6CAS Key Laboratory of Geospace Environment, University of Science and Technology of China, Hefei, People’s Republic of China; 7Institute of Advanced Technology, University of Science and Technology of China, Hefei, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zheng-Wei Wu, University of Science and Technology of China, Hefei, 230026, People’s Republic of China, Tel/Fax +86-551-63606045, Email wuzw@ustc.edu.cn Yun Zhou, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, 230601, People’s Republic of China, Tel +86-0551-65997010, Email zhouyunanhui@sina.comBackground: Rheumatoid arthritis fibroblast-like synovial cells (RA-FLS) have become the core effector cells for the progression of rheumatoid arthritis due to their “tumor-like cell” characteristics, such as being able to break free from growth restrictions caused by contact inhibition, promoting angiogenesis, invading surrounding tissues, and leading to uncontrolled synovial growth. In recent years, cold air plasma (CAP) has been widely recognized for its clear anticancer effect. Inspired by this, this study investigated the inhibito
Published: 2024

12. The Relationship Between Overparenting and Social Avoidance Among Emerging Adults: Mediating Role of Peer Attachment and Gender Differences

Author: Chen,Yifu, Xia,Yu, Ren,Menghao, Zheng,Wei, Wang,Xiao, Gao,Feng, Chen,Yifu, Xia,Yu, Ren,Menghao, Zheng,Wei, Wang,Xiao, and Gao,Feng
Abstract: Yifu Chen,1â 3 Yu Xia,1,3,4 Menghao Ren,1,3,4 Wei Zheng,2 Xiao Wang,2 Feng Gao2 1Center for Mind and Brain Sciences, Hunan Normal University, Changsha, 410081, Peopleâs Republic of China; 2Hunan Railway Professional Technology College, Zhuzhou, 412001, Peopleâs Republic of China; 3China Research Center for Mental Health Education of Hunan Province, Hunan Normal University, Changsha, 410081, Peopleâs Republic of China; 4Cognition and Human Behavior Key Laboratory of Hunan Province, Hunan Normal University, Changsha, 410081, Peopleâs Republic of ChinaCorrespondence: Feng Gao, Hunan Railway Professional Technology College, Zhuzhou, 412001, Peopleâs Republic of China, Email 542322378@qq.comPurpose: We aim to explore the relationship between overparenting and social avoidance among emerging adults, and the mediating effects of peer attachment and gender differences.Participants and Methods: A total of 1161 Chinese college students completed the questionnaire. The structural equation model was established to validate the main effect model and the mediation model.Results: The results found that both paternal and maternal overparenting positively predicted social avoidance among emerging adults. Both attachment avoidance and attachment anxiety played a significant mediating role in the relationship between paternal overparenting and social avoidance. Attachment anxiety played a significant mediating role in the relationship between maternal overparenting and social avoidance, while, the mediating effect of attachment avoidance was not significant. In addition, gender differences were found in the mediating effects of peer attachment. The mediating effect of attachment anxiety in malesâ families had an opposite-gender matching effect, while in femalesâ families, the mediating effect of attachment avoidance had an opposite-gender matching effect.Conclusion: This study contributes to the understanding of the effects of overparenting on emerging adults, enrichin
Published: 2024

13. Efficient and Effective Weakly-Supervised Action Segmentation via Action-Transition-Aware Boundary Alignment

Author: Xu, Angchi, Zheng, Wei-Shi, Xu, Angchi, and Zheng, Wei-Shi
Abstract: Weakly-supervised action segmentation is a task of learning to partition a long video into several action segments, where training videos are only accompanied by transcripts (ordered list of actions). Most of existing methods need to infer pseudo segmentation for training by serial alignment between all frames and the transcript, which is time-consuming and hard to be parallelized while training. In this work, we aim to escape from this inefficient alignment with massive but redundant frames, and instead to directly localize a few action transitions for pseudo segmentation generation, where a transition refers to the change from an action segment to its next adjacent one in the transcript. As the true transitions are submerged in noisy boundaries due to intra-segment visual variation, we propose a novel Action-Transition-Aware Boundary Alignment (ATBA) framework to efficiently and effectively filter out noisy boundaries and detect transitions. In addition, to boost the semantic learning in the case that noise is inevitably present in the pseudo segmentation, we also introduce video-level losses to utilize the trusted video-level supervision. Extensive experiments show the effectiveness of our approach on both performance and training speed., Comment: Accepted to CVPR 2024
Published: 2024

14. Ranking Distillation for Open-Ended Video Question Answering with Insufficient Labels

Author: Liang, Tianming, Tan, Chaolei, Xia, Beihao, Zheng, Wei-Shi, Hu, Jian-Fang, Liang, Tianming, Tan, Chaolei, Xia, Beihao, Zheng, Wei-Shi, and Hu, Jian-Fang
Abstract: This paper focuses on open-ended video question answering, which aims to find the correct answers from a large answer set in response to a video-related question. This is essentially a multi-label classification task, since a question may have multiple answers. However, due to annotation costs, the labels in existing benchmarks are always extremely insufficient, typically one answer per question. As a result, existing works tend to directly treat all the unlabeled answers as negative labels, leading to limited ability for generalization. In this work, we introduce a simple yet effective ranking distillation framework (RADI) to mitigate this problem without additional manual annotation. RADI employs a teacher model trained with incomplete labels to generate rankings for potential answers, which contain rich knowledge about label priority as well as label-associated visual cues, thereby enriching the insufficient labeling information. To avoid overconfidence in the imperfect teacher model, we further present two robust and parameter-free ranking distillation approaches: a pairwise approach which introduces adaptive soft margins to dynamically refine the optimization constraints on various pairwise rankings, and a listwise approach which adopts sampling-based partial listwise learning to resist the bias in teacher ranking. Extensive experiments on five popular benchmarks consistently show that both our pairwise and listwise RADIs outperform state-of-the-art methods. Further analysis demonstrates the effectiveness of our methods on the insufficient labeling problem., Comment: Accepted to CVPR 2024
Published: 2024

15. A Control-Recoverable Added-Noise-based Privacy Scheme for LQ Control in Networked Control Systems

Author: Tang, Xuening, Cao, Xianghui, Zheng, Wei Xing, Tang, Xuening, Cao, Xianghui, and Zheng, Wei Xing
Abstract: As networked control systems continue to evolve, ensuring the privacy of sensitive data becomes an increasingly pressing concern, especially in situations where the controller is physically separated from the plant. In this paper, we propose a secure control scheme for computing linear quadratic control in a networked control system utilizing two networked controllers, a privacy encoder and a control restorer. Specifically, the encoder generates two state signals blurred with random noise and sends them to the controllers, while the restorer reconstructs the correct control signal. The proposed design effectively preserves the privacy of the control system's state without sacrificing the control performance. We theoretically quantify the privacy-preserving performance in terms of the state estimation error of the controllers and the disclosure probability. Additionally, the proposed privacy-preserving scheme is also proven to satisfy differential privacy. Moreover, we extend the proposed privacy-preserving scheme and evaluation method to cases where collusion between two controllers occurs. Finally, we verify the validity of our proposed scheme through simulations.
Published: 2024

16. Siamese Learning with Joint Alignment and Regression for Weakly-Supervised Video Paragraph Grounding

Author: Tan, Chaolei, Lai, Jianhuang, Zheng, Wei-Shi, Hu, Jian-Fang, Tan, Chaolei, Lai, Jianhuang, Zheng, Wei-Shi, and Hu, Jian-Fang
Abstract: Video Paragraph Grounding (VPG) is an emerging task in video-language understanding, which aims at localizing multiple sentences with semantic relations and temporal order from an untrimmed video. However, existing VPG approaches are heavily reliant on a considerable number of temporal labels that are laborious and time-consuming to acquire. In this work, we introduce and explore Weakly-Supervised Video Paragraph Grounding (WSVPG) to eliminate the need of temporal annotations. Different from previous weakly-supervised grounding frameworks based on multiple instance learning or reconstruction learning for two-stage candidate ranking, we propose a novel siamese learning framework that jointly learns the cross-modal feature alignment and temporal coordinate regression without timestamp labels to achieve concise one-stage localization for WSVPG. Specifically, we devise a Siamese Grounding TRansformer (SiamGTR) consisting of two weight-sharing branches for learning complementary supervision. An Augmentation Branch is utilized for directly regressing the temporal boundaries of a complete paragraph within a pseudo video, and an Inference Branch is designed to capture the order-guided feature correspondence for localizing multiple sentences in a normal video. We demonstrate by extensive experiments that our paradigm has superior practicability and flexibility to achieve efficient weakly-supervised or semi-supervised learning, outperforming state-of-the-art methods trained with the same or stronger supervision., Comment: Accepted to CVPR 2024. v2: fix a typo in figure 1
Published: 2024

17. A Versatile Framework for Multi-scene Person Re-identification

Author: Zheng, Wei-Shi, Yan, Junkai, Peng, Yi-Xing, Zheng, Wei-Shi, Yan, Junkai, and Peng, Yi-Xing
Abstract: Person Re-identification (ReID) has been extensively developed for a decade in order to learn the association of images of the same person across non-overlapping camera views. To overcome significant variations between images across camera views, mountains of variants of ReID models were developed for solving a number of challenges, such as resolution change, clothing change, occlusion, modality change, and so on. Despite the impressive performance of many ReID variants, these variants typically function distinctly and cannot be applied to other challenges. To our best knowledge, there is no versatile ReID model that can handle various ReID challenges at the same time. This work contributes to the first attempt at learning a versatile ReID model to solve such a problem. Our main idea is to form a two-stage prompt-based twin modeling framework called VersReID. Our VersReID firstly leverages the scene label to train a ReID Bank that contains abundant knowledge for handling various scenes, where several groups of scene-specific prompts are used to encode different scene-specific knowledge. In the second stage, we distill a V-Branch model with versatile prompts from the ReID Bank for adaptively solving the ReID of different scenes, eliminating the demand for scene labels during the inference stage. To facilitate training VersReID, we further introduce the multi-scene properties into self-supervised learning of ReID via a multi-scene prioris data augmentation (MPDA) strategy. Through extensive experiments, we demonstrate the success of learning an effective and versatile ReID model for handling ReID tasks under multi-scene conditions without manual assignment of scene labels in the inference stage, including general, low-resolution, clothing change, occlusion, and cross-modality scenes. Codes and models are available at https://github.com/iSEE-Laboratory/VersReID., Comment: To appear in TPAMI
Published: 2024

18. Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Model

Author: Zheng, Dian, Wu, Xiao-Ming, Yang, Shuzhou, Zhang, Jian, Hu, Jian-Fang, Zheng, Wei-Shi, Zheng, Dian, Wu, Xiao-Ming, Yang, Shuzhou, Zhang, Jian, Hu, Jian-Fang, and Zheng, Wei-Shi
Abstract: Universal image restoration is a practical and potential computer vision task for real-world applications. The main challenge of this task is handling the different degradation distributions at once. Existing methods mainly utilize task-specific conditions (e.g., prompt) to guide the model to learn different distributions separately, named multi-partite mapping. However, it is not suitable for universal model learning as it ignores the shared information between different tasks. In this work, we propose an advanced selective hourglass mapping strategy based on diffusion model, termed DiffUIR. Two novel considerations make our DiffUIR non-trivial. Firstly, we equip the model with strong condition guidance to obtain accurate generation direction of diffusion model (selective). More importantly, DiffUIR integrates a flexible shared distribution term (SDT) into the diffusion algorithm elegantly and naturally, which gradually maps different distributions into a shared one. In the reverse process, combined with SDT and strong condition guidance, DiffUIR iteratively guides the shared distribution to the task-specific distribution with high image quality (hourglass). Without bells and whistles, by only modifying the mapping strategy, we achieve state-of-the-art performance on five image restoration tasks, 22 benchmarks in the universal setting and zero-shot generalization setting. Surprisingly, by only using a lightweight model (only 0.89M), we could achieve outstanding performance. The source code and pre-trained models are available at https://github.com/iSEE-Laboratory/DiffUIR, Comment: Accepted to CVPR2024
Published: 2024

19. NECA: Neural Customizable Human Avatar

Author: Xiao, Junjin, Zhang, Qing, Xu, Zhan, Zheng, Wei-Shi, Xiao, Junjin, Zhang, Qing, Xu, Zhan, and Zheng, Wei-Shi
Abstract: Human avatar has become a novel type of 3D asset with various applications. Ideally, a human avatar should be fully customizable to accommodate different settings and environments. In this work, we introduce NECA, an approach capable of learning versatile human representation from monocular or sparse-view videos, enabling granular customization across aspects such as pose, shadow, shape, lighting and texture. The core of our approach is to represent humans in complementary dual spaces and predict disentangled neural fields of geometry, albedo, shadow, as well as an external lighting, from which we are able to derive realistic rendering with high-frequency details via volumetric rendering. Extensive experiments demonstrate the advantage of our method over the state-of-the-art methods in photorealistic rendering, as well as various editing tasks such as novel pose synthesis and relighting. The code is available at https://github.com/iSEE-Laboratory/NECA., Comment: Accepted to CVPR 2024
Published: 2024

20. Rethinking CLIP-based Video Learners in Cross-Domain Open-Vocabulary Action Recognition

Author: Lin, Kun-Yu, Ding, Henghui, Zhou, Jiaming, Tang, Yu-Ming, Peng, Yi-Xing, Zhao, Zhilin, Loy, Chen Change, Zheng, Wei-Shi, Lin, Kun-Yu, Ding, Henghui, Zhou, Jiaming, Tang, Yu-Ming, Peng, Yi-Xing, Zhao, Zhilin, Loy, Chen Change, and Zheng, Wei-Shi
Abstract: Building upon the impressive success of CLIP (Contrastive Language-Image Pretraining), recent pioneer works have proposed to adapt the powerful CLIP to video data, leading to efficient and effective video learners for open-vocabulary action recognition. Inspired by that humans perform actions in diverse environments, our work delves into an intriguing question: Can CLIP-based video learners effectively generalize to video domains they have not encountered during training? To answer this, we establish a CROSS-domain Open-Vocabulary Action recognition benchmark named XOV-Action, and conduct a comprehensive evaluation of five state-of-the-art CLIP-based video learners under various types of domain gaps. The evaluation demonstrates that previous methods exhibit limited action recognition performance in unseen video domains, revealing potential challenges of the cross-domain open-vocabulary action recognition task. In this paper, we focus on one critical challenge of the task, namely scene bias, and accordingly contribute a novel scene-aware video-text alignment method. Our key idea is to distinguish video representations apart from scene-encoded text representations, aiming to learn scene-agnostic video representations for recognizing actions across domains. Extensive experiments demonstrate the effectiveness of our method. The benchmark and code will be available at https://github.com/KunyuLin/XOV-Action/.
Published: 2024

21. Simpson's Paradox and the Accuracy-Fluency Tradeoff in Translation

Author: Lim, Zheng Wei, Vylomova, Ekaterina, Cohn, Trevor, Kemp, Charles, Lim, Zheng Wei, Vylomova, Ekaterina, Cohn, Trevor, and Kemp, Charles
Abstract: A good translation should be faithful to the source and should respect the norms of the target language. We address a theoretical puzzle about the relationship between these objectives. On one hand, intuition and some prior work suggest that accuracy and fluency should trade off against each other, and that capturing every detail of the source can only be achieved at the cost of fluency. On the other hand, quality assessment researchers often suggest that accuracy and fluency are highly correlated and difficult for human raters to distinguish (Callison-Burch et al. 2007). We show that the tension between these views is an instance of Simpson's paradox, and that accuracy and fluency are positively correlated at the level of the corpus but trade off at the level of individual source segments. We further suggest that the relationship between accuracy and fluency is best evaluated at the segment (or sentence) level, and that the trade off between these dimensions has implications both for assessing translation quality and developing improved MT systems.
Published: 2024

22. Multimodal Action Quality Assessment

Author: Zeng, Ling-An, Zheng, Wei-Shi, Zeng, Ling-An, and Zheng, Wei-Shi
Abstract: Action quality assessment (AQA) is to assess how well an action is performed. Previous works perform modelling by only the use of visual information, ignoring audio information. We argue that although AQA is highly dependent on visual information, the audio is useful complementary information for improving the score regression accuracy, especially for sports with background music, such as figure skating and rhythmic gymnastics. To leverage multimodal information for AQA, i.e., RGB, optical flow and audio information, we propose a Progressive Adaptive Multimodal Fusion Network (PAMFN) that separately models modality-specific information and mixed-modality information. Our model consists of with three modality-specific branches that independently explore modality-specific information and a mixed-modality branch that progressively aggregates the modality-specific information from the modality-specific branches. To build the bridge between modality-specific branches and the mixed-modality branch, three novel modules are proposed. First, a Modality-specific Feature Decoder module is designed to selectively transfer modality-specific information to the mixed-modality branch. Second, when exploring the interaction between modality-specific information, we argue that using an invariant multimodal fusion policy may lead to suboptimal results, so as to take the potential diversity in different parts of an action into consideration. Therefore, an Adaptive Fusion Module is proposed to learn adaptive multimodal fusion policies in different parts of an action. This module consists of several FusionNets for exploring different multimodal fusion strategies and a PolicyNet for deciding which FusionNets are enabled. Third, a module called Cross-modal Feature Decoder is designed to transfer cross-modal features generated by Adaptive Fusion Module to the mixed-modality branch., Comment: IEEE Transactions on Image Processing 2024
Published: 2024
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23. Research on Mobile Network High-precision Absolute Time Synchronization based on TAP

Author: Zhang, Chenyu, Wen, Xiangming, Zheng, Wei, Yu, Longdan, Lu, Zhaoming, Wang, Zhengying, Zhang, Chenyu, Wen, Xiangming, Zheng, Wei, Yu, Longdan, Lu, Zhaoming, and Wang, Zhengying
Abstract: With the development of mobile communication and industrial internet technologies, the demand for robust absolute time synchronization based on network for diverse scenarios is significantly growing. TAP is a novel network timing method that aims to achieve sub-microsecond synchronization over air interface. This paper investigates the improvement and end-to-end realization of TAP. This paper first analyzes the effectiveness and deficiencies of TAP by establishing an equivalent clock model which evaluates TAP from timing error composition and allan variance. Second, this paper proposes a detailed base station and terminal design and the corresponding improvement of TAP. Both hardware compensation and protocol software design are taken into account so as to minimize timing error and system cost while maximizing compatibility with 3GPP. Finally, this paper presents a TAP end-to-end 5G prototype system developed based on software defined radio base station and COTS baseband module. The field test results show that the proposed scheme effectively solves the problems of TAP in application and robustly achieves 200ns level timing accuracy in various situations. The average accuracy with long observations can reach 1 nanosecond. It is 2$\sim$3 orders of magnitude better than common network timing methods, including NTP, PTP and the original TAP.
Published: 2024

24. ActionHub: A Large-scale Action Video Description Dataset for Zero-shot Action Recognition

Author: Zhou, Jiaming, Liang, Junwei, Lin, Kun-Yu, Yang, Jinrui, Zheng, Wei-Shi, Zhou, Jiaming, Liang, Junwei, Lin, Kun-Yu, Yang, Jinrui, and Zheng, Wei-Shi
Abstract: Zero-shot action recognition (ZSAR) aims to learn an alignment model between videos and class descriptions of seen actions that is transferable to unseen actions. The text queries (class descriptions) used in existing ZSAR works, however, are often short action names that fail to capture the rich semantics in the videos, leading to misalignment. With the intuition that video content descriptions (e.g., video captions) can provide rich contextual information of visual concepts in videos, we propose to utilize human annotated video descriptions to enrich the semantics of the class descriptions of each action. However, all existing action video description datasets are limited in terms of the number of actions, the semantics of video descriptions, etc. To this end, we collect a large-scale action video descriptions dataset named ActionHub, which covers a total of 1,211 common actions and provides 3.6 million action video descriptions. With the proposed ActionHub dataset, we further propose a novel Cross-modality and Cross-action Modeling (CoCo) framework for ZSAR, which consists of a Dual Cross-modality Alignment module and a Cross-action Invariance Mining module. Specifically, the Dual Cross-modality Alignment module utilizes both action labels and video descriptions from ActionHub to obtain rich class semantic features for feature alignment. The Cross-action Invariance Mining module exploits a cycle-reconstruction process between the class semantic feature spaces of seen actions and unseen actions, aiming to guide the model to learn cross-action invariant representations. Extensive experimental results demonstrate that our CoCo framework significantly outperforms the state-of-the-art on three popular ZSAR benchmarks (i.e., Kinetics-ZSAR, UCF101 and HMDB51) under two different learning protocols in ZSAR. We will release our code, models, and the proposed ActionHub dataset.
Published: 2024

25. Transformer for Object Re-Identification: A Survey

Author: Ye, Mang, Chen, Shuoyi, Li, Chenyue, Zheng, Wei-Shi, Crandall, David, Du, Bo, Ye, Mang, Chen, Shuoyi, Li, Chenyue, Zheng, Wei-Shi, Crandall, David, and Du, Bo
Abstract: Object Re-Identification (Re-ID) aims to identify and retrieve specific objects from varying viewpoints. For a prolonged period, this field has been predominantly driven by deep convolutional neural networks. In recent years, the Transformer has witnessed remarkable advancements in computer vision, prompting an increasing body of research to delve into the application of Transformer in Re-ID. This paper provides a comprehensive review and in-depth analysis of the Transformer-based Re-ID. In categorizing existing works into Image/Video-Based Re-ID, Re-ID with limited data/annotations, Cross-Modal Re-ID, and Special Re-ID Scenarios, we thoroughly elucidate the advantages demonstrated by the Transformer in addressing a multitude of challenges across these domains. Considering the trending unsupervised Re-ID, we propose a new Transformer baseline, UntransReID, achieving state-of-the-art performance on both single-/cross modal tasks. Besides, this survey also covers a wide range of Re-ID research objects, including progress in animal Re-ID. Given the diversity of species in animal Re-ID, we devise a standardized experimental benchmark and conduct extensive experiments to explore the applicability of Transformer for this task to facilitate future research. Finally, we discuss some important yet under-investigated open issues in the big foundation model era, we believe it will serve as a new handbook for researchers in this field.
Published: 2024

26. Grasp as You Say: Language-guided Dexterous Grasp Generation

Author: Wei, Yi-Lin, Jiang, Jian-Jian, Xing, Chengyi, Tan, Xiantuo, Wu, Xiao-Ming, Li, Hao, Cutkosky, Mark, Zheng, Wei-Shi, Wei, Yi-Lin, Jiang, Jian-Jian, Xing, Chengyi, Tan, Xiantuo, Wu, Xiao-Ming, Li, Hao, Cutkosky, Mark, and Zheng, Wei-Shi
Abstract: This paper explores a novel task ""Dexterous Grasp as You Say"" (DexGYS), enabling robots to perform dexterous grasping based on human commands expressed in natural language. However, the development of this field is hindered by the lack of datasets with natural human guidance; thus, we propose a language-guided dexterous grasp dataset, named DexGYSNet, offering high-quality dexterous grasp annotations along with flexible and fine-grained human language guidance. Our dataset construction is cost-efficient, with the carefully-design hand-object interaction retargeting strategy, and the LLM-assisted language guidance annotation system. Equipped with this dataset, we introduce the DexGYSGrasp framework for generating dexterous grasps based on human language instructions, with the capability of producing grasps that are intent-aligned, high quality and diversity. To achieve this capability, our framework decomposes the complex learning process into two manageable progressive objectives and introduce two components to realize them. The first component learns the grasp distribution focusing on intention alignment and generation diversity. And the second component refines the grasp quality while maintaining intention consistency. Extensive experiments are conducted on DexGYSNet and real world environment for validation., Comment: 9 pages, 7 figures
Published: 2024

27. Code Repair with LLMs gives an Exploration-Exploitation Tradeoff

Author: Tang, Hao, Hu, Keya, Zhou, Jin Peng, Zhong, Sicheng, Zheng, Wei-Long, Si, Xujie, Ellis, Kevin, Tang, Hao, Hu, Keya, Zhou, Jin Peng, Zhong, Sicheng, Zheng, Wei-Long, Si, Xujie, and Ellis, Kevin
Abstract: Iteratively improving and repairing source code with large language models (LLMs), known as refinement, has emerged as a popular way of generating programs that would be too complex to construct in one shot. Given a bank of test cases, together with a candidate program, an LLM can improve that program by being prompted with failed test cases. But it remains an open question how to best iteratively refine code, with prior work employing simple greedy or breadth-first strategies. We show here that refinement exposes an explore-exploit tradeoff: exploit by refining the program that passes the most test cases, or explore by refining a lesser considered program. We frame this as an arm-acquiring bandit problem, which we solve with Thompson Sampling. The resulting LLM-based program synthesis algorithm is broadly applicable: Across loop invariant synthesis, visual reasoning puzzles, and competition programming problems, we find that our new method can solve more problems using fewer language model calls.
Published: 2024

28. DreamView: Injecting View-specific Text Guidance into Text-to-3D Generation

Author: Yan, Junkai, Gao, Yipeng, Yang, Qize, Wei, Xihan, Xie, Xuansong, Wu, Ancong, Zheng, Wei-Shi, Yan, Junkai, Gao, Yipeng, Yang, Qize, Wei, Xihan, Xie, Xuansong, Wu, Ancong, and Zheng, Wei-Shi
Abstract: Text-to-3D generation, which synthesizes 3D assets according to an overall text description, has significantly progressed. However, a challenge arises when the specific appearances need customizing at designated viewpoints but referring solely to the overall description for generating 3D objects. For instance, ambiguity easily occurs when producing a T-shirt with distinct patterns on its front and back using a single overall text guidance. In this work, we propose DreamView, a text-to-image approach enabling multi-view customization while maintaining overall consistency by adaptively injecting the view-specific and overall text guidance through a collaborative text guidance injection module, which can also be lifted to 3D generation via score distillation sampling. DreamView is trained with large-scale rendered multi-view images and their corresponding view-specific texts to learn to balance the separate content manipulation in each view and the global consistency of the overall object, resulting in a dual achievement of customization and consistency. Consequently, DreamView empowers artists to design 3D objects creatively, fostering the creation of more innovative and diverse 3D assets. Code and model will be released at https://github.com/iSEE-Laboratory/DreamView.
Published: 2024

29. Dexterous Grasp Transformer

Author: Xu, Guo-Hao, Wei, Yi-Lin, Zheng, Dian, Wu, Xiao-Ming, Zheng, Wei-Shi, Xu, Guo-Hao, Wei, Yi-Lin, Zheng, Dian, Wu, Xiao-Ming, and Zheng, Wei-Shi
Abstract: In this work, we propose a novel discriminative framework for dexterous grasp generation, named Dexterous Grasp TRansformer (DGTR), capable of predicting a diverse set of feasible grasp poses by processing the object point cloud with only one forward pass. We formulate dexterous grasp generation as a set prediction task and design a transformer-based grasping model for it. However, we identify that this set prediction paradigm encounters several optimization challenges in the field of dexterous grasping and results in restricted performance. To address these issues, we propose progressive strategies for both the training and testing phases. First, the dynamic-static matching training (DSMT) strategy is presented to enhance the optimization stability during the training phase. Second, we introduce the adversarial-balanced test-time adaptation (AB-TTA) with a pair of adversarial losses to improve grasping quality during the testing phase. Experimental results on the DexGraspNet dataset demonstrate the capability of DGTR to predict dexterous grasp poses with both high quality and diversity. Notably, while keeping high quality, the diversity of grasp poses predicted by DGTR significantly outperforms previous works in multiple metrics without any data pre-processing. Codes are available at https://github.com/iSEE-Laboratory/DGTR ., Comment: Accepted to CVPR 2024
Published: 2024

30. Single-View Scene Point Cloud Human Grasp Generation

Author: Wang, Yan-Kang, Xing, Chengyi, Wei, Yi-Lin, Wu, Xiao-Ming, Zheng, Wei-Shi, Wang, Yan-Kang, Xing, Chengyi, Wei, Yi-Lin, Wu, Xiao-Ming, and Zheng, Wei-Shi
Abstract: In this work, we explore a novel task of generating human grasps based on single-view scene point clouds, which more accurately mirrors the typical real-world situation of observing objects from a single viewpoint. Due to the incompleteness of object point clouds and the presence of numerous scene points, the generated hand is prone to penetrating into the invisible parts of the object and the model is easily affected by scene points. Thus, we introduce S2HGrasp, a framework composed of two key modules: the Global Perception module that globally perceives partial object point clouds, and the DiffuGrasp module designed to generate high-quality human grasps based on complex inputs that include scene points. Additionally, we introduce S2HGD dataset, which comprises approximately 99,000 single-object single-view scene point clouds of 1,668 unique objects, each annotated with one human grasp. Our extensive experiments demonstrate that S2HGrasp can not only generate natural human grasps regardless of scene points, but also effectively prevent penetration between the hand and invisible parts of the object. Moreover, our model showcases strong generalization capability when applied to unseen objects. Our code and dataset are available at https://github.com/iSEE-Laboratory/S2HGrasp.
Published: 2024

31. The LAR protein tyrosine phosphatase enables PDGF β-receptor activation and signal transduction

Author: Zheng, Wei
Subjects: 500, Q Science (General), QH301 Biology
Abstract: Many cellular activities including cell survival, proliferation, migration and differentiation are controlled by growth factors and their corresponding tyrosine kinases receptor (RTKs). Growth factor receptor activation is strictly regulated by protein tyrosine phosphatases (PTPs). Here I investigated whether the receptor protein tyrosine phosphatase (RPTP) LAR, which is known to modify the activity of several RTKs, also regulates platelet derived growth factor (PDGF) receptor activity and signalling. Mouse embryonic fibroblasts (MEFs) expressing mutant LAR lacking its phosphatase domains (LARΔP) showed reduced phosphorylation of PDGFβ receptor (PDGFβR) compared with wild type (WT) cells. This was rescued by re-expression of WT LAR. The decreased phosphorylation of the PDGFβR was independent of ligand concentration and occurred on all tyrosine residues, suggesting that LAR is required for full PDGFβR kinase activation. The decreased kinase activity reduced the amplitude or duration of the different signalling pathways activated downstream of the PDGFβR, and resulted in reduced proliferation in response to PDGF-BB. These findings demonstrate, for the first time, that LAR activity is required for PDGF-induced fibroblast proliferation. The inhibition of PDGFβR kinase activity in LARΔP cells was exerted via increased basal activity of the tyrosine kinase c-Abl and its substrate protein kinase Cδ (PKCδ). Ligand-induced PDGFβR dimerization is defective in LARΔP cells, possibly due to the observed increase in the Nherf2 protein associating with the PDGFβR. In summary, I have identified LAR as a new regulator of PDGFβR activity, and propose a novel mechanism where PDGF-induced activation of c-Abl serves as a negative feedback loop to terminate the PDGFβR kinase activity. This may occur via PKCδ activation promoting the association of Nherf2 with PDGFβR, thereby reducing ligand-induced receptor dimerization and kinase activation. In this model, LAR promotes PDGFβR activity by inactivating c-Abl.
Published: 2013

32. Explorations in grid workflow scheduling

Author: Zheng, Wei and Sakellariou, Rizos
Subjects: 621.382, Grid, Workflow Scheduling
Abstract: Aiming at aggregating numerous distributed resources to provide immense computing power, Grid computing has emerged as a promising paradigm to run complex composite applications such as workflows. However, the inherent uncertainties of grid systems as well as the structural complexity of workflow applications make it extremely challenging to schedule workflows in an efficient way, regardless of whether the objective is to minimize execution time or meet specific user and/or system Quality of Service (QoS) requirements. For both these cases, this thesis considers scheduling problems motivated by grid uncertainties and advances the state-of-the-art by developing new techniques to address these problems.First, based on existing scheduling heuristics, a Monte-Carlo approach is developed to minimize the average makespan (i.e., the overall execution time) in the presence of task estimates exhibiting limited uncertainty in the form of (controlled) random behaviour. Next, a scenario where performance prediction is difficult to obtain and resource availability may vary over time, is considered. A low-cost efficient just-in-time heuristic is proposed to cope with grid uncertainties.After addressing these performance-driven scheduling problems, a QoS-driven problem, which considers not only the aforementioned uncertainties but also the uncertainty caused by queue-based scheduling, is examined. In order to tackle all these uncertainties, an integrated scheduling model consisting of three supportive techniques is developed. Extensive evaluation using simulation shows that the proposed techniques can achieve substantial improvements towards the ultimate goal of providing a good solution for QoS-driven workflow scheduling on the Grid.
Published: 2010

33. Aerodynamic Evaluation of a Reference Body using CFD DES & RANS Solvers

Author: Zheng Wei, Kuek, Mahak, M, Zheng Wei, Kuek, Zheng Wei, Kuek, Mahak, M, and Zheng Wei, Kuek
Abstract: The electric vehicle revolution has transformed the automotive industry into one that prioritises efficiency, lightness, and low-cost. Innovation has become a key cost in automotive companies, where in Europe in 2020, €58.8 billion was invested in Research & Development (Hatton, 2022). Computer simulations have been emerging as a cost-effective and reliable method in early vehicle conceptual development (Dhaubhadel, 1996). In the area of aerodynamics, Computational Fluid Dynamics (CFD) can be a pre-test bed for novel design concepts before wind tunnel validation (Ding et al., 2006). Typically, a separated wake flow forms at the back of the vehicle, which has a significant impact on its fuel efficiency and drag (Velshankar, Senthilkumar & Kannan, 2019). Therefore, the employed solving method must be able to predict air flow behaviour in this recirculation region and is crucial to the accuracy of the results. An accurate simulation model can minimise the cost of unnecessary wind-tunnel testing and speed up the rate of development. The benefit of a combination of the Reynolds Averaged Navier-Stokes (RANS) and the Large Eddy Simulation (LES), namely Detached Eddy Simulation (DES) is determined in this study. DES has been used for performance car aerodynamic simulations by companies such as Koenigsegg in their Jesko hypercar (Hatton, 2022). An investigation to the sensitivity of y+ values to accuracy has been completed in tandem with an implementation of Improved Delayed DES (IDDES) due to its wall modelling capabilities. While it has been shown that Y+ optimisation did not improve the prediction of the velocity in the recirculation region, it is hypothesised that a change in method to a Hybrid RANS-LES method to be more beneficial for this case of external flow around a moving body, which will be investigated in a continuation to this study.
Published: 2022

34. A Likelihood Ratio Approach for Utilizing Case-Control Data in the Clinical Classification of Rare Sequence Variants : Application to BRCA1 and BRCA2

Author: Zanti, Maria, O'Mahony, Denise G., Parsons, Michael T., Li, Hongyan, Dennis, Joe, Aittomakkiki, Kristiina, Andrulis, Irene L., Anton-Culver, Hoda, Aronson, Kristan J., Augustinsson, Annelie, Becher, Heiko, Bojesen, Stig E., Bolla, Manjeet K., Brenner, Hermann, Brown, Melissa A., Buys, Saundra S., Canzian, Federico, Caputo, Sandrine M., Castelao, Jose E., Chang-Claude, Jenny, Czene, Kamila, Daly, Mary B., De Nicolo, Arcangela, Devilee, Peter, Dork, Thilo, Dunning, Alison M., Dwek, Miriam, Eccles, Diana M., Engel, Christoph, Evans, D. Gareth, Fasching, Peter A., Gago-Dominguez, Manuela, Garcia-Closas, Montserrat, Garcia-Saenz, Jose A., Gentry-Maharaj, Aleksandra, Geurts-Giele, Willemina R. R., Giles, Graham G., Glendon, Gord, Goldberg, Mark S., Garcia, Encarna B. Gomez, Guendert, Melanie, Guenel, Pascal, Hahnen, Eric, Haiman, Christopher A., Hall, Per, Hamann, Ute, Harkness, Elaine F., Hogervorst, Frans B. L., Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L., Houdayer, Claude, Houlston, Richard S., Howell, Anthony, Investigators, Abctb, Jakimovska, Milena, Jakubowska, Anna, Jernstrom, Helena, John, Esther M., Kaaks, Rudolf, Kitahara, Cari M., Koutros, Stella, Kraft, Peter, Kristensen, Vessela N., Lacey, James, V, Lambrechts, Diether, Leone, Melanie, Lindblom, Annika, Lush, Michael, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Martinez, Maria Elena, Menon, Usha, Milne, Roger L., Monteiro, Alvaro N., Murphy, Rachel A., Neuhausen, Susan L., Nevanlinna, Heli, Newman, William G., Offit, Kenneth, Park, Sue K., James, Paul, Peterlongo, Paolo, Peto, Julian, Plaseska-Karanfilska, Dijana, Punie, Kevin, Radice, Paolo, Rashid, Muhammad U., Rennert, Gad, Romero, Atocha, Rosenberg, Efraim H., Saloustros, Emmanouil, Sandler, Dale P., Schmidt, Marjanka K., Schmutzler, Rita K., Shu, Xiao-Ou, Simard, Jacques, Southey, Melissa C., Stone, Jennifer, Stoppa-Lyonnet, Dominique, Tamimi, Rulla M., Tapper, William J., Taylor, Jack A., Teo, Soo Hwang, Teras, Lauren R., Terry, Mary Beth, Thomassen, Mads, Troester, Melissa A., Vachon, Celine M., Vega, Ana, Vreeswijk, Maaike P. G., Wang, Qin, Wappenschmidt, Barbara, Weinberg, Clarice R., Wolk, Alicja, Zheng, Wei, Feng, Bingjian, Couch, Fergus J., Spurdle, Amanda B., Easton, Douglas F., Goldgar, David E., Michailidou, Kyriaki, Zanti, Maria, O'Mahony, Denise G., Parsons, Michael T., Li, Hongyan, Dennis, Joe, Aittomakkiki, Kristiina, Andrulis, Irene L., Anton-Culver, Hoda, Aronson, Kristan J., Augustinsson, Annelie, Becher, Heiko, Bojesen, Stig E., Bolla, Manjeet K., Brenner, Hermann, Brown, Melissa A., Buys, Saundra S., Canzian, Federico, Caputo, Sandrine M., Castelao, Jose E., Chang-Claude, Jenny, Czene, Kamila, Daly, Mary B., De Nicolo, Arcangela, Devilee, Peter, Dork, Thilo, Dunning, Alison M., Dwek, Miriam, Eccles, Diana M., Engel, Christoph, Evans, D. Gareth, Fasching, Peter A., Gago-Dominguez, Manuela, Garcia-Closas, Montserrat, Garcia-Saenz, Jose A., Gentry-Maharaj, Aleksandra, Geurts-Giele, Willemina R. R., Giles, Graham G., Glendon, Gord, Goldberg, Mark S., Garcia, Encarna B. Gomez, Guendert, Melanie, Guenel, Pascal, Hahnen, Eric, Haiman, Christopher A., Hall, Per, Hamann, Ute, Harkness, Elaine F., Hogervorst, Frans B. L., Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L., Houdayer, Claude, Houlston, Richard S., Howell, Anthony, Investigators, Abctb, Jakimovska, Milena, Jakubowska, Anna, Jernstrom, Helena, John, Esther M., Kaaks, Rudolf, Kitahara, Cari M., Koutros, Stella, Kraft, Peter, Kristensen, Vessela N., Lacey, James, V, Lambrechts, Diether, Leone, Melanie, Lindblom, Annika, Lush, Michael, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Martinez, Maria Elena, Menon, Usha, Milne, Roger L., Monteiro, Alvaro N., Murphy, Rachel A., Neuhausen, Susan L., Nevanlinna, Heli, Newman, William G., Offit, Kenneth, Park, Sue K., James, Paul, Peterlongo, Paolo, Peto, Julian, Plaseska-Karanfilska, Dijana, Punie, Kevin, Radice, Paolo, Rashid, Muhammad U., Rennert, Gad, Romero, Atocha, Rosenberg, Efraim H., Saloustros, Emmanouil, Sandler, Dale P., Schmidt, Marjanka K., Schmutzler, Rita K., Shu, Xiao-Ou, Simard, Jacques, Southey, Melissa C., Stone, Jennifer, Stoppa-Lyonnet, Dominique, Tamimi, Rulla M., Tapper, William J., Taylor, Jack A., Teo, Soo Hwang, Teras, Lauren R., Terry, Mary Beth, Thomassen, Mads, Troester, Melissa A., Vachon, Celine M., Vega, Ana, Vreeswijk, Maaike P. G., Wang, Qin, Wappenschmidt, Barbara, Weinberg, Clarice R., Wolk, Alicja, Zheng, Wei, Feng, Bingjian, Couch, Fergus J., Spurdle, Amanda B., Easton, Douglas F., Goldgar, David E., and Michailidou, Kyriaki
Abstract: A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity-findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.
Published: 2023
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35. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Author: Middha, Pooja K., Wang, Xiaoliang, Behrens, Sabine, Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J., Auer, Paul L., Augustinsson, Annelie, Baert, Thais, Freeman, Laura E. Beane, Becher, Heiko, Beckmann, Matthias W., Benitez, Javier, Bojesen, Stig E., Brauch, Hiltrud, Brenner, Hermann, Brooks-Wilson, Angela, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Castelao, Jose E., Chanock, Stephen J., Chenevix-Trench, Georgia, Cordina-Duverger, Emilie, Couch, Fergus J., Cox, Angela, Cross, Simon S., Czene, Kamila, Dossus, Laure, Dugue, Pierre-Antoine, Eliassen, A. Heather, Eriksson, Mikael, Evans, D. Gareth, Fasching, Peter A., Figueroa, Jonine, Fletcher, Olivia, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Giles, Graham G., Gonzalez-Neira, Anna, Grassmann, Felix, Grundy, Anne, Guenel, Pascal, Haiman, Christopher A., Hakansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E., Harkness, Elaine F., Holleczek, Bernd, Hoppe, Reiner, Hopper, John L., Houlston, Richard S., Howell, Anthony, Hunter, David J., Ingvar, Christian, Isaksson, Karolin, Jernstroem, Helena, John, Esther M., Jones, Michael E., Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M., Ko, Yon-Dschun, Koutros, Stella, Kurian, Allison W., Lacey, James V., Lambrechts, Diether, Larson, Nicole L., Larsson, Susanna C., Le Marchand, Loic, Lejbkowicz, Flavio, Li, Shuai, Linet, Martha, Lissowska, Jolanta, Martinez, Maria Elena, Maurer, Tabea, Mulligan, Anna Marie, Mulot, Claire, Murphy, Rachel A., Newman, William G., Nielsen, Sune F., Nordestgaard, Borge G., Norman, Aaron, O'Brien, Katie M., Olson, Janet E., Patel, Alpa V., Prentice, Ross, Rees-Punia, Erika, Rennert, Gad, Rhenius, Valerie, Ruddy, Kathryn J., Sandler, Dale P., Scott, Christopher G., Shah, Mitul T., Shu, Xiao-Ou, Smeets, Ann, Southey, Melissa C., Stone, Jennifer, Tamimi, Rulla M., Taylor, Jack A., Teras, Lauren R., Tomczyk, Katarzyna, Troester, Melissa A., Truong, Therese, Vachon, Celine M., Wang, Sophia S., Weinberg, Clarice R., Wildiers, Hans, Willett, Walter, Winham, Stacey J., Wolk, Alicja, Yang, Xiaohong, Zamora, M. Pilar, Zheng, Wei, Ziogas, Argyrios, Dunning, Alison M., Pharoah, Paul D. P., Garcia-Closas, Montserrat, Schmidt, Marjanka K., Kraft, Peter, Milne, Roger L., Lindstroem, Sara, Easton, Douglas F., Chang-Claude, Jenny, Middha, Pooja K., Wang, Xiaoliang, Behrens, Sabine, Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J., Auer, Paul L., Augustinsson, Annelie, Baert, Thais, Freeman, Laura E. Beane, Becher, Heiko, Beckmann, Matthias W., Benitez, Javier, Bojesen, Stig E., Brauch, Hiltrud, Brenner, Hermann, Brooks-Wilson, Angela, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Castelao, Jose E., Chanock, Stephen J., Chenevix-Trench, Georgia, Cordina-Duverger, Emilie, Couch, Fergus J., Cox, Angela, Cross, Simon S., Czene, Kamila, Dossus, Laure, Dugue, Pierre-Antoine, Eliassen, A. Heather, Eriksson, Mikael, Evans, D. Gareth, Fasching, Peter A., Figueroa, Jonine, Fletcher, Olivia, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Giles, Graham G., Gonzalez-Neira, Anna, Grassmann, Felix, Grundy, Anne, Guenel, Pascal, Haiman, Christopher A., Hakansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E., Harkness, Elaine F., Holleczek, Bernd, Hoppe, Reiner, Hopper, John L., Houlston, Richard S., Howell, Anthony, Hunter, David J., Ingvar, Christian, Isaksson, Karolin, Jernstroem, Helena, John, Esther M., Jones, Michael E., Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M., Ko, Yon-Dschun, Koutros, Stella, Kurian, Allison W., Lacey, James V., Lambrechts, Diether, Larson, Nicole L., Larsson, Susanna C., Le Marchand, Loic, Lejbkowicz, Flavio, Li, Shuai, Linet, Martha, Lissowska, Jolanta, Martinez, Maria Elena, Maurer, Tabea, Mulligan, Anna Marie, Mulot, Claire, Murphy, Rachel A., Newman, William G., Nielsen, Sune F., Nordestgaard, Borge G., Norman, Aaron, O'Brien, Katie M., Olson, Janet E., Patel, Alpa V., Prentice, Ross, Rees-Punia, Erika, Rennert, Gad, Rhenius, Valerie, Ruddy, Kathryn J., Sandler, Dale P., Scott, Christopher G., Shah, Mitul T., Shu, Xiao-Ou, Smeets, Ann, Southey, Melissa C., Stone, Jennifer, Tamimi, Rulla M., Taylor, Jack A., Teras, Lauren R., Tomczyk, Katarzyna, Troester, Melissa A., Truong, Therese, Vachon, Celine M., Wang, Sophia S., Weinberg, Clarice R., Wildiers, Hans, Willett, Walter, Winham, Stacey J., Wolk, Alicja, Yang, Xiaohong, Zamora, M. Pilar, Zheng, Wei, Ziogas, Argyrios, Dunning, Alison M., Pharoah, Paul D. P., Garcia-Closas, Montserrat, Schmidt, Marjanka K., Kraft, Peter, Milne, Roger L., Lindstroem, Sara, Easton, Douglas F., and Chang-Claude, Jenny
Abstract: Background Genome-wide studies of gene-environment interactions (GxE) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide GxE analysis of similar to 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer. Methods Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs. Results Assuming a 1 x 10(-5) prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94). Conclusions Overall, the contribution of GxE interactions to the heritability of breast cancer is very small. At the population level, multiplicative GxE interactions do not make an important contribution to risk prediction in breast cancer.
Published: 2023
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36. Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations

Author: Thomas, Minta, Su, Yu-Ru, Rosenthal, Elisabeth A., Sakoda, Lori C., Schmit, Stephanie L., Timofeeva, Maria N., Chen, Zhishan, Fernandez-Rozadilla, Ceres, Law, Philip J., Murphy, Neil, Carreras-Torres, Robert, Diez-Obrero, Virginia, van Duijnhoven, Franzel J. B., Jiang, Shangqing, Shin, Aesun, Wolk, Alicja, Phipps, Amanda I., Burnett-Hartman, Andrea, Gsur, Andrea, Chan, Andrew T., Zauber, Ann G., Wu, Anna H., Lindblom, Annika, Um, Caroline Y., Tangen, Catherine M., Gignoux, Chris, Newton, Christina, Haiman, Christopher A., Qu, Conghui, Bishop, D. Timothy, Buchanan, Daniel D., Crosslin, David R., Conti, David V., Kim, Dong-Hyun, Hauser, Elizabeth, White, Emily, Siegel, Erin, Schumacher, Fredrick R., Rennert, Gad, Giles, Graham G., Hampel, Heather, Brenner, Hermann, Oze, Isao, Oh, Jae Hwan, Lee, Jeffrey K., Schneider, Jennifer L., Chang-Claude, Jenny, Kim, Jeongseon, Huyghe, Jeroen R., Zheng, Jiayin, Hampe, Jochen, Greenson, Joel, Hopper, John L., Palmer, Julie R., Visvanathan, Kala, Matsuo, Keitaro, Matsuda, Koichi, Jung, Keum Ji, Li, Li, Le Marchand, Loic, Vodickova, Ludmila, Bujanda, Luis, Gunter, Marc J., Matejcic, Marco, Jenkins, Mark A., Slattery, Martha L., D’Amato, Mauro, Wang, Meilin, Hoffmeister, Michael, Woods, Michael O., Kim, Michelle, Song, Mingyang, Iwasaki, Motoki, Du, Mulong, Udaltsova, Natalia, Sawada, Norie, Vodicka, Pavel, Campbell, Peter T., Newcomb, Polly A., Cai, Qiuyin, Pearlman, Rachel, Pai, Rish K., Schoen, Robert E., Steinfelder, Robert S., Haile, Robert W., Vandenputtelaar, Rosita, Prentice, Ross L., Küry, Sébastien, Castellví-Bel, Sergi, Tsugane, Shoichiro, Berndt, Sonja I., Lee, Soo Chin, Brezina, Stefanie, Weinstein, Stephanie J., Chanock, Stephen J., Jee, Sun Ha, Kweon, Sun-Seog, Vadaparampil, Susan, Harrison, Tabitha A., Yamaji, Taiki, Keku, Temitope O., Vymetalkova, Veronika, Arndt, Volker, Jia, Wei-Hua, Shu, Xiao-Ou, Lin, Yi, Ahn, Yoon-Ok, Stadler, Zsofia K., van Guelpen, Bethany, Ulrich, Cornelia M., Platz, Elizabeth A., Potter, John D., Li, Christopher I., Meester, Reinier, Moreno, Victor, Figueiredo, Jane C., Casey, Graham, Lansdorp Vogelaar, Iris, Dunlop, Malcolm G., Gruber, Stephen B., Hayes, Richard B., Pharoah, Paul D. P., Houlston, Richard S., Jarvik, Gail P., Tomlinson, Ian P., Zheng, Wei, Corley, Douglas A., Peters, Ulrike, Hsu, Li, Thomas, Minta, Su, Yu-Ru, Rosenthal, Elisabeth A., Sakoda, Lori C., Schmit, Stephanie L., Timofeeva, Maria N., Chen, Zhishan, Fernandez-Rozadilla, Ceres, Law, Philip J., Murphy, Neil, Carreras-Torres, Robert, Diez-Obrero, Virginia, van Duijnhoven, Franzel J. B., Jiang, Shangqing, Shin, Aesun, Wolk, Alicja, Phipps, Amanda I., Burnett-Hartman, Andrea, Gsur, Andrea, Chan, Andrew T., Zauber, Ann G., Wu, Anna H., Lindblom, Annika, Um, Caroline Y., Tangen, Catherine M., Gignoux, Chris, Newton, Christina, Haiman, Christopher A., Qu, Conghui, Bishop, D. Timothy, Buchanan, Daniel D., Crosslin, David R., Conti, David V., Kim, Dong-Hyun, Hauser, Elizabeth, White, Emily, Siegel, Erin, Schumacher, Fredrick R., Rennert, Gad, Giles, Graham G., Hampel, Heather, Brenner, Hermann, Oze, Isao, Oh, Jae Hwan, Lee, Jeffrey K., Schneider, Jennifer L., Chang-Claude, Jenny, Kim, Jeongseon, Huyghe, Jeroen R., Zheng, Jiayin, Hampe, Jochen, Greenson, Joel, Hopper, John L., Palmer, Julie R., Visvanathan, Kala, Matsuo, Keitaro, Matsuda, Koichi, Jung, Keum Ji, Li, Li, Le Marchand, Loic, Vodickova, Ludmila, Bujanda, Luis, Gunter, Marc J., Matejcic, Marco, Jenkins, Mark A., Slattery, Martha L., D’Amato, Mauro, Wang, Meilin, Hoffmeister, Michael, Woods, Michael O., Kim, Michelle, Song, Mingyang, Iwasaki, Motoki, Du, Mulong, Udaltsova, Natalia, Sawada, Norie, Vodicka, Pavel, Campbell, Peter T., Newcomb, Polly A., Cai, Qiuyin, Pearlman, Rachel, Pai, Rish K., Schoen, Robert E., Steinfelder, Robert S., Haile, Robert W., Vandenputtelaar, Rosita, Prentice, Ross L., Küry, Sébastien, Castellví-Bel, Sergi, Tsugane, Shoichiro, Berndt, Sonja I., Lee, Soo Chin, Brezina, Stefanie, Weinstein, Stephanie J., Chanock, Stephen J., Jee, Sun Ha, Kweon, Sun-Seog, Vadaparampil, Susan, Harrison, Tabitha A., Yamaji, Taiki, Keku, Temitope O., Vymetalkova, Veronika, Arndt, Volker, Jia, Wei-Hua, Shu, Xiao-Ou, Lin, Yi, Ahn, Yoon-Ok, Stadler, Zsofia K., van Guelpen, Bethany, Ulrich, Cornelia M., Platz, Elizabeth A., Potter, John D., Li, Christopher I., Meester, Reinier, Moreno, Victor, Figueiredo, Jane C., Casey, Graham, Lansdorp Vogelaar, Iris, Dunlop, Malcolm G., Gruber, Stephen B., Hayes, Richard B., Pharoah, Paul D. P., Houlston, Richard S., Jarvik, Gail P., Tomlinson, Ian P., Zheng, Wei, Corley, Douglas A., Peters, Ulrike, and Hsu, Li
Abstract: Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.
Published: 2023
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37. Universal Aspects of High-Temperature Relaxation Dynamics in Random Spin Models

Author: Zhou, Tian-Gang, Zheng, Wei, Zhang, Pengfei, Zhou, Tian-Gang, Zheng, Wei, and Zhang, Pengfei
Abstract: Universality is a crucial concept in modern physics, allowing us to capture the essential features of a system's behavior using a small set of parameters. In this work, we unveil universal spin relaxation dynamics in anisotropic random Heisenberg models with infinite-range interactions at high temperatures. Starting from a polarized state, the total magnetization can relax monotonically or decay with long-lived oscillations, determined by the sign of a universal single function $A=-\xi_1^2+\xi_2^2-4\xi_2\xi_3+\xi_3^2$. Here $(\xi_1,\xi_3,\xi_3)$ characterizes the anisotropy of the Heisenberg interaction. Furthermore, the oscillation shows up only for $A>0$, with frequency $\Omega \propto \sqrt{A}$. To validate our theory, we compare it to numerical simulations by solving the Kadanoff-Baym (KB) equation with a melon diagram approximation and the exact diagonalization (ED). The results show our theoretical prediction works in both cases, regardless of a small system size $N=8$ in ED simulations. Our study sheds light on the universal aspect of quantum many-body dynamics beyond low energy limit., Comment: 20 pages, 5 figures
Published: 2023

38. Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants

Author: Wang, Anqi, Shen, Jiayi, Rodriguez, Alex A., Saunders, Edward J., Chen, Fei, Janivara, Rohini, Darst, Burcu F., Sheng, Xin, Xu, Yili, Chou, Alisha J., Benlloch, Sara, Dadaev, Tokhir, Brook, Mark N., Plym, Anna, Sahimi, Ali, Hoffman, Thomas J., Takahashi, Atushi, Matsuda, Koichi, Momozawa, Yukihide, Fujita, Masashi, Laisk, Triin, Figueredo, Jessica, Muir, Kenneth, Ito, Shuji, Liu, Xiaoxi, Uchio, Yuji, Kubo, Michiaki, Kamatani, Yoichiro, Lophatananon, Artitaya, Wan, Peggy, Andrews, Caroline, Lori, Adriana, Choudhury, Parichoy P., Schleutker, Johanna, Tammela, Teuvo L. J., Sipeky, Csilla, Auvinen, Anssi, Giles, Graham G., Southey, Melissa C., MacInnis, Robert J., Cybulski, Cezary, Wokolorczyk, Dominika, Lubinski, Jan, Rentsch, Christopher T., Cho, Kelly, Mcmahon, Benjamin H., Neal, David E., Donovan, Jenny L., Hamdy, Freddie C., Martin, Richard M., Nordestgaard, Borge G., Nielsen, Sune F., Weischer, Maren, Bojesen, Stig E., Roder, Andreas, Stroomberg, Hein V., Batra, Jyotsna, Chambers, Suzanne, Horvath, Lisa, Clements, Judith A., Tilly, Wayne, Risbridger, Gail P., Gronberg, Henrik, Aly, Markus, Szulkin, Robert, Eklund, Martin, Nordstrom, Tobias, Pashayan, Nora, Dunning, Alison M., Ghoussaini, Maya, Travis, Ruth C., Key, Tim J., Riboli, Elio, Park, Jong Y., Sellers, Thomas A., Lin, Hui-Yi, Albanes, Demetrius, Weinstein, Stephanie, Cook, Michael B., Mucci, Lorelei A., Giovannucci, Edward, Lindstrom, Sara, Kraft, Peter, Hunter, David J., Penney, Kathryn L., Turman, Constance, Tangen, Catherine M., Goodman, Phyllis J., Thompson, Ian M., Jr., Hamilton, Robert J., Fleshner, Neil E., Finelli, Antonio, Parent, Marie-Elise, Stanford, Janet L., Ostrander, Elaine A., Koutros, Stella, Freeman, Laura E. Beane, Stampfer, Meir, Wolk, Alicja, Hakansson, Niclas, Andriole, Gerald L., Hoover, Robert N., Machiela, Mitchell J., Sorensen, Karina Dalsgaard, Borre, Michael, Blot, William J., Zheng, Wei, Yeboah, Edward D., Mensah, James E., Lu, Yong-Jie, Zhang, Hong-Wei, Feng, Ninghan, Mao, Xueying, Wu, Yudong, Zhao, Shan-Chao, Sun, Zan, Thibodeau, Stephen N., McDonnell, Shannon K., Schaid, Daniel J., West, Catharine M. L., Barnett, Gill, Maier, Christiane, Schnoeller, Thomas, Luedeke, Manuel, Kibel, Adam S., Drake, Bettina F., Cussenot, Olivier, Cancel-Tassin, Geraldine, Menegaux, Florence, Truong, Therese, Koudou, Yves Akoli, John, Esther M., Grindedal, Eli Marie, Maehle, Lovise, Khaw, Kay-Tee, Ingles, Sue A., Stern, Mariana C., Vega, Ana, Gomez-Caamano, Antonio, Fachal, Laura, Rosenstein, Barry S., Kerns, Sarah L., Ostrer, Harry, Teixeira, Manuel R., Paulo, Paula, Brandao, Andreia, Watya, Stephen, Lubwama, Alexander, Bensen, Jeannette T., Butler, Ebonee N., Mohler, James L., Taylor, Jack A., Kogevinas, Manolis, Dierssen-Sotos, Trinidad, Castano-Vinyals, Gemma, Cannon-Albright, Lisa, Teerlink, Craig C., Huff, Chad D., Pilie, Patrick, Yu, Yao, Bohlender, Ryan J., Gu, Jian, Strom, Sara S., Multigner, Luc, Blanchet, Pascal, Brureau, Laurent, Kaneva, Radka, Slavov, Chavdar, Mitev, Vanio, Leach, Robin J., Brenner, Hermann, Chen, Xuechen, Holleczek, Bernd, Schoettker, Ben, Klein, Eric A., Hsing, Ann W., Kittles, Rick A., Murphy, Adam B., Logothetis, Christopher J., Kim, Jeri, Neuhausen, Susan L., Steele, Linda, Ding, Yuan Chun, Isaacs, William B., Nemesure, Barbara, Hennis, Anselm J. M., Carpten, John, Pandha, Hardev, Michael, Agnieszka, De Ruyck, Kim, De Meerleer, Gert, Ost, Piet, Xu, Jianfeng, Razack, Azad, Lim, Jasmine, Teo, Soo-Hwang, Newcomb, Lisa F., Lin, Daniel W., Fowke, Jay H., Neslund-Dudas, Christine M., Rybicki, Benjamin A., Gamulin, Marija, Lessel, Davor, Kulis, Tomislav, Usmani, Nawaid, Abraham, Aswin, Singhal, Sandeep, Parliament, Matthew, Claessens, Frank, Joniau, Steven, Van den Broeck, Thomas, Gago-Dominguez, Manuela, Castelao, Jose Esteban, Martinez, Maria Elena, Larkin, Samantha, Townsend, Paul A., Aukim-Hastie, Claire, Bush, William S., Aldrich, Melinda C., Crawford, Dana C., Srivastava, Shiv, Cullen, Jennifer, Petrovics, Gyorgy, Casey, Graham, Wang, Ying, Tettey, Yao, Lachance, Joseph, Tang, Wei, Biritwum, Richard B., Adjei, Andrew A., Tay, Evelyn, Truelove, Ann, Niwa, Shelley, Yamoah, Kosj, Govindasami, Koveela, Chokkalingam, Anand P., Keaton, Jacob M., Hellwege, Jacklyn N., Clark, Peter E., Jalloh, Mohamed, Gueye, Serigne M., Niang, Lamine, Ogunbiyi, Olufemi, Shittu, Olayiwola, Amodu, Olukemi, Adebiyi, Akindele O., Aisuodionoe-Shadrach, Oseremen I., Ajibola, Hafees O., Jamda, Mustapha A., Oluwole, Olabode P., Nwegbu, Maxwell, Adusei, Ben, Mante, Sunny, Darkwa-Abrahams, Afua, Diop, Halimatou, Gundell, Susan M., Roobol, Monique J., Jenster, Guido, van Schaik, Ron H. N., Hu, Jennifer J., Sanderson, Maureen, Kachuri, Linda, Varma, Rohit, McKean-Cowdin, Roberta, Torres, Mina, Preuss, Michael H., Loos, Ruth J. F., Zawistowski, Matthew, Zollner, Sebastian, Lu, Zeyun, Van Den Eeden, Stephen K., Easton, Douglas F., Ambs, Stefan, Edwards, Todd L., Magi, Reedik, Rebbeck, Timothy R., Fritsche, Lars, Chanock, Stephen J., Berndt, Sonja I., Wiklund, Fredrik, Nakagawa, Hidewaki, Witte, John S., Gaziano, J. Michael, Justice, Amy C., Mancuso, Nick, Terao, Chikashi, Eeles, Rosalind A., Kote-Jarai, Zsofia, Madduri, Ravi K., Conti, David V., Haiman, Christopher A., Wang, Anqi, Shen, Jiayi, Rodriguez, Alex A., Saunders, Edward J., Chen, Fei, Janivara, Rohini, Darst, Burcu F., Sheng, Xin, Xu, Yili, Chou, Alisha J., Benlloch, Sara, Dadaev, Tokhir, Brook, Mark N., Plym, Anna, Sahimi, Ali, Hoffman, Thomas J., Takahashi, Atushi, Matsuda, Koichi, Momozawa, Yukihide, Fujita, Masashi, Laisk, Triin, Figueredo, Jessica, Muir, Kenneth, Ito, Shuji, Liu, Xiaoxi, Uchio, Yuji, Kubo, Michiaki, Kamatani, Yoichiro, Lophatananon, Artitaya, Wan, Peggy, Andrews, Caroline, Lori, Adriana, Choudhury, Parichoy P., Schleutker, Johanna, Tammela, Teuvo L. J., Sipeky, Csilla, Auvinen, Anssi, Giles, Graham G., Southey, Melissa C., MacInnis, Robert J., Cybulski, Cezary, Wokolorczyk, Dominika, Lubinski, Jan, Rentsch, Christopher T., Cho, Kelly, Mcmahon, Benjamin H., Neal, David E., Donovan, Jenny L., Hamdy, Freddie C., Martin, Richard M., Nordestgaard, Borge G., Nielsen, Sune F., Weischer, Maren, Bojesen, Stig E., Roder, Andreas, Stroomberg, Hein V., Batra, Jyotsna, Chambers, Suzanne, Horvath, Lisa, Clements, Judith A., Tilly, Wayne, Risbridger, Gail P., Gronberg, Henrik, Aly, Markus, Szulkin, Robert, Eklund, Martin, Nordstrom, Tobias, Pashayan, Nora, Dunning, Alison M., Ghoussaini, Maya, Travis, Ruth C., Key, Tim J., Riboli, Elio, Park, Jong Y., Sellers, Thomas A., Lin, Hui-Yi, Albanes, Demetrius, Weinstein, Stephanie, Cook, Michael B., Mucci, Lorelei A., Giovannucci, Edward, Lindstrom, Sara, Kraft, Peter, Hunter, David J., Penney, Kathryn L., Turman, Constance, Tangen, Catherine M., Goodman, Phyllis J., Thompson, Ian M., Jr., Hamilton, Robert J., Fleshner, Neil E., Finelli, Antonio, Parent, Marie-Elise, Stanford, Janet L., Ostrander, Elaine A., Koutros, Stella, Freeman, Laura E. Beane, Stampfer, Meir, Wolk, Alicja, Hakansson, Niclas, Andriole, Gerald L., Hoover, Robert N., Machiela, Mitchell J., Sorensen, Karina Dalsgaard, Borre, Michael, Blot, William J., Zheng, Wei, Yeboah, Edward D., Mensah, James E., Lu, Yong-Jie, Zhang, Hong-Wei, Feng, Ninghan, Mao, Xueying, Wu, Yudong, Zhao, Shan-Chao, Sun, Zan, Thibodeau, Stephen N., McDonnell, Shannon K., Schaid, Daniel J., West, Catharine M. L., Barnett, Gill, Maier, Christiane, Schnoeller, Thomas, Luedeke, Manuel, Kibel, Adam S., Drake, Bettina F., Cussenot, Olivier, Cancel-Tassin, Geraldine, Menegaux, Florence, Truong, Therese, Koudou, Yves Akoli, John, Esther M., Grindedal, Eli Marie, Maehle, Lovise, Khaw, Kay-Tee, Ingles, Sue A., Stern, Mariana C., Vega, Ana, Gomez-Caamano, Antonio, Fachal, Laura, Rosenstein, Barry S., Kerns, Sarah L., Ostrer, Harry, Teixeira, Manuel R., Paulo, Paula, Brandao, Andreia, Watya, Stephen, Lubwama, Alexander, Bensen, Jeannette T., Butler, Ebonee N., Mohler, James L., Taylor, Jack A., Kogevinas, Manolis, Dierssen-Sotos, Trinidad, Castano-Vinyals, Gemma, Cannon-Albright, Lisa, Teerlink, Craig C., Huff, Chad D., Pilie, Patrick, Yu, Yao, Bohlender, Ryan J., Gu, Jian, Strom, Sara S., Multigner, Luc, Blanchet, Pascal, Brureau, Laurent, Kaneva, Radka, Slavov, Chavdar, Mitev, Vanio, Leach, Robin J., Brenner, Hermann, Chen, Xuechen, Holleczek, Bernd, Schoettker, Ben, Klein, Eric A., Hsing, Ann W., Kittles, Rick A., Murphy, Adam B., Logothetis, Christopher J., Kim, Jeri, Neuhausen, Susan L., Steele, Linda, Ding, Yuan Chun, Isaacs, William B., Nemesure, Barbara, Hennis, Anselm J. M., Carpten, John, Pandha, Hardev, Michael, Agnieszka, De Ruyck, Kim, De Meerleer, Gert, Ost, Piet, Xu, Jianfeng, Razack, Azad, Lim, Jasmine, Teo, Soo-Hwang, Newcomb, Lisa F., Lin, Daniel W., Fowke, Jay H., Neslund-Dudas, Christine M., Rybicki, Benjamin A., Gamulin, Marija, Lessel, Davor, Kulis, Tomislav, Usmani, Nawaid, Abraham, Aswin, Singhal, Sandeep, Parliament, Matthew, Claessens, Frank, Joniau, Steven, Van den Broeck, Thomas, Gago-Dominguez, Manuela, Castelao, Jose Esteban, Martinez, Maria Elena, Larkin, Samantha, Townsend, Paul A., Aukim-Hastie, Claire, Bush, William S., Aldrich, Melinda C., Crawford, Dana C., Srivastava, Shiv, Cullen, Jennifer, Petrovics, Gyorgy, Casey, Graham, Wang, Ying, Tettey, Yao, Lachance, Joseph, Tang, Wei, Biritwum, Richard B., Adjei, Andrew A., Tay, Evelyn, Truelove, Ann, Niwa, Shelley, Yamoah, Kosj, Govindasami, Koveela, Chokkalingam, Anand P., Keaton, Jacob M., Hellwege, Jacklyn N., Clark, Peter E., Jalloh, Mohamed, Gueye, Serigne M., Niang, Lamine, Ogunbiyi, Olufemi, Shittu, Olayiwola, Amodu, Olukemi, Adebiyi, Akindele O., Aisuodionoe-Shadrach, Oseremen I., Ajibola, Hafees O., Jamda, Mustapha A., Oluwole, Olabode P., Nwegbu, Maxwell, Adusei, Ben, Mante, Sunny, Darkwa-Abrahams, Afua, Diop, Halimatou, Gundell, Susan M., Roobol, Monique J., Jenster, Guido, van Schaik, Ron H. N., Hu, Jennifer J., Sanderson, Maureen, Kachuri, Linda, Varma, Rohit, McKean-Cowdin, Roberta, Torres, Mina, Preuss, Michael H., Loos, Ruth J. F., Zawistowski, Matthew, Zollner, Sebastian, Lu, Zeyun, Van Den Eeden, Stephen K., Easton, Douglas F., Ambs, Stefan, Edwards, Todd L., Magi, Reedik, Rebbeck, Timothy R., Fritsche, Lars, Chanock, Stephen J., Berndt, Sonja I., Wiklund, Fredrik, Nakagawa, Hidewaki, Witte, John S., Gaziano, J. Michael, Justice, Amy C., Mancuso, Nick, Terao, Chikashi, Eeles, Rosalind A., Kote-Jarai, Zsofia, Madduri, Ravi K., Conti, David V., and Haiman, Christopher A.
Abstract: The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
Published: 2023
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39. Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Author: Shi, Jianxin, Shiraishi, Kouya, Choi, Jiyeon, Matsuo, Keitaro, Chen, Tzu-Yu, Dai, Juncheng, Hung, Rayjean J, Chen, Kexin, Shu, Xiao-Ou, Kim, Young Tae, Landi, Maria Teresa, Lin, Dongxin, Zheng, Wei, Yin, Zhihua, Zhou, Baosen, Song, Bao, Wang, Jiucun, Seow, Wei Jie, Song, Lei, Chang, I-Shou, Hu, Wei, Chien, Li-Hsin, Cai, Qiuyin, Hong, Yun-Chul, Kim, Hee Nam, Wu, Yi-Long, Wong, Maria Pik, Richardson, Brian Douglas, Funderburk, Karen M, Li, Shilan, Zhang, Tongwu, Breeze, Charles, Wang, Zhaoming, Blechter, Batel, Bassig, Bryan A, Kim, Jin Hee, Albanes, Demetrius, Wong, Jason Y Y, Shin, Min-Ho, Chung, Lap Ping, Yang, Yang, An, She-Juan, Zheng, Hong, Yatabe, Yasushi, Zhang, Xu-Chao, Kim, Young-Chul, Caporaso, Neil E, Chang, Jiang, Ho, James Chung Man, Kubo, Michiaki, Daigo, Yataro, Song, Minsun, Momozawa, Yukihide, Kamatani, Yoichiro, Kobayashi, Masashi, Okubo, Kenichi, Honda, Takayuki, Hosgood, Dean H, Kunitoh, Hideo, Patel, Harsh, Watanabe, Shun-Ichi, Miyagi, Yohei, Nakayama, Haruhiko, Matsumoto, Shingo, Horinouchi, Hidehito, Tsuboi, Masahiro, Hamamoto, Ryuji, Goto, Koichi, Ohe, Yuichiro, Takahashi, Atsushi, Goto, Akiteru, Minamiya, Yoshihiro, Hara, Megumi, Nishida, Yuichiro, Takeuchi, Kenji, Wakai, Kenji, Matsuda, Koichi, Murakami, Yoshinori, Shimizu, Kimihiro, Suzuki, Hiroyuki, Saito, Motonobu, Ohtaki, Yoichi, Tanaka, Kazumi, Wu, Tangchun, Wei, Fusheng, Dai, Hongji, Machiela, Mitchell J, Su, Jian, Kim, Yeul Hong, Oh, In-Jae, Lee, Victor Ho Fun, Chang, Gee-Chen, Tsai, Ying-Huang, Chen, Kuan-Yu, Huang, Ming-Shyan, Su, Wu-Chou, Chen, Yuh-Min, Seow, Adeline, Park, Jae Yong, Kweon, Sun-Seog, Chen, Kun-Chieh, Gao, Yu-Tang, Qian, Biyun, Wu, Chen, Lu, Daru, Liu, Jianjun, Schwartz, Ann G, Houlston, Richard, Spitz, Margaret R, Gorlov, Ivan P, Wu, Xifeng, Yang, Ping, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E, Johansson, Mattias, Risch, Angela, Bickeböller, Heike, Ji, Bu-Tian, Wichmann, H-Erich, Christiani, David C, Rennert, Gadi, Arnold, Susanne, Brennan, Paul, McKay, James, Field, John K, Shete, Sanjay S, Le Marchand, Loic, Liu, Geoffrey, Andrew, Angeline, Kiemeney, Lambertus A, Zienolddiny-Narui, Shan, Grankvist, Kjell, Johansson, Mikael, Cox, Angela, Taylor, Fiona, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B, Aldrich, Melinda C, Jeon, Hyo-Sung, Jiang, Shih Sheng, Sung, Jae Sook, Chen, Chung-Hsing, Hsiao, Chin-Fu, Jung, Yoo Jin, Guo, Huan, Hu, Zhibin, Burdett, Laurie, Yeager, Meredith, Hutchinson, Amy, Hicks, Belynda, Liu, Jia, Zhu, Bin, Berndt, Sonja I, Wu, Wei, Wang, Junwen, Li, Yuqing, Choi, Jin Eun, Park, Kyong Hwa, Sung, Sook Whan, Liu, Li, Kang, Chang Hyun, Wang, Wen-Chang, Xu, Jun, Guan, Peng, Tan, Wen, Yu, Chong-Jen, Yang, Gong, Sihoe, Alan Dart Loon, Chen, Ying, Choi, Yi Young, Kim, Jun Suk, Yoon, Ho-Il, Park, In Kyu, Xu, Ping, He, Qincheng, Wang, Chih-Liang, Hung, Hsiao-Han, Vermeulen, Roel C H, Cheng, Iona, Wu, Junjie, Lim, Wei-Yen, Tsai, Fang-Yu, Chan, John K C, Li, Jihua, Chen, Hongyan, Lin, Hsien-Chih, Jin, Li, Liu, Jie, Sawada, Norie, Yamaji, Taiki, Wyatt, Kathleen, Li, Shengchao A, Ma, Hongxia, Zhu, Meng, Wang, Zhehai, Cheng, Sensen, Li, Xuelian, Ren, Yangwu, Chao, Ann, Iwasaki, Motoki, Zhu, Junjie, Jiang, Gening, Fei, Ke, Wu, Guoping, Chen, Chih-Yi, Chen, Chien-Jen, Yang, Pan-Chyr, Yu, Jinming, Stevens, Victoria L, Fraumeni, Joseph F, Chatterjee, Nilanjan, Gorlova, Olga Y, Hsiung, Chao Agnes, Amos, Christopher I, Shen, Hongbing, Chanock, Stephen J, Rothman, Nathaniel, Kohno, Takashi, Lan, Qing, Shi, Jianxin, Shiraishi, Kouya, Choi, Jiyeon, Matsuo, Keitaro, Chen, Tzu-Yu, Dai, Juncheng, Hung, Rayjean J, Chen, Kexin, Shu, Xiao-Ou, Kim, Young Tae, Landi, Maria Teresa, Lin, Dongxin, Zheng, Wei, Yin, Zhihua, Zhou, Baosen, Song, Bao, Wang, Jiucun, Seow, Wei Jie, Song, Lei, Chang, I-Shou, Hu, Wei, Chien, Li-Hsin, Cai, Qiuyin, Hong, Yun-Chul, Kim, Hee Nam, Wu, Yi-Long, Wong, Maria Pik, Richardson, Brian Douglas, Funderburk, Karen M, Li, Shilan, Zhang, Tongwu, Breeze, Charles, Wang, Zhaoming, Blechter, Batel, Bassig, Bryan A, Kim, Jin Hee, Albanes, Demetrius, Wong, Jason Y Y, Shin, Min-Ho, Chung, Lap Ping, Yang, Yang, An, She-Juan, Zheng, Hong, Yatabe, Yasushi, Zhang, Xu-Chao, Kim, Young-Chul, Caporaso, Neil E, Chang, Jiang, Ho, James Chung Man, Kubo, Michiaki, Daigo, Yataro, Song, Minsun, Momozawa, Yukihide, Kamatani, Yoichiro, Kobayashi, Masashi, Okubo, Kenichi, Honda, Takayuki, Hosgood, Dean H, Kunitoh, Hideo, Patel, Harsh, Watanabe, Shun-Ichi, Miyagi, Yohei, Nakayama, Haruhiko, Matsumoto, Shingo, Horinouchi, Hidehito, Tsuboi, Masahiro, Hamamoto, Ryuji, Goto, Koichi, Ohe, Yuichiro, Takahashi, Atsushi, Goto, Akiteru, Minamiya, Yoshihiro, Hara, Megumi, Nishida, Yuichiro, Takeuchi, Kenji, Wakai, Kenji, Matsuda, Koichi, Murakami, Yoshinori, Shimizu, Kimihiro, Suzuki, Hiroyuki, Saito, Motonobu, Ohtaki, Yoichi, Tanaka, Kazumi, Wu, Tangchun, Wei, Fusheng, Dai, Hongji, Machiela, Mitchell J, Su, Jian, Kim, Yeul Hong, Oh, In-Jae, Lee, Victor Ho Fun, Chang, Gee-Chen, Tsai, Ying-Huang, Chen, Kuan-Yu, Huang, Ming-Shyan, Su, Wu-Chou, Chen, Yuh-Min, Seow, Adeline, Park, Jae Yong, Kweon, Sun-Seog, Chen, Kun-Chieh, Gao, Yu-Tang, Qian, Biyun, Wu, Chen, Lu, Daru, Liu, Jianjun, Schwartz, Ann G, Houlston, Richard, Spitz, Margaret R, Gorlov, Ivan P, Wu, Xifeng, Yang, Ping, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E, Johansson, Mattias, Risch, Angela, Bickeböller, Heike, Ji, Bu-Tian, Wichmann, H-Erich, Christiani, David C, Rennert, Gadi, Arnold, Susanne, Brennan, Paul, McKay, James, Field, John K, Shete, Sanjay S, Le Marchand, Loic, Liu, Geoffrey, Andrew, Angeline, Kiemeney, Lambertus A, Zienolddiny-Narui, Shan, Grankvist, Kjell, Johansson, Mikael, Cox, Angela, Taylor, Fiona, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B, Aldrich, Melinda C, Jeon, Hyo-Sung, Jiang, Shih Sheng, Sung, Jae Sook, Chen, Chung-Hsing, Hsiao, Chin-Fu, Jung, Yoo Jin, Guo, Huan, Hu, Zhibin, Burdett, Laurie, Yeager, Meredith, Hutchinson, Amy, Hicks, Belynda, Liu, Jia, Zhu, Bin, Berndt, Sonja I, Wu, Wei, Wang, Junwen, Li, Yuqing, Choi, Jin Eun, Park, Kyong Hwa, Sung, Sook Whan, Liu, Li, Kang, Chang Hyun, Wang, Wen-Chang, Xu, Jun, Guan, Peng, Tan, Wen, Yu, Chong-Jen, Yang, Gong, Sihoe, Alan Dart Loon, Chen, Ying, Choi, Yi Young, Kim, Jun Suk, Yoon, Ho-Il, Park, In Kyu, Xu, Ping, He, Qincheng, Wang, Chih-Liang, Hung, Hsiao-Han, Vermeulen, Roel C H, Cheng, Iona, Wu, Junjie, Lim, Wei-Yen, Tsai, Fang-Yu, Chan, John K C, Li, Jihua, Chen, Hongyan, Lin, Hsien-Chih, Jin, Li, Liu, Jie, Sawada, Norie, Yamaji, Taiki, Wyatt, Kathleen, Li, Shengchao A, Ma, Hongxia, Zhu, Meng, Wang, Zhehai, Cheng, Sensen, Li, Xuelian, Ren, Yangwu, Chao, Ann, Iwasaki, Motoki, Zhu, Junjie, Jiang, Gening, Fei, Ke, Wu, Guoping, Chen, Chih-Yi, Chen, Chien-Jen, Yang, Pan-Chyr, Yu, Jinming, Stevens, Victoria L, Fraumeni, Joseph F, Chatterjee, Nilanjan, Gorlova, Olga Y, Hsiung, Chao Agnes, Amos, Christopher I, Shen, Hongbing, Chanock, Stephen J, Rothman, Nathaniel, Kohno, Takashi, and Lan, Qing
Abstract: Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (P interaction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.
Published: 2023

40. Impact of input dataset size and fine-tuning on faster R-CNN with transfer learning

Author: Tartu Ülikool, Cabral Pinheiro, Victor Henrique, Björklund, Tomas, Zheng, Wei, Tartu Ülikool, Cabral Pinheiro, Victor Henrique, Björklund, Tomas, and Zheng, Wei
Abstract: Deep learning models are widely used for machine learning tasks such as object detection. The lack of available data to train these models is a common hindrance in many industrial applications, where data gathering/annotation and insufficient computational resources often impose a barrier to the financial feasibility of deep learning implementations. Transfer learning is a possible answer to this challenge by exploiting the information learned by a model from data in a different domain than that of the target dataset. This technique has been typically applied on the backbone network of a two-stage object detection pipeline. In this work, we investigate the association between the input dataset size and the proportion of trainable layers in the backbone. In particular, we show some interesting findings on Faster R-CNN ResNet-50 FPN, a state-of-the-art object detection model, and MS COCO, a benchmarking dataset. The outcomes of our experiments indicate that, although a model generally performs better when trained with more layers fine-tuned to the training data, such an advantage reduces as the input dataset becomes smaller, as unfreezing too many layers can even lead to a severe overfitting problem. Choosing the right number of layers to freeze when applying transfer learning not only allows the model to reach its best possible performance but also saves computational resources and training time. Additionally, we explore the association between the effect of learning rate decay and the input dataset size, and also discuss the advantage of using pre-trained weights when compared to training a network from scratch.
Published: 2023

41. Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Author: IRAS OH Epidemiology Chemical Agents, Shi, Jianxin, Shiraishi, Kouya, Choi, Jiyeon, Matsuo, Keitaro, Chen, Tzu-Yu, Dai, Juncheng, Hung, Rayjean J, Chen, Kexin, Shu, Xiao-Ou, Kim, Young Tae, Landi, Maria Teresa, Lin, Dongxin, Zheng, Wei, Yin, Zhihua, Zhou, Baosen, Song, Bao, Wang, Jiucun, Seow, Wei Jie, Song, Lei, Chang, I-Shou, Hu, Wei, Chien, Li-Hsin, Cai, Qiuyin, Hong, Yun-Chul, Kim, Hee Nam, Wu, Yi-Long, Wong, Maria Pik, Richardson, Brian Douglas, Funderburk, Karen M, Li, Shilan, Zhang, Tongwu, Breeze, Charles, Wang, Zhaoming, Blechter, Batel, Bassig, Bryan A, Kim, Jin Hee, Albanes, Demetrius, Wong, Jason Y Y, Shin, Min-Ho, Chung, Lap Ping, Yang, Yang, An, She-Juan, Zheng, Hong, Yatabe, Yasushi, Zhang, Xu-Chao, Kim, Young-Chul, Caporaso, Neil E, Chang, Jiang, Ho, James Chung Man, Kubo, Michiaki, Daigo, Yataro, Song, Minsun, Momozawa, Yukihide, Kamatani, Yoichiro, Kobayashi, Masashi, Okubo, Kenichi, Honda, Takayuki, Hosgood, Dean H, Kunitoh, Hideo, Patel, Harsh, Watanabe, Shun-Ichi, Miyagi, Yohei, Nakayama, Haruhiko, Matsumoto, Shingo, Horinouchi, Hidehito, Tsuboi, Masahiro, Hamamoto, Ryuji, Goto, Koichi, Ohe, Yuichiro, Takahashi, Atsushi, Goto, Akiteru, Minamiya, Yoshihiro, Hara, Megumi, Nishida, Yuichiro, Takeuchi, Kenji, Wakai, Kenji, Matsuda, Koichi, Murakami, Yoshinori, Shimizu, Kimihiro, Suzuki, Hiroyuki, Saito, Motonobu, Ohtaki, Yoichi, Tanaka, Kazumi, Wu, Tangchun, Wei, Fusheng, Dai, Hongji, Machiela, Mitchell J, Su, Jian, Kim, Yeul Hong, Oh, In-Jae, Lee, Victor Ho Fun, Chang, Gee-Chen, Tsai, Ying-Huang, Chen, Kuan-Yu, Huang, Ming-Shyan, Su, Wu-Chou, Chen, Yuh-Min, Seow, Adeline, Park, Jae Yong, Kweon, Sun-Seog, Chen, Kun-Chieh, Gao, Yu-Tang, Qian, Biyun, Wu, Chen, Lu, Daru, Liu, Jianjun, Schwartz, Ann G, Houlston, Richard, Spitz, Margaret R, Gorlov, Ivan P, Wu, Xifeng, Yang, Ping, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E, Johansson, Mattias, Risch, Angela, Bickeböller, Heike, Ji, Bu-Tian, Wichmann, H-Erich, Christiani, David C, Rennert, Gadi, Arnold, Susanne, Brennan, Paul, McKay, James, Field, John K, Shete, Sanjay S, Le Marchand, Loic, Liu, Geoffrey, Andrew, Angeline, Kiemeney, Lambertus A, Zienolddiny-Narui, Shan, Grankvist, Kjell, Johansson, Mikael, Cox, Angela, Taylor, Fiona, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B, Aldrich, Melinda C, Jeon, Hyo-Sung, Jiang, Shih Sheng, Sung, Jae Sook, Chen, Chung-Hsing, Hsiao, Chin-Fu, Jung, Yoo Jin, Guo, Huan, Hu, Zhibin, Burdett, Laurie, Yeager, Meredith, Hutchinson, Amy, Hicks, Belynda, Liu, Jia, Zhu, Bin, Berndt, Sonja I, Wu, Wei, Wang, Junwen, Li, Yuqing, Choi, Jin Eun, Park, Kyong Hwa, Sung, Sook Whan, Liu, Li, Kang, Chang Hyun, Wang, Wen-Chang, Xu, Jun, Guan, Peng, Tan, Wen, Yu, Chong-Jen, Yang, Gong, Sihoe, Alan Dart Loon, Chen, Ying, Choi, Yi Young, Kim, Jun Suk, Yoon, Ho-Il, Park, In Kyu, Xu, Ping, He, Qincheng, Wang, Chih-Liang, Hung, Hsiao-Han, Vermeulen, Roel C H, Cheng, Iona, Wu, Junjie, Lim, Wei-Yen, Tsai, Fang-Yu, Chan, John K C, Li, Jihua, Chen, Hongyan, Lin, Hsien-Chih, Jin, Li, Liu, Jie, Sawada, Norie, Yamaji, Taiki, Wyatt, Kathleen, Li, Shengchao A, Ma, Hongxia, Zhu, Meng, Wang, Zhehai, Cheng, Sensen, Li, Xuelian, Ren, Yangwu, Chao, Ann, Iwasaki, Motoki, Zhu, Junjie, Jiang, Gening, Fei, Ke, Wu, Guoping, Chen, Chih-Yi, Chen, Chien-Jen, Yang, Pan-Chyr, Yu, Jinming, Stevens, Victoria L, Fraumeni, Joseph F, Chatterjee, Nilanjan, Gorlova, Olga Y, Hsiung, Chao Agnes, Amos, Christopher I, Shen, Hongbing, Chanock, Stephen J, Rothman, Nathaniel, Kohno, Takashi, Lan, Qing, IRAS OH Epidemiology Chemical Agents, Shi, Jianxin, Shiraishi, Kouya, Choi, Jiyeon, Matsuo, Keitaro, Chen, Tzu-Yu, Dai, Juncheng, Hung, Rayjean J, Chen, Kexin, Shu, Xiao-Ou, Kim, Young Tae, Landi, Maria Teresa, Lin, Dongxin, Zheng, Wei, Yin, Zhihua, Zhou, Baosen, Song, Bao, Wang, Jiucun, Seow, Wei Jie, Song, Lei, Chang, I-Shou, Hu, Wei, Chien, Li-Hsin, Cai, Qiuyin, Hong, Yun-Chul, Kim, Hee Nam, Wu, Yi-Long, Wong, Maria Pik, Richardson, Brian Douglas, Funderburk, Karen M, Li, Shilan, Zhang, Tongwu, Breeze, Charles, Wang, Zhaoming, Blechter, Batel, Bassig, Bryan A, Kim, Jin Hee, Albanes, Demetrius, Wong, Jason Y Y, Shin, Min-Ho, Chung, Lap Ping, Yang, Yang, An, She-Juan, Zheng, Hong, Yatabe, Yasushi, Zhang, Xu-Chao, Kim, Young-Chul, Caporaso, Neil E, Chang, Jiang, Ho, James Chung Man, Kubo, Michiaki, Daigo, Yataro, Song, Minsun, Momozawa, Yukihide, Kamatani, Yoichiro, Kobayashi, Masashi, Okubo, Kenichi, Honda, Takayuki, Hosgood, Dean H, Kunitoh, Hideo, Patel, Harsh, Watanabe, Shun-Ichi, Miyagi, Yohei, Nakayama, Haruhiko, Matsumoto, Shingo, Horinouchi, Hidehito, Tsuboi, Masahiro, Hamamoto, Ryuji, Goto, Koichi, Ohe, Yuichiro, Takahashi, Atsushi, Goto, Akiteru, Minamiya, Yoshihiro, Hara, Megumi, Nishida, Yuichiro, Takeuchi, Kenji, Wakai, Kenji, Matsuda, Koichi, Murakami, Yoshinori, Shimizu, Kimihiro, Suzuki, Hiroyuki, Saito, Motonobu, Ohtaki, Yoichi, Tanaka, Kazumi, Wu, Tangchun, Wei, Fusheng, Dai, Hongji, Machiela, Mitchell J, Su, Jian, Kim, Yeul Hong, Oh, In-Jae, Lee, Victor Ho Fun, Chang, Gee-Chen, Tsai, Ying-Huang, Chen, Kuan-Yu, Huang, Ming-Shyan, Su, Wu-Chou, Chen, Yuh-Min, Seow, Adeline, Park, Jae Yong, Kweon, Sun-Seog, Chen, Kun-Chieh, Gao, Yu-Tang, Qian, Biyun, Wu, Chen, Lu, Daru, Liu, Jianjun, Schwartz, Ann G, Houlston, Richard, Spitz, Margaret R, Gorlov, Ivan P, Wu, Xifeng, Yang, Ping, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E, Johansson, Mattias, Risch, Angela, Bickeböller, Heike, Ji, Bu-Tian, Wichmann, H-Erich, Christiani, David C, Rennert, Gadi, Arnold, Susanne, Brennan, Paul, McKay, James, Field, John K, Shete, Sanjay S, Le Marchand, Loic, Liu, Geoffrey, Andrew, Angeline, Kiemeney, Lambertus A, Zienolddiny-Narui, Shan, Grankvist, Kjell, Johansson, Mikael, Cox, Angela, Taylor, Fiona, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B, Aldrich, Melinda C, Jeon, Hyo-Sung, Jiang, Shih Sheng, Sung, Jae Sook, Chen, Chung-Hsing, Hsiao, Chin-Fu, Jung, Yoo Jin, Guo, Huan, Hu, Zhibin, Burdett, Laurie, Yeager, Meredith, Hutchinson, Amy, Hicks, Belynda, Liu, Jia, Zhu, Bin, Berndt, Sonja I, Wu, Wei, Wang, Junwen, Li, Yuqing, Choi, Jin Eun, Park, Kyong Hwa, Sung, Sook Whan, Liu, Li, Kang, Chang Hyun, Wang, Wen-Chang, Xu, Jun, Guan, Peng, Tan, Wen, Yu, Chong-Jen, Yang, Gong, Sihoe, Alan Dart Loon, Chen, Ying, Choi, Yi Young, Kim, Jun Suk, Yoon, Ho-Il, Park, In Kyu, Xu, Ping, He, Qincheng, Wang, Chih-Liang, Hung, Hsiao-Han, Vermeulen, Roel C H, Cheng, Iona, Wu, Junjie, Lim, Wei-Yen, Tsai, Fang-Yu, Chan, John K C, Li, Jihua, Chen, Hongyan, Lin, Hsien-Chih, Jin, Li, Liu, Jie, Sawada, Norie, Yamaji, Taiki, Wyatt, Kathleen, Li, Shengchao A, Ma, Hongxia, Zhu, Meng, Wang, Zhehai, Cheng, Sensen, Li, Xuelian, Ren, Yangwu, Chao, Ann, Iwasaki, Motoki, Zhu, Junjie, Jiang, Gening, Fei, Ke, Wu, Guoping, Chen, Chih-Yi, Chen, Chien-Jen, Yang, Pan-Chyr, Yu, Jinming, Stevens, Victoria L, Fraumeni, Joseph F, Chatterjee, Nilanjan, Gorlova, Olga Y, Hsiung, Chao Agnes, Amos, Christopher I, Shen, Hongbing, Chanock, Stephen J, Rothman, Nathaniel, Kohno, Takashi, and Lan, Qing
Published: 2023

42. Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

Author: Mueller, Stefanie H., Lai, Alvina G., Valkovskaya, Maria, Michailidou, Kyriaki, Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Lush, Michael, Abu-Ful, Zomoruda, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Antonenkova, Natalia N., Arndt, Volker, Aronson, Kristan J., Augustinsson, Annelie, Baert, Thais, Freeman, Laura E. Beane, Beckmann, Matthias W., Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Bogdanova, Natalia, V, Bojesen, Stig E., Bonanni, Bernardo, Brenner, Hermann, Brucker, Sara Y., Buys, Saundra S., Castelao, Jose E., Chan, Tsun L., Chang-Claude, Jenny, Chanock, Stephen J., Choi, Ji-Yeob, Chung, Wendy K., Colonna, Sarah, V, Cornelissen, Sten, Couch, Fergus J., Czene, Kamila, Daly, Mary B., Devilee, Peter, Dork, Thilo, Dossus, Laure, Dwek, Miriam, Eccles, Diana M., Ekici, Arif B., Eliassen, A. Heather, Engel, Christoph, Evans, D. Gareth, Fasching, Peter A., Fletcher, Olivia, Flyger, Henrik, Gago-Dominguez, Manuela, Gao, Yu-Tang, Garcia-Closas, Montserrat, Garcia-Saenz, Jose A., Genkinger, Jeanine, Gentry-Maharaj, Aleksandra, Grassmann, Felix, Guenel, Pascal, Gundert, Melanie, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A., Hakansson, Niclas, Hall, Per, Harkness, Elaine F., Harrington, Patricia A., Hartikainen, Jaana M., Hartman, Mikael, Hein, Alexander, Ho, Weang-Kee, Hooning, Maartje J., Hoppe, Reiner, Hopper, John L., Houlston, Richard S., Howell, Anthony, Hunter, David J., Huo, Dezheng, Investigators, Abctb, Ito, Hidemi, Iwasaki, Motoki, Jakubowska, Anna, Janni, Wolfgang, John, Esther M., Jones, Michael E., Jung, Audrey, Kaaks, Rudolf, Kang, Daehee, Khusnutdinova, Elza K., Kim, Sung-Won, Kitahara, Cari M., Koutros, Stella, Kraft, Peter, Kristensen, Vessela N., Kubelka-Sabit, Katerina, Kurian, Allison W., Kwong, Ava, Lacey, James, V, Lambrechts, Diether, Le Marchand, Loic, Li, Jingmei, Linet, Martha, Lo, Wing-Yee, Long, Jirong, Lophatananon, Artitaya, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Matsuo, Keitaro, Mavroudis, Dimitrios, Menon, Usha, Muir, Kenneth, Murphy, Rachel A., Nevanlinna, Heli, Newman, William G., Niederacher, Dieter, O'Brien, Katie M., Obi, Nadia, Offit, Kenneth, Olopade, Olufunmilayo, I, Olshan, Andrew F., Olsson, Hakan, Park, Sue K., Patel, Alpa, V, Patel, Achal, Perou, Charles M., Peto, Julian, Pharoah, Paul D. P., Plaseska-Karanfilska, Dijana, Presneau, Nadege, Rack, Brigitte, Radice, Paolo, Ramachandran, Dhanya, Rashid, Muhammad U., Rennert, Gad, Romero, Atocha, Ruddy, Kathryn J., Ruebner, Matthias, Saloustros, Emmanouil, Sandler, Dale P., Sawyer, Elinor J., Schmidt, Marjanka K., Schmutzler, Rita K., Schneider, Michael O., Scott, Christopher, Shah, Mitul, Sharma, Priyanka, Shen, Chen-Yang, Shu, Xiao-Ou, Simard, Jacques, Surowy, Harald, Tamimi, Rulla M., Tapper, William J., Taylor, Jack A., Teo, Soo Hwang, Teras, Lauren R., Toland, Amanda E., Tollenaar, Rob A. E. M., Torres, Diana, Torres-Mejia, Gabriela, Troester, Melissa A., Truong, Therese, Vachon, Celine M., Vijai, Joseph, Weinberg, Clarice R., Wendt, Camilla, Winqvist, Robert, Wolk, Alicja, Wu, Anna H., Yamaji, Taiki, Yang, Xiaohong R., Yu, Jyh-Cherng, Zheng, Wei, Ziogas, Argyrios, Ziv, Elad, Dunning, Alison M., Easton, Douglas F., Hemingway, Harry, Hamann, Ute, Kuchenbaecker, Karoline B., Mueller, Stefanie H., Lai, Alvina G., Valkovskaya, Maria, Michailidou, Kyriaki, Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Lush, Michael, Abu-Ful, Zomoruda, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Antonenkova, Natalia N., Arndt, Volker, Aronson, Kristan J., Augustinsson, Annelie, Baert, Thais, Freeman, Laura E. Beane, Beckmann, Matthias W., Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Bogdanova, Natalia, V, Bojesen, Stig E., Bonanni, Bernardo, Brenner, Hermann, Brucker, Sara Y., Buys, Saundra S., Castelao, Jose E., Chan, Tsun L., Chang-Claude, Jenny, Chanock, Stephen J., Choi, Ji-Yeob, Chung, Wendy K., Colonna, Sarah, V, Cornelissen, Sten, Couch, Fergus J., Czene, Kamila, Daly, Mary B., Devilee, Peter, Dork, Thilo, Dossus, Laure, Dwek, Miriam, Eccles, Diana M., Ekici, Arif B., Eliassen, A. Heather, Engel, Christoph, Evans, D. Gareth, Fasching, Peter A., Fletcher, Olivia, Flyger, Henrik, Gago-Dominguez, Manuela, Gao, Yu-Tang, Garcia-Closas, Montserrat, Garcia-Saenz, Jose A., Genkinger, Jeanine, Gentry-Maharaj, Aleksandra, Grassmann, Felix, Guenel, Pascal, Gundert, Melanie, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A., Hakansson, Niclas, Hall, Per, Harkness, Elaine F., Harrington, Patricia A., Hartikainen, Jaana M., Hartman, Mikael, Hein, Alexander, Ho, Weang-Kee, Hooning, Maartje J., Hoppe, Reiner, Hopper, John L., Houlston, Richard S., Howell, Anthony, Hunter, David J., Huo, Dezheng, Investigators, Abctb, Ito, Hidemi, Iwasaki, Motoki, Jakubowska, Anna, Janni, Wolfgang, John, Esther M., Jones, Michael E., Jung, Audrey, Kaaks, Rudolf, Kang, Daehee, Khusnutdinova, Elza K., Kim, Sung-Won, Kitahara, Cari M., Koutros, Stella, Kraft, Peter, Kristensen, Vessela N., Kubelka-Sabit, Katerina, Kurian, Allison W., Kwong, Ava, Lacey, James, V, Lambrechts, Diether, Le Marchand, Loic, Li, Jingmei, Linet, Martha, Lo, Wing-Yee, Long, Jirong, Lophatananon, Artitaya, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Matsuo, Keitaro, Mavroudis, Dimitrios, Menon, Usha, Muir, Kenneth, Murphy, Rachel A., Nevanlinna, Heli, Newman, William G., Niederacher, Dieter, O'Brien, Katie M., Obi, Nadia, Offit, Kenneth, Olopade, Olufunmilayo, I, Olshan, Andrew F., Olsson, Hakan, Park, Sue K., Patel, Alpa, V, Patel, Achal, Perou, Charles M., Peto, Julian, Pharoah, Paul D. P., Plaseska-Karanfilska, Dijana, Presneau, Nadege, Rack, Brigitte, Radice, Paolo, Ramachandran, Dhanya, Rashid, Muhammad U., Rennert, Gad, Romero, Atocha, Ruddy, Kathryn J., Ruebner, Matthias, Saloustros, Emmanouil, Sandler, Dale P., Sawyer, Elinor J., Schmidt, Marjanka K., Schmutzler, Rita K., Schneider, Michael O., Scott, Christopher, Shah, Mitul, Sharma, Priyanka, Shen, Chen-Yang, Shu, Xiao-Ou, Simard, Jacques, Surowy, Harald, Tamimi, Rulla M., Tapper, William J., Taylor, Jack A., Teo, Soo Hwang, Teras, Lauren R., Toland, Amanda E., Tollenaar, Rob A. E. M., Torres, Diana, Torres-Mejia, Gabriela, Troester, Melissa A., Truong, Therese, Vachon, Celine M., Vijai, Joseph, Weinberg, Clarice R., Wendt, Camilla, Winqvist, Robert, Wolk, Alicja, Wu, Anna H., Yamaji, Taiki, Yang, Xiaohong R., Yu, Jyh-Cherng, Zheng, Wei, Ziogas, Argyrios, Ziv, Elad, Dunning, Alison M., Easton, Douglas F., Hemingway, Harry, Hamann, Ute, and Kuchenbaecker, Karoline B.
Abstract: Background: Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes. Methods: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry. Results: In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 x 10(-6)) and AC058822.1 (P = 1.47 x 10(-4)), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C. Conclusions: Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 x 10(-5)), demonstrating the importance of diversifying study cohorts.
Published: 2023
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43. Design and methodological considerations for biomarker discovery and validation in the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Program

Author: Robbins, Hilary A., Alcala, Karine, Moez, Elham Khodayari, Guida, Florence, Thomas, Sera, Zahed, Hana, Warkentin, Matthew T., Smith-Byrne, Karl, Brhane, Yonathan, Muller, David, Feng, Xiaoshuang, Albanes, Demetrius, Aldrich, Melinda C., Arslan, Alan A., Bassett, Julie, Berg, Christine D., Cai, Qiuyin, Chen, Chu, Davies, Michael P.A., Diergaarde, Brenda, Field, John K., Freedman, Neal D., Huang, Wen-Yi, Johansson, Mikael, Jones, Michael, Koh, Woon-Puay, Lam, Stephen, Lan, Qing, Langhammer, Arnulf, Liao, Linda M., Liu, Geoffrey, Malekzadeh, Reza, Milne, Roger L., Montuenga, Luis M., Rohan, Thomas, Sesso, Howard D., Severi, Gianluca, Sheikh, Mahdi, Sinha, Rashmi, Shu, Xiao-Ou, Stevens, Victoria L., Tammemägi, Martin C., Tinker, Lesley F., Visvanathan, Kala, Wang, Ying, Wang, Renwei, Weinstein, Stephanie J., White, Emily, Wilson, David, Yuan, Jian-Min, Zhang, Xuehong, Zheng, Wei, Amos, Christopher I., Brennan, Paul, Johansson, Mattias, Hung, Rayjean J., Robbins, Hilary A., Alcala, Karine, Moez, Elham Khodayari, Guida, Florence, Thomas, Sera, Zahed, Hana, Warkentin, Matthew T., Smith-Byrne, Karl, Brhane, Yonathan, Muller, David, Feng, Xiaoshuang, Albanes, Demetrius, Aldrich, Melinda C., Arslan, Alan A., Bassett, Julie, Berg, Christine D., Cai, Qiuyin, Chen, Chu, Davies, Michael P.A., Diergaarde, Brenda, Field, John K., Freedman, Neal D., Huang, Wen-Yi, Johansson, Mikael, Jones, Michael, Koh, Woon-Puay, Lam, Stephen, Lan, Qing, Langhammer, Arnulf, Liao, Linda M., Liu, Geoffrey, Malekzadeh, Reza, Milne, Roger L., Montuenga, Luis M., Rohan, Thomas, Sesso, Howard D., Severi, Gianluca, Sheikh, Mahdi, Sinha, Rashmi, Shu, Xiao-Ou, Stevens, Victoria L., Tammemägi, Martin C., Tinker, Lesley F., Visvanathan, Kala, Wang, Ying, Wang, Renwei, Weinstein, Stephanie J., White, Emily, Wilson, David, Yuan, Jian-Min, Zhang, Xuehong, Zheng, Wei, Amos, Christopher I., Brennan, Paul, Johansson, Mattias, and Hung, Rayjean J.
Abstract: The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize low-dose CT (LDCT) lung cancer screening. Here, we describe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1161 proteins in a nested-case control study within 2 prospective cohorts (n = 252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n = 479 cases and 479 controls). Eligible participants had a current or former history of smoking and cases were diagnosed up to 3 years following blood draw. The Nodule Malignancy project measured 1078 proteins among participants with a heavy smoking history within four LDCT screening studies (n = 425 cases diagnosed up to 5 years following blood draw, 430 benign-nodule controls, and 398 nodule-free controls). The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its performance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n = 1696 cases and 2926 subcohort representatives), and in the Nodule Malignancy project within five LDCT screening studies (n = 675 cases, 680 benign-nodule controls, and 648 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies.
Published: 2023
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44. A Highly Reversible Aqueous Ammonium-Ion Battery based on alpha-MoO3/Ti3C2Tz Anodes and (NH4)(x)MnO2/CNTs Cathodes

Author: Yang, Li, Zheng, Wei, Halim, Joseph, Rosén, Johanna, Sun, ZhengMing, Barsoum, Michel, Yang, Li, Zheng, Wei, Halim, Joseph, Rosén, Johanna, Sun, ZhengMing, and Barsoum, Michel
Abstract: Aqueous ammonium-ion batteries (AAIBs) are appealing due to their relatively low cost and good rate performance. In general, AAIBs are environmentally friendlier than their non-aqueous counterparts. However, it is still a challenge to achieve highly reversible AAIBs with decent voltages and energy/power densities. Herein, we report on a full-cell configuration using alpha-MoO3/Ti3C2Tz films as anodes, and (NH4)(x)MnO2/CNTs films as cathodes in a 1 M ammonium acetate (NH4Ac) electrolyte. At 2 V, the operating cell voltage, OCV, is one of the highest reported for AAIBs. A maximum energy density of similar to 32 Wh kg(-1) (similar to 54 Wh L-1) at 0.2 A g(-1) and a maximum power density of similar to 10 kW kg(-1) (similar to 17 kW L-1) at 10 A g(-1) are attained. When the full cells are cycled 2,000 times at 1 A g(-1) they retain similar to 73 % of their initial capacity. When cycling at 10 A g(-1), similar to 96 % of capacity is retained after 43,500 cycles. After 10 h, self-discharge reduces the OCV to similar to 72 % of its original value. This work provides a roadmap for developing high performance AAIBs with high voltages and high energy/power densities. Before this is possible it is imperative that the self-discharge rate be substantially reduced., Funding Agencies|Knut and Alice Wallenberg (KAW) Foundation for a Fellowship/Scholar Grant [KAW 2020.0033]; China Postdoctoral Science Foundation [2020TQ0063, 2021M700759]; Jiangsu Planned Projects for Postdoctoral Research Funds; Fundamental Research Funds for the Central Universities; Zhishan Youth Scholar Program of Southeast University
Published: 2023
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45. Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries

Author: Fernandez-Rozadilla, Ceres, Timofeeva, Maria, Chen, Zhishan, Law, Philip, Thomas, Minta, Schmit, Stephanie, Díez-Obrero, Virginia, Hsu, Li, Fernandez-Tajes, Juan, Palles, Claire, Sherwood, Kitty, Briggs, Sarah, Svinti, Victoria, Donnelly, Kevin, Farrington, Susan, Blackmur, James, Vaughan-Shaw, Peter, Shu, Xiao-ou, Long, Jirong, Cai, Qiuyin, Guo, Xingyi, Lu, Yingchang, Broderick, Peter, Studd, James, Huyghe, Jeroen, Harrison, Tabitha, Conti, David, Dampier, Christopher, Devall, Mathew, Schumacher, Fredrick, Melas, Marilena, Rennert, Gad, Obón-Santacana, Mireia, Martín-Sánchez, Vicente, Moratalla-Navarro, Ferran, Oh, Jae Hwan, Kim, Jeongseon, Jee, Sun Ha, Jung, Keum Ji, Kweon, Sun-Seog, Shin, Min-Ho, Shin, Aesun, Ahn, Yoon-Ok, Kim, Dong-Hyun, Oze, Isao, Wen, Wanqing, Matsuo, Keitaro, Matsuda, Koichi, Tanikawa, Chizu, Ren, Zefang, Gao, Yu-Tang, Jia, Wei-Hua, Hopper, John, Jenkins, Mark, Win, Aung Ko, Pai, Rish, Figueiredo, Jane, Haile, Robert, Gallinger, Steven, Woods, Michael, Newcomb, Polly, Duggan, David, Cheadle, Jeremy, Kaplan, Richard, Maughan, Timothy, Kerr, Rachel, Kerr, David, Kirac, Iva, Böhm, Jan, Mecklin, Lukka-Pekka, Jousilahti, Pekka, Knekt, Paul, Aaltonen, Lauri, Rissanen, Harri, Pukkala, Eero, Eriksson, Johan, Cajuso, Tatiana, Hänninen, Ulrika, Kondelin, Johanna, Palin, Kimmo, Tanskanen, Tomas, Renkonen-Sinisalo, Laura, Zanke, Brent, Männistö, Satu, Albanes, Demetrius, Weinstein, Stephanie, Ruiz-Narvaez, Edward, Palmer, Julie, Buchanan, Daniel, Platz, Elizabeth, Visvanathan, Kala, Ulrich, Cornelia, Siegel, Erin, Brezina, Stefanie, Gsur, Andrea, Campbell, Peter, Chang-Claude, Jenny, Hoffmeister, Michael, Brenner, Hermann, Slattery, Martha, Potter, John, Tsilidis, Konstantinos, Schulze, Matthias, Gunter, Marc, Murphy, Neil, Castells, Antoni, Castellví-Bel, Sergi, Moreira, Leticia, Arndt, Volker, Shcherbina, Anna, Stern, Mariana, Pardamean, Bens, Bishop, Timothy, Giles, Graham, Southey, Melissa, Idos, Gregory, McDonnell, Kevin, Abu-Ful, Zomoroda, Greenson, Joel, Shulman, Katerina, Lejbkowicz, Flavio, Offit, Kenneth, Su, Yu-Ru, Steinfelder, Robert, Keku, Temitope, van Guelpen, Bethany, Hudson, Thomas, Hampel, Heather, Pearlman, Rachel, Berndt, Sonja, Hayes, Richard, Martinez, Marie Elena, Thomas, Sushma, Corley, Douglas, Pharoah, Paul, Larsson, Susanna, Yen, Yun, Lenz, Heinz-Josef, White, Emily, Li, Li, Doheny, Kimberly, Pugh, Elizabeth, Shelford, Tameka, Chan, Andrew, Cruz-Correa, Marcia, Lindblom, Annika, Hunter, David, Joshi, Amit, Schafmayer, Clemens, Scacheri, Peter, Kundaje, Anshul, Nickerson, Deborah, Schoen, Robert, Hampe, Jochen, Stadler, Zsofia, Vodicka, Pavel, Vodickova, Ludmila, Vymetalkova, Veronika, Papadopoulos, Nickolas, Edlund, Chistopher, Gauderman, William, Thomas, Duncan, Shibata, David, Toland, Amanda, Markowitz, Sanford, Kim, Andre, Chanock, Stephen, van Duijnhoven, Franzel, Feskens, Edith, Sakoda, Lori, Gago-Dominguez, Manuela, Wolk, Alicja, Naccarati, Alessio, Pardini, Barbara, FitzGerald, Liesel, Lee, Soo Chin, Ogino, Shuji, Bien, Stephanie, Kooperberg, Charles, Li, Christopher, Lin, Yi, Prentice, Ross, Qu, Conghui, Bézieau, Stéphane, Tangen, Catherine, Mardis, Elaine, Yamaji, Taiki, Sawada, Norie, Iwasaki, Motoki, Haiman, Christopher, Le Marchand, Loic, Wu, Anna, Qu, Chenxu, McNeil, Caroline, Coetzee, Gerhard, Hayward, Caroline, Deary, Ian, Harris, Sarah, Theodoratou, Evropi, Reid, Stuart, Walker, Marion, Ooi, Li Yin, Moreno, Victor, Casey, Graham, Gruber, Stephen, Tomlinson, Ian, Zheng, Wei, Dunlop, Malcolm, Houlston, Richard, Peters, Ulrike, Fernandez-Rozadilla, Ceres, Timofeeva, Maria, Chen, Zhishan, Law, Philip, Thomas, Minta, Schmit, Stephanie, Díez-Obrero, Virginia, Hsu, Li, Fernandez-Tajes, Juan, Palles, Claire, Sherwood, Kitty, Briggs, Sarah, Svinti, Victoria, Donnelly, Kevin, Farrington, Susan, Blackmur, James, Vaughan-Shaw, Peter, Shu, Xiao-ou, Long, Jirong, Cai, Qiuyin, Guo, Xingyi, Lu, Yingchang, Broderick, Peter, Studd, James, Huyghe, Jeroen, Harrison, Tabitha, Conti, David, Dampier, Christopher, Devall, Mathew, Schumacher, Fredrick, Melas, Marilena, Rennert, Gad, Obón-Santacana, Mireia, Martín-Sánchez, Vicente, Moratalla-Navarro, Ferran, Oh, Jae Hwan, Kim, Jeongseon, Jee, Sun Ha, Jung, Keum Ji, Kweon, Sun-Seog, Shin, Min-Ho, Shin, Aesun, Ahn, Yoon-Ok, Kim, Dong-Hyun, Oze, Isao, Wen, Wanqing, Matsuo, Keitaro, Matsuda, Koichi, Tanikawa, Chizu, Ren, Zefang, Gao, Yu-Tang, Jia, Wei-Hua, Hopper, John, Jenkins, Mark, Win, Aung Ko, Pai, Rish, Figueiredo, Jane, Haile, Robert, Gallinger, Steven, Woods, Michael, Newcomb, Polly, Duggan, David, Cheadle, Jeremy, Kaplan, Richard, Maughan, Timothy, Kerr, Rachel, Kerr, David, Kirac, Iva, Böhm, Jan, Mecklin, Lukka-Pekka, Jousilahti, Pekka, Knekt, Paul, Aaltonen, Lauri, Rissanen, Harri, Pukkala, Eero, Eriksson, Johan, Cajuso, Tatiana, Hänninen, Ulrika, Kondelin, Johanna, Palin, Kimmo, Tanskanen, Tomas, Renkonen-Sinisalo, Laura, Zanke, Brent, Männistö, Satu, Albanes, Demetrius, Weinstein, Stephanie, Ruiz-Narvaez, Edward, Palmer, Julie, Buchanan, Daniel, Platz, Elizabeth, Visvanathan, Kala, Ulrich, Cornelia, Siegel, Erin, Brezina, Stefanie, Gsur, Andrea, Campbell, Peter, Chang-Claude, Jenny, Hoffmeister, Michael, Brenner, Hermann, Slattery, Martha, Potter, John, Tsilidis, Konstantinos, Schulze, Matthias, Gunter, Marc, Murphy, Neil, Castells, Antoni, Castellví-Bel, Sergi, Moreira, Leticia, Arndt, Volker, Shcherbina, Anna, Stern, Mariana, Pardamean, Bens, Bishop, Timothy, Giles, Graham, Southey, Melissa, Idos, Gregory, McDonnell, Kevin, Abu-Ful, Zomoroda, Greenson, Joel, Shulman, Katerina, Lejbkowicz, Flavio, Offit, Kenneth, Su, Yu-Ru, Steinfelder, Robert, Keku, Temitope, van Guelpen, Bethany, Hudson, Thomas, Hampel, Heather, Pearlman, Rachel, Berndt, Sonja, Hayes, Richard, Martinez, Marie Elena, Thomas, Sushma, Corley, Douglas, Pharoah, Paul, Larsson, Susanna, Yen, Yun, Lenz, Heinz-Josef, White, Emily, Li, Li, Doheny, Kimberly, Pugh, Elizabeth, Shelford, Tameka, Chan, Andrew, Cruz-Correa, Marcia, Lindblom, Annika, Hunter, David, Joshi, Amit, Schafmayer, Clemens, Scacheri, Peter, Kundaje, Anshul, Nickerson, Deborah, Schoen, Robert, Hampe, Jochen, Stadler, Zsofia, Vodicka, Pavel, Vodickova, Ludmila, Vymetalkova, Veronika, Papadopoulos, Nickolas, Edlund, Chistopher, Gauderman, William, Thomas, Duncan, Shibata, David, Toland, Amanda, Markowitz, Sanford, Kim, Andre, Chanock, Stephen, van Duijnhoven, Franzel, Feskens, Edith, Sakoda, Lori, Gago-Dominguez, Manuela, Wolk, Alicja, Naccarati, Alessio, Pardini, Barbara, FitzGerald, Liesel, Lee, Soo Chin, Ogino, Shuji, Bien, Stephanie, Kooperberg, Charles, Li, Christopher, Lin, Yi, Prentice, Ross, Qu, Conghui, Bézieau, Stéphane, Tangen, Catherine, Mardis, Elaine, Yamaji, Taiki, Sawada, Norie, Iwasaki, Motoki, Haiman, Christopher, Le Marchand, Loic, Wu, Anna, Qu, Chenxu, McNeil, Caroline, Coetzee, Gerhard, Hayward, Caroline, Deary, Ian, Harris, Sarah, Theodoratou, Evropi, Reid, Stuart, Walker, Marion, Ooi, Li Yin, Moreno, Victor, Casey, Graham, Gruber, Stephen, Tomlinson, Ian, Zheng, Wei, Dunlop, Malcolm, Houlston, Richard, and Peters, Ulrike
Abstract: Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies., Errata: Fernandez-Rozadilla, C., Timofeeva, M., Chen, Z. et al. Author Correction: Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries. Nat Genet (2023). DOI: 10.1038/s41588-023-01334-w
Published: 2023
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46. The association between genetically elevated polyunsaturated fatty acids and risk of cancer.

Author: Haycock, Philip C, Borges, Maria Carolina, Burrows, Kimberley, Lemaitre, Rozenn N, Burgess, Stephen, Khankari, Nikhil K, Tsilidis, Konstantinos K, Gaunt, Tom R, Hemani, Gibran, Zheng, Jie, Truong, Therese, Birmann, Brenda M, OMara, Tracy, Spurdle, Amanda B, Iles, Mark M, Law, Matthew H, Slager, Susan L, Saberi Hosnijeh, Fatemeh, Mariosa, Daniela, Cotterchio, Michelle, Cerhan, James R, Peters, Ulrike, Enroth, Stefan, Gharahkhani, Puya, Le Marchand, Loic, Williams, Ann C, Block, Robert C, Amos, Christopher I, Hung, Rayjean J, Zheng, Wei, Gunter, Marc J, Smith, George Davey, Relton, Caroline, Martin, Richard M, Haycock, Philip C, Borges, Maria Carolina, Burrows, Kimberley, Lemaitre, Rozenn N, Burgess, Stephen, Khankari, Nikhil K, Tsilidis, Konstantinos K, Gaunt, Tom R, Hemani, Gibran, Zheng, Jie, Truong, Therese, Birmann, Brenda M, OMara, Tracy, Spurdle, Amanda B, Iles, Mark M, Law, Matthew H, Slager, Susan L, Saberi Hosnijeh, Fatemeh, Mariosa, Daniela, Cotterchio, Michelle, Cerhan, James R, Peters, Ulrike, Enroth, Stefan, Gharahkhani, Puya, Le Marchand, Loic, Williams, Ann C, Block, Robert C, Amos, Christopher I, Hung, Rayjean J, Zheng, Wei, Gunter, Marc J, Smith, George Davey, Relton, Caroline, and Martin, Richard M
Abstract: BACKGROUND: The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain. METHODS: Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures. FINDINGS: Genetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07-1.11]), esophageal squamous cell carcinoma (1.16 [1.06-1.26]), lung cancer (1.06 [1.03-1.08]) and basal cell carcinoma (1.05 [1.02-1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99-1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99-1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95-1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98-1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activi
Published: 2023
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47. Observation of microscopic confinement dynamics by a tunable topological $\theta$-angle

Author: Zhang, Wei-Yong, Liu, Ying, Cheng, Yanting, He, Ming-Gen, Wang, Han-Yi, Wang, Tian-Yi, Zhu, Zi-Hang, Su, Guo-Xian, Zhou, Zhao-Yu, Zheng, Yong-Guang, Sun, Hui, Yang, Bing, Hauke, Philipp, Zheng, Wei, Halimeh, Jad C., Yuan, Zhen-Sheng, Pan, Jian-Wei, Zhang, Wei-Yong, Liu, Ying, Cheng, Yanting, He, Ming-Gen, Wang, Han-Yi, Wang, Tian-Yi, Zhu, Zi-Hang, Su, Guo-Xian, Zhou, Zhao-Yu, Zheng, Yong-Guang, Sun, Hui, Yang, Bing, Hauke, Philipp, Zheng, Wei, Halimeh, Jad C., Yuan, Zhen-Sheng, and Pan, Jian-Wei
Abstract: The topological $\theta$-angle is central to the understanding of a plethora of phenomena in condensed matter and high-energy physics such as the strong CP problem, dynamical quantum topological phase transitions, and the confinement--deconfinement transition. Difficulties arise when probing the effects of the topological $\theta$-angle using classical methods, in particular through the appearance of a sign problem in numerical simulations. Quantum simulators offer a powerful alternate venue for realizing the $\theta$-angle, which has hitherto remained an outstanding challenge due to the difficulty of introducing a dynamical electric field in the experiment. Here, we report on the experimental realization of a tunable topological $\theta$-angle in a Bose--Hubbard gauge-theory quantum simulator, implemented through a tilted superlattice potential that induces an effective background electric field. We demonstrate the rich physics due to this angle by the direct observation of the confinement--deconfinement transition of $(1+1)$-dimensional quantum electrodynamics. Using an atomic-precision quantum gas microscope, we distinguish between the confined and deconfined phases by monitoring the real-time evolution of particle--antiparticle pairs, which exhibit constrained (ballistic) propagation for a finite (vanishing) deviation of the $\theta$-angle from $\pi$. Our work provides a major step forward in the realization of topological terms on modern quantum simulators, and the exploration of rich physics they have been theorized to entail., Comment: $7+7$ pages, $4+7$ figures, $1+0$ table
Published: 2023

48. Gauge Violation Spectroscopy in Synthetic Gauge Theories

Author: Qi, Hao-Yue, Zheng, Wei, Qi, Hao-Yue, and Zheng, Wei
Abstract: Recently synthetic gauge fields have been implemented on quantum simulators. Unlike the gauge fields in the real world, in synthetic gauge fields, the gauge charge can fluctuate and gauge invariance can be violated, which leading rich physics unexplored before. In this work, we propose the gauge violation spectroscopy as a useful experimentally accessible measurement in the synthetic gauge theories. We show that the gauge violation spectroscopy exhibits no dispersion. Using three models as examples, two of them can be exactly solved by bosonization, and one has been realized in experiment, we further demonstrate the gauge violation spectroscopy can be used to detect the confinement and deconfinement phases. In the confinement phase, it shows a delta function behavior, while in the deconfinement phase, it has a finite width., Comment: 12 pages, 6 figures
Published: 2023

49. Acute Hepatitis E Induced the First Episode of Immune-Mediated Thrombotic Thrombocytopenic Purpura: The First Case Report

Author: Lv,Fei, Zhao,Yue, Yang,Xing-Di, Chen,Han-Zhu, Ren,Wen-Ya, Chen,Ling-Xia, Yi,Qiao-Qiao, Zheng,Wei, Pan,Hong-Ying, Lv,Fei, Zhao,Yue, Yang,Xing-Di, Chen,Han-Zhu, Ren,Wen-Ya, Chen,Ling-Xia, Yi,Qiao-Qiao, Zheng,Wei, and Pan,Hong-Ying
Abstract: Fei Lv,1,2 Yue Zhao,2 Xing-Di Yang,2 Han-Zhu Chen,2 Wen-Ya Ren,2 Ling-Xia Chen,2 Qiao-Qiao Yi,2 Wei Zheng,2 Hong-Ying Pan2 1The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, 310053, Peopleâs Republic of China; 2Department of Infectious Diseases, Zhejiang Provincial Peopleâs Hospital, Affiliated Peopleâs Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, 310014, Peopleâs Republic of ChinaCorrespondence: Hong-Ying Pan, Tel/Fax +86-571-8589-3603, Email hypanzjsrmyy@126.comPurpose: Hepatitis E virus infection mainly presents with liver-related symptoms, and multiple studies have shown that hepatitis E virus infection can also induce extrahepatic-related symptoms. Thrombotic thrombocytopenic purpura is an uncommon and fatal thrombotic microangiopathy characterized by severe thrombocytopenia, organ damage, and microangiopathic haemolytic anaemia. We report the first case in which acute hepatitis E induced the first episode of immune-mediated thrombotic thrombocytopenic purpura.Patients and Methods: A 53-year-old male was admitted to our emergency department with fever, thrombocytopenia, and abnormal liver function. Laboratory tests revealed significant bilirubin, AST, and ALT elevations, renal impairment, positive anti-HEV IgM and IgG antibody results, schistocytes on the blood smear, 0% ADAMTS-13 activity, and positive ADAMTS13 inhibitor results. He was diagnosed with acute hepatitis E, which induced the first episode of immune-mediated thrombotic thrombocytopenic purpura.Results: After receiving treatment with plasmapheresis, glucocorticoid medication, rituximab, and other supportive medicines, the patientâs physiological circumstances and laboratory indicators improved, and a 4-month follow-up revealed no abnormalities.Conclusion: This is a unique case report of an acute hepatitis E-induced immune-mediated thrombotic thrombocytopenic purpura initial episode. This case report offers evidence that hepatitis E vir
Published: 2023

50. Genetic Susceptibility to Nonalcoholic Fatty Liver Disease and Risk for Pancreatic Cancer: Mendelian Randomization

Author: King, Sontoria D., Veliginti, Swathi, Brouwers, Martijn C G J, Ren, Zhewen, Zheng, Wei, Setiawan, Veronica W., Wilkens, Lynne R., Shu, Xiao-Ou, Arslan, Alan A., Beane Freeman, Laura E., Bracci, Paige M., Canzian, Federico, Du, Mengmeng, Gallinger, Steven J., Giles, Graham G., Goodman, Phyllis J., Haiman, Christopher A., Kogevinas, Manolis, Kooperberg, Charles, LeMarchand, Loic, Neale, Rachel E., Visvanathan, Kala, White, Emily, Albanes, Demetrius, Andreotti, Gabriella, Babic, Ana, Berndt, Sonja I., Brais, Lauren K., Brennan, Paul, Buring, Julie E., Rabe, Kari G., Bamlet, William R., Chanock, Stephen J., Fuchs, Charles S., Gaziano, J Michael, Giovannucci, Edward L., Hackert, Thilo, Hassan, Manal M., Katzke, Verena, Kurtz, Robert C., Lee, I-Min, Malats, Núria, Murphy, Neil, Oberg, Ann L., Orlow, Irene, Porta, Miquel, Real, Francisco X., Rothman, Nathaniel, Sesso, Howard D., Silverman, Debra T., Thompson, Ian M., Wactawski-Wende, Jean, Wang, Xiaoliang, Wentzensen, Nicolas, Yu, Herbert, Zeleniuch-Jacquotte, Anne, Yu, Kai, Wolpin, Brian M., Duell, Eric J., Li, Donghui, Hung, Rayjean J., Perdomo, Sandra, McCullough, Marjorie L., Freedman, Neal D., Patel, Alpa V., Peters, Ulrike, Riboli, Elio, Sund, Malin, Tjønneland, Anne, Zhong, Jun, Van Den Eeden, Stephen K., Kraft, Peter, Risch, Harvey A., Amundadottir, Laufey T., Klein, Alison P., Stolzenberg-Solomon, Rachael Z., Antwi, Samuel O., King, Sontoria D., Veliginti, Swathi, Brouwers, Martijn C G J, Ren, Zhewen, Zheng, Wei, Setiawan, Veronica W., Wilkens, Lynne R., Shu, Xiao-Ou, Arslan, Alan A., Beane Freeman, Laura E., Bracci, Paige M., Canzian, Federico, Du, Mengmeng, Gallinger, Steven J., Giles, Graham G., Goodman, Phyllis J., Haiman, Christopher A., Kogevinas, Manolis, Kooperberg, Charles, LeMarchand, Loic, Neale, Rachel E., Visvanathan, Kala, White, Emily, Albanes, Demetrius, Andreotti, Gabriella, Babic, Ana, Berndt, Sonja I., Brais, Lauren K., Brennan, Paul, Buring, Julie E., Rabe, Kari G., Bamlet, William R., Chanock, Stephen J., Fuchs, Charles S., Gaziano, J Michael, Giovannucci, Edward L., Hackert, Thilo, Hassan, Manal M., Katzke, Verena, Kurtz, Robert C., Lee, I-Min, Malats, Núria, Murphy, Neil, Oberg, Ann L., Orlow, Irene, Porta, Miquel, Real, Francisco X., Rothman, Nathaniel, Sesso, Howard D., Silverman, Debra T., Thompson, Ian M., Wactawski-Wende, Jean, Wang, Xiaoliang, Wentzensen, Nicolas, Yu, Herbert, Zeleniuch-Jacquotte, Anne, Yu, Kai, Wolpin, Brian M., Duell, Eric J., Li, Donghui, Hung, Rayjean J., Perdomo, Sandra, McCullough, Marjorie L., Freedman, Neal D., Patel, Alpa V., Peters, Ulrike, Riboli, Elio, Sund, Malin, Tjønneland, Anne, Zhong, Jun, Van Den Eeden, Stephen K., Kraft, Peter, Risch, Harvey A., Amundadottir, Laufey T., Klein, Alison P., Stolzenberg-Solomon, Rachael Z., and Antwi, Samuel O.
Abstract: BACKGROUND: There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer. METHODS: Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes. RESULTS: No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88-1.22; MR-Egger OR, 0.89; 95% CI, 0.65-1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90-1.27; MR-Egger OR, 0.93; 95% CI, 0.67-1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample. CONCLUSIONS: Genetic predisposition to NAFLD is not associated with pancreatic cancer risk. IMPACT: Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer.
Published: 2023
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