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2,861 results on '"Invernizzi, P."'

1. Semantic Gaps in the Theory and the Practice of Physical and Sports Education in the Italian Context

Author

Pietro Luigi Invernizzi, Raffaele Scurati, Gabriele Signorini, Franco Mauro, Marta Rigon, Francesca D'Elia, and Gaetano Raiola

Abstract

Nowadays, we face a profound fragmentation of knowledge, which is addressed in distinctive ways, conforming to the specifics of each field of knowledge and having a specific lexicon and ways to interpret reality. To better understand and communicate the complexity of the reality of motor and sports sciences in Italy, it is necessary to study its ontology based on a holistic and comprehensive approach such as System Thinking (ST). So, this preliminary review aimed to verify the coherence of terminology used by Italian academics (who study methodologies related to teaching) and practical communities (who live the reality of daily teaching) in motor and sports sciences, specifically regarding the didactic of physical and sports education. For this purpose, according to Design Based Research (DBR), a first investigation of the interpretative semantics of the discipline's specific terms was accomplished with the support of multiple sources of information such as documents, databases, and brainstorming performed by experts (representing the guiding team and stakeholders from all considered communities). Moreover, the frequency of some terms and keywords considered in European (ERC) and Italian (CUN) legislation was assessed to contextualize better the impact of common practice community keywords on the scientific and regulatory community. Successively, the studies that analyzed the terms from 2000 to 2020 in the leading scientific search engines (SCOPUS and Web of Science) were also investigated. Results indicate that in the CUN and ERC areas, there is a total absence of the most relevant lemma to the community of practice. Furthermore, significant terms such as play, sports education, psychomotricity, and gymnastics are less considered or unconsidered in the specific scientific and didactic fields. Possible solutions for a specific semantic model to reduce the gap are finally hypothesized and presented.

Published
2024

2. Efficient mapping of phase diagrams with conditional Boltzmann Generators

Author

Schebek, Maximilian, Invernizzi, Michele, Noé, Frank, and Rogal, Jutta

Subjects
Condensed Matter - Statistical Mechanics, Computer Science - Machine Learning
Abstract

The accurate prediction of phase diagrams is of central importance for both the fundamental understanding of materials as well as for technological applications in material sciences. However, the computational prediction of the relative stability between phases based on their free energy is a daunting task, as traditional free energy estimators require a large amount of simulation data to obtain uncorrelated equilibrium samples over a grid of thermodynamic states. In this work, we develop deep generative machine learning models based on the Boltzmann Generator approach for entire phase diagrams, employing normalizing flows conditioned on the thermodynamic states, e.g., temperature and pressure, that they map to. By training a single normalizing flow to transform the equilibrium distribution sampled at only one reference thermodynamic state to a wide range of target temperatures and pressures, we can efficiently generate equilibrium samples across the entire phase diagram. Using a permutation-equivariant architecture allows us, thereby, to treat solid and liquid phases on the same footing. We demonstrate our approach by predicting the solid-liquid coexistence line for a Lennard-Jones system in excellent agreement with state-of-the-art free energy methods while significantly reducing the number of energy evaluations needed.

Published
2024

3. Give and Take: An End-To-End Investigation of Giveaway Scam Conversion Rates

Author

Liu, Enze, Kappos, George, Mugnier, Eric, Invernizzi, Luca, Savage, Stefan, Tao, David, Thomas, Kurt, Voelker, Geoffrey M., and Meiklejohn, Sarah

Subjects
Computer Science - Cryptography and Security
Abstract

Scams -- fraudulent schemes designed to swindle money from victims -- have existed for as long as recorded history. However, the Internet's combination of low communication cost, global reach, and functional anonymity has allowed scam volumes to reach new heights. Designing effective interventions requires first understanding the context: how scammers reach potential victims, the earnings they make, and any potential bottlenecks for durable interventions. In this short paper, we focus on these questions in the context of cryptocurrency giveaway scams, where victims are tricked into irreversibly transferring funds to scammers under the pretense of even greater returns. Combining data from Twitter, YouTube and Twitch livestreams, landing pages, and cryptocurrency blockchains, we measure how giveaway scams operate at scale. We find that 1 in 1000 scam tweets, and 4 in 100,000 livestream views, net a victim, and that scammers managed to extract nearly \$4.62 million from just hundreds of victims during our measurement window., Comment: Under review

Published
2024

4. Machine learning assisted optical diagnostics on a cylindrical atmospheric pressure surface dielectric barrier discharge

Author

Stefas, Dimitrios, Giotis, Konstantinos, Invernizzi, Laurent, Höft, Hans, Hassouni, Khaled, Prasanna, Swaminathan, Svarnas, Panagiotis, Lombardi, Guillaume, and Gazeli, Kristaq

Subjects
Physics - Plasma Physics, Physics - Data Analysis, Statistics and Probability
Abstract

The present study explores combining machine learning (ML) algorithms with standard optical diagnostics (such as time-integrated emission spectroscopy and imaging) to accurately predict operating conditions and assess the emission uniformity of a cylindrical surface Dielectric Barrier Discharge (SDBD). It is demonstrated that ML can be complementary with these optical diagnostics and identify peculiarities associated with the discharge emission pattern at different high voltage waveforms (AC and pulsed) and amplitudes. By employing unsupervised (Principal Component Analysis (PCA)) and supervised (Multilayer Perceptron (MLP) neural networks) algorithms, the applied voltage waveform and amplitude are categorised and predicted based on correlations/differences identified within large amounts of corresponding data. PCA allowed us to effectively classify the voltage waveforms and amplitudes applied to the SDBD through a transformation of the spectroscopic/imaging data into principal components (PCs) and their projection to a two-dimensional PC space. Furthermore, an accurate prediction of the voltage amplitude is achieved using the MLP which is trained with PCA-preprocessed data. A particularly interesting aspect of this concept involves examining the uniformity of the emission pattern of the discharge. This is achieved by analysing spectroscopic data recorded at four different regions around the SDBD surface using the two ML-based techniques. These discoveries are instrumental in enhancing plasma-induced processes. They open up new avenues for real-time control, monitoring, and optimization of plasma-based applications across diverse fields such as flow control for the present SDBD.

Published
2024

5. Optimal s-boxes against alternative operations

Author

Calderini, Marco, Civino, Roberto, and Invernizzi, Riccardo

Subjects
Computer Science - Cryptography and Security, Mathematics - Group Theory, 20B35, 94A60, 68P25
Abstract

Civino et al. have characterised diffusion layers that expose an SPN to vulnerability from differential cryptanalysis when employing alternative operations coming from groups isomorphic to the translation group on the message space. In this study, we present a classification of diffusion layers that exhibit linearity in parallel alternative operations for ciphers with 4-bit s-boxes, enabling the possibility of an alternative differential attack simultaneously targeting all the s-boxes within the block. Furthermore, we investigate the differential behaviour with respect to alternative operations for all classes of optimal 4-bit s-boxes, as defined by Leander and Poschmann (2007). Our examination reveals that certain classes contain weak permutations w.r.t. alternative differential attacks, and we leverage these vulnerabilities to execute a series of experiments.

Published
2024

6. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Author

Gemini Team, Georgiev, Petko, Lei, Ving Ian, Burnell, Ryan, Bai, Libin, Gulati, Anmol, Tanzer, Garrett, Vincent, Damien, Pan, Zhufeng, Wang, Shibo, Mariooryad, Soroosh, Ding, Yifan, Geng, Xinyang, Alcober, Fred, Frostig, Roy, Omernick, Mark, Walker, Lexi, Paduraru, Cosmin, Sorokin, Christina, Tacchetti, Andrea, Gaffney, Colin, Daruki, Samira, Sercinoglu, Olcan, Gleicher, Zach, Love, Juliette, Voigtlaender, Paul, Jain, Rohan, Surita, Gabriela, Mohamed, Kareem, Blevins, Rory, Ahn, Junwhan, Zhu, Tao, Kawintiranon, Kornraphop, Firat, Orhan, Gu, Yiming, Zhang, Yujing, Rahtz, Matthew, Faruqui, Manaal, Clay, Natalie, Gilmer, Justin, Co-Reyes, JD, Penchev, Ivo, Zhu, Rui, Morioka, Nobuyuki, Hui, Kevin, Haridasan, Krishna, Campos, Victor, Mahdieh, Mahdis, Guo, Mandy, Hassan, Samer, Kilgour, Kevin, Vezer, Arpi, Cheng, Heng-Tze, de Liedekerke, Raoul, Goyal, Siddharth, Barham, Paul, Strouse, DJ, Noury, Seb, Adler, Jonas, Sundararajan, Mukund, Vikram, Sharad, Lepikhin, Dmitry, Paganini, Michela, Garcia, Xavier, Yang, Fan, Valter, Dasha, Trebacz, Maja, Vodrahalli, Kiran, Asawaroengchai, Chulayuth, Ring, Roman, Kalb, Norbert, Soares, Livio Baldini, Brahma, Siddhartha, Steiner, David, Yu, Tianhe, Mentzer, Fabian, He, Antoine, Gonzalez, Lucas, Xu, Bibo, Kaufman, Raphael Lopez, Shafey, Laurent El, Oh, Junhyuk, Hennigan, Tom, Driessche, George van den, Odoom, Seth, Lucic, Mario, Roelofs, Becca, Lall, Sid, Marathe, Amit, Chan, Betty, Ontanon, Santiago, He, Luheng, Teplyashin, Denis, Lai, Jonathan, Crone, Phil, Damoc, Bogdan, Ho, Lewis, Riedel, Sebastian, Lenc, Karel, Yeh, Chih-Kuan, Chowdhery, Aakanksha, Xu, Yang, Kazemi, Mehran, Amid, Ehsan, Petrushkina, Anastasia, Swersky, Kevin, Khodaei, Ali, Chen, Gowoon, Larkin, Chris, Pinto, Mario, Yan, Geng, Badia, Adria Puigdomenech, Patil, Piyush, Hansen, Steven, Orr, Dave, Arnold, Sebastien M. R., Grimstad, Jordan, Dai, Andrew, Douglas, Sholto, Sinha, Rishika, Yadav, Vikas, Chen, Xi, Gribovskaya, Elena, Austin, Jacob, Zhao, Jeffrey, Patel, Kaushal, Komarek, Paul, Austin, Sophia, Borgeaud, Sebastian, Friso, Linda, Goyal, Abhimanyu, Caine, Ben, Cao, Kris, Chung, Da-Woon, Lamm, Matthew, Barth-Maron, Gabe, Kagohara, Thais, Olszewska, Kate, Chen, Mia, Shivakumar, Kaushik, Agarwal, Rishabh, Godhia, Harshal, Rajwar, Ravi, Snaider, Javier, Dotiwalla, Xerxes, Liu, Yuan, Barua, Aditya, Ungureanu, Victor, Zhang, Yuan, Batsaikhan, Bat-Orgil, Wirth, Mateo, Qin, James, Danihelka, Ivo, Doshi, Tulsee, Chadwick, Martin, Chen, Jilin, Jain, Sanil, Le, Quoc, Kar, Arjun, Gurumurthy, Madhu, Li, Cheng, Sang, Ruoxin, Liu, Fangyu, Lamprou, Lampros, Munoz, Rich, Lintz, Nathan, Mehta, Harsh, Howard, Heidi, Reynolds, Malcolm, Aroyo, Lora, Wang, Quan, Blanco, Lorenzo, Cassirer, Albin, Griffith, Jordan, Das, Dipanjan, Lee, Stephan, Sygnowski, Jakub, Fisher, Zach, Besley, James, Powell, Richard, Ahmed, Zafarali, Paulus, Dominik, Reitter, David, Borsos, Zalan, Joshi, Rishabh, Pope, Aedan, Hand, Steven, Selo, Vittorio, Jain, Vihan, Sethi, Nikhil, Goel, Megha, Makino, Takaki, May, Rhys, Yang, Zhen, Schalkwyk, Johan, Butterfield, Christina, Hauth, Anja, Goldin, Alex, Hawkins, Will, Senter, Evan, Brin, Sergey, Woodman, Oliver, Ritter, Marvin, Noland, Eric, Giang, Minh, Bolina, Vijay, Lee, Lisa, Blyth, Tim, Mackinnon, Ian, Reid, Machel, Sarvana, Obaid, Silver, David, Chen, Alexander, Wang, Lily, Maggiore, Loren, Chang, Oscar, Attaluri, Nithya, Thornton, Gregory, Chiu, Chung-Cheng, Bunyan, Oskar, Levine, Nir, Chung, Timothy, Eltyshev, Evgenii, Si, Xiance, Lillicrap, Timothy, Brady, Demetra, Aggarwal, Vaibhav, Wu, Boxi, Xu, Yuanzhong, McIlroy, Ross, Badola, Kartikeya, Sandhu, Paramjit, Moreira, Erica, Stokowiec, Wojciech, Hemsley, Ross, Li, Dong, Tudor, Alex, Shyam, Pranav, Rahimtoroghi, Elahe, Haykal, Salem, Sprechmann, Pablo, Zhou, Xiang, Mincu, Diana, Li, Yujia, Addanki, Ravi, Krishna, Kalpesh, Wu, Xiao, Frechette, Alexandre, Eyal, Matan, Dafoe, Allan, Lacey, Dave, Whang, Jay, Avrahami, Thi, Zhang, Ye, Taropa, Emanuel, Lin, Hanzhao, Toyama, Daniel, Rutherford, Eliza, Sano, Motoki, Choe, HyunJeong, Tomala, Alex, Safranek-Shrader, Chalence, Kassner, Nora, Pajarskas, Mantas, Harvey, Matt, Sechrist, Sean, Fortunato, Meire, Lyu, Christina, Elsayed, Gamaleldin, Kuang, Chenkai, Lottes, James, Chu, Eric, Jia, Chao, Chen, Chih-Wei, Humphreys, Peter, Baumli, Kate, Tao, Connie, Samuel, Rajkumar, Santos, Cicero Nogueira dos, Andreassen, Anders, Rakićević, Nemanja, Grewe, Dominik, Kumar, Aviral, Winkler, Stephanie, Caton, Jonathan, Brock, Andrew, Dalmia, Sid, Sheahan, Hannah, Barr, Iain, Miao, Yingjie, Natsev, Paul, Devlin, Jacob, Behbahani, Feryal, Prost, Flavien, Sun, Yanhua, Myaskovsky, Artiom, Pillai, Thanumalayan Sankaranarayana, Hurt, Dan, Lazaridou, Angeliki, Xiong, Xi, Zheng, Ce, Pardo, Fabio, Li, Xiaowei, Horgan, Dan, Stanton, Joe, Ambar, Moran, Xia, Fei, Lince, Alejandro, Wang, Mingqiu, Mustafa, Basil, Webson, Albert, Lee, Hyo, Anil, Rohan, Wicke, Martin, Dozat, Timothy, Sinha, Abhishek, Piqueras, Enrique, Dabir, Elahe, Upadhyay, Shyam, Boral, Anudhyan, Hendricks, Lisa Anne, Fry, Corey, Djolonga, Josip, Su, Yi, Walker, Jake, Labanowski, Jane, Huang, Ronny, Misra, Vedant, Chen, Jeremy, Skerry-Ryan, RJ, Singh, Avi, Rijhwani, Shruti, Yu, Dian, Castro-Ros, Alex, Changpinyo, Beer, Datta, Romina, Bagri, Sumit, Hrafnkelsson, Arnar Mar, Maggioni, Marcello, Zheng, Daniel, Sulsky, Yury, Hou, Shaobo, Paine, Tom Le, Yang, Antoine, Riesa, Jason, Rogozinska, Dominika, Marcus, Dror, Badawy, Dalia El, Zhang, Qiao, Wang, Luyu, Miller, Helen, Greer, Jeremy, Sjos, Lars Lowe, Nova, Azade, Zen, Heiga, Chaabouni, Rahma, Rosca, Mihaela, Jiang, Jiepu, Chen, Charlie, Liu, Ruibo, Sainath, Tara, Krikun, Maxim, Polozov, Alex, Lespiau, Jean-Baptiste, Newlan, Josh, Cankara, Zeyncep, Kwak, Soo, Xu, Yunhan, Chen, Phil, Coenen, Andy, Meyer, Clemens, Tsihlas, Katerina, Ma, Ada, Gottweis, Juraj, Xing, Jinwei, Gu, Chenjie, Miao, Jin, Frank, Christian, Cankara, Zeynep, Ganapathy, Sanjay, Dasgupta, Ishita, Hughes-Fitt, Steph, Chen, Heng, Reid, David, Rong, Keran, Fan, Hongmin, van Amersfoort, Joost, Zhuang, Vincent, Cohen, Aaron, Gu, Shixiang Shane, Mohananey, Anhad, Ilic, Anastasija, Tobin, Taylor, Wieting, John, Bortsova, Anna, Thacker, Phoebe, Wang, Emma, Caveness, Emily, Chiu, Justin, Sezener, Eren, Kaskasoli, Alex, Baker, Steven, Millican, Katie, Elhawaty, Mohamed, Aisopos, Kostas, Lebsack, Carl, Byrd, Nathan, Dai, Hanjun, Jia, Wenhao, Wiethoff, Matthew, Davoodi, Elnaz, Weston, Albert, Yagati, Lakshman, Ahuja, Arun, Gao, Isabel, Pundak, Golan, Zhang, Susan, Azzam, Michael, Sim, Khe Chai, Caelles, Sergi, Keeling, James, Sharma, Abhanshu, Swing, Andy, Li, YaGuang, Liu, Chenxi, Bostock, Carrie Grimes, Bansal, Yamini, Nado, Zachary, Anand, Ankesh, Lipschultz, Josh, Karmarkar, Abhijit, Proleev, Lev, Ittycheriah, Abe, Yeganeh, Soheil Hassas, Polovets, George, Faust, Aleksandra, Sun, Jiao, Rrustemi, Alban, Li, Pen, Shivanna, Rakesh, Liu, Jeremiah, Welty, Chris, Lebron, Federico, Baddepudi, Anirudh, Krause, Sebastian, Parisotto, Emilio, Soricut, Radu, Xu, Zheng, Bloxwich, Dawn, Johnson, Melvin, Neyshabur, Behnam, Mao-Jones, Justin, Wang, Renshen, Ramasesh, Vinay, Abbas, Zaheer, Guez, Arthur, Segal, Constant, Nguyen, Duc Dung, Svensson, James, Hou, Le, York, Sarah, Milan, Kieran, Bridgers, Sophie, Gworek, Wiktor, Tagliasacchi, Marco, Lee-Thorp, James, Chang, Michael, Guseynov, Alexey, Hartman, Ale Jakse, Kwong, Michael, Zhao, Ruizhe, Kashem, Sheleem, Cole, Elizabeth, Miech, Antoine, Tanburn, Richard, Phuong, Mary, Pavetic, Filip, Cevey, Sebastien, Comanescu, Ramona, Ives, Richard, Yang, Sherry, Du, Cosmo, Li, Bo, Zhang, Zizhao, Iinuma, Mariko, Hu, Clara Huiyi, Roy, Aurko, Bijwadia, Shaan, Zhu, Zhenkai, Martins, Danilo, Saputro, Rachel, Gergely, Anita, Zheng, Steven, Jia, Dawei, Antonoglou, Ioannis, Sadovsky, Adam, Gu, Shane, Bi, Yingying, Andreev, Alek, Samangooei, Sina, Khan, Mina, Kocisky, Tomas, Filos, Angelos, Kumar, Chintu, Bishop, Colton, Yu, Adams, Hodkinson, Sarah, Mittal, Sid, Shah, Premal, Moufarek, Alexandre, Cheng, Yong, Bloniarz, Adam, Lee, Jaehoon, Pejman, Pedram, Michel, Paul, Spencer, Stephen, Feinberg, Vladimir, Xiong, Xuehan, Savinov, Nikolay, Smith, Charlotte, Shakeri, Siamak, Tran, Dustin, Chesus, Mary, Bohnet, Bernd, Tucker, George, von Glehn, Tamara, Muir, Carrie, Mao, Yiran, Kazawa, Hideto, Slone, Ambrose, Soparkar, Kedar, Shrivastava, Disha, Cobon-Kerr, James, Sharman, Michael, Pavagadhi, Jay, Araya, Carlos, Misiunas, Karolis, Ghelani, Nimesh, Laskin, Michael, Barker, David, Li, Qiujia, Briukhov, Anton, Houlsby, Neil, Glaese, Mia, Lakshminarayanan, Balaji, Schucher, Nathan, Tang, Yunhao, Collins, Eli, Lim, Hyeontaek, Feng, Fangxiaoyu, Recasens, Adria, Lai, Guangda, Magni, Alberto, De Cao, Nicola, Siddhant, Aditya, Ashwood, Zoe, Orbay, Jordi, Dehghani, Mostafa, Brennan, Jenny, He, Yifan, Xu, Kelvin, Gao, Yang, Saroufim, Carl, Molloy, James, Wu, Xinyi, Arnold, Seb, Chang, Solomon, Schrittwieser, Julian, Buchatskaya, Elena, Radpour, Soroush, Polacek, Martin, Giordano, Skye, Bapna, Ankur, Tokumine, Simon, Hellendoorn, Vincent, Sottiaux, Thibault, Cogan, Sarah, Severyn, Aliaksei, Saleh, Mohammad, Thakoor, Shantanu, Shefey, Laurent, Qiao, Siyuan, Gaba, Meenu, Chang, Shuo-yiin, Swanson, Craig, Zhang, Biao, Lee, Benjamin, Rubenstein, Paul Kishan, Song, Gan, Kwiatkowski, Tom, Koop, Anna, Kannan, Ajay, Kao, David, Schuh, Parker, Stjerngren, Axel, Ghiasi, Golnaz, Gibson, Gena, Vilnis, Luke, Yuan, Ye, Ferreira, Felipe Tiengo, Kamath, Aishwarya, Klimenko, Ted, Franko, Ken, Xiao, Kefan, Bhattacharya, Indro, Patel, Miteyan, Wang, Rui, Morris, Alex, Strudel, Robin, Sharma, Vivek, Choy, Peter, Hashemi, Sayed Hadi, Landon, Jessica, Finkelstein, Mara, Jhakra, Priya, Frye, Justin, Barnes, Megan, Mauger, Matthew, Daun, Dennis, Baatarsukh, Khuslen, Tung, Matthew, Farhan, Wael, Michalewski, Henryk, Viola, Fabio, Quitry, Felix de Chaumont, Lan, Charline Le, Hudson, Tom, Wang, Qingze, Fischer, Felix, Zheng, Ivy, White, Elspeth, Dragan, Anca, Alayrac, Jean-baptiste, Ni, Eric, Pritzel, Alexander, Iwanicki, Adam, Isard, Michael, Bulanova, Anna, Zilka, Lukas, Dyer, Ethan, Sachan, Devendra, Srinivasan, Srivatsan, Muckenhirn, Hannah, Cai, Honglong, Mandhane, Amol, Tariq, Mukarram, Rae, Jack W., Wang, Gary, Ayoub, Kareem, FitzGerald, Nicholas, Zhao, Yao, Han, Woohyun, Alberti, Chris, Garrette, Dan, Krishnakumar, Kashyap, Gimenez, Mai, Levskaya, Anselm, Sohn, Daniel, Matak, Josip, Iturrate, Inaki, Chang, Michael B., Xiang, Jackie, Cao, Yuan, Ranka, Nishant, Brown, Geoff, Hutter, Adrian, Mirrokni, Vahab, Chen, Nanxin, Yao, Kaisheng, Egyed, Zoltan, Galilee, Francois, Liechty, Tyler, Kallakuri, Praveen, Palmer, Evan, Ghemawat, Sanjay, Liu, Jasmine, Tao, David, Thornton, Chloe, Green, Tim, Jasarevic, Mimi, Lin, Sharon, Cotruta, Victor, Tan, Yi-Xuan, Fiedel, Noah, Yu, Hongkun, Chi, Ed, Neitz, Alexander, Heitkaemper, Jens, Sinha, Anu, Zhou, Denny, Sun, Yi, Kaed, Charbel, Hulse, Brice, Mishra, Swaroop, Georgaki, Maria, Kudugunta, Sneha, Farabet, Clement, Shafran, Izhak, Vlasic, Daniel, Tsitsulin, Anton, Ananthanarayanan, Rajagopal, Carin, Alen, Su, Guolong, Sun, Pei, V, Shashank, Carvajal, Gabriel, Broder, Josef, Comsa, Iulia, Repina, Alena, Wong, William, Chen, Warren Weilun, Hawkins, Peter, Filonov, Egor, Loher, Lucia, Hirnschall, Christoph, Wang, Weiyi, Ye, Jingchen, Burns, Andrea, Cate, Hardie, Wright, Diana Gage, Piccinini, Federico, Zhang, Lei, Lin, Chu-Cheng, Gog, Ionel, Kulizhskaya, Yana, Sreevatsa, Ashwin, Song, Shuang, Cobo, Luis C., Iyer, Anand, Tekur, Chetan, Garrido, Guillermo, Xiao, Zhuyun, Kemp, Rupert, Zheng, Huaixiu Steven, Li, Hui, Agarwal, Ananth, Ngani, Christel, Goshvadi, Kati, Santamaria-Fernandez, Rebeca, Fica, Wojciech, Chen, Xinyun, Gorgolewski, Chris, Sun, Sean, Garg, Roopal, Ye, Xinyu, Eslami, S. M. Ali, Hua, Nan, Simon, Jon, Joshi, Pratik, Kim, Yelin, Tenney, Ian, Potluri, Sahitya, Thiet, Lam Nguyen, Yuan, Quan, Luisier, Florian, Chronopoulou, Alexandra, Scellato, Salvatore, Srinivasan, Praveen, Chen, Minmin, Koverkathu, Vinod, Dalibard, Valentin, Xu, Yaming, Saeta, Brennan, Anderson, Keith, Sellam, Thibault, Fernando, Nick, Huot, Fantine, Jung, Junehyuk, Varadarajan, Mani, Quinn, Michael, Raul, Amit, Le, Maigo, Habalov, Ruslan, Clark, Jon, Jalan, Komal, Bullard, Kalesha, Singhal, Achintya, Luong, Thang, Wang, Boyu, Rajayogam, Sujeevan, Eisenschlos, Julian, Jia, Johnson, Finchelstein, Daniel, Yakubovich, Alex, Balle, Daniel, Fink, Michael, Agarwal, Sameer, Li, Jing, Dvijotham, Dj, Pal, Shalini, Kang, Kai, Konzelmann, Jaclyn, Beattie, Jennifer, Dousse, Olivier, Wu, Diane, Crocker, Remi, Elkind, Chen, Jonnalagadda, Siddhartha Reddy, Lee, Jong, Holtmann-Rice, Dan, Kallarackal, Krystal, Liu, Rosanne, Vnukov, Denis, Vats, Neera, Invernizzi, Luca, Jafari, Mohsen, Zhou, Huanjie, Taylor, Lilly, Prendki, Jennifer, Wu, Marcus, Eccles, Tom, Liu, Tianqi, Kopparapu, Kavya, Beaufays, Francoise, Angermueller, Christof, Marzoca, Andreea, Sarcar, Shourya, Dib, Hilal, Stanway, Jeff, Perbet, Frank, Trdin, Nejc, Sterneck, Rachel, Khorlin, Andrey, Li, Dinghua, Wu, Xihui, Goenka, Sonam, Madras, David, Goldshtein, Sasha, Gierke, Willi, Zhou, Tong, Liu, Yaxin, Liang, Yannie, White, Anais, Li, Yunjie, Singh, Shreya, Bahargam, Sanaz, Epstein, Mark, Basu, Sujoy, Lao, Li, Ozturel, Adnan, Crous, Carl, Zhai, Alex, Lu, Han, Tung, Zora, Gaur, Neeraj, Walton, Alanna, Dixon, Lucas, Zhang, Ming, Globerson, Amir, Uy, Grant, Bolt, Andrew, Wiles, Olivia, Nasr, Milad, Shumailov, Ilia, Selvi, Marco, Piccinno, Francesco, Aguilar, Ricardo, McCarthy, Sara, Khalman, Misha, Shukla, Mrinal, Galic, Vlado, Carpenter, John, Villela, Kevin, Zhang, Haibin, Richardson, Harry, Martens, James, Bosnjak, Matko, Belle, Shreyas Rammohan, Seibert, Jeff, Alnahlawi, Mahmoud, McWilliams, Brian, Singh, Sankalp, Louis, Annie, Ding, Wen, Popovici, Dan, Simicich, Lenin, Knight, Laura, Mehta, Pulkit, Gupta, Nishesh, Shi, Chongyang, Fatehi, Saaber, Mitrovic, Jovana, Grills, Alex, Pagadora, Joseph, Petrova, Dessie, Eisenbud, Danielle, Zhang, Zhishuai, Yates, Damion, Mittal, Bhavishya, Tripuraneni, Nilesh, Assael, Yannis, Brovelli, Thomas, Jain, Prateek, Velimirovic, Mihajlo, Akbulut, Canfer, Mu, Jiaqi, Macherey, Wolfgang, Kumar, Ravin, Xu, Jun, Qureshi, Haroon, Comanici, Gheorghe, Wiesner, Jeremy, Gong, Zhitao, Ruddock, Anton, Bauer, Matthias, Felt, Nick, GP, Anirudh, Arnab, Anurag, Zelle, Dustin, Rothfuss, Jonas, Rosgen, Bill, Shenoy, Ashish, Seybold, Bryan, Li, Xinjian, Mudigonda, Jayaram, Erdogan, Goker, Xia, Jiawei, Simsa, Jiri, Michi, Andrea, Yao, Yi, Yew, Christopher, Kan, Steven, Caswell, Isaac, Radebaugh, Carey, Elisseeff, Andre, Valenzuela, Pedro, McKinney, Kay, Paterson, Kim, Cui, Albert, Latorre-Chimoto, Eri, Kim, Solomon, Zeng, William, Durden, Ken, Ponnapalli, Priya, Sosea, Tiberiu, Choquette-Choo, Christopher A., Manyika, James, Robenek, Brona, Vashisht, Harsha, Pereira, Sebastien, Lam, Hoi, Velic, Marko, Owusu-Afriyie, Denese, Lee, Katherine, Bolukbasi, Tolga, Parrish, Alicia, Lu, Shawn, Park, Jane, Venkatraman, Balaji, Talbert, Alice, Rosique, Lambert, Cheng, Yuchung, Sozanschi, Andrei, Paszke, Adam, Kumar, Praveen, Austin, Jessica, Li, Lu, Salama, Khalid, Kim, Wooyeol, Dukkipati, Nandita, Baryshnikov, Anthony, Kaplanis, Christos, Sheng, XiangHai, Chervonyi, Yuri, Unlu, Caglar, Casas, Diego de Las, Askham, Harry, Tunyasuvunakool, Kathryn, Gimeno, Felix, Poder, Siim, Kwak, Chester, Miecnikowski, Matt, Dimitriev, Alek, Parisi, Aaron, Liu, Dangyi, Tsai, Tomy, Shevlane, Toby, Kouridi, Christina, Garmon, Drew, Goedeckemeyer, Adrian, Brown, Adam R., Vijayakumar, Anitha, Elqursh, Ali, Jazayeri, Sadegh, Huang, Jin, Carthy, Sara Mc, Hoover, Jay, Kim, Lucy, Kumar, Sandeep, Chen, Wei, Biles, Courtney, Bingham, Garrett, Rosen, Evan, Wang, Lisa, Tan, Qijun, Engel, David, Pongetti, Francesco, de Cesare, Dario, Hwang, Dongseong, Yu, Lily, Pullman, Jennifer, Narayanan, Srini, Levin, Kyle, Gopal, Siddharth, Li, Megan, Aharoni, Asaf, Trinh, Trieu, Lo, Jessica, Casagrande, Norman, Vij, Roopali, Matthey, Loic, Ramadhana, Bramandia, Matthews, Austin, Carey, CJ, Johnson, Matthew, Goranova, Kremena, Shah, Rohin, Ashraf, Shereen, Dasgupta, Kingshuk, Larsen, Rasmus, Wang, Yicheng, Vuyyuru, Manish Reddy, Jiang, Chong, Ijazi, Joana, Osawa, Kazuki, Smith, Celine, Boppana, Ramya Sree, Bilal, Taylan, Koizumi, Yuma, Xu, Ying, Altun, Yasemin, Shabat, Nir, Bariach, Ben, Korchemniy, Alex, Choo, Kiam, Ronneberger, Olaf, Iwuanyanwu, Chimezie, Zhao, Shubin, Soergel, David, Hsieh, Cho-Jui, Cai, Irene, Iqbal, Shariq, Sundermeyer, Martin, Chen, Zhe, Bursztein, Elie, Malaviya, Chaitanya, Biadsy, Fadi, Shroff, Prakash, Dhillon, Inderjit, Latkar, Tejasi, Dyer, Chris, Forbes, Hannah, Nicosia, Massimo, Nikolaev, Vitaly, Greene, Somer, Georgiev, Marin, Wang, Pidong, Martin, Nina, Sedghi, Hanie, Zhang, John, Banzal, Praseem, Fritz, Doug, Rao, Vikram, Wang, Xuezhi, Zhang, Jiageng, Patraucean, Viorica, Du, Dayou, Mordatch, Igor, Jurin, Ivan, Liu, Lewis, Dubey, Ayush, Mohan, Abhi, Nowakowski, Janek, Ion, Vlad-Doru, Wei, Nan, Tojo, Reiko, Raad, Maria Abi, Hudson, Drew A., Keshava, Vaishakh, Agrawal, Shubham, Ramirez, Kevin, Wu, Zhichun, Nguyen, Hoang, Liu, Ji, Sewak, Madhavi, Petrini, Bryce, Choi, DongHyun, Philips, Ivan, Wang, Ziyue, Bica, Ioana, Garg, Ankush, Wilkiewicz, Jarek, Agrawal, Priyanka, Guo, Danhao, Xue, Emily, Shaik, Naseer, Leach, Andrew, Khan, Sadh MNM, Wiesinger, Julia, Jerome, Sammy, Chakladar, Abhishek, Wang, Alek Wenjiao, Ornduff, Tina, Abu, Folake, Ghaffarkhah, Alireza, Wainwright, Marcus, Cortes, Mario, Liu, Frederick, Maynez, Joshua, Terzis, Andreas, Samangouei, Pouya, Mansour, Riham, Kępa, Tomasz, Aubet, François-Xavier, Algymr, Anton, Banica, Dan, Weisz, Agoston, Orban, Andras, Senges, Alexandre, Andrejczuk, Ewa, Geller, Mark, Santo, Niccolo Dal, Anklin, Valentin, Merey, Majd Al, Baeuml, Martin, Strohman, Trevor, Bai, Junwen, Petrov, Slav, Wu, Yonghui, Hassabis, Demis, Kavukcuoglu, Koray, Dean, Jeffrey, and Vinyals, Oriol

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

In this report, we introduce the Gemini 1.5 family of models, representing the next generation of highly compute-efficient multimodal models capable of recalling and reasoning over fine-grained information from millions of tokens of context, including multiple long documents and hours of video and audio. The family includes two new models: (1) an updated Gemini 1.5 Pro, which exceeds the February version on the great majority of capabilities and benchmarks; (2) Gemini 1.5 Flash, a more lightweight variant designed for efficiency with minimal regression in quality. Gemini 1.5 models achieve near-perfect recall on long-context retrieval tasks across modalities, improve the state-of-the-art in long-document QA, long-video QA and long-context ASR, and match or surpass Gemini 1.0 Ultra's state-of-the-art performance across a broad set of benchmarks. Studying the limits of Gemini 1.5's long-context ability, we find continued improvement in next-token prediction and near-perfect retrieval (>99%) up to at least 10M tokens, a generational leap over existing models such as Claude 3.0 (200k) and GPT-4 Turbo (128k). Finally, we highlight real-world use cases, such as Gemini 1.5 collaborating with professionals on completing their tasks achieving 26 to 75% time savings across 10 different job categories, as well as surprising new capabilities of large language models at the frontier; when given a grammar manual for Kalamang, a language with fewer than 200 speakers worldwide, the model learns to translate English to Kalamang at a similar level to a person who learned from the same content.

Published
2024

7. Differential experiments using parallel alternative operations

Author

Calderini, Marco, Civino, Roberto, and Invernizzi, Riccardo

Subjects
Computer Science - Cryptography and Security, Computer Science - Information Theory, Mathematics - Group Theory, 20B35, 94A60, 68P25
Abstract

The use of alternative operations in differential cryptanalysis, or alternative notions of differentials, are lately receiving increasing attention. Recently, Civino et al. managed to design a block cipher which is secure w.r.t. classical differential cryptanalysis performed using XOR-differentials, but weaker with respect to the attack based on an alternative difference operation acting on the first s-box of the block. We extend this result to parallel alternative operations, i.e. acting on each s-box of the block. First, we recall the mathematical framework needed to define and use such operations. After that, we perform some differential experiments against a toy cipher and compare the effectiveness of the attack w.r.t. the one that uses XOR-differentials.

Published
2024

9. Thrombectomy in ischemic stroke patients with tandem occlusion in the posterior versus anterior circulation

Author

Cappellari, Manuel, Pracucci, Giovanni, Saia, Valentina, Mandruzzato, Nicolò, Valletta, Francesco, Sallustio, Fabrizio, Casetta, Ilaria, Fainardi, Enrico, Da Ros, Valerio, Diomedi, Marina, Capasso, Francesco, Nencini, Patrizia, Vallone, Stefano, Bigliardi, Guido, Tessitore, Agostino, La Spina, Paolino, Bracco, Sandra, Tassi, Rossana, Bergui, Mauro, Cerrato, Paolo, Ruggiero, Maria, Longoni, Marco, Castellan, Lucio, Malfatto, Laura, Saletti, Andrea, De Vito, Alessandro, Menozzi, Roberto, Scoditti, Umberto, Simonetti, Luigi, Zini, Andrea, Lafe, Elvis, Cavallini, Anna, Lazzarotti, Guido Andrea, Giannini, Nicola, Boghi, Andrea, Naldi, Andrea, Romano, Daniele, Napoletano, Rosa, Comai, Alessio, Franchini, Enrica, Cavasin, Nicola, Critelli, Adriana, Giorgianni, Andrea, Cariddi, Lucia Princiotta, Semeraro, Vittorio, Boero, Giovanni, Zimatore, Domenico Sergio, Petruzzellis, Marco, Biraschi, Francesco, Nicolini, Ettore, Pedicelli, Alessandro, Frisullo, Giovanni, Calzoni, Andrea, Tassinari, Tiziana, Gallesio, Ivan, Sepe, Federica, Filauri, Pietro, Sacco, Simona, Lozupone, Emilio, Rizzo, Annalisa, Besana, Michele, Giossi, Alessia, Pavia, Marco, Invernizzi, Paolo, Amistà, Pietro, Russo, Monia, Florio, Francesco, Inchingolo, Vincenzo, Filizzolo, Marco, Mannino, Marina, Mangiafico, Salvatore, and Toni, Danilo

Published
2024
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10. Accelerated Benders Decomposition for Variable-Height Transport Packaging Optimisation

Author

Lehmann, Alain, Kleiminger, Wilhelm, Invernizzi, Hakim, and Gautschi, Aurel

Subjects
Mathematics - Optimization and Control
Abstract

This paper tackles the problem of finding optimal variable-height transport packaging. The goal is to reduce the empty space left in a box when shipping goods to customers, thereby saving on filler and reducing waste. We cast this problem as a large-scale mixed integer problem (with over seven billion variables) and demonstrate various acceleration techniques to solve it efficiently in about three hours on a laptop. We present a KD-Tree algorithm to avoid exhaustive grid evaluation of the 3D-bin-packing, provide analytical transformations to accelerate the Benders decomposition, and an efficient implementation of the Benders sub problem for significant memory savings and a three order of magnitude runtime speedup.

Published
2023

11. Prioritised identification of structural classes of natural products from higher plants in the expedition of antimalarial drug discovery.

Author

Moyo, Phanankosi, Invernizzi, Luke, Mianda, Sephora, Rudolph, Wiehan, Andayi, Andrew, Crouch, Neil, Maharaj, Vinesh, and Wang, Mingxun

Subjects
Antiplasmodial drug resistance, Compound classes, Drug development, Malaria, Natural products, Phytochemicals, Plasmodium falciparum
Abstract

The emergence and spread of drug-recalcitrant Plasmodium falciparum parasites threaten to reverse the gains made in the fight against malaria. Urgent measures need to be taken to curb this impending challenge. The higher plant-derived sesquiterpene, quinoline alkaloids, and naphthoquinone natural product classes of compounds have previously served as phenomenal chemical scaffolds from which integral antimalarial drugs were developed. Historical successes serve as an inspiration for the continued investigation of plant-derived natural products compounds in search of novel molecular templates from which new antimalarial drugs could be developed. The aim of this study was to identify potential chemical scaffolds for malaria drug discovery following analysis of historical data on phytochemicals screened in vitro against P. falciparum. To identify these novel scaffolds, we queried an in-house manually curated database of plant-derived natural product compounds and their in vitro biological data. Natural products were assigned to different structural classes using NPClassifier. To identify the most promising chemical scaffolds, we then correlated natural compound class with bioactivity and other data, namely (i) potency, (ii) resistance index, (iii) selectivity index and (iv) physicochemical properties. We used an unbiased scoring system to rank the different natural product classes based on the assessment of their bioactivity data. From this analysis we identified the top-ranked natural product pathway as the alkaloids. The top three ranked super classes identified were (i) pseudoalkaloids, (ii) naphthalenes and (iii) tyrosine alkaloids and the top five ranked classes (i) quassinoids (of super class triterpenoids), (ii) steroidal alkaloids (of super class pseudoalkaloids) (iii) cycloeudesmane sesquiterpenoids (of super class triterpenoids) (iv) isoquinoline alkaloids (of super class tyrosine alkaloids) and (v) naphthoquinones (of super class naphthalenes). Launched chemical space of these identified classes of compounds was, by and large, distinct from that of legacy antimalarial drugs. Our study was able to identify chemical scaffolds with acceptable biological properties that are structurally different from current and previously used antimalarial drugs. These molecules have the potential to be developed into new antimalarial drugs.

Published
2023

12. Leveraging off higher plant phylogenetic insights for antiplasmodial drug discovery.

Author

Moyo, Phanankosi, Invernizzi, Luke, Mianda, Sephora, Rudolph, Wiehan, Andayi, Warren, Crouch, Neil, Maharaj, Vinesh, and Wang, Mingxun

Subjects
Drug-resistance, Malaria, Natural products, Phylogenetics, Plants, ‘Hot’ plants
Abstract

The antimalarial drug-resistance conundrum which threatens to reverse the great strides taken to curb the malaria scourge warrants an urgent need to find novel chemical scaffolds to serve as templates for the development of new antimalarial drugs. Plants represent a viable alternative source for the discovery of unique potential antiplasmodial chemical scaffolds. To expedite the discovery of new antiplasmodial compounds from plants, the aim of this study was to use phylogenetic analysis to identify higher plant orders and families that can be rationally prioritised for antimalarial drug discovery. We queried the PubMed database for publications documenting antiplasmodial properties of natural compounds isolated from higher plants. Thereafter, we manually collated compounds reported along with plant species of origin and relevant pharmacological data. We systematically assigned antiplasmodial-associated plant species into recognised families and orders, and then computed the resistance index, selectivity index and physicochemical properties of the compounds from each taxonomic group. Correlating the generated phylogenetic trees and the biological data of each clade allowed for the identification of 3 hot plant orders and families. The top 3 ranked plant orders were the (i) Caryophyllales, (ii) Buxales, and (iii) Chloranthales. The top 3 ranked plant families were the (i) Ancistrocladaceae, (ii) Simaroubaceae, and (iii) Buxaceae. The highly active natural compounds (IC50 ≤ 1 µM) isolated from these plant orders and families are structurally unique to the legacy antimalarial drugs. Our study was able to identify the most prolific taxa at order and family rank that we propose be prioritised in the search for potent, safe and drug-like antimalarial molecules.

Published
2023

13. Rehabilitation for Functioning and Quality of Life in Patients with Malignant Pleural Mesothelioma: A Scoping Review

Author

Lorenzo Lippi, Alessandro de Sire, Vittorio Aprile, Dario Calafiore, Arianna Folli, Fjorelo Refati, Andrea Balduit, Alessandro Mangogna, Mariia Ivanova, Konstantinos Venetis, Nicola Fusco, and Marco Invernizzi

Subjects
malignant pleural mesothelioma, physical function, muscle, complementary treatment, physical exercise, rehabilitation, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Malignant pleural mesothelioma (MPM) represents a significant clinical challenge due to limited therapeutic options and poor prognosis. Beyond mere survivorship, setting up an effective framework to improve functioning and quality of life is an urgent need in the comprehensive management of MPM patients. Therefore, this study aims to review the current understanding of MPM sequelae and the effectiveness of rehabilitative interventions in the holistic approach to MPM. A narrative review was conducted to summarize MPM sequelae and their impact on functioning, disability, and quality of life, focusing on rehabilitation interventions in MPM management and highlighting gaps in knowledge and areas for further investigation. Our findings showed that MPM patients experience debilitating symptoms, including fatigue, dyspnea, pain, and reduced exercise tolerance, decreasing quality of life. Supportive and rehabilitative interventions, including pulmonary rehabilitation, physical exercise improvement, psychological support, pain management, and nutritional supplementation, seem promising approaches in relieving symptoms and improving quality of life but require further research. These programs emphasize the pivotal synergy among patient-tailored plans, multidisciplinary team involvement, and disease-specific focus. Despite advancements in therapeutic management, MPM remains a challenging disease with limited effective interventions that should be adapted to disease progressions. Rehabilitative strategies are essential to mitigate symptoms and improve the quality of life in MPM patients. Further research is needed to establish evidence-based guidelines for rehabilitative interventions tailored to the unique needs of MPM patients.

Published
2024
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14. Generalized Power Attacks against Crypto Hardware using Long-Range Deep Learning

Author

Bursztein, Elie, Invernizzi, Luca, Král, Karel, Moghimi, Daniel, Picod, Jean-Michel, and Zhang, Marina

Subjects
Computer Science - Cryptography and Security
Abstract

To make cryptographic processors more resilient against side-channel attacks, engineers have developed various countermeasures. However, the effectiveness of these countermeasures is often uncertain, as it depends on the complex interplay between software and hardware. Assessing a countermeasure's effectiveness using profiling techniques or machine learning so far requires significant expertise and effort to be adapted to new targets which makes those assessments expensive. We argue that including cost-effective automated attacks will help chip design teams to quickly evaluate their countermeasures during the development phase, paving the way to more secure chips. In this paper, we lay the foundations toward such automated system by proposing GPAM, the first deep-learning system for power side-channel analysis that generalizes across multiple cryptographic algorithms, implementations, and side-channel countermeasures without the need for manual tuning or trace preprocessing. We demonstrate GPAM's capability by successfully attacking four hardened hardware-accelerated elliptic-curve digital-signature implementations. We showcase GPAM's ability to generalize across multiple algorithms by attacking a protected AES implementation and achieving comparable performance to state-of-the-art attacks, but without manual trace curation and within a limited budget. We release our data and models as an open-source contribution to allow the community to independently replicate our results and build on them.

Published
2023

15. Seladelpar efficacy and safety at 3 months in patients with primary biliary cholangitis: ENHANCE, a phase 3, randomized, placebo-controlled study.

Author

Hirschfield, Gideon M, Shiffman, Mitchell L, Gulamhusein, Aliya, Kowdley, Kris V, Vierling, John M, Levy, Cynthia, Kremer, Andreas E, Zigmond, Ehud, Andreone, Pietro, Gordon, Stuart C, Bowlus, Christopher L, Lawitz, Eric J, Aspinall, Richard J, Pratt, Daniel S, Raikhelson, Karina, Gonzalez-Huezo, Maria S, Heneghan, Michael A, Jeong, Sook-Hyang, Ladrón de Guevara, Alma L, Mayo, Marlyn J, Dalekos, George N, Drenth, Joost PH, Janczewska, Ewa, Leggett, Barbara A, Nevens, Frederik, Vargas, Victor, Zuckerman, Eli, Corpechot, Christophe, Fassio, Eduardo, Hinrichsen, Holger, Invernizzi, Pietro, Trivedi, Palak J, Forman, Lisa, Jones, David EJ, Ryder, Stephen D, Swain, Mark G, Steinberg, Alexandra, Boudes, Pol F, Choi, Yun-Jung, McWherter, Charles A, and ENHANCE Study Group*

Subjects
ENHANCE Study Group*, Humans, Liver Cirrhosis, Biliary, Pruritus, Acetates, Ursodeoxycholic Acid, Alkaline Phosphatase, Cholagogues and Choleretics, Digestive Diseases, Liver Disease, Rare Diseases, Clinical Trials and Supportive Activities, Clinical Research, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Medical Biochemistry and Metabolomics, Clinical Sciences, Immunology, Gastroenterology & Hepatology
Abstract

Background and aimsENHANCE was a phase 3 study that evaluated efficacy and safety of seladelpar, a selective peroxisome proliferator-activated receptor-δ (PPAR) agonist, versus placebo in patients with primary biliary cholangitis with inadequate response or intolerance to ursodeoxycholic acid (UDCA).Approach and resultsPatients were randomized 1:1:1 to oral seladelpar 5 mg (n=89), 10 mg (n=89), placebo (n=87) daily (with UDCA, as appropriate). Primary end point was a composite biochemical response [alkaline phosphatase (ALP) < 1.67×upper limit of normal (ULN), ≥15% ALP decrease from baseline, and total bilirubin ≤ ULN] at month 12. Key secondary end points were ALP normalization at month 12 and change in pruritus numerical rating scale (NRS) at month 6 in patients with baseline score ≥4. Aminotransferases were assessed. ENHANCE was terminated early following an erroneous safety signal in a concurrent, NASH trial. While blinded, primary and secondary efficacy end points were amended to month 3. Significantly more patients receiving seladelpar met the primary end point (seladelpar 5 mg: 57.1%, 10 mg: 78.2%) versus placebo (12.5%) ( p < 0.0001). ALP normalization occurred in 5.4% ( p =0.08) and 27.3% ( p < 0.0001) of patients receiving 5 and 10 mg seladelpar, respectively, versus 0% receiving placebo. Seladelpar 10 mg significantly reduced mean pruritus NRS versus placebo [10 mg: -3.14 ( p =0.02); placebo: -1.55]. Alanine aminotransferase decreased significantly with seladelpar versus placebo [5 mg: 23.4% ( p =0.0008); 10 mg: 16.7% ( p =0.03); placebo: 4%]. There were no serious treatment-related adverse events.ConclusionsPatients with primary biliary cholangitis (PBC) with inadequate response or intolerance to UDCA who were treated with seladelpar 10 mg had significant improvements in liver biochemistry and pruritus. Seladelpar appeared safe and well tolerated.

Published
2023

16. Early-Life Critical Windows of Susceptibility to Manganese Exposure and Sex-Specific Changes in Brain Connectivity in Late Adolescence.

Author

Rechtman, Elza, Navarro, Esmeralda, de Water, Erik, Tang, Cheuk, Curtin, Paul, Papazaharias, Demetrios, Ambrosi, Claudia, Mascaro, Lorella, Cagna, Giuseppa, Gasparotti, Roberto, Invernizzi, Azzurra, Reichenberg, Abraham, Austin, Christine, Arora, Manish, Lucchini, Roberto, Wright, Robert, Placidi, Donatella, Horton, Megan, and Smith, Don

Subjects
Adolescence, Critical windows, Functional connectivity, MRI, Manganese, Sex-specific
Abstract

BACKGROUND: Early-life environmental exposures during critical windows (CWs) of development can impact life course health. Exposure to neuroactive metals such as manganese (Mn) during prenatal and early postnatal CWs may disrupt typical brain development, leading to persistent behavioral changes. Males and females may be differentially vulnerable to Mn, presenting distinctive CWs to Mn exposure. METHODS: We used magnetic resonance imaging to investigate sex-specific associations between early-life Mn uptake and intrinsic functional connectivity in adolescence. A total of 71 participants (15-23 years old; 53% female) from the Public Health Impact of Manganese Exposure study completed a resting-state functional magnetic resonance imaging scan. We estimated dentine Mn concentrations at prenatal, postnatal, and early childhood periods using laser ablation-inductively coupled plasma-mass spectrometry. We performed seed-based correlation analyses to investigate the moderating effect of sex on the associations between Mn and intrinsic functional connectivity adjusting for age and socioeconomic status. RESULTS: We identified significant sex-specific associations between dentine Mn at all time points and intrinsic functional connectivity in brain regions involved in cognitive and motor function: 1) prenatal: dorsal striatum, occipital/frontal lobes, and middle frontal gyrus; 2) postnatal: right putamen and cerebellum; and 3) early childhood: putamen and occipital, frontal, and temporal lobes. Network associations differed depending on exposure timing, suggesting that different brain networks may present distinctive CWs to Mn. CONCLUSIONS: These findings suggest that the developing brain is vulnerable to Mn exposure, with effects lasting through late adolescence, and that females and males are not equally vulnerable to these effects. Future studies should investigate cognitive and motor outcomes related to these associations.

Published
2023

23. Multiplication polynomials for elliptic curves over finite local rings

Author

Invernizzi, Riccardo and Taufer, Daniele

Subjects
Mathematics - Number Theory, Computer Science - Cryptography and Security, 11G07, 11T55, 11C08, 13B25
Abstract

For a given elliptic curve $E$ over a finite local ring, we denote by $E^{\infty}$ its subgroup at infinity. Every point $P \in E^{\infty}$ can be described solely in terms of its $x$-coordinate $P_x$, which can be therefore used to parameterize all its multiples $nP$. We refer to the coefficient of $(P_x)^i$ in the parameterization of $(nP)_x$ as the $i$-th multiplication polynomial. We show that this coefficient is a degree-$i$ rational polynomial without a constant term in $n$. We also prove that no primes greater than $i$ may appear in the denominators of its terms. As a consequence, for every finite field $\mathbb{F}_q$ and any $k\in\mathbb{N}^*$, we prescribe the group structure of a generic elliptic curve defined over $\mathbb{F}_q[X]/(X^k)$, and we show that their ECDLP on $E^{\infty}$ may be efficiently solved.

Published
2023
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24. Rigid Body Flows for Sampling Molecular Crystal Structures

Author

Köhler, Jonas, Invernizzi, Michele, de Haan, Pim, and Noé, Frank

Subjects
Computer Science - Machine Learning, Physics - Chemical Physics, Physics - Computational Physics, Statistics - Machine Learning
Abstract

Normalizing flows (NF) are a class of powerful generative models that have gained popularity in recent years due to their ability to model complex distributions with high flexibility and expressiveness. In this work, we introduce a new type of normalizing flow that is tailored for modeling positions and orientations of multiple objects in three-dimensional space, such as molecules in a crystal. Our approach is based on two key ideas: first, we define smooth and expressive flows on the group of unit quaternions, which allows us to capture the continuous rotational motion of rigid bodies; second, we use the double cover property of unit quaternions to define a proper density on the rotation group. This ensures that our model can be trained using standard likelihood-based methods or variational inference with respect to a thermodynamic target density. We evaluate the method by training Boltzmann generators for two molecular examples, namely the multi-modal density of a tetrahedral system in an external field and the ice XI phase in the TIP4P water model. Our flows can be combined with flows operating on the internal degrees of freedom of molecules and constitute an important step towards the modeling of distributions of many interacting molecules., Comment: International Conference on Machine Learning, 2023

Published
2023

25. Antioxidant capacity and peptidomic analysis of in vitro digested Camelina sativa L. Crantz and Cynara cardunculus co-products

Author

Davide Lanzoni, Francesca Grassi Scalvini, Elena Petrosillo, Simona Nonnis, Gabriella Tedeschi, Giovanni Savoini, Arianna Buccioni, Guido Invernizzi, Antonella Baldi, and Carlotta Giromini

Subjects
Antioxidant activity, Bioactive peptides, Camelina, Cardoon, NanoLC-MS/MS, Peptidomics, Medicine, Science
Abstract

Abstract In recent decades, the food system has been faced with the significant problem of increasing food waste. Therefore, the feed industry, supported by scientific research, is attempting to valorise the use of discarded biomass as co-products for the livestock sector, in line with EU objectives. In parallel, the search for functional products that can ensure animal health and performances is a common fundamental goal for both animal husbandry and feeding. In this context, camelina cake (CAMC), cardoon cake (CC) and cardoon meal (CM), due valuable nutritional profile, represent prospective alternatives. Therefore, the aim of this work was to investigate the antioxidant activity of CAMC, CC and CM following in vitro digestion using 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS), Ferric reducing antioxidant power (FRAP) and oxygen radical absorbance capacity (ORAC) assays. Total phenolic content (TPC) and angiotensin converting enzyme (ACE) inhibitory activity, actively involved in modulating antioxidant properties, were also studied. Further, a peptidomic analysis was adopted to substantiate the presence of bioactive peptides after in vitro digestion. The results obtained confirmed an interesting nutritional profile of CAMC, CC and CM and relevant antioxidant and ACE inhibitory activities. In particular, considering antioxidant profile, CM and CC revealed a significantly higher (10969.80 ± 18.93 mg TE/100 g and 10451.40 ± 149.17 mg TE/100 g, respectively; p

Published
2024
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26. Skipping the Replica Exchange Ladder with Normalizing Flows

Author

Invernizzi, Michele, Krämer, Andreas, Clementi, Cecilia, and Noé, Frank

Subjects
Physics - Computational Physics
Abstract

We combine replica exchange (parallel tempering) with normalizing flows, a class of deep generative models. These two sampling strategies complement each other, resulting in an efficient strategy for sampling molecular systems characterized by rare events, which we call learned replica exchange (LREX). In LREX, a normalizing flow is trained to map the configurations of the fastest-mixing replica into configurations belonging to the target distribution, allowing direct exchanges between the two without the need to simulate intermediate replicas. This can significantly reduce the computational cost compared to standard replica exchange. The proposed method also offers several advantages with respect to Boltzmann generators that directly use normalizing flows to sample the target distribution. We apply LREX to some prototypical molecular dynamics systems, highlighting the improvements over previous methods.

Published
2022
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27. First line therapy in stage IV BRAF mutated colorectal cancer

Author

Fausto Petrelli, Maria Antista, Lorenzo Dottorini, Alessandro Russo, Marcella Arru, Roberta Invernizzi, Mariangela Manzoni, Chiara Cremolini, Alberto Zaniboni, Ornella Garrone, Gianluca Tomasello, and Michele Ghidini

Subjects
Colorectal cancer, BRAF mutation, First-line chemotherapy, Survival, Network meta-analysis, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Introduction: The molecular profile of colorectal cancer (CRC) plays a crucial role in understanding patient prognosis and treatment response. Within CRC, a distinct subgroup can be identified by the presence of the BRAF V600E mutation. This specific mutation, classified as Class I of BRAF mutations, is known to be associated with a poor prognosis and resistance to standard therapy. To determine the most effective treatment approach for this specific subgroup of CRC, we conducted a network meta-analysis (NMA) to compare various pharmacological interventions and evaluate their relative effectiveness in BRAF-mutated CRCs. Materials and methods: On July 31, 2023, we conducted a systematic search of PubMed, Cochrane Central Register of Controlled Trials, and Embase. The inclusion criteria were as follows: 1) reporting of outcomes in patients with BRAF-mutated CRC who underwent first-line chemotherapy; 2) reporting of survival information as hazard ratios (HR); and 3) publication in English. The data were combined using HRs for overall and progression-free survival (OS and PFS) using random-effects models. NMA was performed under the Bayesian framework, utilizing the GeMTC package. The relative rankings of the treatments were determined using SUCRA scores. Results: A total of 16 studies were included. When compared to standard chemotherapy (CT) doublets (such as FOLFOX or FOLFIRI), none of the comparison arms demonstrated a gain in OS. CT doublet + bevacizumab did not show significant superiority over either CT doublet alone or 5FU/capecitabine + bevacizumab. FOLFOXIRI and FOLFOXIRI + bevacizumab did not show superiority over any other treatment schedule that was compared. CT doublets + bevacizumab had the highest SUCRA score (0.87), followed by single-agent fluoropyrimidines + bevacizumab (0.61), and FOLFOXIRI (0.56). Regarding PFS, no regimen was found to be superior to the combination of CT doublet plus bevacizumab. However, FOLFOXIRI + bevacizumab + atezolizumab showed a tendency towards better results (HR = 0.26, 95 % CI 0.05–1.1). Conclusions: Our review suggests that a CT doublet with bevacizumab is the most favorable option for OS. However, a reasonable alternative could be a triplet CT without bevacizumab.

Published
2024
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29. Honey bee populations surviving Varroa destructor parasitism in Latin America and their mechanisms of resistance

Author

Ernesto Guzman-Novoa, Miguel Corona, Mohamed Alburaki, Francisco José Reynaldi, Ciro Invernizzi, Gregorio Fernández de Landa, and Matías Maggi

Subjects
Apis mellifera, Varroa destructor, adaptation, Africanized honey bee, mechanisms of resistance, host-parasite, Evolution, QH359-425, Ecology, QH540-549.5
Abstract

The honey bee (Apis mellifera) parasitic mite, Varroa destructor, is considered one of the main causes of colony losses in European honey bee (EHB) populations around the world. However, some EHB and Africanized honey bee (AHB) populations (derived from the African subspecies A. m. scutellata) that inhabit tropical and subtropical regions of the Americas, have survived varroa mite infestations in the absence of acaricide treatments. It is conceivable to expect that these honey bee populations, which have been subjected to natural selection over decades, would have developed resistance against V. destructor or possess pre-existing adaptations that allow them to survive mite parasitism. Here, we present a comprehensive literature review describing the spread of V. destructor and the honey bee populations occurring in Latin America (LA), and summarize the evidence of resistance of those populations to V. destructor. We also analyze reports describing the potential mechanisms of mite resistance and how they operate in those honey bee populations. Studies of a few EHB, as well as of numerous AHB populations exhibiting resistance to V. destructor in LA, unveil the existence of evolutionary adaptations that restrain V. destructor population growth and provide insight into the current host-parasite relationship. This review supports the notion that selective breeding of local honey bee populations from LA could be a viable strategy to manage varroa mite infestations in colonies.

Published
2024
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30. Analisi di un processo didattico formativo multi-sport per un’educazione sportiva sostenibile

Author

Pietro Luigi Invernizzi, Marta Rigon, Gabriele Signorini, Domenico Cherubini, and Raffaele Scurati

Subjects
Insegnante, Rugby, Comunicazione, Competenze didattiche, Physical literacy, Education
Abstract

Oggetto del presente lavoro è il tema della formazione dell’insegnante sportivo. L’argomento verrà inizialmente approcciato con metafore al fine di meglio comprendere alcuni concetti del percorso formativo quali il processo necessario al suo compimento, la forma didattica (arte o razionalità?), la competenza (tecnica o empatia?) e l’approccio comunicativo dell’insegnante. Successivamente sarà illustrato un progetto formativo in corso di svolgimento basato su un modello integrato multi-sportivo, nella sua fase sperimentale inizialmente orientata all'istruttore federale di rugby, il cui successo, sostenibilità, e trasferibilità didattica nei corsi per istruttori di sport giovanile verrà verificata con metodo scientifico, del quale è descritto il protocollo di studio. L’esito dell’iniziativa potrà confermare l’adeguatezza del metodo per raggiungere gli obiettivi della formazione dei professionisti nell’ambito motorio-sportivo e, in forma più estesa, per la promozione della physical literacy dei destinatari finali di suddetta formazione, vale a dire i bambini.

Published
2024

31. Experimental isochoric apparatus for bubble points determination: Application to CO2 binary mixtures as advanced working fluids

Author

M. Doninelli, G. Di Marcoberardino, C. M. Invernizzi, and P. Iora

Subjects
CO2 mixtures, Vapour–liquid equilibrium, Bubble points, Transcritical cycles, Experimental campaign, Heat, QC251-338.5
Abstract

Carbon dioxide binary mixtures are increasingly considered as working fluids in transcritical power cycles, due to the capability to perform liquid-phase compression even at high environmental temperatures. However, a robust thermodynamic model is essential for optimal and reliable design conditions. It is widely recognised that fine-tuning the equation of state with experimental vapour-liquid equilibrium data of the mixture significantly enhances its reliability.In this work, a new apparatus dedicated to vapour-liquid equilibrium measurements of mixtures is presented. The proposed method consists of a constant-volume system, where bubble points are identified from the divergence of slope of the isochoric lines between the two-phase and liquid regions, in the temperature-pressure plane. The temperature and pressure limits of the apparatus are 503 K and 25 MPa.Bubble points of CO2 binary mixtures with hexafluorobenzene (C6F6) and n-pentane (C5H12) have been measured and compared with previous literature data for validation purposes. Then, the CO2 mixture with octafluorocyclobutane (c-C4F8) is experimentally studied, addressing a literature gap in bubble point data. The data are used to calibrate the thermodynamic model, leading to affordable design conditions of the power cycle compared to the non-optimised thermodynamics scenario, in a concentrated solar power tower plant.

Published
2024
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32. Generalized Power Attacks against Crypto Hardware using Long-Range Deep Learning

Author

Elie Bursztein, Luca Invernizzi, Karel Král, Daniel Moghimi, Jean-Michel Picod, and Marina Zhang

Subjects
Deep Learning, Side-Channel Analysis, AES, ECC, Computer engineering. Computer hardware, TK7885-7895, Information technology, T58.5-58.64
Abstract

To make cryptographic processors more resilient against side-channel attacks, engineers have developed various countermeasures. However, the effectiveness of these countermeasures is often uncertain, as it depends on the complex interplay between software and hardware. Assessing a countermeasure’s effectiveness using profiling techniques or machine learning so far requires significant expertise and effort to be adapted to new targets which makes those assessments expensive. We argue that including cost-effective automated attacks will help chip design teams to quickly evaluate their countermeasures during the development phase, paving the way to more secure chips. In this paper, we lay the foundations toward such automated system by proposing GPAM, the first deep-learning system for power side-channel analysis that generalizes across multiple cryptographic algorithms, implementations, and side-channel countermeasures without the need for manual tuning or trace preprocessing. We demonstrate GPAM’s capability by successfully attacking four hardened hardware-accelerated elliptic-curve digital-signature implementations. We showcase GPAM’s ability to generalize across multiple algorithms by attacking a protected AES implementation and achieving comparable performance to state-of-the-art attacks, but without manual trace curation and within a limited budget. We release our data and models as an open-source contribution to allow the community to independently replicate our results and build on them.

Published
2024
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33. Evaluation of three different bottom boards in honeybee hives for the control of Varroa destructor

Author

Pablo Juri, Enrique Nogueira, José Anzola, Valentina Rodríguez-Batista, Belén Branchiccela, and Ciro Invernizzi

Subjects
Varroa destructor, colony losses, bottom boards, integrated pest management, beekeeping innovations, beekeeping sustainability, Ecology, QH540-549.5, Science
Abstract

IntroductionVarroa destructor stands as the primary global pest of honey bees, inflicting direct harm on bees while also acting as a vector for a multitude of viruses. Integrated pest management is widely recognized as the optimal strategy for minimizing acaricide application. Designed bottom boards that can limit the growth of the mite population by removing them from the hive and preventing their return and reinfestation of the colony show promising potential.MethodsThe aim of this study was to compare Varroa population growth by employing three different types of bottom boards. An apiary of 55 colonies was randomly divided into five groups according to the bottom board they had: 1) tubular bottom board, 2) screen bottom board, 3) sticky bottom board, 4) conventional bottom board with a permanent treatment with acaricide (positive control), and 5) conventional bottom board (negative control). Varroa infestation level in bees, colony strength (bee and brood population), and honey reserves were determined between April and December (between autumn and spring in the southern hemisphere).ResultsColonies that had sticky bottom boards had approximately 50% less Varroa infestation than colonies with conventional bottom boards at the end of the study. Varroa infestation levels did not differ significantly between the tubular, screen, and conventional bottom boards. Colony strength was similar in all groups. No differences were observed in honey production between colonies from different groups.DiscussionThe use of sticky bottom boards was the most promising board to limit Varroa population growth and prevent colonies' reinfestation. This result encourages future studies to analyze the incorporation of this strategy in integrated pest management programs.

Published
2024
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34. Making inroads to precision medicine for the treatment of autoimmune diseases: Harnessing genomic studies to better diagnose and treat complex disorders

Author

Baglaenko, Yuriy, Wagner, Catriona, Bhoj, Vijay G, Brodin, Petter, Gershwin, M Eric, Graham, Daniel, Invernizzi, Pietro, Kidd, Kenneth K, Korsunsky, Ilya, Levy, Michael, Mammen, Andrew L, Nizet, Victor, Ramirez-Valle, Francisco, Stites, Edward C, Williams, Marc S, Wilson, Michael, Rose, Noel R, Ladd, Virginia, and Sirota, Marina

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Autoimmune Disease, Biotechnology, Human Genome, Brain Disorders, Prevention, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Generic health relevance, Good Health and Well Being, Autoimmunity, bioinformatics, data integration, diagnosis, genomics
Abstract

Precision Medicine is an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle. Autoimmune diseases are those in which the body's natural defense system loses discriminating power between its own cells and foreign cells, causing the body to mistakenly attack healthy tissues. These conditions are very heterogeneous in their presentation and therefore difficult to diagnose and treat. Achieving precision medicine in autoimmune diseases has been challenging due to the complex etiologies of these conditions, involving an interplay between genetic, epigenetic, and environmental factors. However, recent technological and computational advances in molecular profiling have helped identify patient subtypes and molecular pathways which can be used to improve diagnostics and therapeutics. This review discusses the current understanding of the disease mechanisms, heterogeneity, and pathogenic autoantigens in autoimmune diseases gained from genomic and transcriptomic studies and highlights how these findings can be applied to better understand disease heterogeneity in the context of disease diagnostics and therapeutics.

Published
2023

35. Topological network properties of resting-state functional connectivity patterns are associated with metal mixture exposure in adolescents.

Author

Invernizzi, Azzurra, Rechtman, Elza, Oluyemi, Kristie, Renzetti, Stefano, Curtin, Paul, Colicino, Elena, Ambrosi, Claudia, Mascaro, Lorella, Patrono, Alessandra, Corbo, Daniele, Cagna, Giuseppa, Gasparotti, Roberto, Reichenberg, Abraham, Tang, Cheuk, Smith, Donald, Placidi, Donatella, Lucchini, Roberto, Wright, Robert, and Horton, Megan

Subjects
exposure, global and local efficiency, graph theory, neurotoxic metals, resting state–fMRI, topological network properties
Abstract

INTRODUCTION: Adolescent exposure to neurotoxic metals adversely impacts cognitive, motor, and behavioral development. Few studies have addressed the underlying brain mechanisms of these metal-associated developmental outcomes. Furthermore, metal exposure occurs as a mixture, yet previous studies most often consider impacts of each metal individually. In this cross-sectional study, we investigated the relationship between exposure to neurotoxic metals and topological brain metrics in adolescents. METHODS: In 193 participants (53% females, ages: 15-25 years) enrolled in the Public Health Impact of Metals Exposure (PHIME) study, we measured concentrations of four metals (manganese, lead, copper, and chromium) in multiple biological media (blood, urine, hair, and saliva) and acquired resting-state functional magnetic resonance imaging scans. Using graph theory metrics, we computed global and local efficiency (global:GE; local:LE) in 111 brain areas (Harvard Oxford Atlas). We used weighted quantile sum (WQS) regression models to examine association between metal mixtures and each graph metric (GE or LE), adjusted for sex and age. RESULTS: We observed significant negative associations between the metal mixture and GE and LE [βGE = -0.076, 95% CI (-0.122, -0.031); βLE= -0.051, 95% CI (-0.095, -0.006)]. Lead and chromium measured in blood contributed most to this association for GE, while chromium measured in hair contributed the most for LE. DISCUSSION: Our results suggest that exposure to this metal mixture during adolescence reduces the efficiency of integrating information in brain networks at both local and global levels, informing potential neural mechanisms underlying the developmental toxicity of metals. Results further suggest these associations are due to combined joint effects to different metals, rather than to a single metal.

Published
2023

36. Guarantees for Spontaneous Synchronization on Random Geometric Graphs

Author

Abdalla, Pedro, Bandeira, Afonso S., and Invernizzi, Clara

Subjects
Mathematics - Probability, Mathematics - Combinatorics, Mathematics - Optimization and Control
Abstract

The Kuramoto model is a classical mathematical model in the field of non-linear dynamical systems that describes the evolution of coupled oscillators in a network that may reach a synchronous state. The relationship between the network's topology and whether the oscillators synchronize is a central question in the field of synchronization, and random graphs are often employed as a proxy for complex networks. On the other hand, the random graphs on which the Kuramoto model is rigorously analyzed in the literature are homogeneous models and fail to capture the underlying geometric structure that appears in several examples. In this work, we leverage tools from random matrix theory, random graphs, and mathematical statistics to prove that the Kuramoto model on a random geometric graph on the sphere synchronizes with probability tending to one as the number of nodes tends to infinity. To the best of our knowledge, this is the first rigorous result for the Kuramoto model on random geometric graphs.

Published
2022

37. Rare Event Kinetics from Adaptive Bias Enhanced Sampling

Author

Ray, Dhiman, Ansari, Narjes, Rizzi, Valerio, Invernizzi, Michele, and Parrinello, Michele

Subjects
Physics - Chemical Physics
Abstract

We introduce a novel enhanced sampling approach named OPES flooding for calculating the kinetics of rare events from atomistic molecular dynamics simulation. This method is derived from the On-the-fly-Probability-Enhanced-Sampling (OPES) approach [Invernizzi and Parrinello, JPC Lett. 2020], which has been recently developed for calculating converged free energy surfaces for complex systems. In this paper, we describe the theoretical details of the OPES flooding technique and demonstrate the application on three systems of increasing complexity: barrier crossing in a two-dimensional double well potential, conformational transition in the alanine dipeptide in gas phase, and the folding and unfolding of the chignolin polypeptide in aqueous environment. From extensive tests, we show that the calculation of accurate kinetics not only requires the transition state to be bias-free, but the amount of bias deposited should also not exceed the effective barrier height measured along the chosen collective variables. In this vein, the possibility of computing rates from biasing suboptimal order parameters has also been explored. Furthermore, we describe the choice of optimum parameter combinations for obtaining accurate results from limited computational effort.

Published
2022
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39. Mechanical thrombectomy in patients with heart failure: the Italian registry of Endovascular Treatment in Acute Stroke

Author

Gentile, Luana, Pracucci, Giovanni, Saia, Valentina, Falcou, Anne, Biraschi, Francesco, Zini, Andrea, Simonetti, Luigi, Riva, Letizia, Bigliardi, Guido, Vallone, Stefano, Nencini, Patrizia, Limbucci, Nicola, Diomedi, Marina, Da Ros, Valerio, Longoni, Marco, Ruggiero, Maria, Tassinari, Tiziana, Allegretti, Luca, Cerrato, Paolo, Rubino, Elisa, Bergui, Mauro, Cavallo, Roberto, Naldi, Andrea, Comelli, Chiara, Cappellari, Manuel, Zivelonghi, Cecilia, Plebani, Mauro, De Vito, Alessandro, Merli, Nicola, Saletti, Andrea, Musolino, Rosa Fortunata, Ferraù, Ludovica, Vinci, Sergio Lucio, Sacco, Simona, Orlandi, Berardino, De Santis, Federica, Filauri, Pietro, Ruiz, Luigi, Sepe, Federica Nicoletta, Gallesio, Ivan, Petruzzellis, Marco, Chiumarulo, Luigi, Sangalli, Davide, Salmaggi, Andrea, Filizzolo, Marco, Moller, Jessica, Melis, Maurizio, Comelli, Simone, Magoni, Mauro, Gilberti, Nicola, Gasparotti, Roberto, Invernizzi, Paolo, Pavia, Marco, Pinto, Vincenza, Laspada, Salvatore, Marcheselli, Simona, Ajello, Daniele, Viaro, Federica, Baracchini, Claudio, Causin, Francesco, Giannini, Nicola, Caselli, Maria Chiara, Mancuso, Michelangelo, Cosottini, Mirco, Scoditti, Umberto, Menozzi, Roberto, Russo, Monia, Amistá, Pietro, Napoletano, Rosa, Romano, Daniele Giuseppe, Tassi, Rossana, Bracco, Sandra, Carimati, Federico, Versino, Maurizio, Giorgianni, Andrea, De Boni, Antonella, Fasano, Antonio, Barbarini, Leonardo, Paladini, Adriana, Franchini, Enrica, Dall’Ora, Elisa, Comai, Alessio, Giovanni, Frisullo, Pedicelli, Alessandro, Sallustio, Fabrizio, Casetta, Ilaria, Fainardi, Enrico, Mangiafico, Salvatore, and Toni, Danilo

Published
2023
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40. Initial response and 12-month outcomes after commencing dexamethasone or vascular endothelial growth factor inhibitors for retinal vein occlusion in the FRB registry

Author

Gonzaga Garay-Aramburu, Adrian Hunt, Carolina Arruabarrena, Hemal Mehta, Alessandro Invernizzi, Pierre-Henry Gabrielle, Tremeur Guillaumie, Benjamin Wolff, Mark C. Gillies, and Javier Zarranz-Ventura

Subjects
Medicine, Science
Abstract

Abstract To compare baseline characteristics, initial response and 12-month efficacy and safety outcomes in eyes with branch and central retinal vein occlusion (BRVO and CRVO) treated with dexamethasone implants (DEX) or anti-vascular endothelial growth factor (anti-VEGF) we performed a multi-centre, retrospective and observational study using Fight Retinal Blindness! Registry. Of 725 eligible eyes, 10% received DEX initially with very frequent adjunctive anti-VEGF (BRVO-DEX 49%, CRVO-DEX 60%). The primary outcome of mean adjusted change in VA at 12 months with DEX and anti-VEGF initiated groups were not statistically significantly different (BRVO: DEX + 6.7, anti-VEGF + 10.6 letters; CRVO: DEX + 2.8, anti-VEGF + 6.8 letters). DEX initiated eyes had fewer injections and visits than anti-VEGF initiated eyes. The BRVO-DEX eyes had greater initial mean changes in VA and central subfield thickness (CST) and achieved inactivity sooner than BRVO-anti-VEGF eyes. The mean CST after the first three months was above 350 μm in all but the BRVO-anti-VEGF group, suggesting undertreatment. In routine care DEX is uncommonly used when available as initial treatment of BRVO and CRVO requiring supplemental anti-VEGF within the first year. The 12-month outcomes were similar, but DEX initiated eyes had fewer injections and visits but more episodes of raised IOP Vs those starting anti-VEGF.

Published
2024
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41. Posiciones de sectores sociales frente a las nanotecnologías

Author

Guillermo Foladori and Noelia Invernizzi

Subjects
nanopartículas, riesgos, políticas públicas, ongs, sindicatos, Social Sciences, Political science
Abstract

El crecimiento exponencial de las nanotecnologías desde comienzos de este siglo ha planteado cuestionamientos relativos a riesgos a la salud, al ambiente, así como implicaciones sociales como concentración del capital, desempleo y otros. Frente a estos problemas los diferentes grupos y clases sociales se han posicionado científica y políticamente. Este texto expone un abanico de diferentes posiciones y explica su íntima relación con la situación de clase y facciones que las respaldan. Se trata de un mapa teórico de utilidad para las políticas públicas de ciencia y tecnología así como las actividades de organizaciones sociales y sindicales.

Published
2024
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43. Differential experiments using parallel alternative operations

Author

Calderini Marco, Civino Roberto, and Invernizzi Riccardo

Subjects
differential cryptanalysis, alternative operations, distinguisher, block ciphers, 20b35, 94a60, 68p25, Mathematics, QA1-939
Abstract

The use of alternative operations in differential cryptanalysis, or alternative notions of differentials, is lately receiving increasing attention. Recently, Civino et al. managed to design a block cipher that is secure with respect to the classical differential cryptanalysis performed using XOR-differentials, but weaker with respect to the attack based on an alternative difference operation acting on the first s-box of the block. We extend this result to parallel alternative operations, i.e. acting on each s-box of the block. First, we recall the mathematical framework needed to define and use such operations. After that, we perform some differential experiments against a toy cipher and compare the effectiveness of the attack with respect to the one that uses XOR-differentials.

Published
2024
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44. Hypoalbuminemia and Risk of Portal Vein Thrombosis in Cirrhosis

Author

Roberto Cangemi, Valeria Raparelli, Giovanni Talerico, Stefania Basili, Francesco Violi, Palasciano Giuseppe, D’Alitto Felicia, Palmieri Vincenzo Ostilio, Santovito Daniela, Di Michele Dario, Croce Giuseppe, Sacerdoti David, Brocco Silvia, Fasolato Silvano, Cecchetto Lara, Bombonato Giancarlo, Bertoni Michele, Restuccia Tea, Andreozzi Paola, Liguori Maria Livia, Perticone Francesco, Caroleo Benedetto, Perticone Maria, Staltari Orietta, Manfredini Roberto, De Giorgi Alfredo, Averna Maurizio, Giammanco Antonina, Granito Alessandro, Pettinari Irene, Marinelli Sara, Bolondi Luigi, Falsetti Lorenzo, Salvi Aldo, Durante-Mangoni Emanuele, Cesaro Flavio, Farinaro Vincenza, Ragone Enrico, Morana Ignazio, Andriulli Angelo, Ippolito Antonio, Iacobellis Angelo, Niro Grazia, Merla Antonio, Raimondo Giovanni, Maimone Sergio, Cacciola Irene, Varvara Doriana, Drenaggi Davide, Staffolani Silvia, Picardi Antonio, Vespasiani-Gentilucci Umberto, Galati Giovanni, Gallo Paolo, Davì Giovanni, Schiavone Cosima, Santilli Francesca, Tana Claudio, Licata Anna, Soresi Maurizio, Bianchi Giovanni Battista, Carderi Isabella, Pinto Antonio, Tuttolomondo Antonino, Ferrari Giovanni, Gresele Paolo, Fierro Tiziana, Morelli Olivia, Laffi Giacomo, Romanelli Roberto Giulio, Arena Umberto, Stasi Cristina, Gasbarrini Antonio, Gargovich Matteo, Zocco Maria Assunta, Riccardi Laura, Ainora Maria Elena, Capeci William, Martino Giuseppe Pio, Nobili Lorenzo, Cavallo Maurizio, Frugiuele Pierluigi, Greco Antonio, Pietrangelo Antonello, Ventura Paolo, Cuoghi Chiara, Marcacci Matteo, Serviddio Gaetano, Vendemiale Gianluigi, Villani Rosanna, Gargano Ruggiero, Vidili Gianpaolo, Di Cesare Valentina, Masala Maristella, Delitala Giuseppe, Invernizzi Pietro, Di Minno Giovanni, Tufano Antonella, Purrello Francesco, Privitera Graziella, Forgione Alessandra, Curigliano Valentina, Senzolo Marco, Rodríguez-Castro Kryssia Isabel, Giannelli Gianluigi, Serra Carla, Neri Sergio, Pignataro Pietro, Rizzetto Mario, Debernardi Venon Wilma, Svegliati Baroni Gianluca, Bergamaschi Gaetano, Masotti Michela, Costanzo Filippo, Corazza Gino Roberto, Caldwell Stephen Hugh, Angelico Francesco, Del Ben Maria, Napoleone Laura, Polimeni Licia, Proietti Marco, Raparelli Valeria, Romiti Giulio Francesco, Ruscio Eleonora, Severoni Andrea, Talerico Giovanni, Toriello Filippo, and Vestri Annarita

Subjects
Albumin, Cirrhosis, Portal Vein Thrombosis, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

Background and Aims: Hypoalbuminemia, as defined by serum albumin (SA) levels ≤35 g/L, is associated to venous and arterial thrombosis in general population and in patients at risk of cardiovascular disease. It is unknown if SA ≤35 g/L is also associated to portal vein thrombosis (PVT) in cirrhosis. Methods: Cirrhotic patients enrolled in the Portal vein thrombosis Relevance On Liver cirrhosis: Italian Venous thrombotic Events Registry (PRO-LIVER) study (n = 753), were followed-up for 2 years to assess the risk of PVT, that was diagnosed by Doppler ultrasonography. Child-Pugh classes, Model for End-Stage Liver Disease score, presence of hepatocellular carcinoma and laboratory variables including SA, D-dimer, and high-sensitivity C-reactive protein (hs-CRP) were measured at baseline. Results: SA ≤35 g/L was detected in 52% of patients. A logistic multivariate regression analysis showed that higher Child-Pugh class, hepatocellular carcinoma and thrombocytopenia were significantly associated to SA ≤35 g/L. In a subgroup of patients where data regarding hs-CRP and D-dimer were available, SA ≤35 g/L was inversely associated with hs-CRP and D-dimer. During the follow-up, a total of 61 patients experienced PVT. A Kaplan Meier survival analysis showed SA ≤35 g/L was associated to increased risk of PVT compared to SA >35 g/L (P = .005). A multivariate Cox proportional hazards regression analysis showed that male sex, lower platelet count, and SA ≤35 g/L remained associated to PVT after adjusting for confounding factors. Conclusion: Cirrhotic patients with SA ≤35 g/L are at higher risk of experiencing PVT compared to those with SA >35 g/L and could be considered as potential candidates to anticoagulant prophylaxis for PVT prevention.

Published
2024
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45. A nurse-led coaching intervention with home telemonitoring for patients with heart failure: Protocol for a feasibility randomized clinical trial

Author

Ines Basso, Erika Bassi, Silvia Caristia, Angela Durante, Cristian Vairo, Salvatore Giuseppe Rocco Patti, Mario Pirisi, Mauro Campanini, Marco Invernizzi, Mattia Bellan, Alberto Dal Molin, Francesca Caldera, Domenico D'amario, Grabriele Dell'Era, Inelsy Gomez, Alessandra Lazzati, Elena Massara, Claudia Milanese, Antonella Molon, Marta Petteneo, Salvatore Scaramuzzino, Cristina Torgano, and Patrizia Zumbo

Subjects
Heart failure, Mentoring, Telemonitoring, Transitional care, Hospitalizations, Science
Abstract

Poor treatment adherence and lack of self-care behaviors are significant contributors to hospital readmissions of people with heart failure (HF). A transitional program with non-invasive telemonitoring may help sustain patients and their caregivers to timely recognize signs and symptoms of exacerbation.We will conduct a Randomized Clinical Trial (RCT) to evaluate the feasibility and acceptability of a 6-month supportive intervention for patients discharged home after cardiac decompensation. Forty-five people aged 65 years and over will be randomized to either receive a supportive intervention in addition to standard care, which combines nurse-led telephone coaching and a home-based self-monitoring vital signs program, or standard care alone. Four aspects of the feasibility will be assessed using a mixed-methods approach: process outcomes (e.g., recruitment rate), resources required (e.g., adherence to the intervention), management data (e.g., completeness of data collection), and scientific value (e.g. 90- and 180-day all-cause and HF-related readmissions, self-care capacity, quality of life, psychological well-being, mortality, etc.). Participants will be interviewed to explore preferences and satisfaction with the intervention. The study is expected to provide valuable insight into the design of a definitive RCT.

Published
2024
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46. Stratified analyses refine association between TLR7 rare variants and severe COVID-19

Author

Jannik Boos, Caspar I. van der Made, Gayatri Ramakrishnan, Eamon Coughlan, Rosanna Asselta, Britt-Sabina Löscher, Luca V.C. Valenti, Rafael de Cid, Luis Bujanda, Antonio Julià, Erola Pairo-Castineira, J. Kenneth Baillie, Sandra May, Berina Zametica, Julia Heggemann, Agustín Albillos, Jesus M. Banales, Jordi Barretina, Natalia Blay, Paolo Bonfanti, Maria Buti, Javier Fernandez, Sara Marsal, Daniele Prati, Luisa Ronzoni, Nicoletta Sacchi, Joachim L. Schultze, Olaf Riess, Andre Franke, Konrad Rawlik, David Ellinghaus, Alexander Hoischen, Axel Schmidt, Kerstin U. Ludwig, Valeria Rimoldi, Elvezia M. Paraboschi, Alessandra Bandera, Flora Peyvandi, Giacomo Grasselli, Francesco Blasi, Francesco Malvestiti, Serena Pelusi, Cristiana Bianco, Lorenzo Miano, Angela Lombardi, Pietro Invernizzi, Alessio Gerussi, Giuseppe Citerio, Andrea Biondi, Maria Grazia Valsecchi, Marina Elena Cazzaniga, Giuseppe Foti, Ilaria Beretta, Mariella D'Angiò, Laura Rachele Bettini, Xavier Farré, Susana Iraola-Guzmán, Manolis Kogevinas, Gemma Castaño-Vinyals, Koldo Garcia-Etxebarria, Beatriz Nafria, Mauro D'Amato, Adriana Palom, Colin Begg, Sara Clohisey, Charles Hinds, Peter Horby, Julian Knight, Lowell Ling, David Maslove, Danny McAuley, Johnny Millar, Hugh Montgomery, Alistair Nichol, Peter J.M. Openshaw, Alexandre C. Pereira, Chris P. Ponting, Kathy Rowan, Malcolm G. Semple, Manu Shankar-Hari, Charlotte Summers, Timothy Walsh, Latha Aravindan, Ruth Armstrong, Heather Biggs, Ceilia Boz, Adam Brown, Richard Clark, Audrey Coutts, Judy Coyle, Louise Cullum, Sukamal Das, Nicky Day, Lorna Donnelly, Esther Duncan, Angie Fawkes, Paul Fineran, Max Head Fourman, Anita Furlong, James Furniss, Bernadette Gallagher, Tammy Gilchrist, Ailsa Golightly, Fiona Griffiths, Katarzyna Hafezi, Debbie Hamilton, Ross Hendry, Andy Law, Dawn Law, Rachel Law, Sarah Law, Rebecca Lidstone-Scott, Louise Macgillivray, Alan Maclean, Hanning Mal, Sarah McCafferty, Ellie Mcmaster, Jen Meikle, Shona C. Moore, Kirstie Morrice, Lee Murphy, Sheena Murphy, Mybaya Hellen, Wilna Oosthuyzen, Chenqing Zheng, Jiantao Chen, Nick Parkinson, Trevor Paterson, Katherine Schon, Andrew Stenhouse, Mihaela Das, Maaike Swets, Helen Szoor-McElhinney, Filip Taneski, Lance Turtle, Tony Wackett, Mairi Ward, Jane Weaver, Nicola Wrobel, Marie Zechner, Gill Arbane, Aneta Bociek, Sara Campos, Neus Grau, Tim Owen Jones, Rosario Lim, Martina Marotti, Marlies Ostermann, Christopher Whitton, Zoe Alldis, Raine Astin-Chamberlain, Fatima Bibi, Jack Biddle, Sarah Blow, Matthew Bolton, Catherine Borra, Ruth Bowles, Maudrian Burton, Yasmin Choudhury, David Collier, Amber Cox, Amy Easthope, Patrizia Ebano, Stavros Fotiadis, Jana Gurasashvili, Rosslyn Halls, Pippa Hartridge, Delordson Kallon, Jamila Kassam, Ivone Lancoma-Malcolm, Maninderpal Matharu, Peter May, Oliver Mitchelmore, Tabitha Newman, Mital Patel, Jane Pheby, Irene Pinzuti, Zoe Prime, Oleksandra Prysyazhna, Julian Shiel, Melanie Taylor, Carey Tierney, Suzanne Wood, Anne Zak, Olivier Zongo, Stephen Bonner, Keith Hugill, Jessica Jones, Steven Liggett, Evie Headlam, Nageswar Bandla, Minnie Gellamucho, Michelle Davies, Christopher Thompson, Marwa Abdelrazik, Dhanalakshmi Bakthavatsalam, Munzir Elhassan, Arunkumar Ganesan, Anne Haldeos, Jeronimo Moreno-Cuesta, Dharam Purohit, Rachel Vincent, Kugan Xavier, Kumar Rohit, Frater Alasdair, Malik Saleem, Carter David, Jenkins Samuel, Zoe Lamond, Wall Alanna, Jaime Fernandez-Roman, David O. Hamilton, Emily Johnson, Brian Johnston, Maria Lopez Martinez, Suleman Mulla, David Shaw, Alicia A.C. Waite, Victoria Waugh, Ingeborg D. Welters, Karen Williams, Anna Cavazza, Maeve Cockrell, Eleanor Corcoran, Maria Depante, Clare Finney, Ellen Jerome, Mark McPhail, Monalisa Nayak, Harriet Noble, Kevin O'Reilly, Evita Pappa, Rohit Saha, Sian Saha, John Smith, Abigail Knighton, David Antcliffe, Dorota Banach, Stephen Brett, Phoebe Coghlan, Ziortza Fernandez, Anthony Gordon, Roceld Rojo, Sonia Sousa Arias, Maie Templeton, Megan Meredith, Lucy Morris, Lucy Ryan, Amy Clark, Julia Sampson, Cecilia Peters, Martin Dent, Margaret Langley, Saima Ashraf, Shuying Wei, Angela Andrew, Archana Bashyal, Neil Davidson, Paula Hutton, Stuart McKechnie, Jean Wilson, David Baptista, Rebecca Crowe, Rita Fernandes, Rosaleen Herdman-Grant, Anna Joseph, Denise O'Connor, Meryem Allen, Adam Loveridge, India McKenley, Eriko Morino, Andres Naranjo, Richard Simms, Kathryn Sollesta, Andrew Swain, Harish Venkatesh, Jacyntha Khera, Jonathan Fox, Gillian Andrew, Lucy Barclay, Marie Callaghan, Rachael Campbell, Sarah Clark, Dave Hope, Lucy Marshall, Corrienne McCulloch, Kate Briton, Jo Singleton, Sohphie Birch, Lutece Brimfield, Zoe Daly, David Pogson, Steve Rose, Ceri Battle, Elaine Brinkworth, Rachel Harford, Carl Murphy, Luke Newey, Tabitha Rees, Marie Williams, Sophie Arnold, Petra Polgarova, Katerina Stroud, Eoghan Meaney, Megan Jones, Anthony Ng, Shruti Agrawal, Nazima Pathan, Deborah White, Esther Daubney, Kay Elston, Lina Grauslyte, Musarat Hussain, Mandeep Phull, Tatiana Pogreban, Lace Rosaroso, Erika Salciute, George Franke, Joanna Wong, Aparna George, Laura Ortiz-Ruiz de Gordoa, Emily Peasgood, Claire Phillips, Michelle Bates, Jo Dasgin, Jaspret Gill, Annette Nilsson, James Scriven, Carlos Castro Delgado, Deborah Dawson, Lijun Ding, Georgia Durrant, Obiageri Ezeobu, Sarah Farnell-Ward, Abiola Harrison, Rebecca Kanu, Susannah Leaver, Elena Maccacari, Soumendu Manna, Romina Pepermans Saluzzio, Joana Queiroz, Tinashe Samakomva, Christine Sicat, Joana Texeira, Edna Fernandes Da Gloria, Ana Lisboa, John Rawlins, Jisha Mathew, Ashley Kinch, William James Hurt, Nirav Shah, Victoria Clark, Maria Thanasi, Nikki Yun, Kamal Patel, Sara Bennett, Emma Goodwin, Matthew Jackson, Alissa Kent, Clare Tibke, Wiesia Woodyatt, Ahmed Zaki, Azmerelda Abraheem, Peter Bamford, Kathryn Cawley, Charlie Dunmore, Maria Faulkner, Rumanah Girach, Helen Jeffrey, Rhianna Jones, Emily London, Imrun Nagra, Farah Nasir, Hannah Sainsbury, Clare Smedley, Tahera Patel, Matthew Smith, Srikanth Chukkambotla, Aayesha Kazi, Janice Hartley, Joseph Dykes, Muhammad Hijazi, Sarah Keith, Meherunnisa Khan, Janet Ryan-Smith, Philippa Springle, Jacqueline Thomas, Nick Truman, Samuel Saad, Dabheoc Coleman, Christopher Fine, Roseanna Matt, Bethan Gay, Jack Dalziel, Syamlan Ali, Drew Goodchild, Rhiannan Harling, Ravi Bhatterjee, Wendy Goddard, Chloe Davison, Stephen Duberly, Jeanette Hargreaves, Rachel Bolton, Miriam Davey, David Golden, Rebecca Seaman, Shiney Cherian, Sean Cutler, Anne Emma Heron, Anna Roynon-Reed, Tamas Szakmany, Gemma Williams, 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Krishnamurthy, Lai Lim, Li Lim, Edward Combes, Teishel Joefield, Sonja Monnery, Valerie Beech, Sallyanne Trotman, Christine Almaden-Boyle, Pauline Austin, Louise Cabrelli, Stephen Cole, Matt Casey, Susan Chapman, Clare Whyte, Yolanda Baird, Aaron Butler, Indra Chadbourn, Linda Folkes, Heather Fox, Amy Gardner, Raquel Gomez, Gillian Hobden, Luke Hodgson, Kirsten King, Michael Margarson, Tim Martindale, Emma Meadows, Dana Raynard, Yvette Thirlwall, David Helm, Jordi Margalef, Kristine Criste, Rebecca Cusack, Kim Golder, Hannah Golding, Oliver Jones, Samantha Leggett, Michelle Male, Martyna Marani, Kirsty Prager, Toran Williams, Belinda Roberts, Karen Salmon, Peter Anderson, Katie Archer, Karen Austin, Caroline Davis, Alison Durie, Olivia Kelsall, Jessica Thrush, Charlie Vigurs, Laura Wild, Hannah-Louise Wood, Helen Tranter, Alison Harrison, Nicholas Cowley, Michael McAlindon, Andrew Burtenshaw, Stephen Digby, Emma Low, Aled Morgan, Naiara Cother, Tobias Rankin, Sarah Clayton, Alex 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Gulati, Carole Hays, K. Webster, Anne Hudson, Andrea Webster, Elaine Stephenson, Louise McCormack, Victoria Slater, Rachel Nixon, Helen Hanson, Maggie Fearby, Sinead Kelly, Victoria Bridgett, Philip Robinson, Julie Camsooksai, Charlotte Humphrey, Sarah Jenkins, Henrik Reschreiter, Beverley Wadams, Yasmin Death, Victoria Bastion, Daphene Clarke, Beena David, Harriet Kent, Rachel Lorusso, Gamu Lubimbi, Sophie Murdoch, Melchizedek Penacerrada, Alastair Thomas, Jennifer Valentine, Ana Vochin, Retno Wulandari, Brice Djeugam, Gillian Bell, Katy English, Amro Katary, Louise Wilcox, Michelle Bruce, Karen Connolly, Tracy Duncan, Helen T-Michael, Gabriella Lindergard, Samuel Hey, Claire Fox, Jordan Alfonso, Laura Jayne Durrans, Jacinta Guerin, Bethan Blackledge, Jade Harris, Martin Hruska, Ayaa Eltayeb, Thomas Lamb, Tracey Hodgkiss, Lisa Cooper, Joanne Rothwell, Angela Allan, Felicity Anderson, Callum Kaye, Jade Liew, Jasmine Medhora, Teresa Scott, Erin Trumper, Adriana Botello, Liana Lankester, Nikitas Nikitas, Colin Wells, Bethan Stowe, Kayleigh Spencer, Craig Brandwood, Lara Smith, Katie Birchall, Laurel Kolakaluri, Deborah Baines, Anila Sukumaran, Elena Apetri, Cathrine Basikolo, Laura Catlow, Bethan Charles, Paul Dark, Reece Doonan, Alice Harvey, Daniel Horner, Karen Knowles, Stephanie Lee, Diane Lomas, Chloe Lyons, Tracy Marsden, Danielle McLaughlan, Liam McMorrow, Jessica Pendlebury, Jane Perez, Maria Poulaka, Nicola Proudfoot, Melanie Slaughter, Kathryn Slevin, Vicky Thomas, Danielle Walker, Angiy Michael, Matthew Collis, Tracey Cosier, Gemma Millen, Neil Richardson, Natasha Schumacher, Heather Weston, James Rand, Nicola Baxter, Steven Henderson, Sophie Kennedy-Hay, Christopher McParland, Laura Rooney, Malcolm Sim, Gordan McCreath, Louise Akeroyd, Shereen Bano, Matt Bromley, Lucy Gurr, Tom Lawton, James Morgan, Kirsten Sellick, Deborah Warren, Brian Wilkinson, Janet McGowan, Camilla Ledgard, Amelia Stacey, Kate Pye, Ruth Bellwood, Michael Bentley, Jeremy Bewley, Zoe Garland, Lisa Grimmer, Bethany Gumbrill, Rebekah Johnson, Katie Sweet, Denise Webster, Georgia Efford, Karen Convery, Deirdre Fottrell-Gould, Lisa Hudig, Jocelyn Keshet-Price, Georgina Randell, Katie Stammers, Maria Bokhari, Vanessa Linnett, Rachael Lucas, Wendy McCormick, Jenny Ritzema, Amanda Sanderson, Helen Wild, Anthony Rostron, Alistair Roy, Lindsey Woods, Sarah Cornell, Fiona Wakinshaw, Kimberley Rogerson, Jordan Jarmain, Robert Parker, Amie Reddy, Ian Turner-Bone, Laura Wilding, Peter Harding, Caroline Abernathy, Louise Foster, Andrew Gratrix, Vicky Martinson, Priyai Parkinson, Elizabeth Stones, Llucia Carbral-Ortega, Georgia Bercades, David Brealey, Ingrid Hass, Niall MacCallum, Gladys Martir, Eamon Raith, Anna Reyes, Deborah Smyth, Letizia Zitter, Sarah Benyon, Suzie Marriott, Linda Park, Samantha Keenan, Elizabeth Gordon, Helen Quinn, Kizzy Baines, Lenka Cagova, Adama Fofano, Lucie Garner, Helen Holcombe, Sue Mepham, Alice Michael Mitchell, Lucy Mwaura, Krithivasan Praman, Alain Vuylsteke, Julie Zamikula, Bally Purewal, Vanessa Rivers, Stephanie Bell, Hayley Blakemore, Borislava Borislavova, Beverley Faulkner, Emma Gendall, Elizabeth Goff, Kati Hayes, Matt Thomas, Ruth Worner, Kerry Smith, Deanna Stephens, Louise Mew, Esther Mwaura, Richard Stewart, Felicity Williams, Lynn Wren, Sara-Beth Sutherland, Emily Bevan, Jane Martin, Dawn Trodd, Geoff Watson, Caroline Wrey Brown, Amy Collins, Waqas Khaliq, Estefania Treus Gude, Olugbenga Akinkugbe, Alasdair Bamford, Emily Beech, Holly Belfield, Michael Bell, Charlene Davies, Gareth A.L. Jones, Tara McHugh, Hamza Meghari, Lauran O'Neill, Mark J. Peters, Samiran Ray, Ana Luisa Tomas, Iona Burn, Geraldine Hambrook, Katarina Manso, Ruth Penn, Pradeep Shanmugasundaram, Julie Tebbutt, Danielle Thornton, Jade Cole, Rhys Davies, Donna Duffin, Helen Hill, Ben Player, Emma Thomas, Angharad Williams, Denise Griffin, Nycola Muchenje, Mcdonald Mupudzi, Richard Partridge, Jo-Anna Conyngham, Rachel Thomas, Mary Wright, Maria Alvarez Corral, Reni Jacob, Cathy Jones, Craig Denmade, Sarah Beavis, Katie Dale, Rachel Gascoyne, Joanne Hawes, Kelly Pritchard, Lesley Stevenson, Amanda Whileman, Patricia Doble, Joanne Hutter, Corinne Pawley, Charmaine Shovelton, Marius Vaida, Deborah Butcher, Susie O'Sullivan, Nicola Butterworth-Cowin, Norfaizan Ahmad, Joann Barker, Kris Bauchmuller, Sarah Bird, Kay Cawthron, Kate Harrington, Yvonne Jackson, Faith Kibutu, Becky Lenagh, Shamiso Masuko, Gary H. Mills, Ajay Raithatha, Matthew Wiles, Jayne Willson, Helen Newell, Alison Lye, Lorenza Nwafor, Claire Jarman, Sarah Rowland-Jones, David Foote, Joby Cole, Roger Thompson, James Watson, Lisa Hesseldon, Irene Macharia, Luke Chetam, Jacqui Smith, Amber Ford, Samantha Anderson, Kathryn Birchall, Kay Housley, Sara Walker, Leanne Milner, Helena Hanratty, Helen Trower, Patrick Phillips, Simon Oxspring, Ben Donne, Catherine Jardine, Dewi Williams, Alasdair Hay, Rebecca Flanagan, Gareth Hughes, Scott Latham, Emma McKenna, Jennifer Anderson, Robert Hull, Kat Rhead, Carina Cruz, Natalie Pattison, Rob Charnock, Denise McFarland, Denise Cosgrove, Ashar Ahmed, Anna Morris, Srinivas Jakkula, Asifa Ali, Megan Brady, Sam Dale, Annalisa Dance, Lisa Gledhill, Jill Greig, Kathryn Hanson, Kelly Holdroyd, Marie Home, Diane Kelly, Ross Kitson, Lear Matapure, Deborah Melia, Samantha Mellor, Tonicha Nortcliffe, Jez Pinnell, Matthew Robinson, Lisa Shaw, Ryan Shaw, Lesley Thomis, Alison Wilson, Tracy Wood, Lee-Ann Bayo, Ekta Merwaha, Tahira Ishaq, Sarah Hanley, Meg Hibbert, Dariusz Tetla, Chrsitopher Woodford, Latha Durga, Gareth Kennard-Holden, Debbie Branney, Jordan Frankham, Sally Pitts, Nigel White, Shondipon Laha, Mark Verlander, Alexandra Williams, Abdelhakim Altabaibeh, Ana Alvaro, Kayleigh Gilbert, Louise Ma, Loreta Mostoles, Chetan Parmar, Kathryn Simpson, Champa Jetha, Lauren Booker, Anezka Pratley, Colene Adams, Anita Agasou, Tracie Arden, Amy Bowes, Pauline Boyle, Mandy Beekes, Heather Button, Nigel Capps, Mandy Carnahan, Anne Carter, Danielle Childs, Denise Donaldson, Kelly Hard, Fran Hurford, Yasmin Hussain, Ayesha Javaid, James Jones, Sanal Jose, Michael Leigh, Terry Martin, Helen Millward, Nichola Motherwell, Rachel Rikunenko, Jo Stickley, Julie Summers, Louise Ting, Helen Tivenan, Louise Tonks, Rebecca Wilcox, Maureen Holland, Natalie Keenan, Marc Lyons, Helen Wassall, Chris Marsh, Mervin Mahenthran, Emma Carter, Thomas Kong, Helen Blackman, Ben Creagh-Brown, Sinead Donlon, Natalia Michalak-Glinska, Sheila Mtuwa, Veronika Pristopan, Armorel Salberg, Eleanor Smith, Sarah Stone, Charles Piercy, Jerik Verula, Dorota Burda, Rugia Montaser, Lesley Harden, Irving Mayangao, Cheryl Marriott, Paul Bradley, Celia Harris, Susan Anderson, Eleanor Andrews, Janine Birch, Emma Collins, Kate Hammerton, Ryan O'Leary, Michele Clark, Sarah Purvis, Russell Barber, Claire Hewitt, Annette Hilldrith, Karen Jackson-Lawrence, Sarah Shepardson, Maryanne Wills, Susan Butler, Silvia Tavares, Amy Cunningham, Julia Hindale, Sarwat Arif, Sarah Bean, Karen Burt, Michael Spivey, Carrie Demetriou, Charlotte Eckbad, Sarah Hierons, Lucy Howie, Sarah Mitchard, Lidia Ramos, Alfredo Serrano-Ruiz, Katie White, Fiona Kelly, Daniele Cristiano, Natalie Dormand, Zohreh Farzad, Mahitha Gummadi, Kamal Liyanage, Brijesh Patel, Sara Salmi, Geraldine Sloane, Vicky Thwaites, Mathew Varghese, Anelise C. Zborowski, John Allan, Tim Geary, Gordon Houston, Alistair Meikle, Peter O'Brien, Miranda Forsey, Agilan Kaliappan, Anne Nicholson, Joanne Riches, Mark Vertue, Elizabeth Allan, Kate Darlington, Ffyon Davies, Jack Easton, Sumit Kumar, Richard Lean, Daniel Menzies, Richard Pugh, Xinyi Qiu, Llinos Davies, Hannah Williams, Jeremy Scanlon, Gwyneth Davies, Callum Mackay, Joannne Lewis, Stephanie Rees, Metod Oblak, Monica Popescu, Mini Thankachen, Andrew Higham, Kerry Simpson, Jayne Craig, Rosie Baruah, Sheila Morris, Susie Ferguson, Amy Shepherd, Luke Stephen Prockter Moore, Marcela Paola Vizcaychipi, Laura Gomes de Almeida Martins, Jaime Carungcong, Inthakab Ali Mohamed Ali, Karen Beaumont, Mark Blunt, Zoe Coton, Hollie Curgenven, Mohamed Elsaadany, Kay Fernandes, Sameena Mohamed Ally, Harini Rangarajan, Varun Sarathy, Sivarupan Selvanayagam, Dave Vedage, Matthew White, Mandy Gill, Paul Paul, Valli Ratnam, Sarah Shelton, Inez Wynter, Siobhain Carmody, Valerie Joan Page, Claire Marie Beith, Karen Black, Suzanne Clements, Alan Morrison, Dominic Strachan, Margaret Taylor, Michelle Clarkson, Stuart D'Sylva, Kathryn Norman, Fiona Auld, Joanne Donnachie, Ian Edmond, Lynn Prentice, Nikole Runciman, Dario Salutous, Lesley Symon, Anne Todd, Patricia Turner, Abigail Short, Laura Sweeney, Euan Murdoch, Dhaneesha Senaratne, Michaela Hill, Thogulava Kannan, Wild Laura, Rikki Crawley, Abigail Crew, Mishell Cunningham, Allison Daniels, Laura Harrison, Susan Hope, Ken Inweregbu, Sian Jones, Nicola Lancaster, Jamie Matthews, Alice Nicholson, Gemma Wray, Helen Langton, Rachel Prout, Malcolm Watters, Catherine Novis, Anthony Barron, Ciara Collins, Sundeep Kaul, Heather Passmore, Claire Prendergast, Anna Reed, Paula Rogers, Rajvinder Shokkar, Meriel Woodruff, Hayley Middleton, Oliver Polgar, Claire Nolan, Kanta Mahay, Dawn Collier, Anil Hormis, Victoria Maynard, Cheryl Graham, Rachel Walker, Ellen Knights, Alicia Price, Alice Thomas, Chris Thorpe, Teresa Behan, Caroline Burnett, Jonathan Hatton, Elaine Heeney, Atideb Mitra, Maria Newton, Rachel Pollard, Rachael Stead, Vishal Amin, Elena Anastasescu, Vikram Anumakonda, Komala Karthik, Rizwana Kausar, Karen Reid, Jacqueline Smith, Janet Imeson-Wood, Denise Skinner, Jane Gaylard, Dee Mullan, Julie Newman, Alison Brown, Vikki Crickmore, Gabor Debreceni, Joy Wilkins, Liz Nicol, Rosie Reece-Anthony, Mark Birt, Alison Ghosh, Emma Williams, Louise Allen, Eva Beranova, Nikki Crisp, Joanne Deery, Tracy Hazelton, Alicia Knight, Carly Price, Sorrell Tilbey, Salah Turki, Sharon Turney, Joshua Cooper, Cheryl Finch, Sarah Liderth, Alison Quinn, Natalia Waddington, Tina Coventry, Susan Fowler, Michael MacMahon, Amanda McGregor, Anne Cowley, Judith Highgate, Jane Gregory, Susan O'Connell, Tim Smith, Luigi Barberis, Shameer Gopal, Nichola Harris, Victoria Lake, Stella Metherell, Elizabeth Radford, Amelia Daniel, Joanne Finn, Rajnish Saha, Nikki White, Phil Donnison, Fiona Trim, Beena Eapen, Jenny Birch, Laura Bough, Josie Goodsell, Rebecca Tutton, Patricia Williams, Sarah Williams, Barbara Winter-Goodwin, Ailstair Nichol, Kathy Brickell, Michelle Smyth, Lorna Murphy, Samantha Coetzee, Alistair Gales, Igor Otahal, Meena Raj, Craig Sell, Paula Hilltout, Jayne Evitts, Amanda Tyler, Joanne Waldron, Kate Beesley, Sarah Board, Agnieszka Kubisz-Pudelko, Alison Lewis, Jess Perry, Lucy Pippard, Di Wood, Clare Buckley, Peter Barry, Neil Flint, Patel Rekha, Dawn Hales, Lara Bunni, Claire Jennings, Monica Latif, Rebecca Marshall, Gayathri Subramanian, Peter J. McGuigan, Christopher Wasson, Stephanie Finn, Jackie Green, Erin Collins, Bernadette King, Andy Campbell, Sara Smuts, Joseph Duffield, Oliver Smith, Lewis Mallon, Watkins Claire, Liam Botfield, Joanna Butler, Catherine Dexter, Jo Fletcher, Atul Garg, Aditya Kuravi, Poonam Ranga, Emma Virgilio, Zakaula Belagodu, Bridget Fuller, Anca Gherman, Olumide Olufuwa, Remi Paramsothy, Carmel Stuart, Naomi Oakley, Charlotte Kamundi, David Tyl, Katy Collins, Pedro Silva, June Taylor, Laura King, Charlotte Coates, Maria Crowley, Phillipa Wakefield, Jane Beadle, Laura Johnson, Janet Sargeant, Madeleine Anderson, Ailbhe Brady, Rebekah Chan, Jeff Little, Shane McIvor, Helena Prady, Helen Whittle, Bijoy Mathew, Ben Attwood, Penny Parsons, Geraldine Ward, Pamela Bremmer, West Joe, Baird Tracy, Ruddy Jim, Ellie Davies, Sonia Sathe, Catherine Dennis, Alastair McGregor, Victoria Parris, Sinduya Srikaran, Anisha Sukha, Noreen Clarke, Jonathan Whiteside, Mairi Mascarenhas, Avril Donaldson, Joanna Matheson, Fiona Barrett, Marianne O'Hara, Laura Okeefe, Clare Bradley, Christine Eastgate-Jackson, Helder Filipe, Daniel Martin, Amitaa Maharajh, Sara Mingo Garcia, Glykeria Pakou, Mark De Neef, Kathy Dent, Elizabeth Horsley, Muhmmad Nauman Akhtar, Sandra Pearson, Dorota Potoczna, Sue Spencer, Melanie Clapham, Rosemary Harper, Una Poultney, Polly Rice, Rachel Mutch, Lisa Armstrong, Hayley Bates, Emma Dooks, Fiona Farquhar, Brigid Hairsine, Chantal McParland, Sophie Packham, Rehana Bi, Barney Scholefield, Lydia Ashton, Linsha George, Sophie Twiss, David Wright, Manish Chablani, Amy Kirkby, Kimberley Netherton, Kim Davies, Linda O'Brien, Zohra Omar, Emma Perkins, Tracy Lewis, Isobel Sutherland, Karen Burns, Dr Ben Chandler, Kerry Elliott, Janine Mallinson, Alison Turnbull, Prisca Gondo, Bernard Hadebe, Abdul Kayani, Bridgett Masunda, Taya Anderson, Dan Hawcutt, Laura O'Malley, Laura Rad, Naomi Rogers, Paula Saunderson, Kathryn Sian Allison, Deborah Afolabi, Jennifer Whitbread, Dawn Jones, Rachael Dore, Matthew Halkes, Pauline Mercer, Lorraine Thornton, Joy Dawson, Sweyn Garrioch, Melanie Tolson, Jonathan Aldridge, Ritoo Kapoor, David Loader, Karen Castle, Sally Humphreys, Ruth Tampsett, Katherine Mackintosh, Amanda Ayers, Wendy Harrison, Julie North, Suzanne Allibone, Roman Genetu, Vidya Kasipandian, Amit Patel, Ainhi Mac, Anthony Murphy, Parisa Mahjoob, Roonak Nazari, Lucy Worsley, Andrew Fagan, Thomas Bemand, Ethel Black, Arnold Dela Rosa, Ryan Howle, Shaman Jhanji, Ravishankar Rao Baikady, Kate Colette Tatham, Benjamin Thomas, Dina Bell, Rosalind Boyle, Katie Douglas, Lynn Glass, Emma Lee, Liz Lennon, Austin Rattray, Abigail Taylor, Rachel Anne Hughes, Helen Thomas, Alun Rees, Michaela Duskova, Janet Phipps, Suzanne Brooks, Michelle Edwards, Sheena Quaid, Ekaterina Watson, Adam Brayne, Emma Fisher, Jane Hunt, Peter Jackson, Duncan Kaye, Nicholas Love, Juliet Parkin, Victoria Tuckey, Lynne Van Koutrik, Sasha Carter, Benedict Andrew, Louise Findlay, Katie Adams, Jen Service, Alison Williams, Claire Cheyne, Anne Saunderson, Sam Moultrie, Miranda Odam, Kathryn Hall, Isheunesu Mapfunde, Charlotte Willis, Alex Lyon, Chunda Sri-Chandana, Joslan Scherewode, Lorraine Stephenson, Sarah Marsh, John Hardy, Henry Houlden, Eleanor Moncur, Ambreen Tariq, Arianna Tucci, Maria Hobrok, Ronda Loosley, Heather McGuinness, Helen Tench, Rebecca Wolf-Roberts, Val Irvine, Benjamin Shelley, Claire Gorman, Abhinav Gupta, Elizabeth Timlick, Rebecca Brady, Barry Milligan, Arianna Bellini, Jade Bryant, Anton Mayer, Amy Pickard, Nicholas Roe, Jason Sowter, Alex Howlett, Katy Fidler, Emma Tagliavini, and Kevin Donnelly

Subjects
SARS-CoV-2, host genetics, toll-like receptor 7, targeted sequencing, rare variants, variant collapsing analysis, Genetics, QH426-470
Abstract

Summary: Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (

Published
2024
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47. Exodoncia de premolar inferior supernumerario con posterior colocación de Fibrina Rica en Plaquetas y Leucocitos (L-PRF)

Author

Angeles Zelada, Diego Benitez, Jessica Kang, Melissa Sanabria, Patricia Cabrera, and Carlos Rafael Invernizzi-Mendoza

Subjects
diente supernumerario, fibrina rica en plaquetas y leucocitos, regeneración tisular, Medicine (General), R5-920
Abstract

Los dientes supernumerarios son una anomalía odontogénica, consiste en aumento del número dentario con respecto a la cantidad normal. La Fibrina rica en Plaquetas y Leucocitos (L-PRF) es una matriz rica en plaquetas y glóbulos blancos, que promueve la curación y regeneración de los tejidos. La exodoncia de un tercer premolar inferior supernumerario con posterior colocación de membrana de L-PRF. Paciente de sexo masculino de 27 años de edad con un probable premolar supernumerario por lingual. Se programó la cirugía incluyendo L-PRF. Se realizó extracción de sangre para preparar la membrana de L-PRF, anestesia, incisión lineal, despegamiento mucoperióstico, osteotomía, exodoncia, tratamiento del lecho quirúrgico colocando la membrana de L-PRF y sutura interdental. Se prescribió medicación antibiótica, antiinflamatoria y analgésica. La técnica con L-PRF es sencilla y económica. Los resultados postoperatorios fueron favorables, observándose una buena cicatrización, ausencia de dolor, edema o infección.

Published
2024
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48. O jornal como plataforma pública. Amadorismo, pedagogia corporal, retórica futebolísticas (Florianópolis, 1920-1930)

Author

Alexandre Fernandez Vaz, Alessandra Pires Machado, and Lisandra Invernizzi

Subjects
futebol, modernização, florianópolis, imprensa, Communication. Mass media, P87-96
Abstract

O futebol é um importante marcador dos processos de modernização que encontram lugar no século vinte. Não é diferente em Florianópolis, capital de Santa Catarina, Sul do Brasil, que se supõe ter sido o viu pela primeira vez em 1910. Nas duas décadas seguintes esse esporte já era um fenômeno que, junto com o desenvolvimento da imprensa e de uma crescente vida urbana, estabelecia-se como dispositivo de distinção social. O presente trabalho ocupa-se do lugar que tal modalidade encontrou na imprensa local nas décadas de 1920 e 1930, com especial atenção ao movimento de profissionalização do esporte. Os documentos compõem-se de notas, colunas e cartas dedicadas ao futebol, em jornais como O Tempo e O Estado. Elas foram analisadas a partir do desenvolvimento de algumas categorias-chave, como a formação do sportsman, a presença do futebol como prática efetiva de sociabilização, a emergência e circularidade de novas equipes, a instituição de um espaço público, ainda que limitado às camadas sociais mais altas. Os resultados apontam, entre outras questões, para a reafirmação do etos amadorístico demarcado na figura do gentleman, com sua específica masculinidade, a incipiente preocupação com uma pedagogia corporal adequada ao esporte, a instituição de uma retórica futebolística na imprensa periódica. Identificador permanente (ARK): http://id.caicyt.gov.ar/ark:/s18535925/yvxx0t7vj

Published
2024
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49. Aspiración de cuerpo extraño en adulto

Author

Mariana Invernizzi, Lucía Romero, Ana Gruss, Andrés Berke, and Ignacio Lapiedra

Subjects
aspiración, cuerpo extraño, fibrobroncoscopía, Surgery, RD1-811
Abstract

Se trata de un paciente de sexo masculino, de 28 años de edad, los antecedentes personales son: asma y consumo problemático de sustancias. Se presenta con una ingesta de un objeto metálico de unos 10 cm aproximadamente de largo, con un diámetro mayoren uno de sus extremos puntiforme (clavo); producida dos horas antes de la consulta en el Departamento de Emergencia, seguido de un breve episodio de tos.

Published
2024
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50. Changes in the prevalence of mental health problems during the first year of the pandemic: a systematic review and dose-response meta-analysis

Author

Toshi A Furukawa, Edoardo G Ostinelli, Andrea Cipriani, Pim Cuijpers, Lin Ma, Akira Onishi, Tianjing Li, Georgia Salanti, Vikram Patel, Christian Kieling, Sanae Kishimoto, Ronald C Kessler, Seena Fazel, Marialena Trivella, Akira Sato, Yikang Zhu, Raman Sharma, Matthias Egger, Simone N. Vigod, Yu-Kang Tu, Tou-Yuan Tsai, Yuan-Pang Wang, Irene Bighelli, Alessandro Rodolico, Stefan Leucht, Michael Ostacher, Ian White, Virginia Chiocchia, Ethan Sahker, Rie Toyomoto, Kazufumi Yoshida, Trevor Thompson, Dongfang Wang, Jing Tian, Katharine A Smith, Gonzalo Arrondo, Meenakshi Sharma, Silviya Ralovska, Andreas D Haas, Michael A Wewege, Bartosz Helfer, Erika Kalocsanyiova, Harrison Nelson, Gandy Dolores-Maldonado, Caroline Zangani, Kenji Omae, Shimeng Dong, Shino Kikuchi, Thomy Tonia, James S W Hong, Natalie Luise Peter, Letao Sun, Aurélie M Lasserre, Alexander Holloway, Leila Darwish, Andrea Zucchetti, Amin Sharifan, Ana Cristina Solis, Antonio Vita, Carmen Concerto, Chinonso Igwesi-Chidobe, Carlos Rios-Gonzalez, Anna Ceraso, Daniel Prates Baldez, Dicle Dilay Demir, Ying-Chun Lin, Elena Invernizzi, Gabriel Henrique Beraldi, Gamze Erzin, Giulia Ottaviano, Graciela J Balbin-Ramón, Chin-Yen Ho, Helio Elkis, Yun Chen Liu, Javier Ballesteros, Johanna Schneckenburger, Jessie Jingxia Lin, Abdulkadir Usman Sambo, Lena Feber, Mattia Marchetti, Mauro Italia, Mengchang Qin, Yi-Chih Lin, Nurul Husna Salahuddin, Rossella Virgillito, Ogulcan Ciray, Sergio A Covarrubias-Castillo, Yun Hsia, Shiue-Shiuan Tu, and Vidya Giri Shankar

Subjects
Psychiatry, RC435-571
Abstract

Aim To describe the pattern of the prevalence of mental health problems during the first year of the COVID-19 pandemic and examine the impact of containment measures on these trends.Methods We identified articles published until 30 August 2021 that reported the prevalence of mental health problems in the general population at two or more time points. A crowd of 114 reviewers extracted data on prevalence, study and participant characteristics. We collected information on the number of days since the first SARS-CoV-2 infection in the study country, the stringency of containment measures and the number of cases and deaths. We synthesised changes in prevalence during the pandemic using a random-effects model. We used dose-response meta-analysis to evaluate the trajectory of the changes in mental health problems.Results We included 41 studies for 7 mental health conditions. The average odds of symptoms increased during the pandemic (mean OR ranging from 1.23 to 2.08). Heterogeneity was very large and could not be explained by differences in participants or study characteristics. Average odds of psychological distress, depression and anxiety increased during the first 2 months of the pandemic, with increased stringency of the measures, reported infections and deaths. The confidence in the evidence was low to very low.Conclusions We observed an initial increase in the average risk of psychological distress, depression-related and anxiety-related problems during the first 2 months of the pandemic. However, large heterogeneity suggests that different populations had different responses to the challenges imposed by the pandemic.

Published
2024
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