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27,621 results on '"Baroni A"'

202. Suboptimal outcomes of sorafenib as a second-line treatment after atezolizumab-bevacizumab for unresectable hepatocellular carcinoma

Author

Tovoli, Francesco, Pallotta, Dante Pio, Vivaldi, Caterina, Campani, Claudia, Federico, Piera, Palloni, Andrea, Dalbeni, Andrea, Soldà, Caterina, Lani, Lorenzo, Svegliati-Baroni, Gianluca, Garajova, Ingrid, Ielasi, Luca, De Lorenzo, Stefania, Granito, Alessandro, Stefanini, Bernardo, Masi, Gianluca, Marra, Fabio, Lonardi, Sara, Brandi, Giovanni, Daniele, Bruno, Auriemma, Alessandra, Schiadà, Laura, Chen, Rusi, and Piscaglia, Fabio

Published
2024
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204. Identifying prognostic hub genes and key pathways in pediatric adrenocortical tumors through RNA sequencing and Co-expression analysis

Author

Veronez, Luciana Chain, Xavier, Alcides Euzebio Tavares, Nagano, Luiz Fernando, Correa, Carolina Alves Pereira, Borges, Kleiton Silva, Santos, Paula, Baroni, Mirella, Silva Queiroz, Rosane de Paula, Antonini, Sonir Roberto Rauber, Yunes, José Andres, Brandalise, Silvia Regina, Molina, Carlos Augusto Fernandes, Pinto, Emilia Modolo, Valera, Elvis Terci, Tone, Luiz Gonzaga, and Scrideli, Carlos Alberto

Published
2024
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206. Analysis of miR-483-3p and miR-630 expression profile in pediatric adrenocortical tumors and the effect of their modulation on adrenal tumorigenesis in vitro

Author

Corrêa, Carolina Alves Pereira, Andrade, Augusto Faria, Veronez, Luciana Chain, da Silva, Keteryne Rodrigues, Baroni, Mirella, Suazo, Veridiana Kill, de Paula Gomes Queiroz, Rosane, Lira, Régia Caroline Peixoto, Chagas, Pablo Shimaoka, Brandalise, Silvia Regina, Yunes, José Andres, Molina, Carlos Augusto Fernandes, Antonini, Sonir Roberto Rauber, Valera, Elvis Terci, Tone, Luiz Gonzaga, and Scrideli, Carlos Alberto

Published
2024
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207. 'Expect to Be Taken out of Class': Comparing School Experiences of Trauma-Exposed Black Girls and Boys

Author

Crosby, Shantel D., Jones, Kristian, Day, Angelique, Somers, Cheryl, Baroni, Beverly, and Feltner Williams, Alanna

Abstract

This study explores the intersections of race, gender, and trauma in students' school experiences. We collected focus group data from 36 trauma-exposed Black girls and 10 trauma-exposed Black boys from two urban high schools. Data was analyzed using an intersectional framework and resulted in the following themes: (1) Don't Touch the Students; (2) You Gettin' Suspended; (3) You Supposed to Be the Bigger Person; and (4) If We Have a Uniform, They Should Have a Uniform. Implications are discussed.

Published
2023
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210. Temperature- and vacancy-concentration-dependence of heat transport in Li$_3$ClO from multi-method numerical simulations

Author

Pegolo, Paolo, Baroni, Stefano, and Grasselli, Federico

Subjects
Condensed Matter - Materials Science, Condensed Matter - Disordered Systems and Neural Networks
Abstract

Despite governing heat management in any realistic device, the microscopic mechanisms of heat transport in all-solid-state electrolytes are poorly known: existing calculations, all based on simplistic semi-empirical models, are unreliable for superionic conductors and largely overestimate their thermal conductivity. In this work, we deploy a combination of state-of-the-art methods to calculate the thermal conductivity of a prototypical Li-ion conductor, the Li$_3$ClO antiperovskite. By leveraging ab initio, machine-learning, and force-field descriptions of inter-atomic forces, we are able to reveal the massive role of anharmonic interactions and diffusive defects on the thermal conductivity and its temperature dependence, and to eventually embed their effects into a simple rationale which is likely applicable to a wide class of ionic conductors.

Published
2021
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211. Electron energy loss spectroscopy of bulk gold with ultrasoft pseudopotentials and the Liouville-Lanczos method

Author

Motornyi, Oleksandr, Vast, Nathalie, Timrov, Iurii, Baseggio, Oscar, Baroni, Stefano, and Corso, Andrea Dal

Subjects
Condensed Matter - Materials Science
Abstract

The implementation of ultrasoft pseudopotentials into time-dependent density-functional perturbation theory is detailed for both the Sternheimer approach and the Liouville-Lanczos (LL) method, and equations are presented in the scalar relativistic approximation for periodic solids with finite momentum transfer q. The LL method is applied to calculations of the electron energy loss (EEL) spectrum of face-centered cubic bulk Au both at vanishing and finite q. Our study reveals the richness of the physics underlying the various contributions to the density fluctuation in gold. In particular, our calculations suggest the existence in gold of two quasi-separate 5d and 6s electron gasses, each one oscillating with its own frequency at resp. 5.1 eV and 10.2 eV. We find that the contribution near 2.2 eV comes from 5d to 6s interband transitions modified by the intraband contribution to the real part of the dielectric function, which we call a mixed excitation.

Published
2021
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212. turboEELS -- A code for the simulation of the electron energy loss and inelastic X-ray scattering spectra using the Liouville-Lanczos approach to time-dependent density-functional perturbation theory

Author

Timrov, Iurii, Vast, Nathalie, Gebauer, Ralph, and Baroni, Stefano

Subjects
Condensed Matter - Materials Science, Physics - Computational Physics
Abstract

We introduce turboEELS, an implementation of the Liouville-Lanczos approach to linearized time-dependent density-functional theory, designed to simulate electron energy loss and inelastic X-ray scattering spectra in periodic solids. turboEELS is open-source software distributed under the terms of the GPL as a component of Quantum ESPRESSO. As with other components, turboEELS is optimized to run on a variety of different platforms, from laptops to massively parallel architectures, using native mathematical libraries (LAPACK and FFTW) and a hierarchy of custom parallelization layers built on top of MPI.

Published
2021
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213. Nuclear two point correlation functions on a quantum-computer

Author

Baroni, Alessandro, Carlson, Joseph, Gupta, Rajan, Li, Andy C. Y., Perdue, Gabriel N., and Roggero, Alessandro

Subjects
Quantum Physics, High Energy Physics - Lattice, Nuclear Theory
Abstract

The calculation of dynamic response functions is expected to be an early application benefiting from rapidly developing quantum hardware resources. The ability to calculate real-time quantities of strongly-correlated quantum systems is one of the most exciting applications that can easily reach beyond the capabilities of traditional classical hardware. Response functions of fermionic systems at moderate momenta and energies corresponding roughly to the Fermi energy of the system are a potential early application because the relevant operators are nearly local and the energies can be resolved in moderately short real time, reducing the spatial resolution and gate depth required. This is particularly the case in quasielastic electron and neutrino scattering from nuclei, a topic of great interest in the nuclear and particle physics communities and directly related to experiments designed to probe neutrino properties. In this work we use current quantum hardware and error mitigation protocols to calculate response functions for a highly simplified nuclear model through calculations of a 2-point real time correlation function for a modified Fermi-Hubbard model in two dimensions with three distinguishable nucleons on four lattice sites., Comment: 13 pages, 6 figures

Published
2021
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214. Variational approaches to constructing the many-body nuclear ground state for quantum computing

Author

Stetcu, I., Baroni, A., and Carlson, J.

Subjects
Nuclear Theory
Abstract

We explore the preparation of specific nuclear states on gate-based quantum hardware using variational algorithms. Large scale classical diagonalization of the nuclear shell model have reached sizes of $10^9 - 10^{10}$ basis states, but are still severely limited by computational resources. Quantum computing can, in principle, solve such systems exactly with exponentially fewer resources than classical computing. Exact solutions for large systems require many qubits and large gate depth, but variational approaches can effectively limit the required gate depth. We use the unitary coupled cluster approach to construct approximations of the ground-state vectors, later to be used in dynamics calculations. The testing ground is the phenomenological shell model space, which allows us to mimic the complexity of the inter-nucleon interactions. We find that often one needs to minimize over a large number of parameters, using a large number of entanglements that makes challenging the application on existing hardware. Prospects for rapid improvements with more capable hardware are, however, very encouraging., Comment: 10 pages, 5 figures

Published
2021
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215. How BPE Affects Memorization in Transformers

Author

Kharitonov, Eugene, Baroni, Marco, and Hupkes, Dieuwke

Subjects
Computer Science - Computation and Language
Abstract

Training data memorization in NLP can both be beneficial (e.g., closed-book QA) and undesirable (personal data extraction). In any case, successful model training requires a non-trivial amount of memorization to store word spellings, various linguistic idiosyncrasies and common knowledge. However, little is known about what affects the memorization behavior of NLP models, as the field tends to focus on the equally important question of generalization. In this work, we demonstrate that the size of the subword vocabulary learned by Byte-Pair Encoding (BPE) greatly affects both ability and tendency of standard Transformer models to memorize training data, even when we control for the number of learned parameters. We find that with a large subword vocabulary size, Transformer models fit random mappings more easily and are more vulnerable to membership inference attacks. Similarly, given a prompt, Transformer-based language models with large subword vocabularies reproduce the training data more often. We conjecture this effect is caused by reduction in the sequences' length that happens as the BPE vocabulary grows. Our findings can allow a more informed choice of hyper-parameters, that is better tailored for a particular use-case.

Published
2021

219. Predicting Role of GFAP and UCH-L1 biomarkers in Spontaneous Subarachnoid Hemorrhage: a preliminary study to evaluate in the short-term their correlation with severity of bleeding and prognosis

Author

Auricchio, Anna Maria, Baroni, Silvia, Rezai Jahromi, Behnam, Valz Gris, Angelica, Sturiale, Carmelo Lucio, Ceccarelli, Giovanni Maria, Obersnel, Marco, Menna, Grazia, Martinelli, Renata, Napoli, Giulia, Scarcia, Luca, Alexandre, Andrea, Caricato, Anselmo, Di Bonaventura, Rina, Albanese, Alessio, Marchese, Enrico, Covino, Marcello, Olivi, Alessandro, and Della Pepa, Giuseppe Maria

Published
2024
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221. Trends in liver transplantation for primary sclerosing cholangitis

Author

Viganò, Raffaella, Fornasiere, Ezio, Catanzaro, Elisa, Marrone, Giuseppe, Milana, Martina, Calleri, Alberto, Scorzoni, Chiara, Frassanito, Gabriella, Lionetti, Raffaella, Dibenedetto, Clara, Morelli, Maria Cristina, Gambato, Martina, Martini, Silvia, Carrai, Paola, Toniutto, Pierluigi, Giannelli, Valerio, Donato, Francesca, Lenci, Ilaria, Pasulo, Luisa, Mazzarelli, Chiara, Ferrarese, Alberto, Rendina, Maria, Grieco, Antonio, Lanza, Alfonso Galeota, Baroni, Gianluca Svegliati, De Maria, Nicola, Marenco, Simona, Mameli, Laura, Ponziani, Francesca Romana, Vitale, Giovanni, and Burra, Patrizia

Published
2024
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230. Extreme Solar Events: Setting up a Paradigm

Author

Usoskin, Ilya, Miyake, Fusa, Baroni, Melanie, Brehm, Nicolas, Dalla, Silvia, Hayakawa, Hisashi, Hudson, Hugh, Jull, A. J. Timothy, Knipp, Delores, Koldobskiy, Sergey, Maehara, Hiroyuki, Mekhaldi, Florian, Notsu, Yuta, Poluianov, Stepan, Rozanov, Eugene, Shapiro, Alexander, Spiegl, Tobias, Sukhodolov, Timofei, Uusitalo, Joonas, and Wacker, Lukas

Published
2023
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231. Temporal validation of the MMCD score to predict kidney replacement therapy and in-hospital mortality in COVID-19 patients

Author

das Graças José Ventura, Vanessa, Pereira, Polianna Delfino, Pires, Magda Carvalho, Asevedo, Alisson Alves, de Oliveira Jorge, Alzira, dos Santos, Ana Carolina Pitanga, de Moura Costa, André Soares, dos Reis Gomes, Angélica Gomides, Lima, Beatriz Figueiredo, Pessoa, Bruno Porto, Cimini, Christiane Corrêa Rodrigues, de Andrade, Claudio Moisés Valiense, Ponce, Daniela, Rios, Danyelle Romana Alves, Pereira, Elayne Crestani, Manenti, Euler Roberto Fernandes, de Almeida Cenci, Evelin Paola, Costa, Felício Roberto, Anschau, Fernando, Aranha, Fernando Graça, Vigil, Flavia Maria Borges, Bartolazzi, Frederico, Aguiar, Gabriella Genta, Grizende, Genna Maira Santos, Batista, Joanna d’Arc Lyra, Neves, João Victor Baroni, Ruschel, Karen Brasil, do Nascimento, Letícia, de Oliveira, Lucas Moyses Carvalho, Kopittke, Luciane, de Castro, Luís César, Sacioto, Manuela Furtado, Carneiro, Marcelo, Gonçalves, Marcos André, Bicalho, Maria Aparecida Camargos, da Paula Sordi, Mônica Aparecida, da Cunha Severino Sampaio, Natália, Paraíso, Pedro Gibson, Menezes, Rochele Mosmann, Araújo, Silvia Ferreira, de Assis, Vivian Costa Morais, de Paula Farah, Katia, and Marcolino, Milena Soriano

Published
2023
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233. Hepatic steatosis with significant fibrosis is associated with an increased 10-year estimated risk of cardiovascular disease in adults with type 1 diabetes mellitus

Author

Mantovani, Alessandro, Morieri, Mario Luca, Palmisano, Luisa, Masulli, Maria, Cossu, Efisio, Baroni, Marco Giorgio, Bonomo, Katia, Cimini, Flavia Agata, Cavallo, Gisella, Buzzetti, Raffaella, Mignogna, Carmen, Leonetti, Frida, Bacci, Simonetta, Trevisan, Roberto, Pollis, Riccardo Maria, Aldigeri, Raffaella, Cas, Alessandra Dei, de Kreutzenberg, Saula Vigili, and Targher, Giovanni

Published
2023
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235. Correction: SELP Asp603Asn and severe thrombosis in COVID-19 males

Author

Fallerini, Chiara, Daga, Sergio, Benetti, Elisa, Picchiotti, Nicola, Zguro, Kristina, Catapano, Francesca, Baroni, Virginia, Lanini, Simone, Bucalossi, Alessandro, Marotta, Giuseppe, Colombo, Francesca, Baldassarri, Margherita, Fava, Francesca, Beligni, Giada, Di Sarno, Laura, Alaverdian, Diana, Palmieri, Maria, Croci, Susanna, Isidori, Andrea M., Furini, Simone, Frullanti, Elisa, Renieri, Alessandra, and Mari, Francesca

Published
2023
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238. Supporting decision-making in agricultural water management under data scarcity using global datasets – chances, limits and potential improvements

Author

Benjamin Kayatz, Gabriele Baroni, Jon Hillier, Stefan Lüdtke, Dirk Freese, and Martin Wattenbach

Subjects
Crop water use, Crop water requirement, Evapotranspiration, Irrigation, Cool farm tool, FAO56, Agriculture (General), S1-972, Agricultural industries, HD9000-9495
Abstract

Assessing alternative agricultural water management strategies requires long-term field trials or vast data collection for model calibration and simulation.This work aims to assess whether an uncalibrated agro-hydrological model using global input datasets for climate, soil and crop information can serve as a decision support tool for crop water management under data scarcity.This study employs the Cool Farm Tool Water (CFTW) at eight eddy covariance sites of the FLUXNET2015 dataset. CFTW is tested using global (CFTWglobal) and local (CFTWlocal) input datasets under current and alternative management scenarios.Results show that the use of global datasets for estimating daily evapotranspiration had little effect on the median Root Mean Square Error (RMSE) (CFTWglobal: 1.70 mm, CFTWlocal: 1.79 mm), while, however, the median model bias is much greater (CFTWglobal: −18.6%, CFTWlocal: −4.3%). Furthermore, the periods of water stress were little affected by the use of local or global data (median accuracy: 0.84), whereas the use of global data inputs led to a significant overestimation of irrigation water requirements (median difference: 110 mm). The model performance improves predominantly through the use of more representative local precipitation data, followed by local reference evapotranspiration and soil for some European growing seasons.We identify model outputs that can support decision-making when relying on global data, such as periods of water stress and the daily dynamics of water use. However, our findings also emphasize the difficulty of overcoming data scarcity in decision-making in agricultural water management. Furthermore, we provide recommendations for enhancing model performance and thus may increase the accessibility of reliable decision support tools in the future.

Published
2024
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239. Host genetics and COVID-19 severity: increasing the accuracy of latest severity scores by Boolean quantum features

Author

Gabriele Martelloni, Alessio Turchi, Chiara Fallerini, Andrea Degl’Innocenti, Margherita Baldassarri, Simona Olmi, Simone Furini, Alessandra Renieri, GEN-COVID Multicenter study, Francesca Mari, Sergio Daga, Ilaria Meloni, Mirella Bruttini, Susanna Croci, Mirjam Lista, Debora Maffeo, Elena Pasquinelli, Giulia Brunelli, Kristina Zguro, Viola Bianca Serio, Enrica Antolini, Simona Letizia Basso, Samantha Minetto, Giulia Rollo, Martina Rozza, Angela Rina, Rossella Tita, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Francesca Ariani, Francesca Montagnani, Mario Tumbarello, Ilaria Rancan, Massimiliano Fabbiani, Elena Bargagli, Laura Bergantini, Miriana d’Alessandro, Paolo Cameli, David Bennett, Federico Anedda, Simona Marcantonio, Sabino Scolletta, Federico Franchi, Maria Antonietta Mazzei, Susanna Guerrini, Edoardo Conticini, Luca Cantarini, Bruno Frediani, Danilo Tacconi, Chiara Spertilli Raffaelli, Arianna Emiliozzi, Marco Feri, Alice Donati, Raffaele Scala, Luca Guidelli, Genni Spargi, Marta Corridi, Cesira Nencioni, Leonardo Croci, Gian Piero Caldarelli, Davide Romani, Paolo Piacentini, Maria Bandini, Elena Desanctis, Silvia Cappelli, Anna Canaccini, Agnese Verzuri, Valentina Anemoli, Manola Pisani, Agostino Ognibene, Maria Lorubbio, Alessandro Pancrazzi, Massimo Vaghi, Antonella D’Arminio Monforte, Federica Gaia Miraglia, Mario U. Mondelli, Stefania Mantovani, Raffaele Bruno, Marco Vecchia, Marcello Maffezzoni, Enrico Martinelli, Massimo Girardis, Stefano Busani, Sophie Venturelli, Andrea Cossarizza, Andrea Antinori, Alessandra Vergori, Stefano Rusconi, Matteo Siano, Arianna Gabrieli, Agostino Riva, Daniela Francisci, Elisabetta Schiaroli, Carlo Pallotto, Saverio Giuseppe Parisi, Monica Basso, Sandro Panese, Stefano Baratti, Pier Giorgio Scotton, Francesca Andretta, Mario Giobbia, Renzo Scaggiante, Francesca Gatti, Francesco Castelli, Eugenia Quiros-Roldan, Melania Degli Antoni, Isabella Zanella, Matteo della Monica, Carmelo Piscopo, Mario Capasso, Roberta Russo, Immacolata Andolfo, Achille Iolascon, Giuseppe Fiorentino, Massimo Carella, Marco Castori, Giuseppe Merla, Gabriella Maria Squeo, Filippo Aucella, Pamela Raggi, Rita Perna, Matteo Bassetti, Antonio Di Biagio, Maurizio Sanguinetti, Luca Masucci, Alessandra Guarnaccia, Serafina Valente, Alex Di Florio, Marco Mandalà, Alessia Giorli, Lorenzo Salerni, Patrizia Zucchi, Pierpaolo Parravicini, Elisabetta Menatti, Tullio Trotta, Ferdinando Giannattasio, Gabriella Coiro, Fabio Lena, Gianluca Lacerenza, Cristina Mussini, Luisa Tavecchia, Lia Crotti, Gianfranco Parati, Roberto Menè, Maurizio Sanarico, Marco Gori, Francesco Raimondi, Alessandra Stella, Filippo Biscarini, Tiziana Bachetti, Maria Teresa La Rovere, Maurizio Bussotti, Serena Ludovisi, Katia Capitani, Simona Dei, Sabrina Ravaglia, Annarita Giliberti, Giulia Gori, Rosangela Artuso, Elena Andreucci, Angelica Pagliazzi, Erika Fiorentini, Antonio Perrella, Francesco Bianchi, Paola Bergomi, Emanuele Catena, Riccardo Colombo, Sauro Luchi, Giovanna Morelli, Paola Petrocelli, Sarah Iacopini, Sara Modica, Silvia Baroni, Giulia Micheli, Marco Falcone, Donato Urso, Giusy Tiseo, Tommaso Matucci, Davide Grassi, Claudio Ferri, Franco Marinangeli, Francesco Brancati, Antonella Vincenti, Valentina Borgo, Stefania Lombardi, Mirco Lenzi, Massimo Antonio Di Pietro, Francesca Vichi, Benedetta Romanin, Letizia Attala, Cecilia Costa, Andrea Gabbuti, Alessio Bellucci, Marta Colaneri, Patrizia Casprini, Cristoforo Pomara, Massimiliano Esposito, Roberto Leoncini, Michele Cirianni, Lucrezia Galasso, Marco Antonio Bellini, Chiara Gabbi, and Nicola Picchiotti

Subjects
COVID-19, host genetics, integrated polygenic score, genetic algorithm, logistic regression, genetic science modeling, Genetics, QH426-470
Abstract

The impact of common and rare variants in COVID-19 host genetics has been widely studied. In particular, in Fallerini et al. (Human genetics, 2022, 141, 147–173), common and rare variants were used to define an interpretable machine learning model for predicting COVID-19 severity. First, variants were converted into sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. After that, the Boolean features, selected by these logistic models, were combined into an Integrated PolyGenic Score (IPGS), which offers a very simple description of the contribution of host genetics in COVID-19 severity.. IPGS leads to an accuracy of 55%–60% on different cohorts, and, after a logistic regression with both IPGS and age as inputs, it leads to an accuracy of 75%. The goal of this paper is to improve the previous results, using not only the most informative Boolean features with respect to the genetic bases of severity but also the information on host organs involved in the disease. In this study, we generalize the IPGS adding a statistical weight for each organ, through the transformation of Boolean features into “Boolean quantum features,” inspired by quantum mechanics. The organ coefficients were set via the application of the genetic algorithm PyGAD, and, after that, we defined two new integrated polygenic scores (IPGSph1 and IPGSph2). By applying a logistic regression with both IPGS, (IPGSph2 (or indifferently IPGSph1) and age as inputs, we reached an accuracy of 84%–86%, thus improving the results previously shown in Fallerini et al. (Human genetics, 2022, 141, 147–173) by a factor of 10%.

Published
2024
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240. Traditional versus progressive robot-assisted gait training in people with multiple sclerosis and severe gait disability: study protocol for the PROGR-EX randomised controlled trial

Author

Michela Rimondini, Fabio Manfredini, Andrea Baroni, Sofia Straudi, Nicola Lamberti, Marialuisa Gandolfi, Valeria Bertagnolo, Silvia Grassilli, and Luigi Zerbinati

Subjects
Medicine (General), R5-920
Abstract

Gait disorders are the most frequent symptoms associated to multiple sclerosis (MS). Robot-assisted gait training (RAGT) in people with MS (PwMS) has been proposed as a possible effective treatment option for severe motor disability without significant superiority when compared to intensive overground gait training (OGT). Furthermore, RAGT at high intensity may enhance fatigue and spasticity. This study aims to evaluate the effects of a low-intensity RAGT at progressively increasing intensity compared to conventional RAGT and OGT in PwMS and moderate to severe walking impairment. 24 PwMS will be recruited and assigned to one of the three treatment groups: low-intensity RAGT at progressively increasing intensity, conventional RAGT and OGT. All participants will receive 3-weekly treatment sessions of 3 hours each for 4 weeks. In the first 2 hours of treatment, all participants will receive a rehabilitation programme based on stretching exercises, muscle strengthening and educational interventions. During the last hour, subjects will undergo specific gait training according to the assignment group. Outcomes will be assessed before and after treatment and at 3-month follow-up. The primary outcome is walking speed. Secondary outcomes include mobility and balance, psychological measures, muscle oxygen consumption, electrical and haemodynamic brain activity, urinary biomarkers, usability, and acceptability of robotic devices for motor rehabilitation. The results of this study will provide a safe, affordable and non-operator-dependent, intervention for PwMS. Results in terms of functional, psychological, neurophysiological and biological outcomes will confirm our hypothesis. The study’s trial registration number: NCT06381440.

Published
2024
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241. Atrial tachycardia ablation through the sub‐pulmonary ventricle in a patient with multiple malformations associated with congenitally corrected transposition of the great arteries and double‐sided slow‐pathway

Author

Alberto Preda, Alessio Testoni, Matteo Baroni, Patrizio Mazzone, and Lorenzo Gigli

Subjects
atrial tachycardia, catheter ablation, congenitally corrected transposition of great arteries, situs viscerus inversus, Medicine, Medicine (General), R5-920
Abstract

Key Clinical Message A 46‐year‐old woman with congenitally corrected transposition of the great arteries (ccTGA) associated with dextrocardia, situs viscerus inversus, and left superior vena cava persistence presented with an incessant supraventricular tachycardia. Electrophysiological study was not conclusive in differential diagnosis of atrial tachycardia versus atypical atrioventricular (AV) nodal reentrant tachycardia, also due to the unconventional anatomy of the coronary sinus. By a comprehensive mapping of cardiac chambers, a double side slow‐pathway was localized in both atrial chambers and subsequently ablated by radiofrequency delivery without tachycardia changes. Aortic root and cusps were devoid of electrical activity. The muscular part of the sub‐pulmonary ventricle at the level of interatrial septum showed an earliest activation signal of −90 ms and ablation of this site was effective in abolish the tachycardia. This is the first case to report technical concerns of septal atrial tachycardia ablation in ccTGA associated with multiple anatomical malformations. Moreover, some peculiarities have been reported for the first time including the presence of double‐side AV nodal slow‐pathway and atypical localization of the tachycardia origin into the muscular part of the sub‐pulmonary ventricle instead of posterior pulmonary cusp.

Published
2024
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242. Long-term benefits of dapagliflozin on renal outcomes of type 2 diabetes under routine care: a comparative effectiveness study on propensity score matched cohorts at low renal riskResearch in context

Author

Gian Paolo Fadini, Enrico Longato, Mario Luca Morieri, Stefano Del Prato, Angelo Avogaro, Anna Solini, Mariella Baldassarre, Agostino Consoli, Sara Morganet, Antonella Zugaro, Marco Giorgio Baroni, Francesco Andreozzi, Adriano Gatti, Stefano De Riu, Andrea Del Buono, Raffaella Aldigeri, Riccardo Bonadonna, Alessandra Dei Cas, Angela Vazzana, Monica Antonini, Valentina Moretti, Patrizia Li Volsi, Miranda Cesare, Giorgio Zanette, Silvia Carletti, Paola D'Angelo, Gaetano Leto, Frida Leonetti, Luca D'Onofrio, Ernesto Maddaloni, Raffaella Buzzetti, Simona Frontoni, Giselle Cavallo, Susanna Morano, Tiziana Filardi, Umberto Capece, Andrea Giaccari, Antonio C. Bossi, Giancarla Meregalli, Fabrizio Querci, Alessia Gaglio, Veronica Resi, Emanuela Orsi, Stefano Fazion, Ivano G. Franzetti, Cesare Berra, Silvia Manfrini, Gabriella Garrapa, Giulio Lucarelli, Lara Riccialdelli, Elena Tortato, Marco Zavattaro, Gianluca Aimaretti, Franco Cavalot, Guglielmo Beccuti, Fabio Broglio, Bruno Fattor, Giuliana Cazzetta, Olga Lamacchia, Anna Rauseo, Salvatore De Cosmo, Rosella Cau, Mariangela Ghiani, Antonino Di Benedetto, Antonino Di Pino, Salvatore Piro, Francesco Purrello, Lucia Frittitta, Agostino Milluzzo, and Giuseppina Russo

Subjects
Type 2 diabetes, Chronic kidney disease, SGLT2 inhibitors, Prevention, Observational, Public aspects of medicine, RA1-1270
Abstract

Summary: Background: Despite the overall improvement in care, people with type 2 diabetes (T2D) experience an excess risk of end-stage kidney disease. We evaluated the long-term effectiveness of dapagliflozin on kidney function and albuminuria in patients with T2D. Methods: We included patients with T2D who initiated dapagliflozin or comparators from 2015 to 2020. Propensity score matching (PSM) was performed to balance the two groups. The primary endpoint was the change in estimated glomerular filtration rate (eGFR) from baseline to the end of observation. Secondary endpoints included changes in albuminuria and loss of kidney function. Findings: We analysed two matched groups of 6197 patients each. The comparator group included DPP-4 inhibitors (40%), GLP-1RA (22.3%), sulphonylureas (16.1%), pioglitazone (8%), metformin (5.8%), or acarbose (4%). Only 6.4% had baseline eGFR 30 mg/g. During a mean follow-up of 2.5 year, eGFR declined significantly less in the dapagliflozin vs comparator group by 1.81 ml/min/1.73 m2 (95% C.I. from 1.13 to 2.48; p

Published
2024
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243. Heat transport in liquid water from first-principles and deep-neural-network simulations

Author

Tisi, Davide, Zhang, Linfeng, Bertossa, Riccardo, Wang, Han, Car, Roberto, and Baroni, Stefano

Subjects
Condensed Matter - Materials Science, Condensed Matter - Disordered Systems and Neural Networks, Physics - Computational Physics
Abstract

We compute the thermal conductivity of water within linear response theory from equilibrium molecular dynamics simulations, by adopting two different approaches. In one, the potential energy surface (PES) is derived on the fly from the electronic ground state of density functional theory (DFT) and the corresponding analytical expression is used for the energy flux. In the other, the PES is represented by a deep neural network (DNN) trained on DFT data, whereby the PES has an explicit local decomposition and the energy flux takes a particularly simple expression. By virtue of a gauge invariance principle, established by Marcolongo, Umari, and Baroni, the two approaches should be equivalent if the PES were reproduced accurately by the DNN model. We test this hypothesis by calculating the thermal conductivity, at the GGA (PBE) level of theory, using the direct formulation and its DNN proxy, finding that both approaches yield the same conductivity, in excess of the experimental value by approximately 60%. Besides being numerically much more efficient than its direct DFT counterpart, the DNN scheme has the advantage of being easily applicable to more sophisticated DFT approximations, such as meta-GGA and hybrid functionals, for which it would be hard to derive analytically the expression of the energy flux. We find in this way, that a DNN model, trained on meta-GGA (SCAN) data, reduce the deviation from experiment of the predicted thermal conductivity by about 50%, leaving the question open as to whether the residual error is due to deficiencies of the functional, to a neglect of nuclear quantum effects in the atomic dynamics, or, likely, to a combination of the two.

Published
2021
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244. Electroweak Currents from Chiral Effective Field Theory

Author

Baroni, Alessandro, King, Garrett B., and Pastore, Saori

Subjects
Nuclear Theory
Abstract

Since the pioneering work of Weinberg, Chiral Effective Field Theory ($\chi$EFT) has been widely and successfully utilized in nuclear physics to study many-nucleon interactions and associated electroweak currents. Nuclear $\chi$EFT has now developed into an intense field of research and is applied to study light to medium mass nuclei. In this contribution, we focus on the development of electroweak currents from $\chi$EFT and present applications to selected nuclear electroweak observables.

Published
2021
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245. On the proper role of linguistically-oriented deep net analysis in linguistic theorizing

Author

Baroni, Marco

Subjects
Computer Science - Computation and Language
Abstract

A lively research field has recently emerged that uses experimental methods to probe the linguistic behavior of modern deep networks. While work in this tradition often reports intriguing results about the grammatical skills of deep nets, it is not clear what their implications for linguistic theorizing should be. As a consequence, linguistically-oriented deep net analysis has had very little impact on linguistics at large. In this chapter, I suggest that deep networks should be treated as theories making explicit predictions about the acceptability of linguistic utterances. I argue that, if we overcome some obstacles standing in the way of seriously pursuing this idea, we will gain a powerful new theoretical tool, complementary to mainstream algebraic approaches., Comment: To appear in collective volume on Algebraic Systems and the Representation of Linguistic Knowledge, editor: Shalom Lappin, Taylor & Francis

Published
2021

246. Interpretable agent communication from scratch (with a generic visual processor emerging on the side)

Author

Dessì, Roberto, Kharitonov, Eugene, and Baroni, Marco

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Multiagent Systems
Abstract

As deep networks begin to be deployed as autonomous agents, the issue of how they can communicate with each other becomes important. Here, we train two deep nets from scratch to perform realistic referent identification through unsupervised emergent communication. We show that the largely interpretable emergent protocol allows the nets to successfully communicate even about object types they did not see at training time. The visual representations induced as a by-product of our training regime, moreover, show comparable quality, when re-used as generic visual features, to a recent self-supervised learning model. Our results provide concrete evidence of the viability of (interpretable) emergent deep net communication in a more realistic scenario than previously considered, as well as establishing an intriguing link between this field and self-supervised visual learning., Comment: Accepted at NeurIPS 2021

Published
2021

247. Tuberculosis among children and adolescents with rheumatic diseases - case series

Author

Lenita de Melo Lima, Adriana Rodrigues Fonseca, Clemax Couto Sant’Anna, Ana Alice Amaral Ibiapina Parente, Rafaela Baroni Aurilio, and Maria de Fátima Bazhuni Pombo Sant’Anna

Subjects
Mycobacterium tuberculosis, Pediatric rheumatic Diseases, Juvenile idiopathic arthritis, Pediatrics, RJ1-570, Diseases of the musculoskeletal system, RC925-935
Abstract

Abstract Background: Rheumatic patients have a higher frequency of tuberculosis(TB) than the general population. This study aimed to describe children and adolescents with TB and rheumatic diseases(RD) who were being treated in a reference center. Methods: A series of TB cases were investigated in a reference center for childhood TB in Rio de Janeiro, Brazil, from 1995 to 2022. Results: Fifteen patients with underlying RD and TB were included with 8(53%) being female. The mean age at RD diagnosis was 7.10years (SD ± 0,57 years), and the mean age at TB diagnosis was 9.81 years(SD ± 0.88 years). A total of 9 cases of pulmonary TB(PTB) and 6 cases of extrapulmonary TB—pleural(2), joint/osteoarticular(1), cutaneous(1), ocular(1), and peritoneal(1)- were described. The RD observed in the 15 patients included juvenile idiopathic arthritis(9), juvenile systemic lupus erythematosus(3), juvenile dermatomyositis(1), polyarteritis nodosa(1), and pyoderma gangrenosum(1). Among the immunosuppressants/immunobiologics, methotrexate(8) was the most commonly used, followed by corticosteroids(6), etanercept(2), mycophenolate mofetil(1), cyclosporine A(1), adalimumab(1), and tocilizumab(1). The most common symptoms were fever and weight loss, and a predominance of PTB cases was noted. GeneXpert MTB/RIF® was performed in six patients and was detectable in two without rifampicin resistance; Xpert Ultra® was performed in five patients, and traces with indeterminate rifampicin resistance were detected in three. One female patient discontinued treatment, and another passed away. Conclusions: The case series demonstrated the importance of suspecting and investigating TB in RD affected patients who are using immunosuppressants/ immunobiologics, particularly in countries with high rates of TB such as Brazil.

Published
2023
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248. Diets including Animal Food Are Associated with Gastroesophageal Reflux Disease

Author

Luciana Baroni, Chiara Bonetto, Irene Solinas, Pierfrancesco Visaggi, Alexey V. Galchenko, Lucia Mariani, Andrea Bottari, Mattia Orazzini, Giada Guidi, Christian Lambiase, Linda Ceccarelli, Massimo Bellini, Edoardo V. Savarino, and Nicola de Bortoli

Subjects
gastroesophageal reflux disease, GERD, animal-based diet, vegan diet, heartburn, regurgitation, Public aspects of medicine, RA1-1270, Psychology, BF1-990
Abstract

Gastroesophageal reflux disease (GERD) is a clinical condition with a prevalence of up to 25% in Western countries. Typical GERD symptoms include heartburn and retrosternal regurgitation. Lifestyle modifications, including diet, are considered a first-line therapeutic approach. To evaluate the impact of life habits on GERD in this cross-sectional study, we used data collected through an online survey from 1146 participants. GERD was defined according to the Montreal Consensus. For all participants, clinical and lifestyle characteristics were recorded. Overall, 723 participants (63.1%) consumed a diet including animal food (non-vegans), and 423 participants (36.9%) were vegans. The prevalence of GERD was 11% (CI 95%, 9–14%) in non-vegans and 6% (CI 95%, 4–8%) in vegans. In the multivariate analysis, after adjusting for confounding factors, subjects on a non-vegan diet were associated with a two-fold increase in the prevalence of GERD compared to vegans (OR = 1.96, CI 95%, 1.22–3.17, p = 0.006). BMI and smoking habits were also significantly associated with GERD. This study shows that an animal food-based diet (meat, fish, poultry, dairy, and eggs) is associated with an increased risk of GERD compared to a vegan diet. These findings might inform the lifestyle management of patients with GERD-related symptoms.

Published
2023
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249. Conversa de porta aberta com Fátima Lima

Author

Patrícia Baroni, Allan Rodrigues, and Luís Paulo Cruz Borges

Subjects
epistemologias negras, antirracismo, escrevivências, Education (General), L7-991
Abstract

A entrevista do presente dossiê, que focaliza a “EPISTEMOLOGIAS DA PEDAGOGIA ANTIRRACISTA: alternativas ao pensamento hegemônico estrutural”, foi concedida pela professora doutora Fátima Lima. Mulher, nordestina, negra, lésbica, militante e muitas coisas mais. Professora Associada da Universidade Federal do Rio de Janeiro/UFRJ/Campi Macaé. É colaboradora da Organização Não-Governamental ‘Casa das Pretas’. Professora do Programa Interdisciplinar de Pós-Graduação em Linguística Aplicada (PIPGLA/UFRJ), do Programa de Pós-Graduação em Relações Étnico Raciais (PPRER/CEFET/RJ) e do Programa de Pós-Graduação em Psicossociologia de Comunidades e Ecologia Social do Instituto de Psicologia (PPGPCESI-UFRJ). Coordenadora do Grupo ORI - Grupo de pesquisa em Raça, Gênero e Sexualidade (CNPq). O dossiê focaliza reunir um conjunto de epistemologias da pedagogia antirracista problematizando as narrativas lineares e únicas presentes na contemporaneidade. Em sua entrevista Fátima indica pistas, mas paradoxalmente nos coloca diante de encruzilhadas epistêmicas, políticas e educativas. Sua voz ecoa, também, indicando que muitas outras mulheres, algumas já ancestrais, abriram caminho para que hoje pudéssemos seguir.

Published
2023
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250. STRATEGIES FOR DIGITAL RETAIL TRANSFORMATION: A CASE STUDY OF A SHOE STORE LARGE CHAIN/Estrategias para a Transformacao Digital do Varejo: um estudo de caso de uma grande rede de lojas de calcados/Estrategias para la transformacion digital del comercio minorista: un estudio de caso de una grande cadena de zapaterias

Author

Goulart, Diocelio Dornela, de Carvalho, Rodrigo Baroni, Castro, Joao Paulo de Souza, Guimaraes, Liliane de Oliveira, and Pereira, Bianka Alves Pinheiro de Assis

Published
2024
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