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1. Chromatic Topological Data Analysis

Author

di Montesano, Sebastiano Cultrera, Draganov, Ondrej, Edelsbrunner, Herbert, and Saghafian, Morteza

Subjects
Computer Science - Computational Geometry
Abstract

Exploring the shape of point configurations has been a key driver in the evolution of TDA (short for topological data analysis) since its infancy. This survey illustrates the recent efforts to broaden these ideas to model spatial interactions among multiple configurations, each distinguished by a color. It describes advances in this area and prepares the ground for further exploration by mentioning unresolved questions and promising research avenues while focusing on the overlap with discrete geometry.

Published
2024

2. Banana Trees for the Persistence in Time Series Experimentally

Author

Ost, Lara, di Montesano, Sebastiano Cultrera, and Edelsbrunner, Herbert

Subjects
Computer Science - Data Structures and Algorithms
Abstract

In numerous fields, dynamic time series data require continuous updates, necessitating efficient data processing techniques for accurate analysis. This paper examines the banana tree data structure, specifically designed to efficiently maintain persistent homology -- a multi-scale topological descriptor -- for dynamically changing time series data. We implement this data structure and conduct an experimental study to assess its properties and runtime for update operations. Our findings indicate that banana trees are highly effective with unbiased random data, outperforming state-of-the-art static algorithms in these scenarios. Additionally, our results show that real-world time series share structural properties with unbiased random walks, suggesting potential practical utility for our implementation.

Published
2024

3. EventSleep: Sleep Activity Recognition with Event Cameras

Author

Plou, Carlos, Gallego, Nerea, Sabater, Alberto, Montijano, Eduardo, Urcola, Pablo, Montesano, Luis, Martinez-Cantin, Ruben, and Murillo, Ana C.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Event cameras are a promising technology for activity recognition in dark environments due to their unique properties. However, real event camera datasets under low-lighting conditions are still scarce, which also limits the number of approaches to solve these kind of problems, hindering the potential of this technology in many applications. We present EventSleep, a new dataset and methodology to address this gap and study the suitability of event cameras for a very relevant medical application: sleep monitoring for sleep disorders analysis. The dataset contains synchronized event and infrared recordings emulating common movements that happen during the sleep, resulting in a new challenging and unique dataset for activity recognition in dark environments. Our novel pipeline is able to achieve high accuracy under these challenging conditions and incorporates a Bayesian approach (Laplace ensembles) to increase the robustness in the predictions, which is fundamental for medical applications. Our work is the first application of Bayesian neural networks for event cameras, the first use of Laplace ensembles in a realistic problem, and also demonstrates for the first time the potential of event cameras in a new application domain: to enhance current sleep evaluation procedures. Our activity recognition results highlight the potential of event cameras under dark conditions, and its capacity and robustness for sleep activity recognition, and open problems as the adaptation of event data pre-processing techniques to dark environments.

Published
2024

4. The Euclidean MST-ratio for Bi-colored Lattices

Author

di Montesano, Sebastiano Cultrera, Draganov, Ondřej, Edelsbrunner, Herbert, and Saghafian, Morteza

Subjects
Computer Science - Computational Geometry, Mathematics - Combinatorics, 52C05, 05C10, G.2
Abstract

Given a finite set, $A \subseteq \mathbb{R}^2$, and a subset, $B \subseteq A$, the \emph{MST-ratio} is the combined length of the minimum spanning trees of $B$ and $A \setminus B$ divided by the length of the minimum spanning tree of $A$. The question of the supremum, over all sets $A$, of the maximum, over all subsets $B$, is related to the Steiner ratio, and we prove this sup-max is between $2.154$ and $2.427$. Restricting ourselves to $2$-dimensional lattices, we prove that the sup-max is $2.0$, while the inf-max is $1.25$. By some margin the most difficult of these results is the upper bound for the inf-max, which we prove by showing that the hexagonal lattice cannot have MST-ratio larger than $1.25$.

Published
2024

5. Body Schema Acquisition through Active Learning

Author

Martinez-Cantin, Ruben, Lopes, Manuel, and Montesano, Luis

Subjects
Computer Science - Robotics
Abstract

We present an active learning algorithm for the problem of body schema learning, i.e. estimating a kinematic model of a serial robot. The learning process is done online using Recursive Least Squares (RLS) estimation, which outperforms gradient methods usually applied in the literature. In addiction, the method provides the required information to apply an active learning algorithm to find the optimal set of robot configurations and observations to improve the learning process. By selecting the most informative observations, the proposed method minimizes the required amount of data. We have developed an efficient version of the active learning algorithm to select the points in real-time. The algorithms have been tested and compared using both simulated environments and a real humanoid robot., Comment: International Conference on Robotics and Automation (ICRA) 2010

Published
2024
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10. Interactions between an arbuscular mycorrhizal inoculum and the root-associated microbiome in shaping the response of Capsicum annuum “Locale di Senise” to different irrigation levels

Author

Calvo, Alice, Reitz, Thomas, Sillo, Fabiano, Montesano, Vincenzo, Cañizares, Eva, Zampieri, Elisa, Mahmoudi, Roghayyeh, Gohari, Gholamreza, Chitarra, Walter, Giovannini, Luca, Conte, Adriano, Mennone, Carmelo, Petruzzelli, Gianniantonio, Centritto, Mauro, González-Guzmán, Miguel, Arbona, Vicent, Fotopoulos, Vasileios, and Balestrini, Raffaella

Published
2024
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11. Dynamically Maintaining the Persistent Homology of Time Series

Author

di Montesano, Sebastiano Cultrera, Edelsbrunner, Herbert, Henzinger, Monika, and Ost, Lara

Subjects
Computer Science - Data Structures and Algorithms, Computer Science - Computational Geometry
Abstract

We present a dynamic data structure for maintaining the persistent homology of a time series of real numbers. The data structure supports local operations, including the insertion and deletion of an item and the cutting and concatenating of lists, each in time $O(\log n + k)$, in which $n$ counts the critical items and $k$ the changes in the augmented persistence diagram. To achieve this, we design a tailor-made tree structure with an unconventional representation, referred to as banana tree, which may be useful in its own right., Comment: Corrected the statement and proof of Theorem 5.2; added a missing edge-case to the anti-cancellation algorithm

Published
2023

12. Academic Achievement and Satisfaction among University Students with Specific Learning Disabilities: The Roles of Soft Skills and Study-Related Factors

Author

Casali, Nicole, Meneghetti, Chiara, Tinti, Carla, Re, Anna Maria, Sini, Barbara, Passolunghi, Maria Chiara, Valenti, Antonella, Montesano, Lorena, Pellegrino, Gerardo, and Carretti, Barbara

Abstract

Understanding the individual qualities sustaining students with and without specific learning disabilities (SLDs) is key to supporting their academic achievement and well-being. In this study, we investigated the differences between students with and without SLDs in terms of intraindividual factors (soft skills and study-related factors), academic and nonacademic outcomes (achievement, academic and life satisfaction), and the relationships between such intraindividual factors and the three outcomes. A total of 318 students (79 males; M[subscript age] = 22.7; SD = 3.56; age range = 19-45 years; 147 with SLDs) completed self-reported questionnaires and a measure of fluid intelligence. The results showed that students with SLDs reported higher creativity but lower academic self-efficacy, study resilience, and academic achievement, with small-to-medium effect sizes. In both groups, achievement significantly positively related to academic self-efficacy and negatively to creativity. Life satisfaction was positively related to study resilience; and academic satisfaction was related to critical thinking, curiosity, and academic self-efficacy. Nurturing such intraindividual factors can benefit students with and without SLDs.

Published
2024
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14. Plant Physiological Analysis to Overcome Limitations to Plant Phenotyping.

Author

Haworth, Matthew, Marino, Giovanni, Atzori, Giulia, Fabbri, Andre, Killi, Dilek, Carli, Andrea, Montesano, Vincenzo, Conte, Adriano, Balestrini, Raffaella, Centritto, Mauro, and Daccache, Andre

Subjects
LiDAR, climate resilience, deep-learning, hyperspectral, partial least squares regression, phenomics, photosynthesis, plant ecophysiology, spectral reflectance
Abstract

Plant physiological status is the interaction between the plant genome and the prevailing growth conditions. Accurate characterization of plant physiology is, therefore, fundamental to effective plant phenotyping studies; particularly those focused on identifying traits associated with improved yield, lower input requirements, and climate resilience. Here, we outline the approaches used to assess plant physiology and how these techniques of direct empirical observations of processes such as photosynthetic CO2 assimilation, stomatal conductance, photosystem II electron transport, or the effectiveness of protective energy dissipation mechanisms are unsuited to high-throughput phenotyping applications. Novel optical sensors, remote/proximal sensing (multi- and hyperspectral reflectance, infrared thermography, sun-induced fluorescence), LiDAR, and automated analyses of below-ground development offer the possibility to infer plant physiological status and growth. However, there are limitations to such indirect approaches to gauging plant physiology. These methodologies that are appropriate for the rapid high temporal screening of a number of crop varieties over a wide spatial scale do still require calibration or validation with direct empirical measurement of plant physiological status. The use of deep-learning and artificial intelligence approaches may enable the effective synthesis of large multivariate datasets to more accurately quantify physiological characters rapidly in high numbers of replicate plants. Advances in automated data collection and subsequent data processing represent an opportunity for plant phenotyping efforts to fully integrate fundamental physiological data into vital efforts to ensure food and agro-economic sustainability.

Published
2023

15. Universal and Specific Services for University Students with Specific Learning Disabilities: The Relation to Study Approach, Academic Achievement, and Satisfaction

Author

Pellegrino, Gerardo, Casali, Nicole, Meneghetti, Chiara, Tinti, Carla, Re, Anna Maria, Sini, Barbara, Passolunghi, Maria Chiara, Valenti, Antonella, Montesano, Lorena, and Carretti, Barbara

Abstract

In recent years, an increasing number of students with specific learning disabilities (SLDs) have enrolled in universities. The present exploratory study examined the frequency of use and appreciation of universal (open to every student) and specific services (offered to students with SLDs) and their relation to age, academic achievement, satisfaction, self-efficacy, and use of self-regulated learning (SRL) strategies. Participants were 147 Italian university students with SLD diagnoses (42 males; mean age: 22.49, SD = 3.29). Results showed that, overall, the frequency of use and appreciation of specific services were positively related to academic satisfaction, self-efficacy, and SRL strategies. Furthermore, frequency of use of compensatory tools and dispensatory measures was positively associated with academic achievement. These findings suggest that universities play an important role in supporting students with SLDs during their academic years by providing them with useful services and accommodations.

Published
2023
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17. Artificial Intelligence and MicroRNA: Role in Cancer Evolution

Author

Koroliouk, Dimitri, Mattei, Maurizio, Zoziuk, Maxym, Montesano, Carla, Bernardini, Roberta, Potestà, Marina, Wondeu, Laure Deutou, Pirrò, Stefano, Galgani, Andrea, Colizzi, Vittorio, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Luntovskyy, Andriy, editor, Klymash, Mikhailo, editor, Melnyk, Igor, editor, Beshley, Mykola, editor, and Schill, Alexander, editor

Published
2024
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23. A shift in transitional forests of the North American boreal will persist through 2100

Author

Paul M. Montesano, Melanie Frost, Jian Li, Mark Carroll, Christopher S. R. Neigh, Matthew J. Macander, Joseph O. Sexton, and Gerald V. Frost

Subjects
Geology, QE1-996.5, Environmental sciences, GE1-350
Abstract

Abstract High northern latitude changes with Arctic amplification across a latitudinal forest gradient suggest a shift towards an increased presence of trees and shrubs. The persistence of change may depend on the future scenarios of climate and on the current state, and site history, of forest structure. Here, we explore the persistence of a gradient-based shift in the boreal by connecting current forest patterns to recent tree cover trends and future modeled estimates of canopy height through 2100. Results show variation in the predicted potential height changes across the structural gradient from the boreal forest through the taiga-tundra ecotone. Positive potential changes in height are concentrated in transitional forests, where recent positive changes in cover prevail, while potential change in boreal forest is highly variable. Results are consistent across climate scenarios, revealing a persistent biome shift through 2100 in North America concentrated in transitional landscapes regardless of climate scenario.

Published
2024
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24. Tackling new psychoactive substances through metabolomics: UHPLC-HRMS study on natural and synthetic opioids in male and female murine models

Author

Gaia Di Francesco, Camilla Montesano, Flaminia Vincenti, Sabrine Bilel, Giorgia Corli, Greta Petrella, Daniel Oscar Cicero, Adolfo Gregori, Matteo Marti, and Manuel Sergi

Subjects
Medicine, Science
Abstract

Abstract Novel psychoactive substances (NPS) represent a broad class of drugs new to the illicit market that often allow passing drug-screening tests. They are characterized by a variety of structures, rapid transience on the drug scene and mostly unknown metabolic profiles, thus creating an ever-changing scenario with evolving analytical targets. The present study aims at developing an indirect screening strategy for NPS monitoring, and specifically for new synthetic opioids (NSOs), based on assessing changes in endogenous urinary metabolite levels as a consequence of the systemic response following their intake. The experimental design involved in-vivo mice models: 16 animals of both sex received a single administration of morphine or fentanyl. Urine was collected before and after administration at different time points; the samples were then analysed with an untargeted metabolomics LC-HRMS workflow. According to our results, the intake of opioids resulted in an elevated energy demand, that was more pronounced on male animals, as evidenced by the increase in medium and long chain acylcarnitines levels. It was also shown that opioid administration disrupted the pathways related to catecholamines biosynthesis. The observed alterations were common to both morphine and fentanyl: this evidence indicate that they are not related to the chemical structure of the drug, but rather on the drug class. The proposed strategy may reinforce existing NPS screening approaches, by identifying indirect markers of drug assumption.

Published
2024
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26. Chromatic Alpha Complexes

Author

di Montesano, Sebastiano Cultrera, Draganov, Ondřej, Edelsbrunner, Herbert, and Saghafian, Morteza

Subjects
Mathematics - Algebraic Topology, Computer Science - Computational Geometry, 55N31, 62R40
Abstract

Motivated by applications in the medical sciences, we study finite chromatic sets in Euclidean space from a topological perspective. Based on the persistent homology for images, kernels and cokernels, we design provably stable homological quantifiers that describe the geometric micro- and macro-structure of how the color classes mingle. These can be efficiently computed using chromatic variants of Delaunay and alpha complexes, and code that does these computations is provided., Comment: 26 pages; v4 contains minor reviews and clarifications; v3 only updates the title; v2 brings many changes over v1, most notably adds a proof that the chromatic radius function is generalised discrete Morse

Published
2022

27. On the Size of Chromatic Delaunay Mosaics

Author

Biswas, Ranita, di Montesano, Sebastiano Cultrera, Draganov, Ondřej, Edelsbrunner, Herbert, and Saghafian, Morteza

Subjects
Mathematics - Combinatorics, Computer Science - Computational Geometry
Abstract

Given a locally finite set $A \subseteq \mathbb{R}^d$ and a coloring $\chi \colon A \to \{0,1,\ldots,s\}$, we introduce the chromatic Delaunay mosaic of $\chi$, which is a Delaunay mosaic in $\mathbb{R}^{s+d}$ that represents how points of different colors mingle. Our main results are bounds on the size of the chromatic Delaunay mosaic, in which we assume that $d$ and $s$ are constants. For example, if $A$ is finite with $n = \#{A}$, and the coloring is random, then the chromatic Delaunay mosaic has $O(n^{\lceil{d/2}\rceil})$ cells in expectation. In contrast, for Delone sets and Poisson point processes in $\mathbb{R}^d$, the expected number of cells within a closed ball is only a constant times the number of points in this ball. Furthermore, in $\mathbb{R}^2$ all colorings of a dense set of $n$ points have chromatic Delaunay mosaics of size $O(n)$. This encourages the use of chromatic Delaunay mosaics in applications., Comment: 15 pages, 4 figures

Published
2022

28. Event Transformer+. A multi-purpose solution for efficient event data processing

Author

Sabater, Alberto, Montesano, Luis, and Murillo, Ana C.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Event cameras record sparse illumination changes with high temporal resolution and high dynamic range. Thanks to their sparse recording and low consumption, they are increasingly used in applications such as AR/VR and autonomous driving. Current topperforming methods often ignore specific event-data properties, leading to the development of generic but computationally expensive algorithms, while event-aware methods do not perform as well. We propose Event Transformer+, that improves our seminal work EvT with a refined patch-based event representation and a more robust backbone to achieve more accurate results, while still benefiting from event-data sparsity to increase its efficiency. Additionally, we show how our system can work with different data modalities and propose specific output heads, for event-stream classification (i.e. action recognition) and per-pixel predictions (dense depth estimation). Evaluation results show better performance to the state-of-the-art while requiring minimal computation resources, both on GPU and CPU., Comment: arXiv admin note: text overlap with arXiv:2204.03355

Published
2022
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31. Data Fusion in Neuromarketing: Multimodal Analysis of Biosignals, Lifecycle Stages, Current Advances, Datasets, Trends, and Challenges

Author

Pérez, Mario Quiles, Beltrán, Enrique Tomás Martínez, Bernal, Sergio López, Prat, Eduardo Horna, Del Campo, Luis Montesano, Maimó, Lorenzo Fernández, and Celdrán, Alberto Huertas

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Artificial Intelligence, Computer Science - Human-Computer Interaction
Abstract

The primary goal of any company is to increase its profits by improving both the quality of its products and how they are advertised. In this context, neuromarketing seeks to enhance the promotion of products and generate a greater acceptance on potential buyers. Traditionally, neuromarketing studies have relied on a single biosignal to obtain feedback from presented stimuli. However, thanks to new devices and technological advances studying this area of knowledge, recent trends indicate a shift towards the fusion of diverse biosignals. An example is the usage of electroencephalography for understanding the impact of an advertisement at the neural level and visual tracking to identify the stimuli that induce such impacts. This emerging pattern determines which biosignals to employ for achieving specific neuromarketing objectives. Furthermore, the fusion of data from multiple sources demands advanced processing methodologies. Despite these complexities, there is a lack of literature that adequately collates and organizes the various data sources and the applied processing techniques for the research objectives pursued. To address these challenges, the current paper conducts a comprehensive analysis of the objectives, biosignals, and data processing techniques employed in neuromarketing research. This study provides both the technical definition and a graphical distribution of the elements under revision. Additionally, it presents a categorization based on research objectives and provides an overview of the combinatory methodologies employed. After this, the paper examines primary public datasets designed for neuromarketing research together with others whose main purpose is not neuromarketing, but can be used for this matter. Ultimately, this work provides a historical perspective on the evolution of techniques across various phases over recent years and enumerates key lessons learned., Comment: 26 pages, 15 figures

Published
2022

37. Event Transformer. A sparse-aware solution for efficient event data processing

Author

Sabater, Alberto, Montesano, Luis, and Murillo, Ana C.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Event cameras are sensors of great interest for many applications that run in low-resource and challenging environments. They log sparse illumination changes with high temporal resolution and high dynamic range, while they present minimal power consumption. However, top-performing methods often ignore specific event-data properties, leading to the development of generic but computationally expensive algorithms. Efforts toward efficient solutions usually do not achieve top-accuracy results for complex tasks. This work proposes a novel framework, Event Transformer (EvT), that effectively takes advantage of event-data properties to be highly efficient and accurate. We introduce a new patch-based event representation and a compact transformer-like architecture to process it. EvT is evaluated on different event-based benchmarks for action and gesture recognition. Evaluation results show better or comparable accuracy to the state-of-the-art while requiring significantly less computation resources, which makes EvT able to work with minimal latency both on GPU and CPU.

Published
2022

38. Factors underlying the high occupational risk of healthcare personnel for COVID-19 infection

Author

Priscila Montesano Cunha Crispim, Julia Yaeko Kawagoe, Ana Cristina Rosseti, and Fernando Gatti de Menezes

Subjects
Occupational risks, SARS-CoV-2, COVID-19, Coronavirus infections, Health personnel, Transmission, Medicine
Abstract

ABSTRACT Objective To verify the rate of COVID-19 infection among healthcare personnel at high and low risk of COVID-19 infection and identify the underlying risk factors. Methods This cross-sectional study was conducted between December 1, 2020 and February 28, 2021. Associations were verified between the levels of risk (high or low) of occupational COVID-19 infection and participant characteristics using the World Health Organization risk assessment questionnaire and adjusted using logistic regression models in single and multiple approaches. Results Of the 486 participants, 57.4% were classified as having a high occupational risk for SARS-CoV-2 infection, with a diagnosis rate of 12.1%. The factors identified in the multivariate analysis for high occupational risk were age up to 29 years (odds ratio [OR] = 2.7, 95% confidence interval [95%CI] = 1.63-4.47), monthly family income greater than eight times the basic salary (OR= 1.8, 95%CI= 1.07-3.16), and healthcare personnel who did not participate in initial training to work in the area of patients with COVID-19 infection (OR= 2.39, 95%CI= 1.53-3.75). Conclusion Encouraging training for occupational infection prevention is very important to reduce the impact of infectious diseases on healthcare personnel, especially young health professionals.

Published
2024
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39. External validation of three diabetes prediction scores in a Spanish cohort: does adding high risk for depression improve the validation of the FINDRISC score (FINDRISC-MOOD)?

Author

Fernando Rodriguez-Artalejo, Jose M Mostaza-Prieto, Carlos Lahoz-Rallo, Juan Cárdenas-Valladolid, Sara Artola, Carmen de Burgos-Lunar, Paloma Gómez-Campelo, Leopoldo Pérez-Isla, Ignacio Vicente, Domingo Beamud-Victoria, Isidoro Dujovne-Kohan, Rosa María Chico-Moraleja, Carmen Martín-Madrazo, Concepción Aguilera Linde, Patricio Alonso Sacristán, Paloma Arribas Pérez, Maria Luisa Asensio Ruiz, Pablo Astorga Díaz, Ana Isabel Bezos Varela, María José Calatrava Triguero, Carlos Casanova García, Ángeles Conde Llorente, Concepción Díaz Laso, Emilia Elviro García, Orlando Enríquez Dueñas, María Isabel Ferrer Zapata, Froilán Antuña, Maria Isabel García Lazaro, Maria Teresa Gómez Rodríguez, África Gómez Lucena, Francisco Herrero Hernández, Rosa Julián Viñals, Gerardo López Ruiz Ogarrio, Maria Del Carmen Lumbreras Manzano, Sonsoles Paloma Luquero López, Ana Martínez Cabrera Peláez, Montserrat Nieto Candenas, Ángel Castellanos Rodríguez, Ana López Castellanos, Milagros Velázquez García, Margarita Ruiz Pacheco, Belen Fernández-Puntero, Victor Iriarte-Campo, Miguel Salinero-Fort, Eva Estirado-Decabo, Francisca Garcia-Iglesias, Teresa Gonzalez-Alegre, Victor M Cornejo-Del Rio, Vanesa Sanchez-Arroyo, Concesa Sabín-Rodríguez, Silvia López-López, Belen Taulero-Escalera, Francisco Javier San Andrés-Rebollo, Fernando Laguna, Pedro Fernández-García, Luis Montesano-Sánchez, Pedro Patrón, David Vicent, Ma Isabel Granados Menéndez, Rosario Echegoyen deNicolás, Álvaro R Aguirre De Carcer Escolano, MJesús Álvarez Otero, Begoña Berriatua Ena, and María AlejandraRabanal Carrera

Subjects
Medicine
Abstract

Objectives To evaluate the external validity of the FINDRISC, DESIR and ADA risk scores for the prediction of diabetes in a Spanish population aged >45 years and to test the possible improvement of FINDRISC by adding a new variable of high risk of depression when Patient Health Questionnaire-9 (PHQ-9) questionnaire score ≥10 (FINDRISC-MOOD).Design Prospective population-based cohort study.Setting 10 primary healthcare centres in the north of the city of Madrid (Spain).Participants A total of 1242 participants without a history of diabetes and with 2-hour oral glucose tolerance test (OGTT) plasma glucose

Published
2024
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40. Agentes patógenos aislados en adultos con cateter de diálisis peritoneal. Hospital Docente Francisco e Moscoso Puello, junio 2017 – junio 2019

Author

Danny Dariel Peralta Méndez, Katherine Pamela Rodríguez Martínez, Joel Emilio Santana Fernández, Jorge Octavio Sánchez Orbe, Yordano Montesano Jiménez, and Younine Hernández Castillo

Subjects
agentes patógenos, catéter, diálisis peritoneal, colonización, cultivos, Medicine (General), R5-920, Public aspects of medicine, RA1-1270
Abstract

Objetivo: Identificar los agentes patógenos aislados en pacientes con catéter de diálisis peritoneal en el Hospital Docente Francisco E. Moscoso Puello in Santo Domingo, junio 2017 – junio 2019. Método: Se realizó un estudio descriptivo, de corte transversal con una proyección retrospectiva, y consta de una muestra de 32 registros de pacientes. Los datos obtenidos fueron analizados con el software Epi-info 7.0. Resultados: Los agentes patógenos más frecuentes aislados fueron el Staphylococcus aureus representando un 50%15 de los cultivos positivos, seguidos por Escherichia Coli y Pseudomona aeruginosa, ambos formando 12.5%4 de los cultivos positivos cada uno. En cuanto a los grupos de edad más afectados observamos que los que presentan una mayor frecuencia de casos son de 60-69 años de edad. Conclusión: La investigación identificó varios agentes patógenos asociados al catéter de diálisis peritoneal, entre los que destacan Staphylococcus aureus, Escherichia coli y Pseudomona aeruginosa. Staphylococcus aureus fue el más común en ambos sexos y el más frecuente en pacientes de 1 a 3 años. Este mismo agente, junto con Escherichia coli y otros, fueron responsables de las recurrencias. Se encontró que todos los pacientes utilizaban diálisis peritoneal continua ambulatoria y todos los agentes patógenos identificados fueron aislados en esta terapia.

Published
2024
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41. Determinación del gen Ras como factor pronóstico y predictivo en cáncer colorrectal metastásico en el Instituto de Oncología Dr. Heriberto Pieter, enero 2019 - diciembre 2021

Author

Sui Lanni María Ceballos Sang, Visanlly Carolina Laureano Páez, and Yordano Montesano

Subjects
Cáncer colorrectal, gen RAS, KRAS, valor pronostico, valor predictivo, caracterización molecular, Medicine (General), R5-920, Public aspects of medicine, RA1-1270
Abstract

Objetivo: Determinar el gen RAS como factor pronóstico y predictivo en cáncer colorrectal metastásico. Método: Es un estudio descriptivo y retrospectivo donde se examinaron 67 expedientes de pacientes con cáncer colorrectal metastásico, centrándose en la determinación del gen RAS como factor pronóstico y predictivo. Resultados: Se halló que el 56.7% de los pacientes tenían tumores Wild-type y el 43.3% mostraba tumores con mutaciones KRAS, sin detectarse mutaciones en el gen NRAS. Tanto en el colon derecho como en el izquierdo, los tumores Wild-type fueron algo más comunes que los tumores con mutaciones KRAS. El codón 12 fue el más afectado en un 75.9% de los casos de tumores KRAS mutados. El adenocarcinoma fue el tipo histológico predominante (82%), seguido del adenocarcinoma mucinoso (16.5%). La mayoría de los pacientes (56.7%) se hallaban en estadio IV al diagnóstico. Los tumores KRAS mutados mostraron una mayor tendencia a la recurrencia y metástasis múltiples en comparación con los tumores Wild-type, siendo el hígado y el pulmón los sitios más comunes de metástasis. También se observaron diferencias en la supervivencia libre de progresión y la supervivencia global según el estado mutacional del gen RAS, con una mayor progresión en pacientes con tumores KRAS mutados. Conclusión: Estos hallazgos sugieren que las mutaciones en el gen KRAS podrían asociarse con peor pronóstico en términos de progresión de la enfermedad y supervivencia. La determinación del estado del gen KRAS podría tener implicaciones clínicas significativas en la estratificación del riesgo y la planificación del tratamiento para pacientes con cáncer colorrectal metastásico.

Published
2024
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42. Assessing the effectiveness of cannabidiol additive supplementation on canine behavior and cortisol levels

Author

Giovanna Marliani, Lucrezia Vaccari, Damiano Cavallini, Carmen Silvia Montesano, Giovanni Buonaiuto, and Pier Attilio Accorsi

Subjects
Science (General), Q1-390, Social sciences (General), H1-99
Abstract

In veterinary medicine, Cannabis has been used to treat pain conditions, inflammation, and seizures. However, little is known about its effect on dogs’ behavior. This preliminary research aims to address this knowledge gap by evaluating the effectiveness of cannabidiol (CBD) oil in canine behavioral therapy. Twenty dogs, diagnosed with behavioral disorders and housed in a municipal shelter, participated in a double-blind trial. Ten dogs received CBD oil treatment, while the other ten received a control oil without CBD. Before (T0) and after (T1) the treatment, all the dogs underwent a temperament test to assess their behavior in the presence of four different stimuli: a human stranger, a novel object, a child-like doll, and a conspecific (another dog). Each stimulus was presented individually, and the dogs' behaviors were recorded on video and analyzed. Additionally, hair samples were collected using a shave-reshave technique for cortisol determination through Radio-Immuno-Assay. No behavioral differences were found between the two groups at both T0 and T1. There were no significant differences in the behavioral responses of either group when comparing T0 and T1. However, individual responses to the CBD oil treatment appeared to vary among subjects. A significant increase in hair cortisol levels (p-value

Published
2024
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43. SARS-CoV-2 genomic surveillance and reliability of PCR single point mutation assay (SNPsig® SARS-CoV-2 EscapePLEX CE) for the rapid detection of variants of concern in Cameroon

Author

Joseph Fokam, Davy-Hyacinthe Gouissi Anguechia, Desire Takou, Ezechiel Ngoufack Jagni Semengue, Collins Chenwi, Grace Beloumou, Sandrine Djupsa, Alex Durand Nka, Willy Le Roi Togna Pabo, Aissatou Abba, Aude Christelle Ka'e, Aurelie Kengni, Naomi Karell Etame, Larissa Gaelle Moko, Evariste Molimbou, Rachel Audrey Nayang Mundo, Michel Tommo, Nadine Fainguem, Lionele Mba Fotsing, Luna Colagrossi, Claudia Alteri, Dorine Ngono, John Otokoye Otshudiema, Clement Ndongmo, Yap Boum, Georges Mballa Etoundi, Edie G.E. Halle, Emmanuel Eben-Moussi, Carla Montesano, Anne-Genevieve Marcelin, Vittorio Colizzi, Carlo-Federico Perno, Alexis Ndjolo, and Nicaise Ndembi

Subjects
SARS-CoV-2, Variants of concern, SNPsig®EscapePLEX CE, Cameroon, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Background: Surveillance of SARS-CoV-2 variants of concern (VOCs) and lineages is crucial for decision-making. Our objective was to study the SARS-CoV-2 clade dynamics across epidemiological waves and evaluate the reliability of SNPsig® SARS-CoV-2 EscapePLEX CE in detecting VOCs in Cameroon. Material and methods: A laboratory-based study was conducted on SARS-CoV-2 positive nasopharyngeal specimens cycle threshold (Ct)≤30 at the Chantal BIYA International Reference Centre in Yaoundé-Cameroon, between April-2020 to August-2022. Samples were analyzed in parallel with Sanger sequencing and (SNPsig® SARS-CoV-2 EscapePLEX CE), and performance characteristics were evaluated by Cohen's coefficient and McNemar test. Results: Of the 130 sequences generated, SARS-CoV-2 clades during wave-1 (April–November 2020) showed 97 % (30/31) wild-type lineages and 3 % (1/31) Gamma-variant; wave-2 (December-2020 to May-2021), 25 % (4/16) Alpha-variant, 25 % (4/16) Beta-variant, 44 % (7/16) wild-type and 6 % (1/16) mu; wave-3 (June–October 2021), 94 % (27/29) Delta-variant, 3 % (1/29) Alpha-variant, 3 % (1/29) wild-type; wave-4 (November-2021 to August-2022), 98 % (53/54) Omicron-variant and 2 % (1/54) Delta-variant. Omicron sub-variants were BA.1 (47 %), BA.5 (34 %), BA.2 (13 %) and BA.4 (6 %). Globally, the two genotyping methods accurately identified the SARS-CoV-2 VOCs (P = 0.17, McNemar test; Ka = 0.67). Conclusion: Genomic surveillance reveals a rapid dynamic in SARS-CoV-2 strains between epidemiological waves in Cameroon. For wide-spread variant surveillance in resource-limited settings, SNPsig® SARS-CoV-2 EscapePLEX CEkit represents a suitable tool, pending upgrading for distinguishing Omicron sub-lineages.

Published
2024
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45. Multiple scattering of channeled and non-channeled positively charged particles in bent monocrystalline silicon

Author

Scandale, W., Arduini, G., Cerutti, F., Esposito, L. S., Garattini, M., Gilardoni, S., Losito, R., Masi, A., Mirarchi, D., Montesano, S., Redaelli, S., Rossi, R., Smirnov, G., Burmistrov, L., Dubos, S., Puill, V., Stocchi, A., Bandiera, L., Guidi, V., Mazzolari, A., Romagnoni, M., Murtas, F., Addesa, F., Cavoto, G., Iacoangeli, F., Galluccio, F., Afonin, A. G., Chesnokov, Yu. A., Durum, A. A., Maisheev, V. A., Sandomirskiy, Yu. E., Yanovich, A. A., Kovalenko, A. D., Taratin, A. M., Denisov, A. S., Gavrikov, Yu. A., Ivanov, Yu. M., Malyarenko, L. G., Borg, J., James, T., Hall, G., and Pesaresi, M.

Subjects
Physics - Accelerator Physics
Abstract

We present the results of an experimental study of multiple scattering of positively charged high energy particles in bent samples of monocrystalline silicon. This work confirms the recently discovered effect of a strong reduction in the rms multiple scattering angle of particles channeled in the silicon (111) plane. The effect is observed in the plane orthogonal to the bending plane. We show in detail the influence of angular constraints on the magnitude of the effect. Comparison of the multiple scattering process at different energies indicates a violation of the law of inverse proportionality of the rms angle of channeled particles with energy. By increasing the statistics, we have improved the results of multiple scattering measurements for particles moving, but not channeled, in silicon crystals., Comment: arXiv admin note: text overlap with arXiv:1910.00250 minor fixes

Published
2022

46. The Association of Urinary Sodium Excretion with Glaucoma and Related Traits in a Large United Kingdom Population

Author

Aschard, Hugues, Chia, Mark, Chua, Sharon, Do, Ron, Foster, Paul, Kang, Jae, Kastner, Alan, Khawaja, Anthony, Kim, Jihye, Lentjes, Marleen, Luben, Robert, Madjedi, Kian, Montesano, Giovanni, Pasquale, Louis, Stuart, Kelsey, Warwick, Alasdair, Wiggs, Janey, Allen, Naomi, Aslam, Tariq, Atan, Denize, Barman, Sarah, Barrett, Jenny, Bishop, Paul, Black, Graeme, Braithwaite, Tasanee, Carare, Roxana, Chakravarthy, Usha, Chan, Michelle, Day, Alexander, Desai, Parul, Dhillon, Bal, Dick, Andrew, Doney, Alexander, Egan, Cathy, Ennis, Sarah, Fruttiger, Marcus, Garway-Heath, David (Ted), Gibson, Jane, Guggenheim, Jeremy, Hammond, Chris, Hardcastle, Alison, Harding, Simon, Hogg, Ruth, Hysi, Pirro, Keane, Pearse, Khaw, Peng Tee, Lascaratos, Gerassimos, Littlejohns, Thomas, Lotery, Andrew, Luthert, Phil, MacGillivray, Tom, Mackie, Sarah, McGuinness, Bernadette, McKay, Gareth, McKibbin, Martin, Moore, Tony, Morgan, James, O'Sullivan, Eoin, Oram, Richard, Owen, Chris, Patel, Praveen, Paterson, Euan, Peto, Tunde, Petzold, Axel, Pontikos, Nikolas, Rahi, Jugnoo, Rudnicka, Alicja, Sattar, Naveed, Self, Jay, Sergouniotis, Panagiotis, Sivaprasad, Sobha, Steel, David, Stratton, Irene, Strouthidis, Nicholas, Sudlow, Cathie, Sun, Zihan, Tapp, Robyn, Thomas, Dhanes, Trucco, Emanuele, Tufail, Adnan, Viswanathan, Ananth, Vitart, Veronique, Weedon, Mike, Williams, Katie, Williams, Cathy, Woodside, Jayne, Yates, Max, Yip, Jennifer, Zheng, Yalin, Aung, Tin, Burdon, Kathryn, Chen, Li, Cheng, Ching-Yu, Craig, Jamie, Cree, Angela, de Vries, Victor, Driessen, Sjoerd, Fingert, John, Gharahkhani, Puya, Hammond, Christopher, Hayward, Caroline, Hewitt, Alex, Jansonius, Nomdo, Jonansson, Fridbert, Jonas, Jost, Kass, Michael, Khor, Chiea, Klaver, Caroline, Koh, Jacyline, MacGregor, Stuart, Mackey, David, Mitchell, Paul, Pang, Calvin, Pasutto, Francesca, Pfeiffer, Norbert, Polašek, Ozren, Ramdas, Wishal, Schuster, Alexander, Segrè, Ayellet, Stefansson, Einer, Stefánsson, Kári, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, van Duijn, Cornelia, Vergroesen, Joëlle, Vithana, Eranga, Wilson, James, Wojciechowski, Robert, Wong, Tien, Young, Terri, Stuart, Kelsey V., Biradar, Mahantesh I., Luben, Robert N., Dhaun, Neeraj, Wagner, Siegfried K., Warwick, Alasdair N., Madjedi, Kian M., Pasquale, Louis R., Wiggs, Janey L., Kang, Jae H., Lentjes, Marleen A.H., Foster, Paul J., and Khawaja, Anthony P.

Published
2024
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47. Relationship between Intraocular Pressure Fluctuation and Visual Field Progression Rates in the United Kingdom Glaucoma Treatment Study

Author

Garway-Heath, David F., Crabb, David P., Bunce, Catey, Lascaratos, Gerassimos, Amalfitano, Francesca, Anand, Nitin, Azuara-Blanco, Augusto, Bourne, Rupert R., Broadway, David C., Cunliffe, Ian A., Diamond, Jeremy P., Fraser, Scott G., Ho, Tuan A., Martin, Keith R., McNaught, Andrew I., Negi, Anil, Patel, Krishna, Russell, Richard A., Shah, Ameet, Spry, Paul G., Suzuki, Katsuyoshi, White, Edward T., Wormald, Richard P., Xing, Wen, Zeyen, Thierry G., Rabiolo, Alessandro, and Montesano, Giovanni

Published
2024
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