551 results on '"Vinci P"'
Search Results
2. Shock-driven amorphization and melt in Fe$_2$O$_3$
- Author
-
Crépisson, Céline, Amouretti, Alexis, Harmand, Marion, Sanloup, Chrystèle, Heighway, Patrick, Azadi, Sam, McGonegle, David, Campbell, Thomas, Chin, David Alexander, Smith, Ethan, Hansen, Linda, Forte, Alessandro, Gawne, Thomas, Lee, Hae Ja, Nagler, Bob, Shi, YuanFeng, Fiquet, Guillaume, Guyot, François, Makita, Mikako, Benuzzi-Mounaix, Alessandra, Vinci, Tommaso, Miyanishi, Kohei, Ozaki, Norimasa, Pikuz, Tatiana, Nakamura, Hirotaka, Sueda, Keiichi, Yabuuchi, Toshinori, Yabashi, Makina, Wark, Justin S., Polsin, Danae N., and Vinko, Sam M.
- Subjects
Condensed Matter - Materials Science ,High Energy Physics - Experiment - Abstract
We present measurements on Fe$_2$O$_3$ amorphization and melt under laser-driven shock compression up to 209(10) GPa via time-resolved in situ x-ray diffraction. At 122(3) GPa, a diffuse signal is observed indicating the presence of a non-crystalline phase. Structure factors have been extracted up to 182(6) GPa showing the presence of two well-defined peaks. A rapid change in the intensity ratio of the two peaks is identified between 145(10) and 151(10) GPa, indicative of a phase change. Present DFT+$U$ calculations of temperatures along Fe$_2$O$_3$ Hugoniot are in agreement with SESAME 7440 and indicate relatively low temperatures, below 2000 K, up to 150 GPa. The non-crystalline diffuse scattering is thus consistent with the - as yet unreported - shock amorphization of Fe$_2$O$_3$ between 122(3) and 145(10) GPa, followed by an amorphous-to-liquid transition above 151(10) GPa. Upon release, a non-crystalline phase is observed alongside crystalline $\alpha$-Fe$_2$O$_3$. The extracted structure factor and pair distribution function of this release phase resemble those reported for Fe$_2$O$_3$ melt at ambient pressure., Comment: 11 pages, 4 figures, under review
- Published
- 2024
3. Minimizing Rosenthal's Potential in Monotone Congestion Games
- Author
-
Bilò, Vittorio, Fanelli, Angelo, Gourvès, Laurent, Tsoufis, Christos, and Vinci, Cosimo
- Subjects
Computer Science - Computer Science and Game Theory - Abstract
Congestion games are attractive because they can model many concrete situations where some competing entities interact through the use of some shared resources, and also because they always admit pure Nash equilibria which correspond to the local minima of a potential function. We explore the problem of computing a state of minimum potential in this setting. Using the maximum number of resources that a player can use at a time, and the possible symmetry in the players' strategy spaces, we settle the complexity of the problem for instances having monotone (i.e., either non-decreasing or non-increasing) latency functions on their resources. The picture, delineating polynomial and NP-hard cases, is complemented with tight approximation algorithms.
- Published
- 2024
4. Laser-driven shock compression and equation of state of Fe$_2$O$_3$ up to 700 GPa
- Author
-
Amouretti, Alexis, Harmand, Marion, Albertazzi, Bruno, Boury, Antoine, Benuzzi-Mounaix, Alessandra, Chin, D. Alex, Guyot, François, Koenig, Michel, Vinci, Tommaso, and Fiquet, Guillaume
- Subjects
High Energy Physics - Experiment - Abstract
We report here the first equation of state measurements of Fe$_2$O$_3$ obtained with laser-driven shock compression. The data are in excellent agreement with previous dynamic and static compression measurements at low pressure, and extend the known Hugoniot up to 700 GPa. We observe a large volume drop of $\sim$10% at 86 GPa, which could be associated, according to static compression observations, with the iron spin transition. Our measurements also suggest a change of the Hugoniot curve between 150 and 250 GPa. Above 250 GPa and within our error bars, we do not observe significant modifications up to the maximum pressure of 700 GPa reached in our experiment., Comment: 8 pages, 3 figures, 2 tables
- Published
- 2024
5. Stochastic Multi-round Submodular Optimization with Budget
- Author
-
Auletta, Vincenzo, Ferraioli, Diodato, and Vinci, Cosimo
- Subjects
Computer Science - Data Structures and Algorithms ,Computer Science - Artificial Intelligence - Abstract
In this work we study the problem of {\em Stochastic Budgeted Multi-round Submodular Maximization} (SBMSm), in which we would like to adaptively maximize the sum over multiple rounds of the value of a monotone and submodular objective function defined on a subset of items, subject to the fact that the values of this function depend on the realization of stochastic events and the number of items that we can select over all rounds is limited by a given budget. This problem extends, and generalizes to multiple round settings, well-studied problems such as (adaptive) influence maximization and stochastic probing. We first show that, if the number of items and stochastic events is somehow bounded, there is a polynomial time dynamic programming algorithm for SBMSm. Then, we provide a simple greedy approximation algorithm for SBMSm, that first non-adaptively allocates the budget to be spent at each round, and then greedily and adaptively maximizes the objective function by using the budget assigned at each round. Such algorithm guarantees a $(1-1/e-\epsilon)$-approximation to the optimal adaptive value. Finally, by introducing a metric called {\em budget-adaptivity gap}, we measure how much an optimal policy for SBMSm, that is adaptive in both the budget allocation and item selection, is better than an optimal partially adaptive policy that, as in our greedy algorithm, determined the budget allocation in advance. We show a tight bound of $e/(e-1)$ on the budget-adaptivity gap, and this result implies that our greedy algorithm guarantees the best approximation among all partially adaptive policies.
- Published
- 2024
6. Escape time in bistable neuronal populations driven by colored synaptic noise
- Author
-
Vinci, Gianni Valerio and Mattia, Maurizio
- Subjects
Quantitative Biology - Neurons and Cognition - Abstract
Local networks of neurons are nonlinear systems driven by synaptic currents elicited by its own spiking activity and the input received from other brain areas. Synaptic currents are well approximated by correlated Gaussian noise. Besides, the population dynamics of neuronal networks is often found to be multistable, allowing the noise source to induce state transitions. State changes in neuronal systems underlies the way information is encoded and transformed. The characterization of the escape time from metastable states is then a cornerstone to understand how information is processed in the brain. The effects of correlated input forcing bistable systems have been studied for over half a century, nonetheless most results are perturbative or valid only when a separation of time scales is present. Here, we present a novel and exact result holding when the correlation time of the noise source is identical to that of the neural population, hence solving in a very general setting the mean escape time problem.
- Published
- 2024
7. Covariance matrix completion via auxiliary information
- Author
-
Steneman, Joseph and Vinci, Giuseppe
- Subjects
Statistics - Methodology ,62H12 ,G.3 - Abstract
Covariance matrix estimation is an important task in the analysis of multivariate data in disparate scientific fields, including neuroscience, genomics, and astronomy. However, modern scientific data are often incomplete due to factors beyond the control of researchers, and data missingness may prohibit the use of traditional covariance estimation methods. Some existing methods address this problem by completing the data matrix, or by filling the missing entries of an incomplete sample covariance matrix by assuming a low-rank structure. We propose a novel approach that exploits auxiliary variables to complete covariance matrix estimates. An example of auxiliary variable is the distance between neurons, which is usually inversely related to the strength of neuronal correlation. Our method extracts auxiliary information via regression, and involves a single tuning parameter that can be selected empirically. We compare our method with other matrix completion approaches via simulations, and apply it to the analysis of large-scale neuroscience data., Comment: 16 pages, 6 figures
- Published
- 2024
8. Neuronal functional connectivity graph estimation with the R package neurofuncon
- Author
-
Beede, Lauren Miako and Vinci, Giuseppe
- Subjects
Quantitative Biology - Neurons and Cognition ,Statistics - Computation - Abstract
Researchers continue exploring neurons' intricate patterns of activity in the cerebral visual cortex in response to visual stimuli. The way neurons communicate and optimize their interactions with each other under different experimental conditions remains a topic of active investigation. Probabilistic Graphical Models are invaluable tools in neuroscience research, as they let us identify the functional connections, or conditional statistical dependencies, between neurons. Graphical models represent these connections as a graph, where nodes represent neurons and edges indicate the presence of functional connections between them. We developed the R package neurofuncon for the computation and visualization of functional connectivity graphs from large-scale data based on the Graphical lasso. We illustrate the use of this package with publicly available two-photon calcium microscopy imaging data from approximately 10000 neurons in a 1mm cubic section of a mouse visual cortex., Comment: 7 pages, 5 figures
- Published
- 2024
9. Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge Architecture
- Author
-
Mastroianni, Carlo, Plastina, Francesco, Settino, Jacopo, and Vinci, Andrea
- Subjects
Quantum Physics ,Condensed Matter - Disordered Systems and Neural Networks ,Condensed Matter - Other Condensed Matter - Abstract
Modern Cloud/Edge architectures need to orchestrate multiple layers of heterogeneous computing nodes, including pervasive sensors/actuators, distributed Edge/Fog nodes, centralized data centers and quantum devices. The optimal assignment and scheduling of computation on the different nodes is a very difficult problem, with NP-hard complexity. In this paper, we explore the possibility of solving this problem with Variational Quantum Algorithms, which can become a viable alternative to classical algorithms in the near future. In particular, we compare the performances, in terms of success probability, of two algorithms, i.e., Quantum Approximate Optimization Algorithm (QAOA) and Variational Quantum Eigensolver (VQE). The simulation experiments, performed for a set of simple problems, %CM230124 that involve a Cloud and two Edge nodes, show that the VQE algorithm ensures better performances when it is equipped with appropriate circuit \textit{ansatzes} that are able to restrict the search space. Moreover, experiments executed on real quantum hardware show that the execution time, when increasing the size of the problem, grows much more slowly than the trend obtained with classical computation, which is known to be exponential., Comment: 14 pages, 13 figures
- Published
- 2024
- Full Text
- View/download PDF
10. Linked factor analysis
- Author
-
Vinci, Giuseppe
- Subjects
Statistics - Methodology - Abstract
Factor models are widely used in the analysis of high-dimensional data in several fields of research. Estimating a factor model, in particular its covariance matrix, from partially observed data vectors is very challenging. In this work, we show that when the data are structurally incomplete, the factor model likelihood function can be decomposed into the product of the likelihood functions of multiple partial factor models relative to different subsets of data. If these multiple partial factor models are linked together by common parameters, then we can obtain complete maximum likelihood estimates of the factor model parameters and thereby the full covariance matrix. We call this framework Linked Factor Analysis (LINFA). LINFA can be used for covariance matrix completion, dimension reduction, data completion, and graphical dependence structure recovery. We propose an efficient Expectation-Maximization algorithm for maximum likelihood estimation, accelerated by a novel group vertex tessellation (GVT) algorithm which identifies a minimal partition of the vertex set to implement an efficient optimization in the maximization steps. We illustrate our approach in an extensive simulation study and in the analysis of calcium imaging data collected from mouse visual cortex., Comment: 21 page, 9 figures
- Published
- 2024
11. Results of a Prospective Randomized Multicenter Study Comparing Indocyanine Green (ICG) Fluorescence Combined with a Standard Tracer Versus ICG Alone for Sentinel Lymph Node Biopsy in Early Breast Cancer: The INFLUENCE Trial
- Author
-
Pitsinis, Vassilis, Kanitkar, Rahul, Vinci, Alessio, Choong, Wen Ling, and Benson, John
- Published
- 2024
- Full Text
- View/download PDF
12. A holistic approach to environmentally sustainable computing
- Author
-
Pazienza, Andrea, Baselli, Giovanni, Vinci, Daniele Carlo, and Trussoni, Maria Vittoria
- Published
- 2024
- Full Text
- View/download PDF
13. Secondary Breast Augmentation: The Six Winning Moves
- Author
-
Klinger, Marco, Berrino, Piero, Bandi, Valeria, Catania, Barbara, Veronesi, Alessandra, Fondrini, Riccardo, Agnelli, Benedetta, Berrino, Valeria, Klinger, Francesco, and Vinci, Valeriano
- Published
- 2024
- Full Text
- View/download PDF
14. Psychological dimensions associated with youth engagement in climate change issues: a person-centered approach
- Author
-
Geraci, Alessandro, Giordano, Giulia, Cucinella, Nicla, Cannavò, Marco, Cavarretta, Maria Valentina, Alesi, Marianna, Caci, Barbara, D’Amico, Antonella, Gentile, Ambra, Iannello, Nicolò Maria, Ingoglia, Sonia, Inguglia, Cristiano, Liga, Francesca, Manna, Giovanna, Monzani, Dario, Polizzi, Concetta, De Grazia, Luciana, Vinci, Ignazio Marcello, and Papa, Federica
- Published
- 2024
- Full Text
- View/download PDF
15. Optimizing Postoperative Care in Rhinoplasty and Septoplasty: A Review of the Role of Nasal Packing and Alternatives in Complication Management
- Author
-
Caimi, Edoardo, Balza, Arianna, Vaccari, Stefano, Bandi, Valeria, Klinger, Francesco, and Vinci, Valeriano
- Published
- 2024
- Full Text
- View/download PDF
16. Environmental life cycle assessment of rice production in northern Italy: a case study from Vercelli
- Author
-
Giuliana, Vinci, Lucia, Maddaloni, Marco, Ruggeri, and Simone, Vieri
- Published
- 2024
- Full Text
- View/download PDF
17. Assessment of hydroxychloroquine blood levels in Sjögren’s disease patients: drug adherence and clinical associations
- Author
-
Pasoto, Sandra Gofinet, Villamarín, Lorena Elizabeth Betancourt, de Vinci Kanda Kupa, Léonard, Deveza, Giordano Bruno Henriques, Ribeiro, Carolina Torres, Emi Aikawa, Nádia, Leon, Elaine Pires, de Oliveira Martins, Victor Adriano, Silva, Clovis Artur, and Bonfa, Eloisa
- Published
- 2024
- Full Text
- View/download PDF
18. Forensic Science and How Statistics Can Help It: Evidence, Hypothesis Testing, and Graphical Models
- Author
-
Xu, Xiangyu and Vinci, Giuseppe
- Subjects
Statistics - Applications ,62P25 - Abstract
The persistent issue of wrongful convictions in the United States emphasizes the need for scrutiny and improvement of the criminal justice system. While statistical methods for the evaluation of forensic evidence, including glass, fingerprints, and DNA, have significantly contributed to solving intricate crimes, there is a notable lack of national-level standards to ensure the appropriate application of statistics in forensic investigations. We discuss the obstacles in the application of statistics in court, and emphasize the importance of making statistical interpretation accessible to non-statisticians, especially those who make decisions about potentially innocent individuals. We investigate the use and misuse of statistical methods in crime investigations, in particular the likelihood ratio approach. We further describe the use of graphical models, where hypotheses and evidence can be represented as nodes connected by arrows signifying association or causality. We emphasize the advantages of special graph structures, such as object-oriented Bayesian networks and chain event graphs, which allow for the concurrent examination of evidence of various nature., Comment: 20 pages, 8 figures
- Published
- 2023
19. Assessing Quantum Computing Performance for Energy Optimization in a Prosumer Community
- Author
-
Mastroianni, Carlo, Plastina, Francesco, Scarcello, Luigi, Settino, Jacopo, and Vinci, Andrea
- Subjects
Quantum Physics - Abstract
The efficient management of energy communities relies on the solution of the "prosumer problem", i.e., the problem of scheduling the household loads on the basis of the user needs, the electricity prices, and the availability of local renewable energy, with the aim of reducing costs and energy waste. Quantum computers can offer a significant breakthrough in treating this problem thanks to the intrinsic parallel nature of quantum operations. The most promising approach is to devise variational hybrid algorithms, in which quantum computation is driven by parameters that are optimized classically, in a cycle that aims at finding the best solution with a significant speed-up with respect to classical approaches. This paper provides a reformulation of the prosumer problem, allowing to address it with a hybrid quantum algorithm, namely, Quantum Approximate Optimization Algorithm (QAOA), and with a recent variant, the Recursive QAOA. We report on an extensive set of experiments, on simulators and real quantum hardware, for different problem sizes. Results are encouraging in that Recursive QAOA is able, for problems involving up to 10 qubits, to provide optimal and admissible solutions with good probabilities, while the computation time is nearly independent of the system size, Comment: 14 pages, 13 figures. IEEE Transactions on Smart Grid (2023)
- Published
- 2023
- Full Text
- View/download PDF
20. ezBIDS: Guided standardization of neuroimaging data interoperable with major data archives and platforms
- Author
-
Levitas, Daniel, Hayashi, Soichi, Vinci-Booher, Sophia, Heinsfeld, Anibal, Bhatia, Dheeraj, Lee, Nicholas, Galassi, Anthony, Niso, Guiomar, and Pestilli, Franco
- Subjects
Computer Science - Databases - Abstract
Data standardization has become one of the leading methods neuroimaging researchers rely on for data sharing and reproducibility. Data standardization promotes a common framework through which researchers can utilize others' data. Yet, as of today, formatting datasets that adhere to community best practices requires technical expertise involving coding and considerable knowledge of file formats and standards. We describe ezBIDS, a tool for converting neuroimaging data and associated metadata to the Brain Imaging Data Structure (BIDS) standard. ezBIDS provides four unique features: (1) No installation or programming requirements. (2) Handling of both imaging and task events data and metadata. (3) Automated inference and guidance for adherence to BIDS. (4) Multiple data management options: download BIDS data to local system, or transfer to OpenNeuro.org or brainlife.io. In sum, ezBIDS requires neither coding proficiency nor knowledge of BIDS and is the first BIDS tool to offer guided standardization, support for task events conversion, and interoperability with OpenNeuro and brainlife.io.
- Published
- 2023
- Full Text
- View/download PDF
21. Spiral-Elliptical automated galaxy morphology classification from telescope images
- Author
-
Baumstark, Matthew J. and Vinci, Giuseppe
- Subjects
Astrophysics - Instrumentation and Methods for Astrophysics ,Astrophysics - Astrophysics of Galaxies ,Computer Science - Machine Learning ,Statistics - Applications ,85A35, 62P35 ,G.3 - Abstract
The classification of galaxy morphologies is an important step in the investigation of theories of hierarchical structure formation. While human expert visual classification remains quite effective and accurate, it cannot keep up with the massive influx of data from emerging sky surveys. A variety of approaches have been proposed to classify large numbers of galaxies; these approaches include crowdsourced visual classification, and automated and computational methods, such as machine learning methods based on designed morphology statistics and deep learning. In this work, we develop two novel galaxy morphology statistics, descent average and descent variance, which can be efficiently extracted from telescope galaxy images. We further propose simplified versions of the existing image statistics concentration, asymmetry, and clumpiness, which have been widely used in the literature of galaxy morphologies. We utilize the galaxy image data from the Sloan Digital Sky Survey to demonstrate the effective performance of our proposed image statistics at accurately detecting spiral and elliptical galaxies when used as features of a random forest classifier., Comment: 11 pages, 6 figures
- Published
- 2023
22. Towards social life cycle assessment of food delivery: findings from the Italian case study
- Author
-
Ruggeri, Marco, Zaki, Mary Giò, and Vinci, Giuliana
- Published
- 2024
- Full Text
- View/download PDF
23. brainlife.io: a decentralized and open-source cloud platform to support neuroscience research
- Author
-
Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Avesani, Paolo, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Chaumon, Maximilien, George, Nathalie, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj, Aydogan, Dogu Baran, Yeh, Fang-Cheng F., Delogu, Franco, Guaje, Javier, Veraart, Jelle, Fischer, Jeremy, Faskowitz, Joshua, Fabrega, Ricardo, Hunt, David, McKee, Shawn, Brown, Shawn T., Heyman, Stephanie, Iacovella, Vittorio, Mejia, Amanda F., Marinazzo, Daniele, Craddock, R. Cameron, Olivetti, Emanuale, Hanson, Jamie L., Garyfallidis, Eleftherios, Stanzione, Dan, Carson, James, Henschel, Robert, Hancock, David Y., Stewart, Craig A., Schnyer, David, Eke, Damian O., Poldrack, Russell A., Bollmann, Steffen, Stewart, Ashley, Bridge, Holly, Sani, Ilaria, Freiwald, Winrich A., Puce, Aina, Port, Nicholas L., and Pestilli, Franco
- Published
- 2024
- Full Text
- View/download PDF
24. The Role of Migration for Workplace Safety in Italy
- Author
-
Aldieri, L., Nese, A., and Vinci, C. P.
- Published
- 2024
- Full Text
- View/download PDF
25. Sustainability performance evaluation in the organic durum wheat production: evidence from Italy
- Author
-
Vinci, Giuliana, Prencipe, Sabrina A., Ruggeri, Marco, Gobbi, Laura, and Arcese, Gabriella
- Published
- 2024
- Full Text
- View/download PDF
26. Rejuvenation in Men Facial Aging: A Combined Approach
- Author
-
Klinger, Marco, Fondrini, Riccardo, Bandi, Valeria, Veronesi, Alessandra, Catania, Barbara, Di Giuli, Riccardo, Vaccari, Stefano, Bucci, Flavio, Klinger, Francesco, and Vinci, Valeriano
- Published
- 2024
- Full Text
- View/download PDF
27. T1 relaxation: Chemo-physical fundamentals of magnetic resonance imaging and clinical applications
- Author
-
Michele Gaeta, Karol Galletta, Marco Cavallaro, Enricomaria Mormina, Maria Teresa Cannizzaro, Ludovica Rosa Maria Lanzafame, Tommaso D’Angelo, Alfredo Blandino, Sergio Lucio Vinci, and Francesca Granata
- Subjects
MRI ,T1 relaxation time ,Magnetism ,Chemical shift imaging ,Tumbling ,Medical physics. Medical radiology. Nuclear medicine ,R895-920 - Abstract
Abstract A knowledge of the complex phenomena that regulate T1 signal on Magnetic Resonance Imaging is essential in clinical practice for a more effective characterization of pathological processes. The authors review the physical basis of T1 Relaxation Time and the fundamental aspects of physics and chemistry that can influence this parameter. The main substances (water, fat, macromolecules, methemoglobin, melanin, Gadolinium, calcium) that influence T1 and the different MRI acquisition techniques that can be applied to enhance their presence in diagnostic images are then evaluated. An extensive case illustration of the different phenomena and techniques in the areas of CNS, abdomino-pelvic, and osteoarticular pathology is also proposed. Critical relevance statement T1 relaxation time is strongly influenced by numerous factors related to tissue characteristics and the presence in the context of the lesions of some specific substances. An examination of these phenomena with extensive MRI exemplification is reported. Key Points The purpose of the paper is to illustrate the chemical-physical basis of T1 Relaxation Time. MRI methods in accordance with the various clinical indications are listed. Several examples of clinical application in abdominopelvic and CNS pathology are reported. Graphical Abstract
- Published
- 2024
- Full Text
- View/download PDF
28. Life cycle assessment of manual toothbrush materials
- Author
-
Marta Mazur, Marco Ruggeri, Livia Ottolenghi, Andrea Scrascia, Laura Gobbi, and Giuliana Vinci
- Subjects
Polymers ,Health services research ,Dental public health ,Dental hygiene ,Consumer healthcare products ,Environmental sciences ,GE1-350 - Abstract
Abstract Background A manual toothbrush is an indispensable tool for promoting and maintaining oral health worldwide but given the non-biodegradable and non-recyclable thermoplastic materials from which it is made, it cannot be considered free of threats to the environment. Therefore, also in light of the World Dental Federation's goals to implement and initiate policies for sustainable dentistry, this study evaluates the sustainability of two materials most used for manual toothbrush bristles, namely nylon, and silicone. Objectives The objective is to investigate the optimal solution to reduce the environmental impact of toothbrushes, and how the environmental impact would change if only the brush head was changed instead of the entire toothbrush. Methods Life Cycle Assessment and Carbon Footprint were used. Four manual toothbrushes with nylon bristles, and a handle in polypropylene with/without silicone parts (N1, N2, N3, N4) and two manual toothbrushes, with silicone bristles, but one with polypropylene handle only (Si1), the other with polypropylene handle and silicone parts (Si2) were evaluated. Results A toothbrush with silicone bristles is more sustainable than one with nylon bristles in all 18 impact categories, with average values of − 14%. In addition, eliminating only the brush head instead of the entire toothbrush could result in savings of 4.69 × 10‒3 kg CO2 eq per toothbrush. Therefore, based on the results of this study and to meet Dentistry's need to reduce its environmental impact, the ideal toothbrush should be lightweight, with less superfluous material, and with less impactful materials such as silicone instead of nylon. Conclusions The concluding indications for improving the sustainability of toothbrushes are therefore: (i) eliminate the amount of superfluous material; (ii) develop lighter models; and (iii) develop models in which only the brush head is replaced rather than the entire toothbrush.
- Published
- 2024
- Full Text
- View/download PDF
29. Biostimulation of humic acids on Lepidium sativum L. regulated by their content of stable phenolic O⋅ radicals
- Author
-
Antonella Vitti, Leonardo Coviello, Maria Nuzzaci, Giovanni Vinci, Yiannis Deligiannakis, Evangelos Giannakopoulos, Domenico Ronga, Alessandro Piccolo, Antonio Scopa, and Marios Drosos
- Subjects
Cress seed germination ,Root growth ,Supramolecular structure ,Soil humic acid ,Lignite humic acid ,HALP ,Agriculture - Abstract
Abstract Background Humic acid affects plant growth. Its source and structure may play a central role to its functionality. The relationship between humic acid and plant bioactivity is still unclear. This study investigated the biostimulation effects of two natural humic acids derived from soil (SHA) and lignite (LHA) on Lepidium sativum in comparison to a synthetic humic acid model (HALP) with known structure. Results All humic acids positively affected cress seed germination and root elongation. Greater root hairs density and dry matter, compared to control, were observed using concentration of 5 mg L−1 for HALP, 50 mg L−1 for LHA, and 100 mg L−1 for SHA. The germination index was the largest (698% more effective than control) with 50 mg L−1 of SHA, while it was 528% for LHA, and 493% for HALP at 5 mg L−1. SHA contained the lowest aromatic and phenolic C content, the largest pK2 value of 9.0 (7.7 for LHA and 7.6 for HALP), the least ratio between the aromaticity index and lignin ratio (ARM/LigR) of 0.15 (0.66 for LHA and 129.92 for HALP), and at pH 6.3 the lowest amount of free radicals with a value of 0.567 × 1017 spin g−1 (1.670 × 1017 and 1.780 × 1017 spin g−1 for LHA and HALP, respectively), with the greatest g value of 2.0039 (2.0035 for LHA and 2.0037 for HALP). Conclusions The overall chemical structure of humic acids exerted a biostimulation of cress plantlets. The level of the intrinsic stable free radicals identified by EPR in the humic acids resulted well correlated to the ARM/LigR ratio calculated by NMR. Our results suggested that HA biostimulation effect is related to its applied concentration, which is limited by its free radical content. The modulation of the humic supramolecular structure by ROS and organic acids in root exudates can determine the release of bioactive humic molecules. When the content of the intrinsic humic free radicals is high, possible molecular coupling of the bioactive humic molecules may hinder their biostimulation activity. In such cases, a low humic acid concentration appears to be required to achieve the optimum biostimulation effects. Graphical Abstract
- Published
- 2024
- Full Text
- View/download PDF
30. A de novo ARIH2 gene mutation was detected in a patient with autism spectrum disorders and intellectual disability
- Author
-
Mirella Vinci, Simone Treccarichi, Rosanna Galati Rando, Antonino Musumeci, Valeria Todaro, Concetta Federico, Salvatore Saccone, Maurizio Elia, and Francesco Calì
- Subjects
Ubiquitination ,Whole exome sequencing ,Autism spectrum disorder ,E3 ubiquitin-protein ligase ,Splicing region ,Autosomal dominant inheritance model ,Medicine ,Science - Abstract
Abstract E3 ubiquitin protein ligase encoded by ARIH2 gene catalyses the ubiquitination of target proteins and plays a crucial role in posttranslational modifications across various cellular processes. As prior documented, mutations in genes involved in the ubiquitination process are often associated with autism spectrum disorder (ASD) and/or intellectual disability (ID). In the current study, a de novo heterozygous mutation was identified in the splicing intronic region adjacent to the last exon of the ARIH2 gene using whole exome sequencing (WES). We hypothesize that this mutation, found in an ASD/ID patient, disrupts the protein Ariadne domain which is involved in the autoinhibition of ARIH2 enzyme. Predictive analyses elucidated the implications of the novel mutation in the splicing process and confirmed its autosomal dominant inheritance model. Nevertheless, we cannot exclude the possibility that other genetic factors, undetectable by WES, such as mutations in non-coding regions and polygenic risk in inter-allelic complementation, may contribute to the patient's phenotype. This work aims to suggest potential relationship between the detected mutation in ARIH2 gene and both ASD and ID, even though functional studies combined with new sequencing approaches will be necessary to validate this hypothesis.
- Published
- 2024
- Full Text
- View/download PDF
31. brainlife.io: A decentralized and open source cloud platform to support neuroscience research
- Author
-
Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj, Aydogan, Dogu Baran, Yeh, Fang-Cheng F., Delogu, Franco, Guaje, Javier, Veraart, Jelle, Bollman, Steffen, Stewart, Ashley, Fischer, Jeremy, Faskowitz, Joshua, Chaumon, Maximilien, Fabrega, Ricardo, Hunt, David, McKee, Shawn, Brown, Shawn T., Heyman, Stephanie, Iacovella, Vittorio, Mejia, Amanda F., Marinazzo, Daniele, Craddock, R. Cameron, Olivetti, Emanuele, Hanson, Jamie L., Avesani, Paolo, Garyfallidis, Eleftherios, Stanzione, Dan, Carson, James, Henschel, Robert, Hancock, David Y., Stewart, Craig A., Schnyer, David, Eke, Damian O., Poldrack, Russell A., George, Nathalie, Bridge, Holly, Sani, Ilaria, Freiwald, Winrich A., Puce, Aina, Port, Nicholas L., and Pestilli, Franco
- Subjects
Computer Science - Distributed, Parallel, and Cluster Computing ,Quantitative Biology - Neurons and Cognition ,Quantitative Biology - Quantitative Methods - Abstract
Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR (Findable, Accessible, Interoperabile, and Reusable) data analysis to portions of the worldwide research community. brainlife.io was developed to reduce these burdens and democratize modern neuroscience research across institutions and career levels. Using community software and hardware infrastructure, the platform provides open-source data standardization, management, visualization, and processing and simplifies the data pipeline. brainlife.io automatically tracks the provenance history of thousands of data objects, supporting simplicity, efficiency, and transparency in neuroscience research. Here brainlife.io's technology and data services are described and evaluated for validity, reliability, reproducibility, replicability, and scientific utility. Using data from 4 modalities and 3,200 participants, we demonstrate that brainlife.io's services produce outputs that adhere to best practices in modern neuroscience research.
- Published
- 2023
- Full Text
- View/download PDF
32. The Rise of Rationality in Blockchain Dynamics
- Author
-
Di Antonio, Gabriele, Vinci, Gianni Valerio, Pietronero, Luciano, and Javarone, Marco Alberto
- Subjects
Physics - Physics and Society - Abstract
Taking informed decisions, namely acting rationally, is an individual attitude of paramount relevance in nature and human societies. In this work, we study how rationality spreads in a community. To this end, through an agent-based model, we analyse the dynamics of a population whose individuals, endowed with a rational attitude controlled by a numerical parameter, play a simple game. The latter consists of multiple strategies, each associated with a given reward. The proposed model is then used as a benchmark for studying the behaviour of Bitcoin users, inferred by analysing transactions recorded in the Blockchain. Remarkably, a population undergoing a sharp transition from irrational to rational attitudes shows a behavioural pattern similar to that of Bitcoin users, whose rationality showed up as soon as their cryptocurrency became worth just a few cents (USD). To conclude, a behavioural analysis that relies on an entropy measure combined with a simple agent-based model allows us to detect the rise of rationality across a community. Although further investigations are essential to corroborate our results, we deem the proposed approach could also get used for studying other social phenomena and behaviours., Comment: 10 pages, 5 figures
- Published
- 2023
33. #BrazilianButtLift: The Reel Problem Regarding Gluteal Augmentation Surgery
- Author
-
Caimi, Edoardo, Pellicanò, Francesca, Choueiri, Jad El, Laurelli, Francesco, Vaccari, Stefano, and Vinci, Valeriano
- Published
- 2024
- Full Text
- View/download PDF
34. Evaluation der Rolle einer Advanced Practice Dietitian auf der Intensivstation
- Author
-
Vinci, Gioia and Stocker, Reto
- Published
- 2024
- Full Text
- View/download PDF
35. Point-of-care brain ultrasound and transcranial doppler or color-coded doppler in critically ill neonates and children
- Author
-
Vinci, Francesco, Tiseo, Marco, Colosimo, Denise, Calandrino, Andrea, Ramenghi, Luca Antonio, and Biasucci, Daniele Guerino
- Published
- 2024
- Full Text
- View/download PDF
36. Food security assessment in the light of sustainable development goals: a post-Paris Agreement era
- Author
-
Ghufran, Muhammad, Aldieri, Luigi, Pyka, Andreas, Ali, Sumran, Bimonte, Giovanna, Senatore, Luigi, and Vinci, Concetto Paolo
- Published
- 2024
- Full Text
- View/download PDF
37. Anomaly Detection in Aeronautics Data with Quantum-compatible Discrete Deep Generative Model
- Author
-
Templin, Thomas, Memarzadeh, Milad, Vinci, Walter, Lott, P. Aaron, Asanjan, Ata Akbari, Armenakas, Anthony Alexiades, and Rieffel, Eleanor
- Subjects
Computer Science - Machine Learning ,I.2.6 ,I.5.1 ,J.2 - Abstract
Deep generative learning cannot only be used for generating new data with statistical characteristics derived from input data but also for anomaly detection, by separating nominal and anomalous instances based on their reconstruction quality. In this paper, we explore the performance of three unsupervised deep generative models -- variational autoencoders (VAEs) with Gaussian, Bernoulli, and Boltzmann priors -- in detecting anomalies in flight-operations data of commercial flights consisting of multivariate time series. We devised two VAE models with discrete latent variables (DVAEs), one with a factorized Bernoulli prior and one with a restricted Boltzmann machine (RBM) as prior, because of the demand for discrete-variable models in machine-learning applications and because the integration of quantum devices based on two-level quantum systems requires such models. The DVAE with RBM prior, using a relatively simple -- and classically or quantum-mechanically enhanceable -- sampling technique for the evolution of the RBM's negative phase, performed better than the Bernoulli DVAE and on par with the Gaussian model, which has a continuous latent space. Our studies demonstrate the competitiveness of a discrete deep generative model with its Gaussian counterpart on anomaly-detection tasks. Moreover, the DVAE model with RBM prior can be easily integrated with quantum sampling by outsourcing its generative process to measurements of quantum states obtained from a quantum annealer or gate-model device., Comment: 25 pages, 7 figures, 3 tables, appendix, supplementary material
- Published
- 2023
38. Transonic Dislocation Propagation in Diamond
- Author
-
Katagiri, Kento, Pikuz, Tatiana, Fang, Lichao, Albertazzi, Bruno, Egashira, Shunsuke, Inubushi, Yuichi, Kamimura, Genki, Kodama, Ryosuke, Koenig, Michel, Kozioziemski, Bernard, Masaoka, Gooru, Miyanishi, Kohei, Nakamura, Hirotaka, Ota, Masato, Rigon, Gabriel, Sakawa, Youichi, Sano, Takayoshi, Schoofs, Frank, Smith, Zoe J., Sueda, Keiichi, Togashi, Tadashi, Vinci, Tommaso, Wang, Yifan, Yabashi, Makina, Yabuuchi, Toshinori, Dresselhaus-Marais, Leora E., and Ozaki, Norimasa
- Subjects
Condensed Matter - Materials Science - Abstract
The motion of line defects (dislocations) has been studied for over 60 years but the maximum speed at which they can move is unresolved. Recent models and atomistic simulations predict the existence of a limiting velocity of dislocation motions between the transonic and subsonic ranges at which the self-energy of dislocation diverges, though they do not deny the possibility of the transonic dislocations. We use femtosecond x-ray radiography to track ultrafast dislocation motion in shock-compressed single-crystal diamond. By visualizing stacking faults extending faster than the slowest sound wave speed of diamond, we show the evidence of partial dislocations at their leading edge moving transonically. Understanding the upper limit of dislocation mobility in crystals is essential to accurately model, predict, and control the mechanical properties of materials under extreme conditions.
- Published
- 2023
39. Optimal Coordination and Discount Allocation in Residential Renewable Energy Communities with Smart Home Appliances
- Author
-
Conte, Francesco, Silvestro, Federico, Vinci, Andrea, and Di Fazio, Anna Rita
- Subjects
Electrical Engineering and Systems Science - Systems and Control - Abstract
This paper proposes an optimal management strategy for a Renewable Energy Community defined according to the Italian legislation. The specific case study is composed by a set of houses equipped with smart appliances, that share a PV plant. The objective is to minimize the cost of electrical energy use for each member of the community, taking into account the discount achievable from government incentives with proper shaping of the community daily consumption. Such incentives are indeed proportional to the shared energy, i.e. the portion of the renewable energy consumed at each hour by community members. The management algorithm allows an optimal coordination of houses power demands, according to the degree of flexibility granted by users. Moreover, a policy to fairly distribute the obtained discount is introduced. Simulation results show the potentialities of the approach.
- Published
- 2023
- Full Text
- View/download PDF
40. Overview of Indonesian Community Pharmacy: Understanding Practice Changes
- Author
-
Vinci Mizranita, Thellie Ponto, and Beulah Sipana
- Subjects
community pharmacy ,community pharmacy services ,pharmacist, health-care system, indonesia, developing country ,Medicine - Abstract
Community pharmacy practice in Indonesia has shifted to a patient-centered model, offering a range of services that include treatment advice, chronic disease management, and public health promotion. This shift benefits consumers who visit community pharmacies as their initial healthcare point. The Indonesian healthcare system, a mix of public and private providers, is governed by a decentralized structure, fostering significant investment in private healthcare despite access limitations due to financial capacity. Medicines distribution, managed by the District Health Office, ensures supply to primary healthcare facilities, with community pharmacies regulated by the Ministry of Health and the Indonesian National Food and Drug Agency. Despite stringent regulations mandating comprehensive services, most pharmacists are not remunerated for their services. Pharmacy staff, including formally qualified pharmacists and pharmacy technicians, are registered professionals, with recent trends indicating a shift towards employing pharmacy technicians to enable pharmacists to focus on clinical roles. Economic factors and innovative service delivery modes, such as telepharmacy and online purchasing, are expected to influence future practices, enhancing the pharmacist's role in chronic disease management and other health conditions. The evolving community pharmacy practice in Indonesia reflects broader changes in the healthcare system and professional roles, with continued progression anticipated.
- Published
- 2024
- Full Text
- View/download PDF
41. Implications of a De Novo Variant in the SOX12 Gene in a Patient with Generalized Epilepsy, Intellectual Disability, and Childhood Emotional Behavioral Disorders
- Author
-
Simone Treccarichi, Francesco Calì, Mirella Vinci, Alda Ragalmuto, Antonino Musumeci, Concetta Federico, Carola Costanza, Maria Bottitta, Donatella Greco, Salvatore Saccone, and Maurizio Elia
- Subjects
next generation sequencing ,SOX12 gene ,epilepsy ,neurodevelopmental delay ,Biology (General) ,QH301-705.5 - Abstract
SRY-box transcription factor (SOX) genes, a recently discovered gene family, play crucial roles in the regulation of neuronal stem cell proliferation and glial differentiation during nervous system development and neurogenesis. Whole exome sequencing (WES) in patients presenting with generalized epilepsy, intellectual disability, and childhood emotional behavioral disorder, uncovered a de novo variation within SOX12 gene. Notably, this gene has never been associated with neurodevelopmental disorders. No variants in known genes linked with the patient’s symptoms have been detected by the WES Trio analysis. To date, any MIM phenotype number associated with intellectual developmental disorder has not been assigned for SOX12. In contrast, both SOX4 and SOX11 genes within the same C group (SoxC) of the Sox gene family have been associated with neurodevelopmental disorders. The variant identified in the patient here described was situated within the critical high-mobility group (HMG) functional site of the SOX12 protein. This domain, in the Sox protein family, is essential for DNA binding and bending, as well as being responsible for transcriptional activation or repression during the early stages of gene expression. Sequence alignment within SoxC (SOX12, SOX4 and SOX11) revealed a high conservation rate of the HMG region. The in silico predictive analysis described this novel variant as likely pathogenic. Furthermore, the mutated protein structure predictions unveiled notable changes with potential deleterious effects on the protein structure. The aim of this study is to establish a correlation between the SOX12 gene and the symptoms diagnosed in the patient.
- Published
- 2024
- Full Text
- View/download PDF
42. Associative white matter tracts selectively predict sensorimotor learning
- Author
-
S. Vinci-Booher, D. J. McDonald, E. Berquist, and F. Pestilli
- Subjects
Biology (General) ,QH301-705.5 - Abstract
Abstract Human learning varies greatly among individuals and is related to the microstructure of major white matter tracts in several learning domains, yet the impact of the existing microstructure of white matter tracts on future learning outcomes remains unclear. We employed a machine-learning model selection framework to evaluate whether existing microstructure might predict individual differences in learning a sensorimotor task, and further, if the mapping between tract microstructure and learning was selective for learning outcomes. We used diffusion tractography to measure the mean fractional anisotropy (FA) of white matter tracts in 60 adult participants who then practiced drawing a set of 40 unfamiliar symbols repeatedly using a digital writing tablet. We measured drawing learning as the slope of draw duration over the practice session and measured visual recognition learning for the symbols using an old/new 2-AFC task. Results demonstrated that tract microstructure selectively predicted learning outcomes, with left hemisphere pArc and SLF3 tracts predicting drawing learning and the left hemisphere MDLFspl predicting visual recognition learning. These results were replicated using repeat, held-out data and supported with complementary analyses. Results suggest that individual differences in the microstructure of human white matter tracts may be selectively related to future learning outcomes.
- Published
- 2024
- Full Text
- View/download PDF
43. Release dynamics of nanodiamonds created by laser-driven shock-compression of polyethylene terephthalate
- Author
-
Ben Heuser, Armin Bergermann, Michael G. Stevenson, Divyanshu Ranjan, Zhiyu He, Julian Lütgert, Samuel Schumacher, Mandy Bethkenhagen, Adrien Descamps, Eric Galtier, Arianna E. Gleason, Dimitri Khaghani, Griffin D. Glenn, Eric F. Cunningham, Siegfried H. Glenzer, Nicholas J. Hartley, Jean-Alexis Hernandez, Oliver S. Humphries, Kento Katagiri, Hae Ja Lee, Emma E. McBride, Kohei Miyanishi, Bob Nagler, Benjamin Ofori-Okai, Norimasa Ozaki, Silvia Pandolfi, Chongbing Qu, Philipp Thomas May, Ronald Redmer, Christopher Schoenwaelder, Keiichi Sueda, Toshinori Yabuuchi, Makina Yabashi, Bratislav Lukic, Alexander Rack, Lisa M. V. Zinta, Tommaso Vinci, Alessandra Benuzzi-Mounaix, Alessandra Ravasio, and Dominik Kraus
- Subjects
Medicine ,Science - Abstract
Abstract Laser-driven dynamic compression experiments of plastic materials have found surprisingly fast formation of nanodiamonds (ND) via X-ray probing. This mechanism is relevant for planetary models, but could also open efficient synthesis routes for tailored NDs. We investigate the release mechanics of compressed NDs by molecular dynamics simulation of the isotropic expansion of finite size diamond from different P-T states. Analysing the structural integrity along different release paths via molecular dynamic simulations, we found substantial disintegration rates upon shock release, increasing with the on-Hugnoiot shock temperature. We also find that recrystallization can occur after the expansion and hence during the release, depending on subsequent cooling mechanisms. Our study suggests higher ND recovery rates from off-Hugoniot states, e.g., via double-shocks, due to faster cooling. Laser-driven shock compression experiments of polyethylene terephthalate (PET) samples with in situ X-ray probing at the simulated conditions found diamond signal that persists up to 11 ns after breakout. In the diffraction pattern, we observed peak shifts, which we attribute to thermal expansion of the NDs and thus a total release of pressure, which indicates the stability of the released NDs.
- Published
- 2024
- Full Text
- View/download PDF
44. Multi-density crime predictor: an approach to forecast criminal activities in multi-density crime hotspots
- Author
-
Eugenio Cesario, Paolo Lindia, and Andrea Vinci
- Subjects
Crime data mining ,Crime forecasting ,Crime hotspots ,LSTM ,Multi-density clustering ,Urban crime data analysis ,Computer engineering. Computer hardware ,TK7885-7895 ,Information technology ,T58.5-58.64 ,Electronic computers. Computer science ,QA75.5-76.95 - Abstract
Abstract The increasing pervasiveness of ICT technologies and sensor infrastructures is enabling police departments to gather and store increasing volumes of spatio-temporal crime data. This offers the opportunity to apply data analytics methodologies to extract useful crime predictive models, which can effectively detect spatial and temporal patterns of crime events, and can support police departments in implementing more effective strategies for crime prevention. The detection of crime hotspots from geo-referenced data is a crucial aspect of discovering effective predictive models and implementing efficient crime prevention decisions. In particular, since metropolitan cities are heavily characterized by variable spatial densities of crime events, multi-density clustering seems to be more effective than classic techniques for discovering crime hotspots. This paper presents the design and implementation of MD-CrimePredictor (Multi- Density Crime Predictor), an approach based on multi-density crime hotspots and regressive models to automatically detect high-risk crime areas in urban environments, and to reliably forecast crime trends in each area. The algorithm result is a spatio-temporal crime forecasting model, composed of a set of multi-density crime hotspots, their densities and a set of associated crime predictors, each one representing a predictive model to forecast the number of crimes that are estimated to happen in its specific hotspot. The experimental evaluation of the proposed approach has been performed by analyzing a large area of Chicago, involving more than two million crime events (over a period of 19 years). This evaluation shows that the proposed approach, based on multi-density clustering and regressive models, achieves good accuracy in spatial and temporal crime forecasting over rolling prediction horizons. It also presents a comparative analysis between SARIMA and LSTM models, showing higher accuracy of the first method with respect to the second one.
- Published
- 2024
- Full Text
- View/download PDF
45. Evaluating cell culture reliability in pediatric brain tumor primary cells through DNA methylation profiling
- Author
-
Lucia Pedace, Simone Pizzi, Luana Abballe, Maria Vinci, Celeste Antonacci, Sara Patrizi, Claudia Nardini, Francesca Del Bufalo, Sabrina Rossi, Giulia Pericoli, Francesca Gianno, Zein Mersini Besharat, Luca Tiberi, Angela Mastronuzzi, Elisabetta Ferretti, Marco Tartaglia, Franco Locatelli, Andrea Ciolfi, and Evelina Miele
- Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens ,RC254-282 - Abstract
Abstract In vitro models of pediatric brain tumors (pBT) are instrumental for better understanding the mechanisms contributing to oncogenesis and testing new therapies; thus, ideally, they should recapitulate the original tumor. We applied DNA methylation (DNAm) and copy number variation (CNV) profiling to characterize 241 pBT samples, including 155 tumors and 86 pBT-derived cell cultures, considering serum vs serum-free conditions, late vs early passages, and dimensionality (2D vs 3D cultures). We performed a t-SNE classification and identified differentially methylated regions in tumors compared to cell models. Early cell cultures recapitulate the original tumor, but serum media and 2D culturing were demonstrated to significantly contribute to the divergence of DNAm profiles from the parental ones. All divergent cells clustered together acquiring a common deregulated epigenetic signature suggesting a shared selective pressure. We identified a set of hypomethylated genes shared among unfaithful cells converging on response to growth factors and migration pathways, such as signaling cascade activation, tissue organization, and cellular migration. In conclusion, DNAm and CNV are informative tools that should be used to assess the recapitulation of pBT-cells from parental tumors.
- Published
- 2024
- Full Text
- View/download PDF
46. The role of education in innovation–migration nexus in Europe
- Author
-
Aldieri, L., Autiero, G., Nese, A., and Vinci, C. P.
- Published
- 2024
- Full Text
- View/download PDF
47. Defining Dominance in Domestic Dogs (Canis familiaris): A Scoping Review with Recommendations for Human-Canine Interactions
- Author
-
da Vinci, Gia James, Fausak, Erik Davis, and Grigg, Emma K
- Published
- 2023
48. The Unintended Consequences Of The Things We Say: A Replication and Extension
- Author
-
Cuaderno, Idalys Cuaderno, Gullon, Alicia, Kudriavtsev, Katherine, Neinast, Sinead, Palkar, Esha, Vinci, Samuel, and Zhao, Marina
- Published
- 2023
49. The impact of vaccine hesitancy on psychological impairment among healthcare workers in a Total Worker Health© approach
- Author
-
Reparata Rosa Di Prinzio, Bianca Ceresi, Gabriele Arnesano, Alessia Dosi, Mariarita Maimone, Maria Eugenia Vacca, Maria Rosaria Vinci, Vincenzo Camisa, Annapaola Santoro, Massimiliano Raponi, Paola Tomao, Nicoletta Vonesch, Umberto Moscato, Salvatore Zaffina, and Guendalina Dalmasso
- Subjects
COVID-19 ,vaccine acceptance ,mental health ,flu ,nurse ,vaccine refusal ,Public aspects of medicine ,RA1-1270 - Abstract
IntroductionVaccination practice is a well-known individual protective measure for biological risk in healthcare. During the COVID-19 pandemic vaccine hesitancy has grown among healthcare workers (HCWs). The study aims to investigate how vaccine hesitancy influences the psychological burden experienced by healthcare workers.MethodsThis study aimed to explore attitudes of HCWs in acceptance or refusal of vaccinations related to the risk of psychological impairment (PI) and describe the associated occupational factors, during the seasonal flu/COVID-19 vaccination campaign of 2022–2023. 302 HCWs were enrolled in the study. A questionnaire was self-administered, including two scales on the risk of psychological impairment (Psychological Injury Risk Indicator, PIRI) and vaccine hesitancy (Adult Vaccine Hesitancy Scale, AVHS).ResultsPIRI scores revealed that 29.8% of participants were at risk of PI. Differences in sex, age, occupational seniority, professional category, and night shifts were found between HCWs at risk of PI and those not at risk. Females registered a four-fold higher risk than males (85.6% vs. 14.4%, χ2 = 4.450, p
- Published
- 2024
- Full Text
- View/download PDF
50. Methylome analysis of endothelial cells suggests new insights on sporadic brain arteriovenous malformation
- Author
-
Concetta Scimone, Luigi Donato, Simona Alibrandi, Alfredo Conti, Carlo Bortolotti, Antonino Germanò, Concetta Alafaci, Sergio Lucio Vinci, Rosalia D'Angelo, and Antonina Sidoti
- Subjects
Brain arteriovenous malformation ,Mural cells ,Epigenetics ,Transcription factors ,Science (General) ,Q1-390 ,Social sciences (General) ,H1-99 - Abstract
Arteriovenous malformation of the brain (bAVM) is a vascular phenotype related to brain defective angiogenesis. Involved vessels show impaired expression of vascular differentiation markers resulting in the arteriolar to venule direct shunt. In order to clarify aberrant gene expression occurring in bAVM, here we describe results obtained by methylome analysis performed on endothelial cells (ECs) isolated from bAVM specimens, compared to human cerebral microvascular ECs. Results were validated by quantitative methylation-specific PCR and quantitative realtime-PCR. Differential methylation events occur in genes already linked to bAVM onset, as RBPJ and KRAS. However, among differentially methylated genes, we identified EPHB1 and several other loci involved in EC adhesion as well as in EC/vascular smooth muscle cell (VSMC) crosstalk, suggesting that only endothelial dysfunction might not be sufficient to trigger the bAVM phenotype. Moreover, aberrant methylation pattern was reported for many lncRNA genes targeting transcription factors expressed during neurovascular development. Among these, the YBX1 that was recently shown to target the arteridin coding gene. Finally, in addition to the conventional CpG methylation, we further considered the role of impaired CHG methylation, mainly occurring in brain at embryo stage. We showed as differentially CHG methylated genes are clustered in pathways related to EC homeostasis, as well as to VSMC-EC crosstalk, suggesting as impairment of this interaction plays a prominent role in loss of vascular differentiation, in bAVM phenotype.
- Published
- 2024
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.