1,881 results on '"A. Pacchiarotti"'
Search Results
2. Large and moderate deviations for Gaussian neural networks
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Macci, Claudio, Pacchiarotti, Barbara, and Torrisi, Giovanni Luca
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Mathematics - Probability ,60F10, 60F05, 68T07 - Abstract
We prove large and moderate deviations for the output of Gaussian fully connected neural networks. The main achievements concern deep neural networks (i.e., when the model has more than one hidden layer) and hold for bounded and continuous pre-activation functions. However, for deep neural networks fed by a single input, we have results even if the pre-activation is ReLU. When the network is shallow (i.e., there is exactly one hidden layer) the large and moderate principles hold for quite general pre-activations and in an infinite-dimensional setting.
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- 2024
3. Wearable data from subjects playing Super Mario, sitting university exams, or performing physical exercise help detect acute mood episodes via self-supervised learning
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Corponi, Filippo, Li, Bryan M., Anmella, Gerard, Valenzuela-Pascual, Clàudia, Mas, Ariadna, Pacchiarotti, Isabella, Valentí, Marc, Grande, Iria, Benabarre, Antonio, Garriga, Marina, Vieta, Eduard, Young, Allan H, Lawrie, Stephen M., Whalley, Heather C., Hidalgo-Mazzei, Diego, and Vergari, Antonio
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Electrical Engineering and Systems Science - Signal Processing - Abstract
Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of worldwide disease burden. However, collecting and annotating wearable data is very resource-intensive. Studies of this kind can thus typically afford to recruit only a couple dozens of patients. This constitutes one of the major obstacles to applying modern supervised machine learning techniques to MDs detection. In this paper, we overcome this data bottleneck and advance the detection of MDs acute episode vs stable state from wearables data on the back of recent advances in self-supervised learning (SSL). This leverages unlabelled data to learn representations during pre-training, subsequently exploited for a supervised task. First, we collected open-access datasets recording with an Empatica E4 spanning different, unrelated to MD monitoring, personal sensing tasks -- from emotion recognition in Super Mario players to stress detection in undergraduates -- and devised a pre-processing pipeline performing on-/off-body detection, sleep-wake detection, segmentation, and (optionally) feature extraction. With 161 E4-recorded subjects, we introduce E4SelfLearning, the largest to date open access collection, and its pre-processing pipeline. Second, we show that SSL confidently outperforms fully-supervised pipelines using either our novel E4-tailored Transformer architecture (E4mer) or classical baseline XGBoost: 81.23% against 75.35% (E4mer) and 72.02% (XGBoost) correctly classified recording segments from 64 (half acute, half stable) patients. Lastly, we illustrate that SSL performance is strongly associated with the specific surrogate task employed for pre-training as well as with unlabelled data availability.
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- 2023
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4. A Bayesian analysis of heart rate variability changes over acute episodes of bipolar disorder
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Filippo Corponi, Bryan M. Li, Gerard Anmella, Clàudia Valenzuela-Pascual, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antonio Benabarre, Marina Garriga, Eduard Vieta, Stephen M. Lawrie, Heather C. Whalley, Diego Hidalgo-Mazzei, and Antonio Vergari
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Therapeutics. Psychotherapy ,RC475-489 - Abstract
Abstract Bipolar disorder (BD) involves autonomic nervous system dysfunction, detectable through heart rate variability (HRV). HRV is a promising biomarker, but its dynamics during acute mania or depression episodes are poorly understood. Using a Bayesian approach, we developed a probabilistic model of HRV changes in BD, measured by the natural logarithm of the Root Mean Square of Successive RR interval Differences (lnRMSSD). Patients were assessed three to four times from episode onset to euthymia. Unlike previous studies, which used only two assessments, our model allowed for more accurate tracking of changes. Results showed strong evidence for a positive lnRMSSD change during symptom resolution (95.175% probability of positive direction), though the sample size limited the precision of this effect (95% Highest Density Interval [−0.0366, 0.4706], with a Region of Practical Equivalence: [-0.05; 0.05]). Episode polarity did not significantly influence lnRMSSD changes.
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- 2024
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5. A Bayesian analysis of heart rate variability changes over acute episodes of bipolar disorder
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Corponi, Filippo, Li, Bryan M., Anmella, Gerard, Valenzuela-Pascual, Clàudia, Pacchiarotti, Isabella, Valentí, Marc, Grande, Iria, Benabarre, Antonio, Garriga, Marina, Vieta, Eduard, Lawrie, Stephen M., Whalley, Heather C., Hidalgo-Mazzei, Diego, and Vergari, Antonio
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- 2024
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6. Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number
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Corponi, Filippo, Li, Bryan M., Anmella, Gerard, Mas, Ariadna, Pacchiarotti, Isabella, Valentí, Marc, Grande, Iria, Benabarre, Antoni, Garriga, Marina, Vieta, Eduard, Lawrie, Stephen M., Whalley, Heather C., Hidalgo-Mazzei, Diego, and Vergari, Antonio
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- 2024
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7. Asymptotic results for compound sums in separable Banach spaces
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Macci, Claudio and Pacchiarotti, Barbara
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Mathematics - Probability ,60F10, 60G50, 60B12 - Abstract
We prove large and moderate deviation results for sequences of compound sums, where the summands are i.i.d. random variables taking values in a separable Banach space. We establish that the results hold by proving that we are dealing with exponentially tight sequences. We present two moderate deviation results: in the first one the summands are centered, in the second one the compound sums are centered., Comment: 18pages
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- 2023
8. Identifying digital biomarkers of illness activity and treatment response in bipolar disorder with a novel wearable device (TIMEBASE): protocol for a pragmatic observational clinical study
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Gerard Anmella, Filippo Corponi, Bryan M. Li, Ariadna Mas, Marina Garriga, Miriam Sanabra, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antoni Benabarre, Anna Giménez-Palomo, Isabel Agasi, Anna Bastidas, Myriam Cavero, Miquel Bioque, Clemente García-Rizo, Santiago Madero, Néstor Arbelo, Andrea Murru, Silvia Amoretti, Anabel Martínez-Aran, Victoria Ruiz, Yudit Rivas, Giovanna Fico, Michele De Prisco, Vincenzo Oliva, Aleix Solanes, Joaquim Radua, Ludovic Samalin, Allan H. Young, Antonio Vergari, Eduard Vieta, and Diego Hidalgo-Mazzei
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Bipolar disorder ,mania ,depression ,physiological data ,digital biomarkers ,Psychiatry ,RC435-571 - Abstract
Background Bipolar disorder is highly prevalent and consists of biphasic recurrent mood episodes of mania and depression, which translate into altered mood, sleep and activity alongside their physiological expressions. Aims The IdenTifying dIgital bioMarkers of illnEss activity and treatment response in BipolAr diSordEr with a novel wearable device (TIMEBASE) project aims to identify digital biomarkers of illness activity and treatment response in bipolar disorder. Method We designed a longitudinal observational study including 84 individuals. Group A comprises people with acute episode of mania (n = 12), depression (n = 12 with bipolar disorder and n = 12 with major depressive disorder (MDD)) and bipolar disorder with mixed features (n = 12). Physiological data will be recorded during 48 h with a research-grade wearable (Empatica E4) across four consecutive time points (acute, response, remission and episode recovery). Group B comprises 12 people with euthymic bipolar disorder and 12 with MDD, and group C comprises 12 healthy controls who will be recorded cross-sectionally. Psychopathological symptoms, disease severity, functioning and physical activity will be assessed with standardised psychometric scales. Physiological data will include acceleration, temperature, blood volume pulse, heart rate and electrodermal activity. Machine learning models will be developed to link physiological data to illness activity and treatment response. Generalisation performance will be tested in data from unseen patients. Results Recruitment is ongoing. Conclusions This project should contribute to understanding the pathophysiology of affective disorders. The potential digital biomarkers of illness activity and treatment response in bipolar disorder could be implemented in a real-world clinical setting for clinical monitoring and identification of prodromal symptoms. This would allow early intervention and prevention of affective relapses, as well as personalisation of treatment.
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- 2024
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9. Asymptotic results for sums and extremes
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Giuliano, Rita, Macci, Claudio, and Pacchiarotti, Barbara
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Mathematics - Probability - Abstract
The term moderate deviations is often used in the literature to mean a class of large deviation principles that, in some sense, fills the gap between a convergence in probability of some random variables to a constant and a weak convergence to a centered Gaussian distribution (when such random variables are properly centered and rescaled). We talk about noncentral moderate deviations when the weak convergence is towards a non-Gaussian distribution. In this paper, we prove a noncentral moderate deviation result for the bivariate sequence of sums and maxima of i.i.d. random variables bounded from above. We also prove a result where the random variables are not bounded from above, and the maxima are suitably normalized. Finally, we prove a moderate deviation result for sums of partial minima of i.i.d. exponential random variables., Comment: 19
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- 2022
10. The genetic legacy of the expansion of Bantu-speaking peoples in Africa
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Fortes-Lima, Cesar A., Burgarella, Concetta, Hammarén, Rickard, Eriksson, Anders, Vicente, Mário, Jolly, Cecile, Semo, Armando, Gunnink, Hilde, Pacchiarotti, Sara, Mundeke, Leon, Matonda, Igor, Muluwa, Joseph Koni, Coutros, Peter, Nyambe, Terry S., Cikomola, Justin Cirhuza, Coetzee, Vinet, de Castro, Minique, Ebbesen, Peter, Delanghe, Joris, Stoneking, Mark, Barham, Lawrence, Lombard, Marlize, Meyer, Anja, Steyn, Maryna, Malmström, Helena, Rocha, Jorge, Soodyall, Himla, Pakendorf, Brigitte, Bostoen, Koen, and Schlebusch, Carina M.
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- 2024
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11. Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number
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Filippo Corponi, Bryan M. Li, Gerard Anmella, Ariadna Mas, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antoni Benabarre, Marina Garriga, Eduard Vieta, Stephen M. Lawrie, Heather C. Whalley, Diego Hidalgo-Mazzei, and Antonio Vergari
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Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
Abstract Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited specialized care availability remains a major bottleneck thus hindering pre-emptive interventions. MDs manifest with changes in mood, sleep, and motor activity, observable in ecological physiological recordings thanks to recent advances in wearable technology. Therefore, near-continuous and passive collection of physiological data from wearables in daily life, analyzable with machine learning (ML), could mitigate this problem, bringing MDs monitoring outside the clinician’s office. Previous works predict a single label, either the disease state or a psychometric scale total score. However, clinical practice suggests that the same label may underlie different symptom profiles, requiring specific treatments. Here we bridge this gap by proposing a new task: inferring all items in HDRS and YMRS, the two most widely used standardized scales for assessing MDs symptoms, using physiological data from wearables. To that end, we develop a deep learning pipeline to score the symptoms of a large cohort of MD patients and show that agreement between predictions and assessments by an expert clinician is clinically significant (quadratic Cohen’s κ and macro-average F1 score both of 0.609). While doing so, we investigate several solutions to the ML challenges associated with this task, including multi-task learning, class imbalance, ordinal target variables, and subject-invariant representations. Lastly, we illustrate the importance of testing on out-of-distribution samples.
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- 2024
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12. Large Deviations of continuous Gaussian processes: from small noise to small time
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Baldi, Paolo and Pacchiarotti, Barbara
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Mathematics - Probability ,60F10, 60G15, 60G22 - Abstract
We investigate the Large Deviation behavior in small time of continuous Gaussian processes. We introduce a general procedure allowing to derive Large Deviation Principles in small time starting from the well understood context of Large Deviation Principles with a small parameter, going beyond the self-similar case. Several motivating examples are also treated.
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- 2022
13. Large deviations for perturbed Gaussian processes and logarithmic asymptotic estimates for some exit probabilities
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Macci, C. and Pacchiarotti, B.
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Mathematics - Probability ,60F10, 60G15, 60G22, 91B30 - Abstract
The main results in this paper concern large deviations for families of non-Gaussian processes obtained as suitable perturbations of continuous centered multivariate Gaussian processes which satisfy a large deviation principle. We present some corollaries and, as a consequence, we obtain logarithmic asymptotic estimates for exit probabilities from suitable halfspaces and quadrants., Comment: 22 pages
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- 2022
14. Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via Self-Supervised Learning: Prospective, Exploratory, Observational Study
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Filippo Corponi, Bryan M Li, Gerard Anmella, Clàudia Valenzuela-Pascual, Ariadna Mas, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antoni Benabarre, Marina Garriga, Eduard Vieta, Allan H Young, Stephen M Lawrie, Heather C Whalley, Diego Hidalgo-Mazzei, and Antonio Vergari
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Information technology ,T58.5-58.64 ,Public aspects of medicine ,RA1-1270 - Abstract
BackgroundPersonal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of the worldwide disease burden. However, collecting and annotating wearable data is resource intensive. Studies of this kind can thus typically afford to recruit only a few dozen patients. This constitutes one of the major obstacles to applying modern supervised machine learning techniques to MD detection. ObjectiveIn this paper, we overcame this data bottleneck and advanced the detection of acute MD episodes from wearables’ data on the back of recent advances in self-supervised learning (SSL). This approach leverages unlabeled data to learn representations during pretraining, subsequently exploited for a supervised task. MethodsWe collected open access data sets recording with the Empatica E4 wristband spanning different, unrelated to MD monitoring, personal sensing tasks—from emotion recognition in Super Mario players to stress detection in undergraduates—and devised a preprocessing pipeline performing on-/off-body detection, sleep/wake detection, segmentation, and (optionally) feature extraction. With 161 E4-recorded subjects, we introduced E4SelfLearning, the largest-to-date open access collection, and its preprocessing pipeline. We developed a novel E4-tailored transformer (E4mer) architecture, serving as the blueprint for both SSL and fully supervised learning; we assessed whether and under which conditions self-supervised pretraining led to an improvement over fully supervised baselines (ie, the fully supervised E4mer and pre–deep learning algorithms) in detecting acute MD episodes from recording segments taken in 64 (n=32, 50%, acute, n=32, 50%, stable) patients. ResultsSSL significantly outperformed fully supervised pipelines using either our novel E4mer or extreme gradient boosting (XGBoost): n=3353 (81.23%) against n=3110 (75.35%; E4mer) and n=2973 (72.02%; XGBoost) correctly classified recording segments from a total of 4128 segments. SSL performance was strongly associated with the specific surrogate task used for pretraining, as well as with unlabeled data availability. ConclusionsWe showed that SSL, a paradigm where a model is pretrained on unlabeled data with no need for human annotations before deployment on the supervised target task of interest, helps overcome the annotation bottleneck; the choice of the pretraining surrogate task and the size of unlabeled data for pretraining are key determinants of SSL success. We introduced E4mer, which can be used for SSL, and shared the E4SelfLearning collection, along with its preprocessing pipeline, which can foster and expedite future research into SSL for personal sensing.
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- 2024
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15. Short-time asymptotics for non self-similar stochastic volatility models
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Giorgio, Giacomo, Pacchiarotti, Barbara, and Pigato, Paolo
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Quantitative Finance - Mathematical Finance ,Mathematics - Probability ,91G20, 60H30, 60F10, 60G22 - Abstract
We provide a short-time large deviation principle (LDP) for stochastic volatility models, where the volatility is expressed as a function of a Volterra process. This LDP does not require strict self-similarity assumptions on the Volterra process. For this reason, we are able to apply such an LDP to two notable examples of non self-similar rough volatility models: models where the volatility is given as a function of a log-modulated fractional Brownian motion [Bayer et al., Log-modulated rough stochastic volatility models. SIAM J. Financ. Math, 2021, 12(3), 1257-1284], and models where it is given as a function of a fractional Ornstein-Uhlenbeck (fOU) process [Gatheral et al., Volatility is rough. Quant. Finance, 2018, 18(6), 933-949]. In both cases we derive consequences for short-maturity European option prices, implied volatility surfaces and implied volatility skew. In the fOU case we also discuss moderate deviations pricing and simulation results., Comment: 25 pages, 4 figures
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- 2022
16. Clinical, sociodemographic and environmental predicting factors for relapse in bipolar disorder: A systematic review
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Giménez-Palomo, Anna, Andreu, Helena, Olivier, Luis, Ochandiano, Iñaki, de Juan, Oscar, Fernández-Plaza, Tábatha, Salmerón, Sergi, Bracco, Lorenzo, Colomer, Lluc, Mena, Juan I., Vieta, Eduard, and Pacchiarotti, Isabella
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- 2024
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17. Metabolic regulation to treat bipolar depression: mechanisms and targeting by trimetazidine
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Khanra, Sourav, Reddy, Preethi, Giménez-Palomo, Anna, Park, Chun Hui J., Panizzutti, Bruna, McCallum, Madeleine, Arumugham, Shyam Sundar, Umesh, Shreekantiah, Debnath, Monojit, Das, Basudeb, Venkatasubramanian, Ganesan, Ashton, Melanie, Turner, Alyna, Dean, Olivia M., Walder, Ken, Vieta, Eduard, Yatham, Lakshmi N., Pacchiarotti, Isabella, Reddy, Y. C. Janardhan, Goyal, Nishant, Kesavan, Muralidharan, Colomer, Lluc, Berk, Michael, and Kim, Jee Hyun
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- 2023
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18. A Proof of the Countable Telescope Conjecture for Module Categories
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Pacchiarotti, P. F.
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Mathematics - Rings and Algebras ,Mathematics - Representation Theory - Abstract
The Countable Telescope Conjecture arose in the framework of stable homotopy theory, as a tool conceived to study the chromatic filtration. It turned out, however, to trigger extremely fertile research within the framework of Module Categories. The project aims at presenting an almost self-contained review of the recent work of Saroch on the Countable Telescope Conjecture for Module Categories. After recalling some preliminaries, we report various devices of independent interest that will lead to a proof of the aforementioned result. This will be the outcome of inductive refinements of families of particularly well-behaved dense systems of modules, our witnessing-notion for localness. The procedure will be reminiscent of Cantor diagonal argument in the implementation of a variant of Shelah's Compactness Principle. Then, we briefly review the main applications to Enochs Conjecture of the just developed theory, and we will also state a weaker version of it. The project closely follows the work of Saroch (https://link.springer.com/article/10.1007%2Fs11856-018-1710-4); however, for the sake of completeness and conciseness, we slightly modified some well-known proofs applying the newly developed tools., Comment: 45 pages. Summer Research Project advised by Prof. J. Trlifaj within the activities of the Galilean School of Higher Education
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- 2021
19. Asymptotics for multifactor Volterra type stochastic volatility models
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Catalini, Giulia and Pacchiarotti, Barbara
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Mathematics - Probability ,60F10, 60G15, 60G22 - Abstract
We study multidimensional stochastic volatility models in which the volatility process is a positive continuous function of a continuous multidimensional Volterra process that can be not self-similar. The main results obtained in this paper are a generalization of the results due, in the one-dimensional case, to Cellupica and Pacchiarotti [M. Cellupica and B. Pacchiarotti (2021) Pathwise Asymptotics for Volterra Type Stochastic Volatility Models. Journal of Theoretical Probability, 34(2):682--727]. We state some (pathwise and finite-dimensional) large deviation principles for the scaled log-price and as a consequence some (pathwise and finite-dimensional) short-time large deviation principles., Comment: arXiv admin note: text overlap with arXiv:1902.05896
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- 2021
20. Predictors of relapse in bipolar disorder: an overview of the available evidence
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I. Pacchiarotti
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Psychiatry ,RC435-571 - Abstract
Abstract After the introduction of all the speakers, the main aim of this workshop will be mentioned, which consists of identifying and highlighting those clinical, sociodemographic, environmental and other factors than might predict an increased risk of overall, depressive, manic or mixed relapses in bipolar disorder, which is crucial for the identification of high-risk individuals. Dr. Pacchiarotti will present main results from a systematic review performed recently by the work group aimed at collecting the available evidence regarding different factors that increase rates of mood recurrences or relapses for different polarities in bipolar disorder. Disclosure of Interest None Declared
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- 2024
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21. The role of cannabis in bipolar disorder relapse: a prospective study of hospital acute readmissions
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L. Olivier, A. Giménez, H. Andreu Gracia, L. Bueno, Ó. De Juan Viladegut, T. M. Fernández, I. Ochandiano, S. Salmerón, L. Bracco, L. Tardón Senabre, and I. Pacchiarotti
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Psychiatry ,RC435-571 - Abstract
Introduction With the rapid changes of attitude, investigation and legislation around cannabis and its subproducts in the Western world, there is a need to profoundly examine the consequences of its use in the general population and, specifically, in people affected by mental disorders. There is a clear relationship between cannabis use and psychosis, but there is also growing evidence of its relationship with manic episodes (Sideli et al, 2019). A systematic review published by the CANMAT Task Force in 2022 examined again the relationship between cannabis use and bipolar disorder (BD), establishing association with worsened course and functioning of BD in frequent users (Tourjman et al., 2023). On the other hand, some recent papers have highlighted the role of the endocannabinoid system (ECS) in BD, suggesting even possible beneficial effects, mainly through the CB2 receptor (Arjmand et al, 2019). Objectives To describe the impact of cannabis in the psychiatric readmission in BD and to approach the differences in course in cannabis users with regards to non-users. Methods We conducted a prospective cohort study including the patients admitted to our acute psychiatric unit with the diagnosis of manic or mixed episode during the period between 2015 and 2019 (including patients with one of both final diagnosis: BD or schizoaffective disorder). We established a follow-up of 3 years from the date of admission in which hospital readmissions are examined. Results The study, which included 309 patients, concluded that cannabis users were admitted and had the first episode at a younger age (p=0.005), a higher percentage of them did not have a previous diagnosis (p=0.026) nor a previous history of mental health issues (p=0.019) and it was more likely to be their first admission (p=0.011) and to suffer psychotic symptoms (p=0.002). As of treatment, the results were statistically significant regarding the fact that a lower proportion of patients had received previous psychiatric treatment (p=0.004) and previous electroconvulsive therapy (p=0.003). There was a higher chance of them being non-adherent with medication (p
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- 2024
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22. Mitochondrial respiratory capacity in patients with acute episodes of bipolar disorder compared with clinical remission
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A. Giménez-Palomo, M. Guitart-Mampel, A. Meseguer, M. Valentí, L. Bracco, H. Andreu, E. Vieta, G. Garrabou, and I. Pacchiarotti
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Psychiatry ,RC435-571 - Abstract
Introduction Bipolar disorder (BD) is a chronic and recurrent disease characterized by acute mood episodes alternated with periods of euthymia. The available literature postulates that a biphasic dysregulation of mitochondrial bioenergetics might be observed in BD. Objectives We aimed to explore differences in in vivo mitochondrial respiration (1) intra-individually: longitudinally within patients during an acute mood episode of BD and after clinical remission, and (2) inter-individually: between patients with BD on depressive or manic episodes and healthy controls (HC). Methods Patients admitted to our acute psychiatric ward with a manic episode or bipolar depression were recruited. Different mitochondrial oxygen consumption rates (OCRs) were assessed during the acute episode (T0) and after clinical remission (T1) in one million of peripheral blood mononuclear cells (PBMC): Routine, Leak, ETC and Rox. They were measured as picomoles of oxygen per million cells (pmol O2/million). This experiment was also conducted in HC. High-resolution respirometry was performed at 37°C by polarographic oxygen sensors in a two-chamber Oxygraph-2k system. Manic and depressive symptoms were assessed using standardized psychometric scales. Oxygen consumption capacity was compared (1) intra-individually, during acute episodes and after clinical remission, and (2) inter-individually, during acute manic and depressive episodes, and in HC. Statistical analyses were performed with SPSS, GraphPad and R Statistics. Results 20 patients with BD (15 manic, 5 depressed) and 10 HC were included. A significant increase in the maximal oxygen consumption capacity (ETC) was observed in clinical remission (27.4 ± 17.4) compared to the acute episodes (21.1 ± 11.7, p = 0.001), which remained significant after subtracting Rox from the other rates (p = 0.001). At T1, patients admitted with a manic episode tended to show higher mean ETC (31.2 ± 18.7) compared with T0 (24.1 ± 12.0, p = 0.074); the tendency persisted after Rox subtraction (p = 0.076). Patients admitted with a depressive episode also showed higher ETC means in T1 (16.3 ± 3.8) compared to T0 (12.1 ± 3.4), but there were not significant differences (p = 0.231). When HC, manic and depressive patients at T0 were compared between them, significant differences were observed in ETC (H =8.5; p =0.014) and Rox (H =13.8; p = 0.001). After Rox deduction, differences in ETC remained (H =11.7; p = 0.003). Individuals with bipolar depression showed lower ETC rates (12.1 ± 3.4) than those with a manic episode (24.1 ± 12.0; t = -3.5, p = 0.003), which was also found after Rox deduction (p = 0.001). Conclusions In both manic and depressive episodes in BD, mitochondrial respiration might be reduced and increase after clinical remission. Further studies with larger samples will allow to confirm these results and also to identify potential mitochondrial state-dependent biomarkers. Disclosure of Interest A. Giménez-Palomo Grant / Research support from: AGP is supported by a Rio Hortega 2021 grant (CM21/00094) from the Spanish Ministry of Health financed by ISCIII and cofinanced by Fondo Social Europeo Plus (FSE+)., M. Guitart-Mampel: None Declared, A. Meseguer: None Declared, M. Valentí: None Declared, L. Bracco: None Declared, H. Andreu: None Declared, E. Vieta: None Declared, G. Garrabou: None Declared, I. Pacchiarotti: None Declared
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- 2024
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23. Labial-velar stops in Sakata (Bantu C34)
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Lorenzo Maselli, Véronique Delvaux, Jean-Pierre Donzo, Sara Pacchiarotti, and Koen Bostoen
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phonetic documentation ,articulatory phonology ,Bantu languages ,acoustics ,sound change ,Philology. Linguistics ,P1-1091 - Abstract
The present contribution bears on the documentation and description of a few unusual sounds, i.e. double labial-velar articulations, in a number of Bantu zone C varieties belonging to the so-called “Sakata cluster” in the southwestern Democratic Republic of Congo (DRC). These phonemes, often considered typical of a linguistic area known as the “Macro-Sudan Belt”, are considerably more common in southern Central Africa than previously thought. The case of the Sakata varieties at hand represents one of particular interest considering the wide array of labial-velar articulations they present. First, we provide a spectral analysis of the data available to us, discussing the question of whether some of the sounds documented here should be described as labial-velar fricatives. Second, we proceed to review well-established models of sound change to test them against our data, with special focus on kiNgingele. We conclude by proposing that the presence of labial-velars in Sakata is part of a broader set of “uncommon” linguistic features present in northwestern Bantu: this, in turn, might point to the fact that the languages of the region went through stages of greater phonological diversity than suggested by today’s relative homogeneity. Sakata labial-velars may just be one trace of this diversity. Keywords: phonetic documentation, articulatory phonology, Bantu languages, acoustics, sound change
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- 2024
24. The Introduction of Sugarcane in West-Central Africa
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Sifra Van Acker, Sara Pacchiarotti, and Koen Bostoen
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Central Africa ,historical linguistics ,lexical reconstruction ,Southeast Asian crops ,sugarcane ,West-Coastal Bantu ,Language and Literature ,Social Sciences - Abstract
Due to the extreme scarcity of archaeological and historical data very little is known about the introduction of Southeast Asian crops such as banana, sugarcane, taro and greater yam in Africa and the role they played in the subsistence and lifeways of ancestral African communities. Therefore, we closely examine in this article comparative lexical data as a source to reconstruct the history of sugarcane in West-Central Africa. We focus more specifically on one branch of the Bantu language family, i.e., West-Coastal Bantu, in conjunction with data from Bantu languages spoken in the Congo rainforest and further south. We argue that despite their shared origins, sugarcane and bananas were not introduced in Africa as part of one single Southeast Asian package. Sugarcane made its way through West-Central together with crops of American origin such as maize, cassava, peanut, common bean, and (sweet) potato as part of the so-called “Columbian Exchange”, i.e., not earlier than the sixteenth century CE, while the ancestry of bananas in the Congo rainforest area likely goes back to the Early Iron Age, i.e., about 2,500 years ago.
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- 2024
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25. Aerobic capacity and mitochondrial function in bipolar disorder: a longitudinal study during acute phases and after clinical remission
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Anna Giménez-Palomo, Mariona Guitart-Mampel, Gemma Roqué, Ester Sánchez, Roger Borràs, Ana Meseguer, Francesc Josep García-García, Esther Tobías, Laura Valls-Roca, Gerard Anmella, Marc Valentí, Luis Olivier, Oscar de Juan, Iñaki Ochandiano, Helena Andreu, Joaquim Radua, Norma Verdolini, Michael Berk, Eduard Vieta, Glòria Garrabou, Josep Roca, Xavier Alsina-Restoy, and Isabella Pacchiarotti
- Subjects
bipolar disorder ,mania ,depression ,aerobic capacity ,endurance time ,mitochondrial respiration ,Psychiatry ,RC435-571 - Abstract
BackgroundAerobic capacity has shown to predict physical and mental health-related quality of life in bipolar disorder (BD). However, the correlation between exercise respiratory capacity and mitochondrial function remains understudied. We aimed to assess longitudinally intra-individual differences in these factors during mood episodes and remission in BD.MethodsThis study included eight BD patients admitted to an acute psychiatric unit. Incremental cardiopulmonary exercise test (CPET) was conducted during acute episodes (T0), followed by constant work rate cycle ergometry (CWRCE) to evaluate endurance time, oxygen uptake at peak exercise (VO2peak) and at the anaerobic threshold. The second test was repeated during remission (T1). Mitochondrial respiration rates were assessed at T0 and T1 in peripheral blood mononuclear cells.ResultsEndurance time, VO2peak, and anaerobic threshold oxygen consumption showed no significant variations between T0 and T1. Basal oxygen consumption at T1 tended to inversely correlate with maximal mitochondrial respiratory capacity (r=-0.690, p=0.058), and VO2peak during exercise at T1 inversely correlated with basal and minimum mitochondrial respiration (r=-0.810, p=0.015; r=-0.786, p=0.021, respectively).ConclusionsOur preliminary data showed that lower basal oxygen consumption may be linked to greater mitochondrial respiratory capacity, and maximum oxygen uptake during the exercise task was associated with lower basal mitochondrial respiration, suggesting that lower oxygen requirements could be associated with greater mitochondrial capacity. These findings should be replicated in larger samples stratified for manic and depressive states.
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- 2024
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26. Asymptotic results for certain first-passage times and areas of renewal processes
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Macci, Claudio and Pacchiarotti, Barbara
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Mathematics - Probability - Abstract
We consider the process $\{x-N(t):t\geq 0\}$, where $x\in\mathbb{R}_+$ and $\{N(t):t\geq 0\}$ is a renewal process with light-tailed distributed holding times. We are interested in the joint distribution of $(\tau(x),A(x))$ where $\tau(x)$ is the first-passage time of $\{x-N(t):t\geq 0\}$ to reach zero or a negative value, and $A(x):=\int_0^{\tau(x)}(x-N(t))dt$ is the corresponding first-passage (positive) area swept out by the process $\{x-N(t):t\geq 0\}$. We remark that we can define the sequence $\{(\tau(n),A(n)):n\geq 1\}$ by referring to the concept of integrated random walk. Our aim is to prove asymptotic results as $x\to\infty$ in the fashion of large (and moderate) deviations., Comment: 22 pages
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- 2021
27. Asymptotic results for linear combinations of spacings generated by i.i.d. exponential random variables
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Calì, Camilla, Longobardi, Maria, Macci, Claudio, and Pacchiarotti, Barbara
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Mathematics - Probability ,Computer Science - Information Theory ,Mathematics - Statistics Theory - Abstract
We prove large (and moderate) deviations for a class of linear combinations of spacings generated by i.i.d. exponentially distributed random variables. We allow a wide class of coefficients which can be expressed in terms of continuous functions defined on [0, 1] which satisfy some suitable conditions. In this way we generalize some recent results by Giuliano et al. (2015) which concern the empirical cumulative entropies defined in Di Crescenzo and Longobardi (2009a).
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- 2021
28. Asymptotic results for families of power series distributions
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Macci, Claudio, Pacchiarotti, Barbara, and Villa, Elena
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Mathematics - Probability ,60F10, 60E05, 60G22 - Abstract
In this paper we consider suitable families of power series distributed random variables, and we study their asymptotic behavior in the fashion of large (and moderate) deviations. We also present two examples of fractional counting processes, where the normalizations of the involved power series distributions can be expressed in terms of the Prabhakar function. The first example allows to consider the counting process in \cite{PoganyTomovski}, the second one is inspired by a model studied in \cite{GarraOrsingherPolito}.
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- 2021
29. Electrodermal activity in bipolar disorder: Differences between mood episodes and clinical remission using a wearable device in a real-world clinical setting
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Anmella, Gerard, Mas, Ariadna, Sanabra, Miriam, Valenzuela-Pascual, Clàudia, Valentí, Marc, Pacchiarotti, Isabella, Benabarre, Antoni, Grande, Iria, De Prisco, Michele, Oliva, Vincenzo, Fico, Giovanna, Giménez-Palomo, Anna, Bastidas, Anna, Agasi, Isabel, Young, Allan H., Garriga, Marina, Corponi, Filippo, Li, Bryan M., de Looff, Peter, Vieta, Eduard, and Hidalgo-Mazzei, Diego
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- 2024
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30. Large deviations for a class of tempered subordinators and their inverse processes
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Leonenko, Nikolai, Macci, Claudio, and Pacchiarotti, Barbara
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Mathematics - Probability ,60F10, 60G52, 60J25 - Abstract
We consider a class of tempered subordinators, namely a class of subordinators with one-dimensional marginal tempered distributions which belong to a family studied in [3]. The main contribution in this paper is a non-central moderate deviations result. More precisely we mean a class of large deviation principles that fill the gap between the (trivial) weak convergence of some non-Gaussian identically distributed random variables to their common law, and the convergence of some other related random variables to a constant. Some other minor results concern large deviations for the inverse of the tempered subordinators considered in this paper; actually, in some results, these inverse processes appear as random time-changes of other independent processes.
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- 2020
31. Pathwise asymptotics for Volterra processes conditioned to a noisy version of the Brownian motion
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Pacchiarotti, Barbara
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Mathematics - Probability - Abstract
In this paper we investigate a problem of large deviations for continuous Volterra processes under the influence of model disturbances. More precisely, we study the behavior, in the near future after $T$, of a Volterra process driven by a Brownian motion in a case where the Brownian motion is not directly observable, but only a noisy version is observed or some linear functionals of the noisy version are observed. Some examples are discussed in both cases., Comment: Published at https://doi.org/10.15559/20-VMSTA149 in the Modern Stochastics: Theory and Applications (https://vmsta.org/) by VTeX (http://www.vtex.lt/)
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- 2020
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32. A systematic review of manic/hypomanic and depressive switches in patients with bipolar disorder in naturalistic settings: The role of antidepressant and antipsychotic drugs
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Barbuti, Margherita, Menculini, Giulia, Verdolini, Norma, Pacchiarotti, Isabella, Kotzalidis, Georgios D., Tortorella, Alfonso, Vieta, Eduard, and Perugi, Giulio
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- 2023
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33. First National Prevalence in Italian Horse Population and Phylogenesis Highlight a Fourth Sub-Type Candidate of Equine Hepacivirus
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Roberto Nardini, Giulia Pacchiarotti, Valentina Svicher, Romina Salpini, Maria Concetta Bellocchi, Raffaella Conti, Marcello Giovanni Sala, Davide La Rocca, Luca Carioti, Antonella Cersini, Giuseppe Manna, the Equine Hepatic Viruses Consortium, and Maria Teresa Scicluna
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equine hepacivirus ,horses ,biomolecular prevalence ,Italy ,phylogenesis ,Microbiology ,QR1-502 - Abstract
Equine hepacivirus (EqHV, Flaviviridae, hepacivirus) is a small, enveloped RNA virus generally causing sub-clinical hepatitis with occasional fatalities. EqHV is reported in equids worldwide, but for Italy data are limited. To address this, a survey study was set up to estimate prevalence at a national level and among different production categories (equestrian; competition; work and meat; reproduction) and national macro-regions (North, Central, South, and Islands). Data obtained testing 1801 horse serum samples by Real-Time RT PCR were compared within the categories and regions. The NS3 fragment of the PCR-positive samples was sequenced by Sanger protocol for phylogenetic and mutational analysis. The tertiary structure of the NS3 protein was also assessed. The estimated national prevalence was 4.27% [1.97–6.59, 95% CI] and no statistical differences were detected among production categories and macro-regions. The phylogenesis confirmed the distribution in Italy of the three known EqHV subtypes, also suggesting a possible fourth sub-type that, however, requires further confirmation. Mutational profiles that could also affect the NS3 binding affinity to the viral RNA were detected. The present paper demonstrates that EqHV should be included in diagnostic protocols when investigating causes of hepatitis, and in quality control protocols for blood derived products due to its parental transmission.
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- 2024
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34. First Reported Circulation of Equine Influenza H3N8 Florida Clade 1 Virus in Horses in Italy
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Ida Ricci, Silvia Tofani, Davide Lelli, Giacomo Vincifori, Francesca Rosone, Andrea Carvelli, Elena Lavinia Diaconu, Davide La Rocca, Giuseppe Manna, Samanta Sabatini, Donatella Costantini, Raffaella Conti, Giulia Pacchiarotti, and Maria Teresa Scicluna
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equine influenza ,Florida clade 1 ,horse ,genetic characterization HA and NA ,Veterinary medicine ,SF600-1100 ,Zoology ,QL1-991 - Abstract
Background: Equine influenza (EI) is a highly contagious viral disease of equids characterized by pyrexia and respiratory signs. Like other influenza A viruses, antigenic drift or shift could lead to a vaccine-induced immunity breakdown if vaccine strains are not updated. The aim of this study was to genetically characterize EIV strains circulating in Italy, detected in PCR-positive samples collected from suspected cases, especially in the absence of formal active surveillance. Methods: Between February and April 2019, blood samples and nasal swabs collected from each of the 20 symptomatic horses from North and Central Italy were submitted to the National Reference Centre for Equine Diseases in Italy to confirm preliminary analysis performed by other laboratories. Results: None of the sera analysed using haemagglutination inhibition and single radial haemolysis presented a predominant serological reactivity pattern for any antigen employed. All nasal swabs were positive with IAV RRT-PCR. Only one strain, isolated in an embryonated chicken egg from a sample collected from a horse of a stable located in Brescia, Lombardy, was identified as H3N8 Florida lineage clade 1 (FC1). In the constructed phylogenetic trees, this strain is located within the FC1, together with the virus isolated in France in 2018 (MK501761). Conclusions: This study reports the first detection of H3N8 FC1 in Italy, highlighting the importance of monitoring circulating EIV strains to verify the vaccine composition appropriateness for maximum efficacy.
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- 2024
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35. Pathological and virological insights from an outbreak of European brown hare syndrome in the Italian hare (Lepus corsicanus)
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Mariagiovanna Domanico, Patrizia Cavadini, Roberto Nardini, Daniele Cecca, Giovanni Mastrandrea, Claudia Eleni, Valentina Galietta, Lorenzo Attili, Antonella Pizzarelli, Roberta Onorati, Cristina Amoruso, Donatella Stilli, Giulia Pacchiarotti, Francesca Merzoni, Andrea Caprioli, Ida Ricci, Antonio Battisti, Antonio Lavazza, and Maria Teresa Scicluna
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European brown hare syndrome ,EBHSV ,Lepus corsicanus ,hare ,outbreak ,Lagovirus ,Microbiology ,QR1-502 - Abstract
European brown hare syndrome (EBHS) is a highly contagious and fatal viral disease, mainly affecting European brown hares (Lepus europaeus). The etiological agent, EBHS virus (EBHSV), belongs to the Lagovirus genus within the Caliciviridae family. The Italian hare (Lepus corsicanus) is endemic to Central-Southern Italy and Sicily and is classified as a vulnerable species. L. corsicanus is known to be susceptible to EBHS, but virological data available is scarce due to the few cases detected so far. In this study, we describe the occurrence of EBHS in two free-ranging L. corsicanus, found dead in a protected area of Central Italy. The two hares were identified as L. corsicanus using phenotypic criteria and confirmed through mitochondrial DNA analysis. Distinctive EBHS gross lesions were observed at necropsy and confirmed by subsequent histological examination. EBHSV was detected in the livers of the two animals initially using an antigen detection ELISA, followed by an EBHSV-specific reverse transcription-PCR, thus confirming the viral infection as the probable cause of death. The EBHS viruses detected in the two hares were identical, as based on blast analysis performed for the VP60 sequences and showed 98.86% nucleotide identity and 100% amino acid identity with strain EBHSV/GER-BY/EI97.L03477/2019, isolated in Germany in 2019. Phylogenetic analysis places our virus in group B, which includes strains that emerged after the mid-1980s. This study supports previous reports of EBHS in L. corsicanus and further expands the knowledge of the pathological and virological characteristics of the etiological agent. The ability of EBHSV to cause a fatal disease in the Italian hare represents a serious threat to the conservation of this vulnerable species, especially in populations kept in enclosed protected areas.
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- 2023
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36. Ketoprofen, lysine and gabapentin co-crystal magnifies synergistic efficacy and tolerability of the constituent drugs: Pre-clinical evidences towards an innovative therapeutic approach for neuroinflammatory pain
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Aramini, Andrea, Bianchini, Gianluca, Lillini, Samuele, Tomassetti, Mara, Pacchiarotti, Niccolò, Canestrari, Daniele, Cocchiaro, Pasquale, Novelli, Rubina, Dragani, Maria Concetta, Palmerio, Ferdinando, Mattioli, Simone, Bordignon, Simone, d’Angelo, Michele, Castelli, Vanessa, d’Egidio, Francesco, Maione, Sabatino, Luongo, Livio, Boccella, Serena, Cimini, Annamaria, Brandolini, Laura, Chierotti, Michele Remo, and Allegretti, Marcello
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- 2023
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37. Pathwise asymptotics for Volterra type stochastic volatility models
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Cellupica, M. and Pacchiarotti, B.
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Mathematics - Probability ,60F10, 60G15, 60G22 - Abstract
We study stochastic volatility models in which the volatility process is a positive continuous function of a continuous Volterra stochastic process. We state some pathwise large deviation principles for the scaled log-price., Comment: 32 pagg
- Published
- 2019
38. Large deviations for conditionally Gaussian processes: estimates of level crossing probability
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Pacchiarotti, Barbara and Pigliacelli, Alessandro
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Mathematics - Probability - Abstract
The problem of (pathwise) large deviations for conditionally continuous Gaussian processes is investigated. The theory of large deviations for Gaussian processes is extended to the wider class of random processes -- the conditionally Gaussian processes. The estimates of level crossing probability for such processes are given as an application., Comment: Published at https://doi.org/10.15559/18-VMSTA119 in the Modern Stochastics: Theory and Applications (https://vmsta.org/) by VTeX (http://www.vtex.lt/)
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- 2019
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39. The impact of the Catalonia Suicide Risk Code (CSRC) in a tertiary hospital: Reduction in hospitalizations and emergency room visits for any reason but not for suicide attempt
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Gomes-da-Costa, Susana, Solé, Eva, Williams, Evelyn, Giménez, Anna, Garriga, Marina, Pacchiarotti, Isabella, Vázquez, Mireia, Cavero, Myriam, Blanch, Jordi, Pérez, Víctor, Palao, Diego, Vieta, Eduard, and Verdolini, Norma
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- 2023
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40. Asymptotic results for linear combinations of spacings generated by i.i.d. exponential random variables
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Calì, Camilla, Longobardi, Maria, Macci, Claudio, and Pacchiarotti, Barbara
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- 2022
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41. Ketoprofen, lysine and gabapentin co-crystal magnifies synergistic efficacy and tolerability of the constituent drugs: Pre-clinical evidences towards an innovative therapeutic approach for neuroinflammatory pain
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Andrea Aramini, Gianluca Bianchini, Samuele Lillini, Mara Tomassetti, Niccolò Pacchiarotti, Daniele Canestrari, Pasquale Cocchiaro, Rubina Novelli, Maria Concetta Dragani, Ferdinando Palmerio, Simone Mattioli, Simone Bordignon, Michele d’Angelo, Vanessa Castelli, Francesco d’Egidio, Sabatino Maione, Livio Luongo, Serena Boccella, Annamaria Cimini, Laura Brandolini, Michele Remo Chierotti, and Marcello Allegretti
- Subjects
Drug-drug co-crystal ,Ketoprofen lysine salt ,Gabapentin ,Chronic pain ,Neuropathic pain ,Neuroinflammation ,Therapeutics. Pharmacology ,RM1-950 - Abstract
Chronic pain is an enormous public health concern, and its treatment is still an unmet medical need. Starting from data highlighting the promising effects of some nonsteroidal anti-inflammatory drugs in combination with gabapentin in pain treatment, we sought to combine ketoprofen lysine salt (KLS) and gabapentin to obtain an effective multimodal therapeutic approach for chronic pain. Using relevant in vitro models, we first demonstrated that KLS and gabapentin have supra-additive effects in modulating key pathways in neuropathic pain and gastric mucosal damage. To leverage these supra-additive effects, we then chemically combined the two drugs via co-crystallization to yield a new compound, a ternary drug-drug co-crystal of ketoprofen, lysine and gabapentin (KLS-GABA co-crystal). Physicochemical, biodistribution and pharmacokinetic studies showed that within the co-crystal, ketoprofen reaches an increased gastrointestinal solubility and permeability, as well as a higher systemic exposure in vivo compared to KLS alone or in combination with gabapentin, while both the constituent drugs have increased central nervous system permeation. These unique characteristics led to striking, synergistic anti-nociceptive and anti-inflammatory effects of KLS-GABA co-crystal, as well as significantly reduced spinal neuroinflammation, in translational inflammatory and neuropathic pain rat models, suggesting that the synergistic therapeutic effects of the constituent drugs are further boosted by the co-crystallization. Notably, while strengthening the therapeutic effects of ketoprofen, KLS-GABA co-crystal showed remarkable gastrointestinal tolerability in both inflammatory and chronic neuropathic pain rat models. In conclusion, these results allow us to propose KLS-GABA co-crystal as a new drug candidate with high potential clinical benefit–to–risk ratio for chronic pain treatment.
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- 2023
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42. Exploring Digital Biomarkers of Illness Activity in Mood Episodes: Hypotheses Generating and Model Development Study
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Gerard Anmella, Filippo Corponi, Bryan M Li, Ariadna Mas, Miriam Sanabra, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antoni Benabarre, Anna Giménez-Palomo, Marina Garriga, Isabel Agasi, Anna Bastidas, Myriam Cavero, Tabatha Fernández-Plaza, Néstor Arbelo, Miquel Bioque, Clemente García-Rizo, Norma Verdolini, Santiago Madero, Andrea Murru, Silvia Amoretti, Anabel Martínez-Aran, Victoria Ruiz, Giovanna Fico, Michele De Prisco, Vincenzo Oliva, Aleix Solanes, Joaquim Radua, Ludovic Samalin, Allan H Young, Eduard Vieta, Antonio Vergari, and Diego Hidalgo-Mazzei
- Subjects
Information technology ,T58.5-58.64 ,Public aspects of medicine ,RA1-1270 - Abstract
BackgroundDepressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity, alongside physiological alterations wearables can capture. ObjectiveFirstly, we explored whether physiological wearable data could predict (aim 1) the severity of an acute affective episode at the intra-individual level and (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to prior predictions, generalization across patients, and associations between affective symptoms and physiological data. MethodsWe conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded using a research-grade wearable (Empatica E4) across 3 consecutive time points (acute, response, and remission of episode). Euthymic patients and healthy controls were recorded during a single session (approximately 48 h). Manic and depressive symptoms were assessed using standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), skin temperature, blood volume pulse, heart rate (HR), and electrodermal activity (EDA). Invalid physiological data were removed using a rule-based filter, and channels were time aligned at 1-second time units and segmented at window lengths of 32 seconds, as best-performing parameters. We developed deep learning predictive models, assessed the channels’ individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales’ items normalized mutual information (NMI). We present a novel, fully automated method for the preprocessing and analysis of physiological data from a research-grade wearable device, including a viable supervised learning pipeline for time-series analyses. ResultsOverall, 35 sessions (1512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 healthy controls (mean age 39.7, SD 12.6 years; 6/19, 32% female) were analyzed. The severity of mood episodes was predicted with moderate (62%-85%) accuracies (aim 1), and their polarity with moderate (70%) accuracy (aim 2). The most relevant features for the former tasks were ACC, EDA, and HR. There was a fair agreement in feature importance across classification tasks (Kendall W=0.383). Generalization of the former models on unseen patients was of overall low accuracy, except for the intra-individual models. ACC was associated with “increased motor activity” (NMI>0.55), “insomnia” (NMI=0.6), and “motor inhibition” (NMI=0.75). EDA was associated with “aggressive behavior” (NMI=1.0) and “psychic anxiety” (NMI=0.52). ConclusionsPhysiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression, respectively. These findings represent a promising pathway toward personalized psychiatry, in which physiological wearable data could allow the early identification and intervention of mood episodes.
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- 2023
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43. Asymptotic results for compound sums in separable Banach spaces
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Macci, Claudio, primary and Pacchiarotti, Barbara, additional
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- 2024
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44. Effectiveness and safety of gonadotropins used in female infertility: a population-based study in the Lazio region, Italy
- Author
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Rosa, Alessandro Cesare, Pacchiarotti, Arianna, Addis, Antonio, Ciardulli, Andrea, Belleudi, Valeria, Davoli, Marina, and Kirchmayer, Ursula
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- 2022
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45. Avis d’experts français sur la prise en charge des femmes en âge de procréer et enceintes souffrant d’un trouble bipolaire traitées par valproate
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Samalin, L., Arnould, A., Boudieu, L., Henry, C., Haffen, E., Drapier, D., Anmella, G., Pacchiarotti, I., Vieta, E., Belzeaux, R., and Llorca, P.-M.
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- 2022
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46. 8 Neglected functions of the Bantu applicative in relation to Locations: new insights from Fwe (K402)
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Gunnink, Hilde, primary and Pacchiarotti, Sara, additional
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- 2022
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47. 1 Introduction
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Pacchiarotti, Sara, primary and Zúñiga, Fernando, additional
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- 2022
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48. Applicative Morphology: Neglected Syntactic and Non-syntactic Functions
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Sara Pacchiarotti, Fernando Zuniga, Sara Pacchiarotti, Fernando Zuniga and Sara Pacchiarotti, Fernando Zuniga, Sara Pacchiarotti, Fernando Zuniga
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- 2022
49. Bioenergetic changes and mitochondrial dysfunction in mania versus euthymia in bipolar disorder type I
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A. Giménez-Palomo, M. Guitart-Mampel, G. Garrabou, X. Alsina-Restoy, A. Meseguer, L. Colomer, G. Roqué, F. J. García-García, E. Tobías, J. Moisés, M. Valentí, E. Vieta, and I. Pacchiarotti
- Subjects
Psychiatry ,RC435-571 - Abstract
Introduction Current evidence has hypothesized the involvement of mitochondrial dysfunction during the acute episodes of BD compared to symptomatic remission. So far, no studies have compared mitochondrial and bioenergetic functions both in-vivo (respiratory parameters) and ex-vivo (cellular respiration) in different phases of the disease in the same individuals. Objectives This multidisciplinary pilot study aims at assessing bioenergetic and mitochondrial intra-individual differences between manic and euthymic states. Methods Four patients with a manic episode admitted to our acute psychiatric ward were recruited. Bioenergetic parameters were measured at admission (T0) and after symptomatic remission (T1). At admission (T0) and before discharge (T1), HAMD and YMRS total scores were obtained. For the assessment of cellular respiration, polymorphonuclear cells were obtained by a Ficoll density gradient centrifugation procedure. To determine oxygen consumption (at T0 and T1), a million of living peripheral blood mononuclear cells (PBMC) were used. High-resolution respirometry was performed at 37°C by polarographic oxygen sensors in a two-chamber Oxygraph-2k system. Specific oxygen uptakes (Routine: basal oxygen consumption; Proton Leak: oxygen consumption not coupled to ATP synthesis; and ETC: maximal capacity of the electron transport chain) rates were obtained using mitochondrial chain inhibitors and uncouplers. Oxygen consumption was normalized for protein concentration. Results are expressed as picomoles of oxygen per millilitre (pmol O2/s*μg prot). Also, a constant work rate exercise test was performed on a cycle ergometer and basal and effort respiratory variables were measured. Statistical analysis was performed with the SPSS v. 25.0 and GraphPad. Results were expressed as means and SD. Nonparametric tests (Mann–Whitney, Pearson) were used to determine differences (significant at p value
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- 2023
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50. Shaped before birth: Obstetric complications identify a more severe clinical phenotype among patients presenting a first affective or non-affective episode of psychosis
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Sagué-Vilavella, Maria, Amoretti, Silvia, Garriga, Marina, Mezquida, Gisela, Williams, Evelyn, Serra-Navarro, Maria, Forte, Maria Florencia, Varo, Cristina, Montejo, Laura, Palacios-Garran, Roberto, Madero, Santiago, Sparacino, Giulio, Anmella, Gerard, Fico, Giovanna, Giménez-Palomo, Anna, Pons-Cabrera, Maria Teresa, Salgado-Pineda, Pilar, Montoro Salvatierra, Irene, Sánchez Gistau, Vanessa, Pomarol-Clotet, Edith, Ramos-Quiroga, Josep Antoni, Undurraga, Juan, Reinares, María, Martínez-Arán, Anabel, Pacchiarotti, Isabella, Valli, Isabel, Bernardo, Miguel, Garcia-Rizo, Clemente, Vieta, Eduard, and Verdolini, Norma
- Published
- 2022
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