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5,079 results on '"Clerico, A."'

1. Retina-inspired Object Motion Segmentation

Author

Clerico, Victoria, Snyder, Shay, Lohia, Arya, Kaiser, Md Abdullah-Al, Schwartz, Gregory, Jaiswal, Akhilesh, and Parsa, Maryam

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Dynamic Vision Sensors (DVS) have emerged as a revolutionary technology with a high temporal resolution that far surpasses RGB cameras. DVS technology draws biological inspiration from photoreceptors and the initial retinal synapse. Our research showcases the potential of additional retinal functionalities to extract visual features. We provide a domain-agnostic and efficient algorithm for ego-motion compensation based on Object Motion Sensitivity (OMS), one of the multiple robust features computed within the mammalian retina. We develop a framework based on experimental neuroscience that translates OMS' biological circuitry to a low-overhead algorithm. OMS processes DVS data from dynamic scenes to perform pixel-wise object motion segmentation. Using a real and a synthetic dataset, we highlight OMS' ability to differentiate object motion from ego-motion, bypassing the need for deep networks. This paper introduces a bio-inspired computer vision method that dramatically reduces the number of parameters by a factor of 1000 compared to prior works. Our work paves the way for robust, high-speed, and low-bandwidth decision-making for in-sensor computations.

Published
2024

2. Hardware-Algorithm Re-engineering of Retinal Circuit for Intelligent Object Motion Segmentation

Author

Sinaga, Jason, Clerico, Victoria, Kaiser, Md Abdullah-Al, Snyder, Shay, Lohia, Arya, Schwartz, Gregory, Parsa, Maryam, and Jaiswal, Akhilesh

Subjects
Computer Science - Neural and Evolutionary Computing, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Recent advances in retinal neuroscience have fueled various hardware and algorithmic efforts to develop retina-inspired solutions for computer vision tasks. In this work, we focus on a fundamental visual feature within the mammalian retina, Object Motion Sensitivity (OMS). Using DVS data from EV-IMO dataset, we analyze the performance of an algorithmic implementation of OMS circuitry for motion segmentation in presence of ego-motion. This holistic analysis considers the underlying constraints arising from the hardware circuit implementation. We present novel CMOS circuits that implement OMS functionality inside image sensors, while providing run-time re-configurability for key algorithmic parameters. In-sensor technologies for dynamical environment adaptation are crucial for ensuring high system performance. Finally, we verify the functionality and re-configurability of the proposed CMOS circuit designs through Cadence simulations in 180nm technology. In summary, the presented work lays foundation for hardware-algorithm re-engineering of known biological circuits to suit application needs.

Published
2024

3. Superballistic conduction in hydrodynamic antidot graphene superlattices

Author

Estrada-Álvarez, Jorge, Salvador-Sánchez, Juan, Pérez-Rodríguez, Ana, Sánchez-Sánchez, Carlos, Clericò, Vito, Vaquero, Daniel, Watanabe, Kenji, Taniguchi, Takashi, Diez, Enrique, Domínguez-Adame, Francisco, Amado, Mario, and Díaz, Elena

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Physics - Fluid Dynamics
Abstract

Viscous electron flow exhibits exotic signatures such as superballistic conduction. Bending the geometry of the device is a must to observe hydrodynamic effects. To this end, we build three antidot graphene superlattices with different hole diameters. We measure their electrical properties at various temperatures and under the effect of a perpendicular magnetic field. We find an enhanced superballistic effect, suggesting the effectiveness of the geometry at bending the electron flow. In addition, superballistic conduction behaves non-monotonically with the magnetic field, which is related with the ballistic-hydrodynamic transition. We also analyze the device resistance as a function of the size of the antidot superlattice to find characteristic scaling laws describing the different transport regimes. We prove that the antidot superlattice is a convenient geometry for realizing hydrodynamic flow, and the experiment provides valuable explanations for the technologically relevant effects of superballistic conduction and scaling laws.

Published
2024

4. Generalization bounds for mixing processes via delayed online-to-PAC conversions

Author

Abeles, Baptiste, Clerico, Eugenio, and Neu, Gergely

Subjects
Computer Science - Machine Learning
Abstract

We study the generalization error of statistical learning algorithms in a non-i.i.d. setting, where the training data is sampled from a stationary mixing process. We develop an analytic framework for this scenario based on a reduction to online learning with delayed feedback. In particular, we show that the existence of an online learning algorithm with bounded regret (against a fixed statistical learning algorithm in a specially constructed game of online learning with delayed feedback) implies low generalization error of said statistical learning method even if the data sequence is sampled from a mixing time series. The rates demonstrate a trade-off between the amount of delay in the online learning game and the degree of dependence between consecutive data points, with near-optimal rates recovered in a number of well-studied settings when the delay is tuned appropriately as a function of the mixing time of the process.

Published
2024

5. Parallelized Multi-Agent Bayesian Optimization in Lava

Author

Snyder, Shay, Gobin, Derek, Clerico, Victoria, Risbud, Sumedh R., and Parsa, Maryam

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

In parallel with the continuously increasing parameter space dimensionality, search and optimization algorithms should support distributed parameter evaluations to reduce cumulative runtime. Intel's neuromorphic optimization library, Lava-Optimization, was introduced as an abstract optimization system compatible with neuromorphic systems developed in the broader Lava software framework. In this work, we introduce Lava Multi-Agent Optimization (LMAO) with native support for distributed parameter evaluations communicating with a central Bayesian optimization system. LMAO provides an abstract framework for deploying distributed optimization and search algorithms within the Lava software framework. Moreover, LMAO introduces support for random and grid search along with process connections across multiple levels of mathematical precision. We evaluate the algorithmic performance of LMAO with a traditional non-convex optimization problem, a fixed-precision transductive spiking graph neural network for citation graph classification, and a neuromorphic satellite scheduling problem. Our results highlight LMAO's efficient scaling to multiple processes, reducing cumulative runtime and minimizing the likelihood of converging to local optima., Comment: 4 pages, 2 figures, 2 algorithms, 2 tables

Published
2024

6. Transductive Spiking Graph Neural Networks for Loihi

Author

Snyder, Shay, Clerico, Victoria, Cong, Guojing, Kulkarni, Shruti, Schuman, Catherine, Risbud, Sumedh R., and Parsa, Maryam

Subjects
Computer Science - Emerging Technologies, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract

Graph neural networks have emerged as a specialized branch of deep learning, designed to address problems where pairwise relations between objects are crucial. Recent advancements utilize graph convolutional neural networks to extract features within graph structures. Despite promising results, these methods face challenges in real-world applications due to sparse features, resulting in inefficient resource utilization. Recent studies draw inspiration from the mammalian brain and employ spiking neural networks to model and learn graph structures. However, these approaches are limited to traditional Von Neumann-based computing systems, which still face hardware inefficiencies. In this study, we present a fully neuromorphic implementation of spiking graph neural networks designed for Loihi 2. We optimize network parameters using Lava Bayesian Optimization, a novel hyperparameter optimization system compatible with neuromorphic computing architectures. We showcase the performance benefits of combining neuromorphic Bayesian optimization with our approach for citation graph classification using fixed-precision spiking neurons. Our results demonstrate the capability of integer-precision, Loihi 2 compatible spiking neural networks in performing citation graph classification with comparable accuracy to existing floating point implementations., Comment: 6 pages, 4 figures, 3 tables

Published
2024

7. Diabetes as a risk factor for pneumococcal disease and severe related outcomes and efficacy/effectiveness of vaccination in diabetic population. Results from meta-analysis of observational studies

Author

Silverii, Giovanni Antonio, Gabutti, Giovanni, Tafuri, Silvio, Sarti, Francesca, Pratesi, Anna, Clerico, Alessandra, Fornengo, Riccardo, Greco, Carla, Irace, Concetta, Sordi, Valeria, Sorice, Gian Pio, Cavallo, Massimiliano, Ponziani, Maria Chantal, Mannucci, Edoardo, and Dicembrini, Ilaria

Published
2024
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8. ChatGPT vs. neurologists: a cross-sectional study investigating preference, satisfaction ratings and perceived empathy in responses among people living with multiple sclerosis

Author

Maida, Elisabetta, Moccia, Marcello, Palladino, Raffaele, Borriello, Giovanna, Affinito, Giuseppina, Clerico, Marinella, Repice, Anna Maria, Di Sapio, Alessia, Iodice, Rosa, Spiezia, Antonio Luca, Sparaco, Maddalena, Miele, Giuseppina, Bile, Floriana, Scandurra, Cristiano, Ferraro, Diana, Stromillo, Maria Laura, Docimo, Renato, De Martino, Antonio, Mancinelli, Luca, Abbadessa, Gianmarco, Smolik, Krzysztof, Lorusso, Lorenzo, Leone, Maurizio, Leveraro, Elisa, Lauro, Francesca, Trojsi, Francesca, Streito, Lidia Mislin, Gabriele, Francesca, Marinelli, Fabiana, Ianniello, Antonio, De Santis, Federica, Foschi, Matteo, De Stefano, Nicola, Morra, Vincenzo Brescia, Bisecco, Alvino, Coghe, Giancarlo, Cocco, Eleonora, Romoli, Michele, Corea, Francesco, Leocani, Letizia, Frau, Jessica, Sacco, Simona, Inglese, Matilde, Carotenuto, Antonio, Lanzillo, Roberta, Padovani, Alessandro, Triassi, Maria, Bonavita, Simona, and Lavorgna, Luigi

Published
2024
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9. A note on regularised NTK dynamics with an application to PAC-Bayesian training

Author

Clerico, Eugenio and Guedj, Benjamin

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

We establish explicit dynamics for neural networks whose training objective has a regularising term that constrains the parameters to remain close to their initial value. This keeps the network in a lazy training regime, where the dynamics can be linearised around the initialisation. The standard neural tangent kernel (NTK) governs the evolution during the training in the infinite-width limit, although the regularisation yields an additional term appears in the differential equation describing the dynamics. This setting provides an appropriate framework to study the evolution of wide networks trained to optimise generalisation objectives such as PAC-Bayes bounds, and hence potentially contribute to a deeper theoretical understanding of such networks.

Published
2023

10. Stem cell collection and hematological recovery in the Fondazione Italiana Linfomi (FIL) MCL0208 clinical trial

Author

Michele Clerico, Simone Ferrero, Beatrice Alessandria, Gian Maria Zaccaria, Elisa Genuardi, Simone Ragaini, Rita Tavarozzi, Federica Cavallo, Stefan Hohaus, Gerardo Musuraca, Angelo Michele Carella, Caterina Stelitano, Monica Tani, Gianluca Gaidano, Jacopo Olivieri, Sara Veronica Usai, Sara Galimberti, Francesca Re, Michael Mian, Claudia Castellino, Vincenzo Pavone, Andrea Evangelista, Benedetto Bruno, Sergio Cortelazzo, Roberto Passera, and Marco Ladetto

Subjects
Mantle cell lymphoma (MCL), Autologous stem cell transplantation (ASCT), Peripheral blood stem cells (PBSC), Leukapheresis (LK), Hematological recovery, Medicine, Science
Abstract

Abstract In the frontline high-dose phase 3 FIL-MCL0208 trial (NCT02354313), 8% of enrolled mantle cell lymphoma (MCL) patients could not be randomised to receive lenalidomide (LEN) maintenance vs observation after autologous stem cell transplantation (ASCT) due to inadequate hematological recovery and 52% of those who started LEN, needed a dose reduction due to toxicity. We therefore focused on the role played by CD34 + hematopoietic stem cells (PBSC) harvesting and reinfusion on toxicity and outcome. Overall, 90% (n = 245) of enrolled patients who underwent the first leukapheresis collected ≥ 4 × 106 PBSC/kg, 2.6% (n = 7) mobilized 10 days) was associated with a worse outcome, both in terms of PFS and OS. In conclusion, although the harvesting procedures proved feasible for younger MCL patients, long-lasting cytopenia following ASCT remains a significant issue: this can hinder the administration of effective maintenance therapies, potentially increasing the relapse rate and negatively affecting survival outcomes.

Published
2024
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11. LSTM Framework for Classification of Radar and Communications Signals

Author

Clerico, Victoria, Gonzalez-Lopez, Jorge, Agam, Gady, and Grajal, Jesus

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Although radar and communications signal classification are usually treated separately, they share similar characteristics, and methods applied in one domain can be potentially applied in the other. We propose a simple and unified scheme for the classification of radar and communications signals using Long Short-Term Memory (LSTM) neural networks. This proposal provides an improvement of the state of the art on radar signals where LSTM models are starting to be applied within schemes of higher complexity. To date, there is no standard public dataset for radar signals. Therefore, we propose DeepRadar2022, a radar dataset used in our systematic evaluations that is available publicly and will facilitate a standard comparison between methods., Comment: This paper was submitted to the Radar Conference 2023

Published
2023

13. Stem cell collection and hematological recovery in the Fondazione Italiana Linfomi (FIL) MCL0208 clinical trial

Author

Clerico, Michele, Ferrero, Simone, Alessandria, Beatrice, Zaccaria, Gian Maria, Genuardi, Elisa, Ragaini, Simone, Tavarozzi, Rita, Cavallo, Federica, Hohaus, Stefan, Musuraca, Gerardo, Carella, Angelo Michele, Stelitano, Caterina, Tani, Monica, Gaidano, Gianluca, Olivieri, Jacopo, Usai, Sara Veronica, Galimberti, Sara, Re, Francesca, Mian, Michael, Castellino, Claudia, Pavone, Vincenzo, Evangelista, Andrea, Bruno, Benedetto, Cortelazzo, Sergio, Passera, Roberto, and Ladetto, Marco

Published
2024
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16. SARS-CoV-2 vaccination and multiple sclerosis: a large multicentric study on relapse risk after the third booster dose

Author

Di Filippo, Massimiliano, Ferraro, Diana, Ragonese, Paolo, Prosperini, Luca, Maniscalco, Giorgia Teresa, Gallo, Antonio, Cavalla, Paola, Lorefice, Lorena, Nociti, Viviana, Di Sabatino, Elena, Clerico, Marinella, Guaschino, Clara, Radaelli, Marta, Fantozzi, Roberta, Buttari, Fabio, Laroni, Alice, Gajofatto, Alberto, Calabrese, Massimiliano, Malucchi, Simona, Paolicelli, Damiano, De Luca, Giovanna, Tomassini, Valentina, Lanzillo, Roberta, Moccia, Marcello, Solaro, Claudio, Cocco, Eleonora, Gasperini, Claudio, and Tortorella, Carla

Published
2024
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17. Phonon-mediated room-temperature quantum Hall transport in graphene

Author

Vaquero, Daniel, Clericò, Vito, Schmitz, Michael, Delgado-Notario, Juan Antonio, Martín-Ramos, Adrian, Salvador-Sánchez, Juan, Müller, Claudius S. A., Rubi, Km, Watanabe, Kenji, Taniguchi, Takashi, Beschoten, Bernd, Stampfer, Christoph, Diez, Enrique, Katsnelson, Mikhail I., Zeitler, Uli, Wiedmann, Steffen, and Pezzini, Sergio

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

The quantum Hall (QH) effect in two-dimensional electron systems (2DESs) is conventionally observed at liquid-helium temperatures, where lattice vibrations are strongly suppressed and bulk carrier scattering is dominated by disorder. However, due to large Landau level (LL) separation (~2000 K at B = 30 T), graphene can support the QH effect up to room temperature (RT), concomitant with a non-negligible population of acoustic phonons with a wave-vector commensurate to the inverse electronic magnetic length. Here, we demonstrate that graphene encapsulated in hexagonal boron nitride (hBN) realizes a novel transport regime, where dissipation in the QH phase is governed predominantly by electron-phonon scattering. Investigating thermally-activated transport at filling factor 2 up to RT in an ensemble of back-gated devices, we show that the high B-field behaviour correlates with their zero B-field transport mobility. By this means, we extend the well-accepted notion of phonon-limited resistivity in ultra-clean graphene to a hitherto unexplored high-field realm., Comment: 17 pages, 4 figures. Supplementary information available at https://doi.org/10.1038/s41467-023-35986-3

Published
2023
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19. Long-term effectiveness of natalizumab in secondary progressive multiple sclerosis: A propensity-matched study

Author

Clara G. Chisari, Umberto Aguglia, Maria Pia Amato, Roberto Bergamaschi, Antonio Bertolotto, Simona Bonavita, Vincenzo Brescia Morra, Paola Cavalla, Eleonora Cocco, Antonella Conte, Salvatore Cottone, Giovanna De Luca, Alessia Di Sapio, Massimo Filippi, Antonio Gallo, Claudio Gasperini, Franco Granella, Giacomo Lus, Davide Maimone, Giorgia Teresa Maniscalco, Girolama Marfia, Lucia Moiola, Damiano Paolicelli, Ilaria Pesci, Paolo Ragonese, Marco Rovaris, Giuseppe Salemi, Claudio Solaro, Rocco Totaro, Maria Trojano, Marika Vianello, Mauro Zaffaroni, Vito Lepore, Francesco Patti, Carlo Avolio, Roberto Balgera, Paola Banfi, Paolo Bellantonio, Placido Bramanti, Lorenzo Capone, Guido Cavalletti, Luca Chiveri, Raffaella Clerici, Marinella Clerico, Francesco Corea, Vincenzo Dattola, Francesca De Robertis, Giancarlo Di Battista, Simonetta Galgani, Maurizia Gatto, Maria Grazia Grasso, Matilde Inglese, Lorenzo Lo Russo, Francesco Ottavio Logullo, Renato Mantegazza, Alessandra Protti, Monica Rezzonico, Mariarosa Rottoli, Marco Salvetti, Elio Scarpini, Leonardo Sinisi, Maddalena Sparaco, Daniele Spitaleri, Tiziana Tassinari, Simone Tonietti, Paola Valentino, Franco Valzania, and Simonetta Venturi

Subjects
Natalizumab, Interferon beta 1b, Secondary progressive multiple sclerosis, Disability progression, Neurology. Diseases of the nervous system, RC346-429
Abstract

Treatment options for secondary progressive MS (SPMS) are limited, especially considering that the new drugs recently approved are licensed for actively relapsing patients. We aimed to compare the disability progression in a real-world cohort of SPMS patients treated with natalizumab (NTZ) or interferon beta-1b (IFNb-1b). This multicenter retrospective enrolled patients with a diagnosis of SPMS according to 2014 Lublin criteria, who received NTZ or IFNb-1b for at least 48 months between the 1st June 2012 and the 15th May 2018 ​at 33 Italian MS centers contributing to the Italian MS Registry NTZ or IFNb-1b. Confirmed Expanded Disability Status Scale worsening (CEW) and progression independent of relapse (PIRA) were evaluated. In order to correct for non-randomization, a propensity score matching of the groups was performed. Out of 5206 MS patients identified at the time of data extraction, 421 SPMS patients treated with NTZ (224 [53.2%] females, mean age 45.3 ​± ​25.4 years) and 353 with IFNb-1b (133 [37.8%] females, mean age 48.5 ​± ​19.8 years) were enrolled. After applying the matching procedure, 102 patients were retained in the NTZ group and 98 in the IFNb-2b group. The proportion of patients who reached the 48-month 1-point CEW was significantly higher in IFNb-1b compared to NTZ group (58.2% versus 30.4%, p ​= ​0.01). The proportion of patients who developed PIRA at 48 months were significantly higher in IFNb-1b compared to NTZ (72.4% versus 40.2%, p ​= ​0.01). EDSS before treatment initiation and SPMS duration were risk factors for disability progression in terms of PIRA (HR 2.54, 25%CI 1.67–5.7; p ​= ​0.006 and HR 2.04, 25%CI 1.22–3.35; p ​= ​0.01, respectively). Patients treated with IFNb-1b were 1.64 times more to likely to develop PIRA (HR 1.64, 25%CI 1.04–4.87; p ​= ​0.001). Treatment with NTZ in SPMS patients showed more favorable disability outcomes compared to IFNb-1b with beneficial effects over 48 months.

Published
2024
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20. Real life clinical outcomes of relapsed/refractory diffuse large B cell lymphoma in the rituximab era: The STRIDER study

Author

Irene Dogliotti, Veronica Peri, Michele Clerico, Francesco Vassallo, Davide Musto, Silvio Mercadante, Simone Ragaini, Barbara Botto, Mario Levis, Mattia Novo, Marco Ghislieri, Luca Molinaro, Umberto Mortara, Chiara Consoli, Alessio Lonardo, Giulia Bondielli, Simone Ferrero, Roberto Freilone, Umberto Ricardi, Benedetto Bruno, and Federica Cavallo

Subjects
chemotherapy, diffuse large B cell lymphoma, real world, refractory disease, relapse, rituximab, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Relapse and refractory (R/R) rates after first‐line R‐CHOP in diffuse large B cell lymphomas (DLBCL) are ~40% and ~15% respectively. Aims We conducted a retrospective real‐world analysis aimed at evaluating clinical outcomes of R/R DLBCL patients. Material and Methods Overall, 403 consecutive DLBCL patients treated in two large hematological centers in Torino, Italy were reviewed. Results At a median follow up of 50 months, 5‐year overall survival from diagnosis (OS‐1) was 66.5%, and 2‐year progression free survival (PFS‐1) was 68%. 134 (34.4%) patients relapsed (n = 46, 11.8%) or were refractory (n = 88, 22.6%) to R‐CHOP. Most employed salvage treatments included platinum salt‐based regimens in 38/134 (28.4%), lenalidomide in 14 (10.4%). Median OS and PFS after disease relapse or progression (OS‐2 and PFS‐2) were 6.7 and 5.1 months respectively. No significant difference in overall response rate, OS‐2 or PFS‐2 in patients treated with platinum‐based regimens versus other regimens was observed. By multivariate analysis, age between 60 and 80 years, germinal center B cell type cell of origin and extranodal involvement of

Published
2024
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21. Generalisation under gradient descent via deterministic PAC-Bayes

Author

Clerico, Eugenio, Farghly, Tyler, Deligiannidis, George, Guedj, Benjamin, and Doucet, Arnaud

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

We establish disintegrated PAC-Bayesian generalisation bounds for models trained with gradient descent methods or continuous gradient flows. Contrary to standard practice in the PAC-Bayesian setting, our result applies to optimisation algorithms that are deterministic, without requiring any de-randomisation step. Our bounds are fully computable, depending on the density of the initial distribution and the Hessian of the training objective over the trajectory. We show that our framework can be applied to a variety of iterative optimisation algorithms, including stochastic gradient descent (SGD), momentum-based schemes, and damped Hamiltonian dynamics.

Published
2022

22. Low HDL cholesterol and the eNOS Glu298Asp polymorphism are associated with inducible myocardial ischemia in patients with suspected stable coronary artery disease

Author

Cecilia Vecoli, Chiara Caselli, Martina Modena, Giancarlo Todiere, Rosa Poddighe, Serafina Valente, Fabrizio Bandini, Andrea Natali, Lorenzo Ghiadoni, Aldo Clerico, Concetta Prontera, Simona Vittorini, Nicoletta Botto, Michele Emdin, and Danilo Neglia

Subjects
Endothelial dysfunction, Endothelial nitric oxide synthase, eNOS, Single nucleotide polymorphism, Obstructive coronary artery disease, Inducible myocardial ischemia, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Abstract Background The endothelial nitric oxide synthase (eNOS) gene deficiency is known to cause impaired coronary vasodilating capability in animal models. In the general clinical population, the eNOS gene polymorphisms, able to affect eNOS activity, were associated with cardiometabolic risk features and prevalence of coronary artery disease (CAD). Aim To investigate the association of eNOS Glu298Asp gene polymorphism, cardiometabolic profile, obstructive CAD and inducible myocardial ischemia in patients with suspected stable CAD. Methods A total of 506 patients (314 males; mean age 62 ± 9 years) referred for suspected CAD was enrolled. Among these, 325 patients underwent stress ECG or cardiac imaging to assess the presence of inducible myocardial ischemia and 436 patients underwent non-invasive computerized tomography or invasive coronary angiography to assess the presence of obstructive CAD. Clinical characteristics and blood samples were collected for each patient. Results In the whole population, 49.6% of patients were homozygous for the Glu298 genotype (Glu/Glu), 40.9% heterozygotes (Glu/Asp) and 9.5% homozygous for the 298Asp genotype (Asp/Asp). Obstructive CAD was documented in 178/436 (40.8%) patients undergoing coronary angiography while myocardial ischemia in 160/325 (49.2%) patients undergoing stress testing. Patients with eNOS Asp genotype (Glu/Asp + Asp/Asp) had no significant differences in clinical risk factors and in circulating markers. Independent predictors of obstructive CAD were age, gender, obesity, and low HDL-C. Independent predictors of myocardial ischemia were gender, obesity, low HDL-C and Asp genotype. In the subpopulation in which both stress tests and coronary angiography were performed, the Asp genotype remained associated with increased myocardial ischemia risk after adjustment for obstructive CAD. Conclusion In this population, low-HDL cholesterol was the only cardiometabolic risk determinant of obstructive CAD. The eNOS Glu298Asp gene polymorphism was significantly associated with inducible myocardial ischemia independently of other risk factors and presence of obstructive CAD.

Published
2024
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23. Generation and control of non-local chiral currents in graphene superlattices by orbital Hall effect

Author

Salvador-Sánchez, Juan, Canonico, Luis M., Pérez-Rodríguez, Ana, Cysne, Tarik P., Baba, Yuriko, Clericò, Vito, Vila, Marc, Vaquero, Daniel, Delgado-Notario, Juan Antonio, Caridad, José M., Watanabe, Kenji, Taniguchi, Takashi, Molina, Rafael A., Domínguez-Adame, Francisco, Roche, Stephan, Diez, Enrique, Rappoport, Tatiana G., and Amado, Mario

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Graphene-based superlattices offer a new materials playground to exploit and control a higher number of electronic degrees of freedom, such as charge, spin, or valley for disruptive technologies. Recently, orbital effects, emerging in multivalley band structure lacking inversion symmetry, have been discussed as possible mechanisms for developing orbitronics. Here, we report non-local transport measurements in small gap hBN/graphene/hBN moir\'e superlattices which reveal very strong magnetic field-induced chiral response which is stable up to room temperature. The measured sign dependence of the non-local signal with respect to the magnetic field orientation clearly indicates the manifestation of emerging orbital magnetic moments. The interpretation of experimental data is well supported by numerical simulations, and the reported phenomenon stands as a formidable way of in-situ manipulation of the transverse flow of orbital information, that could enable the design of orbitronic devices., Comment: 5 pages, 5 figures and supplementary information

Published
2022

24. Signs and symptoms of COVID‐19 in patients with multiple sclerosis

Author

Schiavetti, Irene, Carmisciano, Luca, Ponzano, Marta, Cordioli, Cinzia, Cocco, Eleonora, Marfia, Girolama Alessandra, Inglese, Matilde, Filippi, Massimo, Radaelli, Marta, Bergamaschi, Roberto, Immovilli, Paolo, Capobianco, Marco, De Rossi, Nicola, Brichetto, Giampaolo, Scandellari, Cinzia, Cavalla, Paola, Pesci, Ilaria, Confalonieri, Paolo, Perini, Paola, Trojano, Maria, Lanzillo, Roberta, Tedeschi, Gioacchino, Comi, Giancarlo, Battaglia, Mario Alberto, Patti, Francesco, Salvetti, Marco, Sormani, Maria Pia, Group, MuSC‐19 Study, Abbadessa, Gianmarco, Aguglia, Umberto, Allegorico, Lia, Allegri, Beatrice Maria Rossi, Alteno, Anastasia, Amato, Maria Pia, Annovazzi, Pietro, Antozzi, Carlo, Appendino, Lucia, Arena, Sebastiano, Baione, Viola, Balgera, Roberto, Barcella, Valeria, Baroncini, Damiano, Barrilà, Caterina, Bellacosa, Alessandra, Bellucci, Gianmarco, Bergamaschi, Valeria, Bezzini, Daiana, Biolzi, Beatrice, Bisecco, Alvino, Bonavita, Simona, Borriello, Giovanna, Bosa, Chiara, Bosco, Antonio, Bovis, Francesca, Bozzali, Marco, Brambilla, Laura, Morra, Vincenzo Brescia, Buccafusca, Maria, Bucciantini, Elisabetta, Bucello, Sebastiano, Buscarinu, Maria Chiara, Cabboi, Maria Paola, Calabrese, Massimiliano, Calabria, Francesca, Caleri, Francesca, Camilli, Federico, Caniatti, Luisa Maria, Cantello, Roberto, Capra, Ruggero, Capuano, Rocco, Carta, Patrizia, Celani, Maria Grazia, Cellerino, Maria, Cerqua, Raffaella, Chisari, Clara, Clerici, Raffaella, Clerico, Marinella, Cola, Gaia, Conte, Antonella, Conti, Marta Zaffira, Cordano, Christian, Cordera, Susanna, Corea, Francesco, Correale, Claudio, Cottone, Salvatore, Crescenzo, Francesco, Curti, Erica, d’Ambrosio, Alessandro, D’Amico, Emanuele, Danni, Maura Chiara, d’Arma, Alessia, Dattola, Vincenzo, de Biase, Stefano, De Luca, Giovanna, De Mercanti, Stefania Federica, De Mitri, Paolo, De Stefano, Nicola, Della Cava, Fabio Maria, Della Cava, Marco, and Di Lemme, Sonia

Subjects
Neurosciences, Multiple Sclerosis, Brain Disorders, Pain Research, Neurodegenerative, Good Health and Well Being, Humans, Aged, COVID-19, Ageusia, SARS-CoV-2, Anosmia, MuSC-19 Study Group, demyelinating diseases, disease-modifying treatment, multiple sclerosis, neurological disorders, Clinical Sciences, Neurology & Neurosurgery
Abstract

Background and purposeClinical outcomes of multiple sclerosis (MS) patients affected by coronavirus disease 2019 (COVID-19) have been thoroughly investigated, but a further analysis on main signs and symptoms and their risk factors still needs attention. The objective of this study was to group together and describe based on similarity the most common signs and symptoms of COVID-19 in MS patients and identify all factors associated with their manifestation.MethodLogistic and linear regression models were run to recognize factors associated with each pooled group of symptoms and their total number.ResultsFrom March 2020 to November 2021, data were collected from 1354 MS patients with confirmed infection of COVID-19. Ageusia and anosmia was less frequent in older people (odds ratio [OR] 0.98; p = 0.005) and more in smoker patients (OR 1.39; p = 0.049). Smoke was also associated with an incremental number of symptoms (OR 1.24; p = 0.031), substance abuse (drugs or alcohol), conjunctivitis and rash (OR 5.20; p = 0.042) and the presence of at least one comorbidity with shortness of breath, tachycardia or chest pain (OR 1.24; p = 0.008). Some disease-modifying therapies were associated with greater frequencies of certain COVID-19 symptoms (association between anti-CD20 therapies and increment in the number of concomitant symptoms: OR 1.29; p = 0.05). Differences in frequencies between the three waves were found for flu-like symptoms (G1, p = 0.024), joint or muscle pain (G2, p = 0.013) and ageusia and anosmia (G5, p

Published
2022

25. Low-frequency focused thermosonication for Salmonella typhimurium inactivation: an in vitro study

Author

Carlotta Lauteri, Luca Pennisi, Daniele Di Clerico, Viola Pennisi, and Alberto Vergara

Subjects
Salmonella typhimurium, low frequency focused ultrasound, thermosonication, Salmonella inactivation in food matrix, Food processing and manufacture, TP368-456
Abstract

Customer requests are addressed to safe products that best express their characteristics of "naturalness" and "freshness" for the entire shelf life; therefore, scientific research has been exploring the use of "non-thermal technologies". Thermosonication using low-frequency focused ultrasound determines bacterial inactivation through the phenomenon of "cavitation", guaranteeing high-quality standards of safety, nutrition, and freshness of the products. The present work aims to evaluate the effectiveness of inactivation of Salmonella typhimurium in culture broth by low-frequency focused thermosonication with two different operational parameters: sublethal temperature (40°C, 50°C) and treatment time (5, 10, and 15 minutes). Treatment determined a bacterial load reduction compared to the negative control (untreated inoculum), which was statistically significant at the T-test (p

Published
2024
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26. Chained Generalisation Bounds

Author

Clerico, Eugenio, Shidani, Amitis, Deligiannidis, George, and Doucet, Arnaud

Subjects
Statistics - Machine Learning, Computer Science - Information Theory, Computer Science - Machine Learning
Abstract

This work discusses how to derive upper bounds for the expected generalisation error of supervised learning algorithms by means of the chaining technique. By developing a general theoretical framework, we establish a duality between generalisation bounds based on the regularity of the loss function, and their chained counterparts, which can be obtained by lifting the regularity assumption from the loss onto its gradient. This allows us to re-derive the chaining mutual information bound from the literature, and to obtain novel chained information-theoretic generalisation bounds, based on the Wasserstein distance and other probability metrics. We show on some toy examples that the chained generalisation bound can be significantly tighter than its standard counterpart, particularly when the distribution of the hypotheses selected by the algorithm is very concentrated. Keywords: Generalisation bounds; Chaining; Information-theoretic bounds; Mutual information; Wasserstein distance; PAC-Bayes.

Published
2022

27. Long-term effectiveness of natalizumab in secondary progressive multiple sclerosis: A propensity-matched study

Author

Avolio, Carlo, Balgera, Roberto, Banfi, Paola, Bellantonio, Paolo, Bramanti, Placido, Capone, Lorenzo, Cavalletti, Guido, Chiveri, Luca, Clerici, Raffaella, Clerico, Marinella, Corea, Francesco, Dattola, Vincenzo, De Robertis, Francesca, Di Battista, Giancarlo, Galgani, Simonetta, Gatto, Maurizia, Grasso, Maria Grazia, Inglese, Matilde, Lo Russo, Lorenzo, Logullo, Francesco Ottavio, Mantegazza, Renato, Protti, Alessandra, Rezzonico, Monica, Rottoli, Mariarosa, Salvetti, Marco, Scarpini, Elio, Sinisi, Leonardo, Sparaco, Maddalena, Spitaleri, Daniele, Tassinari, Tiziana, Tonietti, Simone, Valentino, Paola, Valzania, Franco, Venturi, Simonetta, Chisari, Clara G., Aguglia, Umberto, Amato, Maria Pia, Bergamaschi, Roberto, Bertolotto, Antonio, Bonavita, Simona, Morra, Vincenzo Brescia, Cavalla, Paola, Cocco, Eleonora, Conte, Antonella, Cottone, Salvatore, De Luca, Giovanna, Di Sapio, Alessia, Filippi, Massimo, Gallo, Antonio, Gasperini, Claudio, Granella, Franco, Lus, Giacomo, Maimone, Davide, Maniscalco, Giorgia Teresa, Marfia, Girolama, Moiola, Lucia, Paolicelli, Damiano, Pesci, Ilaria, Ragonese, Paolo, Rovaris, Marco, Salemi, Giuseppe, Solaro, Claudio, Totaro, Rocco, Trojano, Maria, Vianello, Marika, Zaffaroni, Mauro, Lepore, Vito, and Patti, Francesco

Published
2024
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28. Conditionally Gaussian PAC-Bayes

Author

Clerico, Eugenio, Deligiannidis, George, and Doucet, Arnaud

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Recent studies have empirically investigated different methods to train stochastic neural networks on a classification task by optimising a PAC-Bayesian bound via stochastic gradient descent. Most of these procedures need to replace the misclassification error with a surrogate loss, leading to a mismatch between the optimisation objective and the actual generalisation bound. The present paper proposes a novel training algorithm that optimises the PAC-Bayesian bound, without relying on any surrogate loss. Empirical results show that this approach outperforms currently available PAC-Bayesian training methods.

Published
2021

33. The effect of air pollution on COVID‐19 severity in a sample of patients with multiple sclerosis

Author

Bergamaschi, Roberto, Ponzano, Marta, Schiavetti, Irene, Carmisciano, Luca, Cordioli, Cinzia, Filippi, Massimo, Radaelli, Marta, Immovilli, Paolo, Capobianco, Marco, De Rossi, Nicola, Brichetto, Giampaolo, Cocco, Eleonora, Scandellari, Cinzia, Cavalla, Paola, Pesci, Ilaria, Zito, Antonio, Confalonieri, Paolo, Marfia, Girolama Alessandra, Perini, Paola, Inglese, Matilde, Trojano, Maria, Morra, Vincenzo Brescia, Pisoni, Enrico, Tedeschi, Gioacchino, Comi, Giancarlo, Battaglia, Mario Alberto, Patti, Francesco, Salvetti, Marco, Sormani, Maria Pia, Abbadessa, Gianmarco, Aguglia, Umberto, Allegorico, Lia, Allegri, Rossi Beatrice Maria, Alteno, Anastasia, Amato, Maria Pia, Annovazzi, Pietro, Antozzi, Carlo, Appendino, Lucia, Arena, Sebastiano, Baione, Viola, Balgera, Roberto, Barcella, Valeria, Baroncini, Damiano, Barrilà, Caterina, Battaglia, Mario A, Bellacosa, Alessandra, Bellucci, Gianmarco, Bergamaschi, Valeria, Bezzini, Daiana, Biolzi, Beatrice, Bisecco, Alvino, Bonavita, Simona, Borriello, Giovanna, Bosa, Chiara, Bosco, Antonio, Bovis, Francesca, Bozzali, Marco, Brambilla, Laura, Brescia, Morra Vincenzo, Buccafusca, Maria, Bucciantini, Elisabetta, Bucello, Sebastiano, Buscarinu, Maria Chiara, Cabboi, Maria Paola, Calabrese, Massimiliano, Calabria, Francesca, Caleri, Francesca, Camilli, Federico, Caniatti, Luisa Maria, Cantello, Roberto, Capra, Ruggero, Capuano, Rocco, Carta, Patrizia, Celani, Maria Grazia, Cellerino, Maria, Cerqua, Raffaella, Chisari, Clara, Clerici, Raffaella, Clerico, Marinella, Cola, Gaia, Conte, Antonella, Conti, Marta Zaffira, Cordano, Christian, Cordera, Susanna, Corea, Francesco, Correale, Claudio, Cottone, Salvatore, Crescenzo, Francesco, Curti, Erica, d'Ambrosio, Alessandro, and D'Amico, Emanuele

Subjects
Clinical Research, Neurosciences, Multiple Sclerosis, Brain Disorders, Autoimmune Disease, Neurodegenerative, Climate-Related Exposures and Conditions, Good Health and Well Being, Sustainable Cities and Communities, Air Pollution, COVID-19, Humans, Particulate Matter, SARS-CoV-2, MuSC-19 study group, air pollution, coronavirus, multiple sclerosis, Clinical Sciences, Neurology & Neurosurgery
Abstract

Background and purposeSome studies have shown that air pollution, often assessed by thin particulate matter with diameter below 2.5 µg/m3 (PM2.5), may contribute to severe COVID-19 courses, as well as play a role in the onset and evolution of multiple sclerosis (MS). However, the impact of air pollution on COVID-19 has never been explored specifically amongst patients with MS (PwMS). This retrospective observational study aims to explore associations between PM2.5 and COVID-19 severity amongst PwMS.MethodsData were retrieved from an Italian web-based platform (MuSC-19) which includes PwMS with COVID-19. PM2.5 2016-2018 average concentrations were provided by the Copernicus Atmospheric Monitoring Service. Italian patients inserted in the platform from 15 January 2020 to 9 April 2021 with a COVID-19 positive test were included. Ordered logistic regression models were used to study associations between PM2.5 and COVID-19 severity.ResultsIn all, 1087 patients, of whom 13% required hospitalization and 2% were admitted to an intensive care unit or died, were included. Based on the multivariate analysis, higher concentrations of PM2.5 increased the risk of worse COVID-19 course (odds ratio 1.90; p = 0.009).ConclusionsEven if several other factors explain the unfavourable course of COVID-19 in PwMS, the role of air pollutants must be considered and further investigated.

Published
2022

34. Wide stochastic networks: Gaussian limit and PAC-Bayesian training

Author

Clerico, Eugenio, Deligiannidis, George, and Doucet, Arnaud

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

The limit of infinite width allows for substantial simplifications in the analytical study of over-parameterised neural networks. With a suitable random initialisation, an extremely large network exhibits an approximately Gaussian behaviour. In the present work, we establish a similar result for a simple stochastic architecture whose parameters are random variables, holding both before and during training. The explicit evaluation of the output distribution allows for a PAC-Bayesian training procedure that directly optimises the generalisation bound. For a large but finite-width network, we show empirically on MNIST that this training approach can outperform standard PAC-Bayesian methods.

Published
2021

39. Ultramicronized Palmitoylethanolamide in the Management of Neuropathic Pain Related to Chronic Inflammatory Demyelinating Polyneuropathy: A Proof-of-Concept Study

Author

Dario Cocito, Erdita Peci, Maria Claudia Torrieri, and Marinella Clerico

Subjects
ultramicronized palmitoylethanolamide, neuropathic pain, immunoglobulins, chronic inflammatory demyelinating polyneuropathy, autoimmune disease, Medicine
Abstract

Background/Objectives: Chronic inflammatory demyelinating polyneuropathy (CIDP) is a rare autoimmune disease. Neuropathic pain (NP), related to peripheral inflammation, is among its earliest manifestations. This preliminary open-label investigation aimed to evaluate the efficacy of ultramicronized Palmitoylethanolamide (umPEA) in the management of NP. Methods: A total of 14 patients with CIDP, already undergoing immunoglobulin (Ig) therapy, were divided into two groups: Group A received umPEA 600 mg twice daily in addition to Ig for 60 days, followed by Ig alone until the end of the observation (180 days); Group B received Ig alone for 120 days and subsequently umPEA + Ig in the last 60 days of the study. Painful symptom intensity and quality of life were assessed by the Numeric Rating Scale, Neuropathic Pain Symptoms Inventory, and Five Dimensions Health Questionnaire. The safety umPEA profile was evaluated. Results: UmPEA in addition to immunoglobulins allowed for a significant improvement over time in all NP symptoms intensity (p = 0.0007) and in patients’ quality of life (p = 0.0036). Conclusions: This study suggests umPEA as a safe and effective treatment in addition to immunoglobulins to improve NP, ameliorating the patient’s health status. These results highlight the importance of neuroinflammation modulation in the management of CIDP’s painful symptoms, drawing attention to umPEA’s potential use also in neuropathies of different etiologies.

Published
2024
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40. Multi-Sensor Device for Traceable Monitoring of Indoor Environmental Quality

Author

Virginia Isabella Fissore, Giuseppina Arcamone, Arianna Astolfi, Alberto Barbaro, Alessio Carullo, Pietro Chiavassa, Marina Clerico, Stefano Fantucci, Franco Fiori, Davide Gallione, Edoardo Giusto, Alice Lorenzati, Nicole Mastromatteo, Bartolomeo Montrucchio, Anna Pellegrino, Gabriele Piccablotto, Giuseppina Emma Puglisi, Gustavo Ramirez-Espinosa, Erica Raviola, Antonio Servetti, and Louena Shtrepi

Subjects
indoor environmental quality, multi-sensor, metrological characterization, uncertainty, bare sensors, Chemical technology, TP1-1185
Abstract

The Indoor Environmental Quality (IEQ) combines thermal, visual, acoustic, and air-quality conditions in indoor environments and affects occupants’ health, well-being, and comfort. Performing continuous monitoring to assess IEQ is increasingly proving to be important, also due to the large amount of time that people spend in closed spaces. In the present study, the design, development, and metrological characterization of a low-cost multi-sensor device is presented. The device is part of a wider system, hereafter referred to as PROMET&O (PROactive Monitoring for indoor EnvironmenTal quality & cOmfort), that also includes a questionnaire for the collection of occupants’ feedback on comfort perception and a dashboard to show end users all monitored data. The PROMET&O multi-sensor monitors the quality conditions of indoor environments thanks to a set of low-cost sensors that measure air temperature, relative humidity, illuminance, sound pressure level, carbon monoxide, carbon dioxide, nitrogen dioxide, particulate matter, volatile organic compounds, and formaldehyde. The device architecture is described, and the design criteria related to measurement requirements are highlighted. Particular attention is paid to the calibration of the device to ensure the metrological traceability of the measurements. Calibration procedures, based on the comparison to reference standards and following commonly employed or ad hoc developed technical procedures, were defined and applied to the bare sensors of air temperature and relative humidity, carbon dioxide, illuminance, sound pressure level, particulate matter, and formaldehyde. The next calibration phase in the laboratory will be aimed at analyzing the mutual influences of the assembled multi-sensor hardware components and refining the calibration functions.

Published
2024
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41. Fast response photogating in monolayer MoS2 phototransistors

Author

Vaquero, Daniel, Clericò, Vito, Salvador-Sánchez, Juan, Díaz, Elena, Domínguez-Adame, Francisco, Chico, Leonor, Meziani, Yahya M., Diez, Enrique, and Quereda, Jorge

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics, Condensed Matter - Materials Science
Abstract

Two-dimensional transition metal dichalcogenide (TMD) phototransistors have been object of intensive research during the last years due to their potential for photodetection. Photoresponse in these devices is typically caused by a combination of two physical mechanisms: photoconductive effect (PCE) and photogating effect (PGE). In earlier literature for monolayer (1L) MoS2 phototransistors PGE is generally attributed to charge trapping by polar molecules adsorbed to the semiconductor channel, giving rise to a very slow photoresponse. Thus, the photoresponse of 1L-MoS2 phototransistors at high-frequency light modulation is assigned to PCE alone. Here we investigate the photoresponse of a fully h-BN encapsulated monolayer (1L) MoS2 phototransistor. In contrast with previous understanding, we identify a rapidly responding PGE mechanism that becomes the dominant contribution to photoresponse under high-frequency light modulation. Using a Hornbeck-Haynes model for the photocarrier dynamics, we fit the illumination power dependence of this PGE and estimate the energy level of the involved traps. The resulting energies are compatible with shallow traps in MoS2 caused by the presence of sulfur vacancies., Comment: arXiv admin note: text overlap with arXiv:2004.02526

Published
2020

42. Stable ResNet

Author

Hayou, Soufiane, Clerico, Eugenio, He, Bobby, Deligiannidis, George, Doucet, Arnaud, and Rousseau, Judith

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Deep ResNet architectures have achieved state of the art performance on many tasks. While they solve the problem of gradient vanishing, they might suffer from gradient exploding as the depth becomes large (Yang et al. 2017). Moreover, recent results have shown that ResNet might lose expressivity as the depth goes to infinity (Yang et al. 2017, Hayou et al. 2019). To resolve these issues, we introduce a new class of ResNet architectures, called Stable ResNet, that have the property of stabilizing the gradient while ensuring expressivity in the infinite depth limit., Comment: 43 pages, 4 figures

Published
2020

43. The impact of PM2.5, PM10 and NO2 on Covid-19 severity in a sample of patients with multiple sclerosis: A case-control study

Author

Gianmarco, Abbadessa, Umberto, Aguglia, Lia, Allegorico, Maria, Allegri Rossi Beatrice, Anastasia, Alteno, Pia, Amato Maria, Pietro, Annovazzi, Carlo, Antozzi, Lucia, Appendino, Sebastiano, Arena, Viola, Baione, Roberto, Balgera, Valeria, Barcella, Damiano, Baroncini, Caterina, Barrilà, Mario A, Battaglia, Alessandra, Bellacosa, Gianmarco, Bellucci, Roberto, Bergamaschi, Valeria, Bergamaschi, Daiana, Bezzini, Beatrice, Biolzi, Alvino, Bisecco, Simona, Bonavita, Giovanna, Borriello, Chiara, Bosa, Antonio, Bosco, Francesca, Bovis, Marco, Bozzali, Laura, Brambilla, Vincenzo, Brescia Morra, Giampaolo, Brichetto, Maria, Buccafusca, Elisabetta, Bucciantini, Sebastiano, Bucello, Chiara, Buscarinu Maria, Paola, Cabboi Maria, Massimiliano, Calabrese, Francesca, Calabria, Francesca, Caleri, Federico, Camilli, Maria, Caniatti Luisa, Roberto, Cantello, Marco, Capobianco, Ruggero, Capra, Rocco, Capuano, Luca, Carmisciano, Patrizia, Carta, Paola, Cavalla, Grazia, Celani Maria, Maria, Cellerino, Raffaella, Cerqua, Clara, Chisari, Raffaella, Clerici, Marinella, Clerico, Eleonora, Cocco, Gaia, Cola, Giancarlo, Comi, Paolo, Confalonieri, Antonella, Conte, Zaffira, Conti Marta, Christian, Cordano, Susanna, Cordera, Cinzia, Cordioli, Francesco, Corea, Claudio, Correale, Salvatore, Cottone, Francesco, Crescenzo, Erica, Curti, Alessandro, d'Ambrosio, Emanuele, D'Amico, Chiara, Danni Maura, Alessia, d'Arma, Vincenzo, Dattola, Stefano, de Biase, Giovanna, De Luca, Federica, De Mercanti Stefania, Paolo, De Mitri, Nicola, De Rossi, Nicola, De Stefano, Maria, Della Cava Fabio, Marco, Della Cava, Sonia, Di Lemme, Mario, di Napoli, Alessia, Di Sapio, Renato, Docimo, Anna, Dutto, Luana, Evangelista, Salvatore, Fanara, Roberta, Fantozzi, Diana, Ferraro, Teresa, Ferrò Maria, Massimo, Filippi, Cristina, Fioretti, Mario, Fratta, Jessica, Frau, Marzia, Fronza, Roberto, Furlan, Alberto, Gajofatto, Antonio, Gallo, Paolo, Gallo, Claudio, Gasperini, Anna, Ghazaryan, Bruno, Giometto, Francesca, Gobbin, Flora, Govone, Franco, Granella, Erica, Grange, Grazia, Grasso Maria, Luigi ME, Grimaldi, Angelica, Guareschi, Clara, Guaschino, Simone, Guerrieri, Donata, Guidetti, Barbara, Juergenson Ina, Pietro, Iaffaldano, Antonio, Ianniello, Luigi, Iasevoli, Paolo, Immovilli, Daniele, Imperiale, Teresa, Infante Maria, Matilde, Inglese, Rosa, Iodice, Aniello, Iovino, Giovanna, Konrad, Doriana, Landi, Roberta, Lanzillo, Caterina, Lapucci, Luigi, Lavorgna, Rita, L'Episcopo Maria, Serena, Leva, Giuseppe, Liberatore, Marianna, Lo Re, Marco, Longoni, Leonardo, Lopiano, Lorena, Lorefice, Matteo, Lucchini, Giacomo, Lus, Davide, Maimone, Maria, Malentacchi, Giulia, Mallucci, Simona, Malucchi, Rosa, Mancinelli Chiara, Luca, Mancinelli, Paolo, Manganotti, Teresa, Maniscalco Giorgia, Vittorio, Mantero, Sabrina, Marangoni, Damiano, Marastoni, Alessandra, Marfia Girolama, Fabiana, Marinelli, Alessandro, Marti, Filippo, Martinelli Boneschi, Federco, Masserano Zoli, Francesca, Matta, Laura, Mendozzi, Giuseppe, Meucci, Silvia, Miante, Giuseppina, Miele, Eva, Milano, Massimiliano, Mirabella, Rosanna, Missione, Marcello, Moccia, Lucia, Moiola, Sara, Montepietra, Margherita, MontiBragadin, Federico, Montini, Roberta, Motta, Raffaele, Nardone, Gabri, Nicoletti Carolina, Eduardo, Nobile-Orazio, Agostino, Nozzolillo, Marco, Onofrj, Riccardo, Orlandi, Anna, Palmieri, Damiano, Paolicelli, Livia, Pasquali, Fulvio, Pasquin, Luisa, Pastò, Francesco, Patti, Elisabetta, Pedrazzoli, Paola, Perini, Ilaria, Pesci, Maria, Petracca, Alfredo, Petrone, Carlo, Piantadosi, Anna M, Pietroboni, Federica, Pinardi, Marta, Ponzano, Emilio, Portaccio, Mattia, Pozzato, Carlo, Pozzilli, Luca, Prosperini, Alessandra, Protti, Eugenio, Pucci, Marta, Radaelli, Paolo, Ragonese, Sarah, Rasia, Sabrina, Realmuto, Anna, Repice, Eleonora, Rigoni, Teresa, Rilla Maria, Francesca, Rinaldi, Marcello, Romano Calogero, Marco, Ronzoni, Marco, Rovaris, Francesca, Ruscica, Loredana, Sabattini, Giuseppe, Salemi, Marco, Salvetti, Lorenzo, Saraceno, Alessia, Sartori, Arianna, Sartori, Elvira, Sbragia, Cinzia, Scandellari, Ilaria, Scarano Giuditta, Valentina, Scarano, Irene, Schiavetti, Maria, Sessa, Caterina, Sgarito, Grazia, Sibilia, Gabriele, Siciliano, Alessio, Signori, Elisabetta, Signoriello, Leonardo, Sinisi, Francesca, Sireci, Patrizia, Sola, Claudio, Solaro, Pia, Sormani Maria, Stefano, Sotgiu, Maddalena, Sparaco, Laura, Stromillo Maria, Silvia, Strumia, Laura, Susani Emanuela, Giulietta, Tabiadon, Francesco, Teatini, Gioacchino, Tedeschi, Valentina, Tomassini, Simone, Tonietti, Valentina, Torri Clerici, Carla, Tortorella, Simona, Toscano, Rocco, Totaro, Maria, Trojano, Maria, Trotta, Gabriella, Turano, Monica, Ulivelli, Manzo, Valentino, Giovanna, Vaula, Domizia, Vecchio, Marco, Vercellino, Pinuccia, Verrengia Elena, Marika, Vianello, Eleonora, Virgilio, Francesca, Vitetta, Stefano, Vollaro, Mauro, Zaffaroni, Mauro, Zampolini, Roberto, Zarbo Ignazio, Antonio, Zito, Luigi, Zuliani, Ponzano, Marta, Schiavetti, Irene, Bergamaschi, Roberto, Pisoni, Enrico, Bellavia, Andrea, Mallucci, Giulia, Carmisciano, Luca, Inglese, Matilde, Cordioli, Cinzia, Marfia, Girolama Alessandra, Cocco, Eleonora, Immovilli, Paolo, Pesci, Ilaria, Scandellari, Cinzia, Cavalla, Paola, Radaelli, Marta, Vianello, Marika, Vitetta, Francesca, Montepietra, Sara, Amato, Maria Pia, Fioretti, Cristina, Filippi, Massimo, Sartori, Arianna, Caleri, Francesca, Clerico, Marinella, Gallo, Antonio, Conte, Antonella, Clerici, Raffaella, De Luca, Giovanna, Boneschi, Filippo Martinelli, Cantello, Roberto, Calabrese, Massimiliano, Tortorella, Carla, Rovaris, Marco, Verrengia, Elena Pinuccia, Patti, Francesco, Morra, Vincenzo Brescia, Salvetti, Marco, and Sormani, Maria Pia

Published
2022
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44. Excitons, trions and Rydberg states in monolayer MoS2 revealed by low temperature photocurrent spectroscopy

Author

Vaquero, Daniel, Clericò, Vito, Salvador-Sánchez, Juan, Martín-Ramos, Adrián, Díaz, Elena, Domínguez-Adame, Francisco, Meziani, Yahya M., Diez, Enrique, and Quereda, Jorge

Subjects
Condensed Matter - Materials Science, Physics - Applied Physics, Physics - Optics
Abstract

We investigate excitonic transitions in a h-BN encapsulated monolayer $\textrm{MoS}_2$ phototransistor by photocurrent spectroscopy at cryogenic temperature (T = 5 K). The spectra presents excitonic peaks with linewidths as low as 8 meV, one order of magnitude lower than in earlier photocurrent spectroscopy measurements. We observe four spectral features corresponding to the ground states of neutral excitons ($\textrm{X}_{\textrm{1s}}^\textrm{A}$ and $\textrm{X}_{\textrm{1s}}^\textrm{B}$) and charged trions ($\textrm{T}^\textrm{A}$ and $\textrm{T}^\textrm{B}$) as well as up to eight additional spectral lines at energies above the $\textrm{X}_{\textrm{1s}}^\textrm{B}$ transition, which we attribute to the Rydberg series of excited states of $\textrm{X}^\textrm{A}$ and $\textrm{X}^\textrm{B}$. The relative intensities of the different spectral features can be tuned by the applied gate and drain-source voltages, with trions and Rydberg excited states becoming more prominent at large gate voltages. Using an effective-mass theory for excitons in two-dimensional transition-metal dichalcogenides we are able to accurately fit the measured spectral lines and unambiguously associate them with their corresponding Rydberg states. The fit also allows us to determine the quasiparticle bandgap and spin-orbit splitting of monolayer $\textrm{MoS}_2$, as well as the exciton binding energies of $\textrm{X}^\textrm{A}$ and $\textrm{X}^\textrm{B}$.

Published
2020

46. Optimizing the 'Time to pregnancy' in women with multiple sclerosis: the OPTIMUS Delphi survey

Author

Luigi Carbone, Doriana Landi, Raffaella Di Girolamo, Paola Anserini, Diego Centonze, Girolama Alessandra Marfia, Carlo Alviggi, the Interdisciplinary Group for Fertility in Multiple Sclerosis (IGFMS), Roberta Lanzillo, Pietro Annovazzi, Simona Bonavita, Giovanna Borriello, Paola Cavalla, Raffaella Cerqua, Marinella Clerico, Eleonora Cocco, Cinzia Cordioli, Emanuele D’Amico, Giovanna De Luca, Massimiliano Di Filippo, Roberta Fantozzi, Diana Ferraro, Pietro Iaffaldano, Matilde Inglese, Paola Perini, Emilio Portaccio, Paolo Ragonese, Valentina Torri Clerici, Carla Tortorella, and Paola Valentino

Subjects
multiple sclerosis, infertility, time to pregnancy, Delphi, assisted reproductive technology, Neurology. Diseases of the nervous system, RC346-429
Abstract

BackgroundThe debate on how to manage women affected by multiple sclerosis (MS) during reproductive age is still open, as is the issue of fertility in such patients. Main issue regard the identification of the optimal window for pregnancy and how to deal with medical therapy before and during conception. The aim of this Delphi consensus was to collect the opinions of a multidisciplinary group, involving reproductive medicine specialists and neurologists with experience in the management of multiple sclerosis women with reproductive desire.MethodsFour experts plus scientific coordinators developed a questionnaire distributed online to 10 neurologists and later discussed the responses and amended a list of statements. The statements were then distributed via an online survey to 23 neurologists (comprising the first 10), who voted on their level of agreement/disagreement with each statement. Consensus was achieved if agreement or disagreement with a statement exceeded 66%.ResultsTwenty-one statements reached consensus after two rounds of voting, leading to the following main recommendations: (1) Fertility evaluation should be suggested to wMS, in case of the need to shorten time to pregnancy and before treatment switch in women on DMTs contraindicated in pregnancy, particularly in case of highly active disease and age > 35 years. (2) ART should not be discouraged in wMS, but the use of DMTs until pregnancy confirmation should be suggested; ART may be considered in order to reduce time to pregnancy in MS women with a reduced ovarian reserve and/or age > 35 years, but in case of an expected poor ART prognosis and the need for more than one ART cycle, a switch to a high-efficacy DMD before ART should be offered. (3) Oocyte cryopreservation may be considered in women with reduced ovarian reserve, with unpredictable time to complete diagnostic workup and achieve disease control; a risk/cost–benefit analysis must be performed in women >35 years, considering the diminished ovarian reserve.ConclusionThis consensus will help MS neurologists to support family planning in wMS, respecting MS therapeutic needs while also taking into account the safety and impact of advancing age on fertility.

Published
2023
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48. A Fecal MicroRNA Signature by Small RNA Sequencing Accurately Distinguishes Colorectal Cancers: Results From a Multicenter Study

Author

Pardini, Barbara, Ferrero, Giulio, Tarallo, Sonia, Gallo, Gaetano, Francavilla, Antonio, Licheri, Nicola, Trompetto, Mario, Clerico, Giuseppe, Senore, Carlo, Peyre, Sergio, Vymetalkova, Veronika, Vodickova, Ludmila, Liska, Vaclav, Vycital, Ondrej, Levy, Miroslav, Macinga, Peter, Hucl, Tomas, Budinska, Eva, Vodicka, Pavel, Cordero, Francesca, and Naccarati, Alessio

Published
2023
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49. A Prospective Cohort Analysis of the Prevalence and Predictive Factors of Delayed Discharge After Laparoscopic Cholecystectomy in Italy: The DeDiLaCo Study

Author

Cillara, Nicola, Podda, Mauro, Cicalò, Enrico, Sotgiu, Giovanni, Provenzano, Maria, Fransvea, Pietro, Poillucci, Gaetano, Sechi, Raffaele, Deserra, Antonello, DʼAgostino, Francesca, Margiani, Carla, Scabini, Stefano, Pertile, Davide, Rosa, Raffaele De, Prosperi, Paolo, Bruscino, Alessandro, Bella, Annamaria Di, Casati, Massimiliano, Laface, Letizia, Abate, Emmanuele, Frontali, Alice, Bonomi, Alessandro Michele, Ferrario, Luca, Mucilli, Felice, Barone, Mirko, Borghi, Felice, Sasia, Diego, Giraudo, Giorgio, Puzziello, Alessandro, Loffredo, Andrea, Steccanella, Francesca, Donnarumma, Elio, Galleano, Raffaele, Malerba, Michele, Runfola, Matteo, Agus, Marcello, Fortunato, Federica, Calò, Pietro Giorgio, Medas, Fabio, Canu, Gian Luigi, Stella, Marco, Ferrara, Francesco, Baldi, Caterina, Benuzzi, Laura, Pisanu, Adolfo, Saba, Alessandra, Gessa, Emanuela, Muratore, Andrea, Calabrò, Marcello, Cuzzola, Bruno, Garino, Mauro, Marafante, Chiara, Farfaglia, Roberto, Pandolfo, Gianpiero, Pata, Giacomo, Lantone, Giulio, Marino, Fabio, Perrone, Fabrizio, Scognamillo, Fabrizio, Delogu, Daniele, Tilocca, Pier Luigi, Frena, Antonio, Malpaga, Anna, Bertelli, Giacomo, Memeo, Riccardo, Ferraro, Valentina, Libia, Annarita, Sarro, Giuliano, Marconi, Matteo, Nava, Samuele, Pierpaolo, Bordoni, Fleres, Francesco, Clarizia, Guglielmo, Alfieri, Sergio, Rosa, Fausto, Longo, Fabio, Restini, Enrico, Cianci, Pasquale, Capuzzolo, Sabino, Anania, Gabriele, Bombardini, Cristina, Urbani, Alessia, Bona, Davide, Aiolfi, Alberto, Lastraioli, Caterina, Paola, Massimiliano Di, DallʼOglio, Anna, D’Eletto, Marco, Capelli, Patrizio, Conti, Luigi, Luzietti, Enrico, Banchini, Filippo, Manca, Giuseppe, Calo, Gabriele’, Centomze, Antonella, Andreano, Mauro, Sullo, Pasquale, Giuseppina, Oliva, Anastasi, Alessandro, Canonico, Giuseppe, Nelli, Tommaso, Trompetto, Mario, Gallo, Gaetano, Clerico, Giuseppe, Arganini, Marco, Palmeri, Matteo, Bonuso, Claudio, Mirabella, Antonello, Marino, Marco V., Vaccarella, Gianpaolo, Salzano, Francesco, Meccariello, Renato, Mastrorilli, Maurizio, Campanile, Fabio Cesare, Foti, Nicola, Angelis, Monica De, Palma, Giovanni Domenico De, Aprea, Giovanni, Palomba, Giuseppe, Milone, Marco, Capano, Mariana, Manigrasso, Michele, Baldazzi, Gianandrea, Cassini, Diletta, Epifani, Angelo Gabriele, Bottino, Vincenzo, Canfora, Alfonso, Ferronetti, Antonio, de Manzini, Nicolò, Biloslavo, Alan, Fracon, Stefano, Filauro, Marco, Barberis, Andrea, Azzinnaro, Antonio, Oliva, Alba, Razzore, Andrea, Maira, Lorenzo Di, Bima, Carlo, Gibin, Enrico, Peluso, Chiara, Perrotta, Nicola, Celiento, Marta, Scorzelli, Marco, Tuveri, Antonio, Madeddu, Francesco, Fois, Claudia, Russello, Domenico, Latteri, Saverio, Sofia, Maria, Rio, Paolo Del, Cozzani, Federico, Giuffrida, Mario, Mariani, Pierpaolo, Giussani, Martina, Ansaloni, Luca, Maestri, Marcello, Tartaglia, Giuseppe, Caricato, Marco, Capolupo, Gabriella Teresa, Carannante, Filippo, Gambino, Giovanni, Bertino, Vanessa, Bonilauri, Stefano, Frazzetta, Giuseppe, Amodio, Pietro Maria, Siena, Teresa De, Zanzi, Federico, Guariniello, Anna, Rocco, Giuseppe, Mancini, Stefano, Sagnotta, Andrea, Solinas, Luigi, Porta, Andrea, Sambucci, Daniele, Monti, Eleonora, Quaglino, Francesco, Mantova, Serena, Fiore, Alessia, Costi, Renato, Virgilio, Edoardo, Montali, Filippo, Catarci, Marco, Apa, Daniela, Bertoldi, Innocenzo, Camandona, Michele, Bossotti, Maurizio, Palagi, Silvia, Doria, Emaunele, Caltagirone, Alice, Balani, Alessandro, Petronio, Barbara, Terranova, Susanna, Martuzzi, Federica, Romeo, Carlo, Carluccio, Raffaele, Neri, Silvia, Auriemma, Pasquale Pio, Prestigiacomo, Giorgia, Sala, Stefano, Colli, Francesco, Marini, Pierluigi, Cosimo, Carla Di, Gattolin, Andrea, Rimonda, Roberto, Travaglio, Elisabetta, Cotsoglou, Christian, Granieri, Stefano, Chierici, Andrea Piero, Tamini, Nicolò, Pitoni, Ludovica, Vico, Eleonora, Altomare, Donato Francesco, Martines, Gennaro, Tomasicchio, Giovanni, Coppola, Massimiliano, Aprile, Giovanna, Sau, Paolo, Papa, Mauro Del, Manzi, Fulvio, DʼAmata, Gabriele, Cocorullo, Gianfranco, Venturelli, Paolina, Carollo, Giuseppe, Tondolo, Vincenzo, Dore, Andrea, Giorgio, Danilo Di, Gusai, Giovanni Pietro Paolo, Salaris, Claudia, Sanna, Silvia, Pignata, Giusto, Andreuccetti, Jacopo, DʼAlessio, Rossella, Massani, Marco, Tutino, Roberta, Viola, Vincenzo, Stella, Luigi Persico, Diana, Massimo, Sampietro, Gianluca Matteo, Merlini, David Alessio, Sica, Giuseppe, Bagaglini, Giulia, Manzia, Tommaso Maria, Siracusa, Leandro, Tisone, Giuseppe, Ercolani, Giorgio, DʼAcapito, Fabrizio, Pietrantonio, Daniela Di, Fiscon, Valentino, Portale, Giuseppe, Cipollari, Chiara, Sorrentino, Mario, Piccolo, Roberta, Cojutti, Alessandro, Canova, Gualtiero, Nicotera, Antonella, Zago, Marcello, Montis, Giorgio De, Castaldi, Fabio, Morelli, Maria Morena, Parma, Emilio, Paolini, Claudia, Marco, Giovanni De, Elter, Chiara, Feo, Carlo V., Fabbri, Nicolò, Severi, Silvia, Nasto, Aurelio, Patrone, Renato, Conti, Lorenzo, Rizzi, Andrea, Broggi, Luca, Danelli, Piergiorgio, Cammarata, Francesco, Fiore, Luigi, Grande, Michele, Campanelli, Michela, and Grande, Simona

Published
2023
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50. Lower Multiple Sclerosis Severity Score Is Associated with Higher Adherence to Mediterranean Diet in Subjects with Multiple Sclerosis from Northwestern Italy

Author

Matteo Bronzini, Alessandro Maglione, Rachele Rosso, Federica Masuzzo, Manuela Matta, Raffaella Meroni, Simona Rolla, and Marinella Clerico

Subjects
multiple sclerosis, Mediterranean diet, MSSS, MEDAS, IMI, PyrMDS, Nutrition. Foods and food supply, TX341-641
Abstract

The Mediterranean Diet (MD) is described in the literature as a beneficial dietary pattern for neurodegenerative diseases such as Multiple Sclerosis (MS). The objective of this study was to evaluate the dietary habits in people with MS (pwMS) and to test whether adherence to the MD could have an impact on the severity of the disease measured as the MS severity score (MSSS). Adherence to the MD was assessed in 31 PwMS using the Mediterranean Diet Adherence Screener (MEDAS), the Pyramid-based Mediterranean Diet Score (PyrMDS) index, and the Italian Mediterranean Index (IMI), and their eating habits were recorded in a food diary for a one-year follow-up. When data obtained from dietary analysis were compared to the MSSS, results showed that pwMS with lower MSSS adhere more to the MD than the other pwMS groups according to the MEDAS index. Furthermore, a high consumption of fiber in the MS mild severity class was observed. Further studies are needed to clarify which of the nutritional components of the MD may impact the course of MS and if the sensitization of pwMS to MD adherence can be a strategy for mitigating the disease.

Published
2024
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