Search results for: Piedad Lucia Bolivar Goez

Authors: Christina Klippel, Lucia Pezzi, Silvio Neto, Rafael Bertani, Priscila Mendes, Flavio Machado, Aline Szeliga, Maria Cosendey, Adilson Mariz, Raquel Santos, Lys Bendett, Pedro Velasco, Thalita Rolleigh, Bruna Bellote, Daria Coelho, Bruna Martins, Julia Almeida, Juliana Cerqueira

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This project presents a framework for teaching intracranial pressure monitoring (ICP) concepts using a low-cost experimental model in a neurointensive care education program. Data concerning ICP monitoring contribute to the patient's clinical assessment and may dictate the course of action of a health team (nursing, medical staff) and influence decisions to determine the appropriate intervention. This study aims to present a safe method for teaching ICP monitoring to medical students in a Simulation Center. Methodology: Medical school teachers, along with students from the 4th year, built an experimental model for teaching ICP measurement. The model consists of a mannequin's head with a plastic bag inside simulating the cerebral ventricle and an inserted ventricular catheter connected to the ICP monitoring system. The bag simulating the ventricle can also be changed for others containing bloody or infected simulated cerebrospinal fluid. On the mannequin's ear, there is a blue point indicating the right place to set the "zero point" for accurate pressure reading. The educational program includes four steps: 1st - Students receive a script on ICP measurement for reading before training; 2nd - Students watch a video about the subject created in the Simulation Center demonstrating each step of the ICP monitoring and the proper care, such as: correct positioning of the patient, anatomical structures to establish the zero point for ICP measurement and a secure range of ICP; 3rd - Students train the procedure in the model. Teachers help students during training; 4th - Student assessment based on a checklist form. Feedback and correction of wrong actions. Results: Students expressed interest in learning ICP monitoring. Tests concerning the hit rate are still being performed. ICP's final results and video will be shown at the event. Conclusion: The study of intracranial pressure measurement based on an experimental model consists of an effective and controlled method of learning and research, more appropriate for teaching neurointensive care practices. Assessment based on a checklist form helps teachers keep track of student learning progress. This project offers medical students a safe method to develop intensive neurological monitoring skills for clinical assessment of patients with neurological disorders.

Keywords: neurology, intracranial pressure, medical education, simulation

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Authors: Akhentoolove Corbin, Leta De Jonge, Charmaine De Jonge

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Introduction: Various writers have promoted the adoption of the 4th R in the education curricula (relationships, respect, reasoning, religion, computing, science, art, conflict management, music) and the 5th R (responsibility). They argue that the traditional 3 Rs are not adequate for the modern environment and the requirements for students to become functional citizens in society. In particular, the developing countries of the anglophone Caribbean (most of which are tiny islands) are susceptible to the dangers and complexities of climate change and global economic volatility. These proposed additions to the 3Rs do have some justification, but this research considers Resilience as even more important and relevant in a world that is faced with the negative prospects of climate change, poverty, discrimination, and economic volatility. It is argued that the foundation for resilient citizens, workers, and workplaces, must be built in the elementary and secondary/middle schools and then through the tertiary level, to achieve an outcome of more resilient students. Government, business, and society require widespread resilience to be capable of ‘bouncing back’ and be more adaptable, transformational, and sustainable. Methodology: The paper utilises a mixed-methods approach incorporating a questionnaire and interviews to determine participants’ opinions on the importance and relevance of resilience in the schools’ curricula and to government, business, and society. The target groups are as follows: educators at all levels, education administrators, members of the business sector, public sector, and 3rd sector. The research specifically targets the anglophone Caribbean developing countries (Barbados, Guyana, Jamaica, Trinidad, St. Lucia, and St Vincent, and the Grenadines). The research utilises SPSS for data analysis. Major Findings: The preliminary findings suggest that the majority of participants support the adoption of resilience as a 4th R in the curricula of the elementary, secondary/middle schools, and tertiary level in the anglophone Caribbean. The final results will allow the researchers to reveal more specific details on any variations among the islands in the sample andto engage in an in-depth discussion of the relevance and importance of resilience as the 4th R. Conclusion: Results seem to suggest that the education system should adopt the 4th R of resilience so that educators working in collaboration with the family and community/village can develop young citizens who are more resilient and capable of manifesting the behaviours and attitudes associated with ‘bouncing back,’ adaptability, transformation, and sustainability. These findings may be useful for education decision-makers and governments in these Caribbean islands, who have the authority and responsibility for the development of education policy, laws, and regulations.

Keywords: education, resilient students, adaptable, transformational, resilient citizens, workplaces, government

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Authors: Daniela Manila Bianchi, Samantha Lupi, Elisa Barcucci, Sandra Fragassi, Clara Tramuta, Lucia Decastelli

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Introduction: The undeclared allergens detection in food products plays a fundamental role in the safety of the allergic consumer. The protection of allergic consumers is guaranteed, in Europe, by Regulation (EU) No 1169/2011 of the European Parliament, which governs the consumer's right to information and identifies 14 food allergens to be mandatorily indicated on food labels: among these, an egg is included. An egg can be present as an ingredient or as contamination in raw and cooked products. The main allergen egg proteins are ovomucoid, ovalbumin, lysozyme, and ovotransferrin. This study presents the results of a survey conducted in Northern Italy aimed at detecting the presence of undeclared egg proteins in food matrices in the latest ten years (2011-2021). Method: In the period January 2011 - October 2021, a total of 1205 different types of food matrices (ready-to-eat, meats, and meat products, bakery and pastry products, baby foods, food supplements, pasta, fish and fish products, preparations for soups and broths) were delivered to Food Control Laboratory of Istituto Zooprofilattico Sperimentale of Piemonte Liguria and Valle d’Aosta to be analyzed as official samples in the frame of Regional Monitoring Plan of Food Safety or in the contest of food poisoning. The laboratory is ISO 17025 accredited, and since 2019, it has represented the National Reference Centre for the detection in foods of substances causing food allergies or intolerances (CreNaRiA). All samples were stored in the laboratory according to food business operator instructions and analyzed within the expiry date for the detection of undeclared egg proteins. Analyses were performed with RIDASCREEN®FAST Ei/Egg (R-Biopharm ® Italia srl) kit: the method was internally validated and accredited with a Limit of Detection (LOD) equal to 2 ppm (mg/Kg). It is a sandwich enzyme immunoassay for the quantitative analysis of whole egg powder in foods. Results: The results obtained through this study showed that egg proteins were found in 2% (n. 28) of food matrices, including meats and meat products (n. 16), fish and fish products (n. 4), bakery and pastry products (n. 4), pasta (n. 2), preparations for soups and broths (n.1) and ready-to-eat (n. 1). In particular, in 2011 egg proteins were detected in 5% of samples, in 2012 in 4%, in 2013, 2016 and 2018 in 2%, in 2014, 2015 and 2019 in 3%. No egg protein traces were detected in 2017, 2020, and 2021. Discussion: Food allergies occur in the Western World in 2% of adults and up to 8% of children. Allergy to eggs is one of the most common food allergies in the pediatrics context. The percentage of positivity obtained from this study is, however, low. The trend over the ten years has been slightly variable, with comparable data.

Keywords: allergens, food, egg proteins, immunoassay

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Authors: Paula I. Buonfiglio, Carlos David Bruque, Lucia Salatino, Vanesa Lotersztein, Sebastián Menazzi, Paola Plazas, Ana Belén Elgoyhen, Viviana Dalamón

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Hearing loss (HL) is the most prevalent sensorineural disorder affecting about 10% of the global population, with more than half due to genetic causes. About 1 in 500-1000 newborns present congenital HL. Most of the patients are non-syndromic with an autosomal recessive mode of inheritance. To date, more than 100 genes are related to HL. Therefore, the Whole-exome sequencing (WES) technique has become a cost-effective alternative approach for molecular diagnosis. Nevertheless, new challenges arise from the detection of novel variants, in particular missense changes, which can lead to a spectrum of genotype-to-phenotype correlations, which is not always straightforward. In this work, we aimed to identify the genetic causes of HL in isolated and familial cases by designing a multistep approach to analyze target genes related to hearing impairment. Moreover, we performed in silico and in vivo analyses in order to further study the effect of some of the novel variants identified in the hair cell function using the zebrafish model. A total of 650 patients were studied by Sanger Sequencing and Gap-PCR in GJB2 and GJB6 genes, respectively, diagnosing 15.5% of sporadic cases and 36% of familial ones. Overall, 50 different sequence variants were detected. Fifty of the undiagnosed patients with moderate HL were tested for deletions in STRC gene by Multiplex ligation-dependent probe amplification technique (MLPA), leading to 6% of diagnosis. After this initial screening, 50 families were selected to be analyzed by WES, achieving diagnosis in 44% of them. Half of the identified variants were novel. A missense variant in MYO6 gene detected in a family with postlingual HL was selected to be further analyzed. A protein modeling with AlphaFold2 software was performed, proving its pathogenic effect. In order to functionally validate this novel variant, a knockdown phenotype rescue assay in zebrafish was carried out. Injection of wild-type MYO6 mRNA in embryos rescued the phenotype, whereas using the mutant MYO6 mRNA (carrying c.2782C>A variant) had no effect. These results strongly suggest the deleterious effect of this variant on the mobility of stereocilia in zebrafish neuromasts, and hence on the auditory system. In the present work, we demonstrated that our algorithm is suitable for the sequential multigenic approach to HL in our cohort. These results highlight the importance of a combined strategy in order to identify candidate variants as well as the in silico and in vivo studies to analyze and prove their pathogenicity and accomplish a better understanding of the mechanisms underlying the physiopathology of the hearing impairment.

Keywords: diagnosis, genetics, hearing loss, in silico analysis, in vivo analysis, WES, zebrafish

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Lucia Billeci, Gennaro Tartarisco, Maurizio Varanini

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Fetal cardiac monitoring by fetal electrocardiogram (fECG) can provide significant clinical information about the healthy condition of the fetus. Despite this potentiality till now the use of fECG in clinical practice has been quite limited due to the difficulties in its measuring. The recovery of fECG from the signals acquired non-invasively by using electrodes placed on the maternal abdomen is a challenging task because abdominal signals are a mixture of several components and the fetal one is very weak. This paper presents an approach for fECG extraction from abdominal maternal recordings, which exploits the characteristics of pseudo-periodicity of fetal ECG. It consists of devising a quality index (fQI) for fECG and of finding the linear combinations of preprocessed abdominal signals, which maximize these fQI (quality index optimization - QIO). It aims at improving the performances of the most commonly adopted methods for fECG extraction, usually based on maternal ECG (mECG) estimating and canceling. The procedure for the fECG extraction and fetal QRS (fQRS) detection is completely unsupervised and based on the following steps: signal pre-processing; maternal ECG (mECG) extraction and maternal QRS detection; mECG component approximation and canceling by weighted principal component analysis; fECG extraction by fQI maximization and fetal QRS detection. The proposed method was compared with our previously developed procedure, which obtained the highest at the Physionet/Computing in Cardiology Challenge 2013. That procedure was based on removing the mECG from abdominal signals estimated by a principal component analysis (PCA) and applying the Independent component Analysis (ICA) on the residual signals. Both methods were developed and tuned using 69, 1 min long, abdominal measurements with fetal QRS annotation of the dataset A provided by PhysioNet/Computing in Cardiology Challenge 2013. The QIO-based and the ICA-based methods were compared in analyzing two databases of abdominal maternal ECG available on the Physionet site. The first is the Abdominal and Direct Fetal Electrocardiogram Database (ADdb) which contains the fetal QRS annotations thus allowing a quantitative performance comparison, the second is the Non-Invasive Fetal Electrocardiogram Database (NIdb), which does not contain the fetal QRS annotations so that the comparison between the two methods can be only qualitative. In particular, the comparison on NIdb was performed defining an index of quality for the fetal RR series. On the annotated database ADdb the QIO method, provided the performance indexes Sens=0.9988, PPA=0.9991, F1=0.9989 overcoming the ICA-based one, which provided Sens=0.9966, PPA=0.9972, F1=0.9969. The comparison on NIdb was performed defining an index of quality for the fetal RR series. The index of quality resulted higher for the QIO-based method compared to the ICA-based one in 35 records out 55 cases of the NIdb. The QIO-based method gave very high performances with both the databases. The results of this study foresees the application of the algorithm in a fully unsupervised way for the implementation in wearable devices for self-monitoring of fetal health.

Keywords: fetal electrocardiography, fetal QRS detection, independent component analysis (ICA), optimization, wearable

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Authors: Jimena Alarcon, Andrea Llorens, Gabriel Hernandez, Maritza Palma, Lucia Navarrete

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The research has funding from the Government of Chile and is focused on defining the design of rural primary classroom that stimulates creativity. The relevance of the study consists of its capacity to define adequate educational spaces for the implementation of the design-based learning (DBL) methodology. This methodology promotes creativity and teamwork, generating a meaningful learning experience for students, based on the appreciation of their environment and the generation of projects that contribute positively to their communities; also, is an inquiry-based form of learning that is based on the integration of design thinking and the design process into the classroom. The main goal of the study is to define the design characteristics of rural primary school classrooms, associated with the implementation of the DBL methodology. Along with the change in learning strategies, it is necessary to change the educational spaces in which they develop. The hypothesis indicates that a change in the space and equipment of the classrooms based on the emotions of the students will motivate better learning results based on the implementation of a new methodology. In this case, the pedagogical dynamics require an important interaction between the participants, as well as an environment favorable to creativity. Methodologies from Kansei engineering are used to know the emotional variables associated with their definition. The study is done to 50 students between 6 and 10 years old (average age of seven years), 48% of men and 52% women. Virtual three-dimensional scale models and semantic differential tables are used. To define the semantic differential, self-applied surveys were carried out. Each survey consists of eight separate questions in two groups: question A to find desirable emotions; question B related to emotions. Both questions have a maximum of three alternatives to answer. Data were tabulated with IBM SPSS Statistics version 19. Terms referred to emotions are grouped into twenty concepts with a higher presence in surveys. To select the values obtained as part of the implementation of Semantic Differential, a number expected of 'chi-square test (x2)' frequency calculated for classroom space is considered lower limit. All terms over the N expected a cut point, are included to prepare tables for surveys to find a relation between emotion and space. Statistic contrast (Chi-Square) represents significance level ≥ 0, indicator that frequencies appeared are not random. Then, the most representative terms depend on the variable under study: a) definition of textures and color of vertical surfaces is associated with emotions such as tranquility, attention, concentration, creativity; and, b) distribution of the equipment of the rooms, with emotions associated with happiness, distraction, creativity, freedom. The main findings are linked to the generation of classrooms according to diverse DBL team dynamics. Kansei engineering is the appropriate methodology to know the emotions that students want to feel in the classroom space.

Keywords: creativity, design-based learning, education spaces, emotions

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Authors: Lucia Liu, Matthew Koziol

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Obsessive-compulsive disorder (OCD), a long-lasting anxiety disorder involving recurrent, intrusive thoughts, affects over 2 million adults in the United States. Transcranial magnetic stimulation (TMS) stands out as a noninvasive, cutting-edge therapy that has been shown to reduce symptoms in patients with treatment-resistant OCD. The Food and Drug Administration (FDA) approved protocol pairs TMS sessions with individualized symptom provocation, aiming to improve the susceptibility of brain circuits to stimulation. However, limited standardization or guidance exists on how to conduct symptom provocation and which methods are most effective. This study aims to compare the effect of internal versus external techniques to induce obsessional stress in a clinical setting during TMS therapy. Two symptom provocation methods, (i) Asking patients thought-provoking questions about their obsessions (internal) and (ii) Requesting patients to perform obsession-related tasks (external), were employed in a crossover design with repeated measurement. Thirty-six treatments of NeuroStar TMS were administered to each of two patients over 8 weeks in an outpatient clinic. Patient One received 18 sessions of internal provocation followed by 18 sessions of external provocation, while Patient Two received 18 sessions of external provocation followed by 18 sessions of internal provocation. The primary outcome was the level of self-reported obsessional stress on a visual analog scale from 1 to 10. The secondary outcome was self-reported OCD severity, collected biweekly in a four-level Likert-scale (1 to 4) of bad, fair, good and excellent. Outcomes were compared and tested between provocation arms through repeated measures ANOVA, accounting for intra-patient correlations. Ages were 42 for Patient One (male, White) and 57 for Patient Two (male, White). Both patients had similar moderate symptoms at baseline, as determined through the Yale-Brown Obsessive Compulsive Scale (YBOCS). When comparing obsessional stress induced across the two arms of internal and external provocation methods, the mean (SD) was 6.03 (1.18) for internal and 4.01 (1.28) for external strategies (P=0.0019); ranges were 3 to 8 for internal and 2 to 8 for external strategies. Internal provocation yielded 5 (31.25%) bad, 6 (33.33%) fair, 3 (18.75%) good, and 2 (12.5%) excellent responses for OCD status, while external provocation yielded 5 (31.25%) bad, 9 (56.25%) fair, 1 (6.25%) good, and 1 (6.25%) excellent responses (P=0.58). Internal symptom provocation tactics had a significantly stronger impact on inducing obsessional stress and led to better OCD status (non-significant). This could be attributed to the fact that answering questions may prompt patients to reflect more on their lived experiences and struggles with OCD. In the future, clinical trials with larger sample sizes are warranted to validate this finding. Results support the increased integration of internal methods into structured provocation protocols, potentially reducing the time required for provocation and achieving greater treatment response to TMS.

Keywords: obsessive-compulsive disorder, transcranial magnetic stimulation, mental health, symptom provocation

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Authors: Cristina Diaz, Lucia Perez, Simone Visigalli, Giuseppe Di Florio, Gonzalo Fuentes, Roberto Canziani, Paolo Gronchi

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During the last 50 years, the selection of materials is one of the main decisions in machine design for different industrial applications. It is due to numerous physical, chemical, mechanical and technological factors to consider in it. Corrosion effects are related with all of these factors and impact in the life cycle, machine incidences and the costs for the life of the machine. Corrosion affects the deterioration or destruction of metals due to the reaction with the environment, generally wet. In food industry, dewatering industry, concrete industry, paper industry, etc. corrosion is an unsolved problem and it might introduce some alterations of some characteristics in the final product. Nowadays, depending on the selected metal, its surface and its environment of work, corrosion prevention might be a change of metal, use a coating, cathodic protection, use of corrosion inhibitors, etc. In the vast majority of the situations, use of a corrosion resistant material or in its defect, a corrosion protection coating is the solution. Stainless steels are widely used in machine design, because of their strength, easily cleaned capacity, corrosion resistance and appearance. Typical used are AISI 304 and AISI 316. However, their benefits don’t fit every application, and some coatings are required against corrosion such as some paintings, galvanizing, chrome plating, SiO₂, TiO₂ or ZrO₂ coatings, etc. In this work, some coatings based in a bilayer made of Titanium-Tantalum, Titanium-Niobium, Titanium-Hafnium or Titanium-Zirconium, have been developed used magnetron sputtering configuration by PVD (Physical Vapor Deposition) technology, for trying to reduce corrosion effects on AISI 304, AISI 316 and comparing it with Titanium alloy substrates. Ti alloy display exceptional corrosion resistance to chlorides, sour and oxidising acidic media and seawater. In this study, Ti alloy (99%) has been included for comparison with coated AISI 304 and AISI 316 stainless steel. Corrosion tests were conducted by a Gamry Instrument under ASTM G5-94 standard, using different electrolytes such as tomato salsa, wine, olive oil, wet compost, a mix of sand and concrete with water and NaCl for testing corrosion in different industrial environments. In general, in all tested environments, the results showed an improvement of corrosion resistance of all coated AISI 304 and AISI 316 stainless steel substrates when they were compared to uncoated stainless steel substrates. After that, comparing these results with corrosion studies on uncoated Ti alloy substrate, it was observed that in some cases, coated stainless steel substrates, reached similar current density that uncoated Ti alloy. Moreover, Titanium-Zirconium and Titanium-Tantalum coatings showed for all substrates in study including coated Ti alloy substrates, a reduction in current density more than two order in magnitude. As conclusion, Ti-Ta, Ti-Zr, Ti-Nb and Ti-Hf coatings have been developed for improving corrosion resistance of AISI 304 and AISI 316 materials. After corrosion tests in several industry environments, substrates have shown improvements on corrosion resistance. Similar processes have been carried out in Ti alloy (99%) substrates. Coated AISI 304 and AISI 316 stainless steel, might reach similar corrosion protection on the surface than uncoated Ti alloy (99%). Moreover, coated Ti Alloy (99%) might increase its corrosion resistance using these coatings.

Keywords: coatings, corrosion, PVD, stainless steel

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Authors: Michela Del Vicario, Walter Quattrociocchi, Antonio Scala, Ana Lucía Schmidt, Fabiana Zollo

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Information, rumors, and debates may shape and impact public opinion heavily. In the latest years, several concerns have been expressed about social influence on the Internet and the outcome that online debates might have on real-world processes. Indeed, on online social networks users tend to select information that is coherent to their system of beliefs and to form groups of like-minded people –i.e., echo chambers– where they reinforce and polarize their opinions. In this way, the potential benefits coming from the exposure to different points of view may be reduced dramatically, and individuals' views may become more and more extreme. Such a context fosters misinformation spreading, which has always represented a socio-political and economic risk. The persistence of unsubstantiated rumors –e.g., the hypothetical and hazardous link between vaccines and autism– suggests that social media do have the power to misinform, manipulate, or control public opinion. As an example, current approaches such as debunking efforts or algorithmic-driven solutions based on the reputation of the source seem to prove ineffective against collective superstition. Indeed, experimental evidence shows that confirmatory information gets accepted even when containing deliberately false claims while dissenting information is mainly ignored, influences users’ emotions negatively and may even increase group polarization. Moreover, confirmation bias has been shown to play a pivotal role in information cascades, posing serious warnings about the efficacy of current debunking efforts. Nevertheless, mitigation strategies have to be adopted. To generalize the problem and to better understand social dynamics behind information spreading, in this work we rely on a tight quantitative analysis to investigate the behavior of more than 300M users w.r.t. news consumption on Facebook over a time span of six years (2010-2015). Through a massive analysis on 920 news outlets pages, we are able to characterize the anatomy of news consumption on a global and international scale. We show that users tend to focus on a limited set of pages (selective exposure) eliciting a sharp and polarized community structure among news outlets. Moreover, we find similar patterns around the Brexit –the British referendum to leave the European Union– debate, where we observe the spontaneous emergence of two well segregated and polarized groups of users around news outlets. Our findings provide interesting insights into the determinants of polarization and the evolution of core narratives on online debating. Our main aim is to understand and map the information space on online social media by identifying non-trivial proxies for the early detection of massive informational cascades. Furthermore, by combining users traces, we are finally able to draft the main concepts and beliefs of the core narrative of an echo chamber and its related perceptions.

Keywords: information spreading, misinformation, narratives, online social networks, polarization

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Authors: Morello Sara, Pederiva Sabina, Bianchi Manila, Martucci Francesca, Marchis Daniela, Decastelli Lucia

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Vegetables represent an integral part of a healthy diet due to their valuable nutritional properties and the growth in consumer demand in recent years is particularly remarkable for a diet rich in vitamins and micronutrients. However, plant-based products are involved in several food outbreaks connected to various sources of contamination and quite often, bacteria responsible for side effects showed high resistance to antibiotics. The abuse of antibiotics can be one of the main mechanisms responsible for increasing antibiotic resistance (AR). Plants grown for food use can be contaminated directly by spraying antibiotics on crops or indirectly by treatments with antibiotics due to the use of manure, which may contain both antibiotics and genes of antibiotic resistance (ARG). Antibiotic residues could represent a potential way of human health risk due to exposure through the consumption of plant-based foods. The presence of antibiotic-resistant bacteria might pose a particular risk to consumers. The present work aims to investigate through a multidisciplinary approach the occurrence of ARG by means of a biomolecular approach (PCR) and the prevalence of antibiotic residues using a multi residues LC-MS/MS method, both in different plant-based products. During the period from July 2020 to October 2021, a total of 74 plant samples (33 lettuces and 41 tomatoes) were collected from 57 farms located throughout the Piedmont area, and18 out of 74 samples (11 lettuces and 7 tomatoes) were selected to LC-MS/MS analyses. DNA extracted (ExtractME, Blirt, Poland) from plants used on crops and isolated bacteria were analyzed with 6 sets of end-point multiplex PCR (Qiagen, Germany) to detect the presence of resistance genes of the main antibiotic families, such as tet genes (tetracyclines), bla (β-lactams) and mcr (colistin). Simultaneous detection of 43 molecules of antibiotics belonging to 10 different classes (tetracyclines, sulphonamides, quinolones, penicillins, amphenicols, macrolides, pleuromotilines, lincosamides, diaminopyrimidines) was performed using Exion LC system AB SCIEX coupled to a triple quadrupole mass spectrometer QTRAP 5500 from AB SCIEX. The PCR assays showed the presence of ARG in 57% (n=42): tetB (4.8%; n=2), tetA (9.5%; n=4), tetE (2.4%; n=1), tetL (12%; n=5), tetM (26%; n=11), blaSHV (21.5%; n=9), blaTEM (4.8%; n =2) and blaCTX-M (19%; n=8). In none of the analyzed samples was the mcr gene responsible for colistin resistance detected. Results obtained from LC-MS/MS analyses showed that none of the tested antibiotics appear to exceed the LOQ (100 ppb). Data obtained confirmed the presence of bacterial populations containing antibiotic resistance determinants such as tet gene (tetracycline) and bla genes (beta-lactams), widely used in human medicine, which can join the food chain and represent a risk for consumers, especially with raw products. The presence of traces of antibiotic residues in vegetables, in concentration below the LOQ of the LC-MS/MS method applied, cannot be excluded. In conclusion, traces of antibiotic residues could be a health risk to the consumer due to potential involvement in the spread of AR. PCR represents a useful and effective approach to characterize and monitor AR carried by bacteria from the entire food chain.

Keywords: plant-based products, ARG, PCR, antibiotic residues

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Authors: Antonio Boggia, Luisa Paolotti, Gianluca Massei, Lucia Rocchi, Elaine Pace, Maria Attard

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The aim of this paper is to present a methodology and a computer model for sustainability assessment based on the integration of Multi-criteria Decision Analysis (MCDA) with a Geographic Information System (GIS). It presents the result of a study for the implementation of a model for measuring sustainability to address the policy actions for the improvement of sustainability at territory level. The aim is to rank areas in order to understand the specific technical and/or financial support that is required to develop sustainable growth. Assessing sustainable development is a multidimensional problem: economic, social and environmental aspects have to be taken into account at the same time. The tool for a multidimensional representation is a proper set of indicators. The set of indicators must be integrated into a model, that is an assessment methodology, to be used for measuring sustainability. The model, developed by the Environmental Laboratory of the University of Perugia, is called GeoUmbriaSUIT. It is a calculation procedure developed as a plugin working in the open-source GIS software QuantumGIS. The multi-criteria method used within GeoUmbriaSUIT is the algorithm TOPSIS (Technique for Order Preference by Similarity to Ideal Design), which defines a ranking based on the distance from the worst point and the closeness to an ideal point, for each of the criteria used. For the sustainability assessment procedure, GeoUmbriaSUIT uses a geographic vector file where the graphic data represent the study area and the single evaluation units within it (the alternatives, e.g. the regions of a country, or the municipalities of a region), while the alphanumeric data (attribute table), describe the environmental, economic and social aspects related to the evaluation units by means of a set of indicators (criteria). The use of the algorithm available in the plugin allows to treat individually the indicators representing the three dimensions of sustainability, and to compute three different indices: environmental index, economic index and social index. The graphic output of the model allows for an integrated assessment of the three dimensions, avoiding aggregation. The presence of separate indices and graphic output make GeoUmbriaSUIT a readable and transparent tool, since it doesn’t produce an aggregate index of sustainability as final result of the calculations, which is often cryptic and difficult to interpret. In addition, it is possible to develop a “back analysis”, able to explain the positions obtained by the alternatives in the ranking, based on the criteria used. The case study presented is an assessment of the level of sustainability in the six regions of Malta, an island state in the middle of the Mediterranean Sea and the southernmost member of the European Union. The results show that the integration of MCDA-GIS is an adequate approach for sustainability assessment. In particular, the implemented model is able to provide easy to understand results. This is a very important condition for a sound decision support tool, since most of the time decision makers are not experts and need understandable output. In addition, the evaluation path is traceable and transparent.

Keywords: GIS, multi-criteria analysis, sustainability assessment, sustainable development

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Authors: Tramuta Clara, Masotti Chiara, Pitti Monica, Adriano Daniela, Battistini Roberta, Serraca Laura, Decastelli Lucia

Abstract:

Oysters are considered filter organisms, and their raw consumption may increase health risks for consumers: it is often associated with outbreaks of gastroenteritis or enteric illnesses. Most of these foodborne diseases are caused by Vibrio strains, enteric pathogens also involved in the diffusion of genetic determinants of antibiotic resistance and their entrance along the food chain. The European Food Safety Authority (EFSA), during the European Union report on antimicrobial resistance in 2017, focused the attention about the role of food as a possible carrier of antibiotic-resistant bacteria or antibiotic-resistance genes that determine health risks for humans. This study wants to determine antibiotic resistance and antibiotic-resistance genes in Vibrio spp. isolated from Crassostrea gigas oysters collected in the Golfo della Spezia (Liguria, Italy). A total of 47 Vibrio spp. strains were isolated (ISO21872-2:2017) during the summer of 2021 from oysters of Crassostrea gigas. The strains were identified by MALDI-TOF (Bruker, Germany) mass spectrometry and tested for antibiotic susceptibility using a broth microdiluition method (ISO20776-1:2019) using Sensititre EUVSEC plates (Thermo-Fisher Scientific) to obtain the Minimum Inhibitory Concentration (MIC). The strains were tested with PCR-based biomolecular methods, according to previous works, to define the presence of 23 resistance genes of the main classes of antibiotics used in human and veterinary medicine: tet (B), tet (C), tet (D), tet (A), tet (E), tet (G ), tet (K), tet (L), tet (M), tet (O), tet (S) (tetracycline resistance); blaCTX-M, blaTEM, blaOXA, blaSHV (β-lactam resistance); mcr-1 and mcr-2 (colistin resistance); qnrA, qnrB, and qnrS (quinolone resistance); sul1, sul2 and sul3 (sulfonamide resistance). Six different species have been identified: V. alginolyticus 34% (n=16), V. harveyi 28% (n=13), V. fortis 15% (n=7), V. pelagius 8% (n=4), V. parahaemolyticus 11% (n=5) e V. chagasii 4% (n=2). The PCR assays showed the presence of the blaTEM gene on 40% of the strains (n=19). All the other genes were not detected, except for a V. alginolyticus positive for anrS gene. The broth microdiluition method results showed an high level of resistance for ciprofloxacin (62%; n=29), ampicillin (47%; n=22), and colistin (49%; n=23). Furthermore, 32% (n=15) of strains can be considered multiresistant bacteria for the simultaneous presence of resistance for three different antibiotic classes. Susceptibility towards meropenem, azithromycin, gentamicin, ceftazidime, cefotaxime, chloramphenicol, tetracycline and sulphamethoxazole reached 100%. The Vibrio species identified in this study are widespread in marine environments and can cause gastrointerstinal infections after the ingestion of raw fish products and bivalve molluscs. The level of resistance to antibiotics such as ampicillin, ciprofloxacin and colistin can be connected to anthropic factors (industrial, agricultural and domestic wastes) that promote the spread of resistance to these antibiotics. It can be also observed a strong correlation between phenotypic (resistant MIC) and genotypic (positive blaTEM gene) resistance for ampicillin on the same strains, probably due to the transfer of genetic material between bacterial strains. Consumption of raw bivalve molluscs can represent a risk for consumers heath due to the potentially presence of foodborne pathogens, highly resistant to different antibiotics and source of transferable antibiotic-resistant genes.

Keywords: vibrio species, blaTEM genes, antimicrobial resistance, PCR

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Authors: Clara Tramuta, Lucia Decastelli, Elisa Barcucci, Sandra Fragassi, Samantha Lupi, Enrico Arletti, Melissa Bizzarri, Daniela Manila Bianchi

Abstract:

Introdution: Food allergies occurs, in the Western World, 2% of adults and up to 8% of children. The protection of allergic consumers is guaranted, in Eurrope, by Regulation (EU) No 1169/2011 of the European Parliament which governs the consumer's right to information and identifies 14 food allergens to be mandatory indicated on the label. Among these, mustard is a popular spice added to enhance the flavour and taste of foods. It is frequently present as an ingredient in spice blends, marinades, salad dressings, sausages, and other products. Hypersensitivity to mustard is a public health problem since the ingestion of even low amounts can trigger severe allergic reactions. In order to protect the allergic consumer, high performance methods are required for the detection of allergenic ingredients. Food safety laboratories rely on validated methods that detect hidden allergens in food to ensure the safety and health of allergic consumers. Here we present the test results for the validation and accreditation of a Real time PCR assay (RT-PCR: SPECIALfinder MC Mustard, Generon), for the detection of mustard traces in food. Materials and Methods. The method was tested on five classes of food matrices: bakery and pastry products (chocolate cookies), meats (ragù), ready-to-eat (mixed salad), dairy products (yogurt), grains, and milling products (rice and barley flour). Blank samples were spiked starting with the mustard samples (Sinapis Alba), lyophilized and stored at -18 °C, at a concentration of 1000 ppm. Serial dilutions were then prepared to a final concentration of 0.5 ppm, using the DNA extracted by ION Force FAST (Generon) from the blank samples. The Real Time PCR reaction was performed by RT-PCR SPECIALfinder MC Mustard (Generon), using CFX96 System (BioRad). Results. Real Time PCR showed a limit of detection (LOD) of 0.5 ppm in grains and milling products, ready-to-eat, meats, bakery, pastry products, and dairy products (range Ct 25-34). To determine the exclusivity parameter of the method, the ragù matrix was contaminated with Prunus dulcis (almonds), peanut (Arachis hypogaea), Glycine max (soy), Apium graveolens (celery), Allium cepa (onion), Pisum sativum (peas), Daucus carota (carrots), and Theobroma cacao (cocoa) and no cross-reactions were observed. Discussion. In terms of sensitivity, the Real Time PCR confirmed, even in complex matrix, a LOD of 0.5 ppm in five classes of food matrices tested; these values are compatible with the current regulatory situation that does not consider, at international level, to establish a quantitative criterion for the allergen considered in this study. The Real Time PCR SPECIALfinder kit for the detection of mustard proved to be easy to use and particularly appreciated for the rapid response times considering that the amplification and detection phase has a duration of less than 50 minutes. Method accuracy was rated satisfactory for sensitivity (100%) and specificity (100%) and was fully validated and accreditated. It was found adequate for the needs of the laboratory as it met the purpose for which it was applied. This study was funded in part within a project of the Italian Ministry of Health (IZS PLV 02/19 RC).

Keywords: allergens, food, mustard, real time PCR

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Authors: Sebastião Milton Pinheiro da Silva, Michele Barbosa da Rocha, Ana Lúcia Fernandes Campos, Miquéias Rildo de Souza Silva

Abstract:

Water is an essential natural resource for life on Earth. Rivers, lakes, lagoons and dams are the main sources of water storage for human consumption. The costs of extracting and using these water sources are lower than those of exploiting groundwater on transition zones to semi-arid terrains. However, the volume of surface water has decreased over time, with the depletion of first-order drainage and the disappearance of springs, phenomena which are easily observed in the field. Climate change worsens water scarcity, compromising supply and hydric security for rural populations. To minimize the expected impacts, producing and storing water through watershed management planning requires detailed cartographic information on the relief and topography, and updated data on the stage and intensity of catchment basin environmental degradation problems. The cartography available of the Brazilian northeastern territory dates to the 70s, with topographic maps, printed, at a scale of 1:100,000 which does not meet the requirements to execute this project. Exceptionally, there are topographic maps at scales of 1:50,000 and 1:25,000 of some coastal regions in northeastern Brazil. Still, due to scale limitations and outdatedness, they are products of little utility for mapping low-order watersheds drainage and springs. Remote sensing data and geographic information systems can contribute to guiding the process of mapping and environmental recovery by integrating detailed relief and topographic data besides social and other environmental information in the Guajiru River Basin, located on the east coast of Rio Grande do Norte, on the Northeast region of Brazil. This study aimed to recognize and map catchment basin, springs and low-order drainage features along estimating morphometric parameters. Alos PALSAR and Copernicus DEM digital elevation models were evaluated and provided regional drainage features and the watersheds limits extracted with Terraview/Terrahidro 5.0 software. CBERS 4A satellite images with 2 m spatial resolution, processed with ESA SNAP Toolbox, allowed generating land use land cover map of Guajiru River. A Mappir Survey 3 multiespectral camera onboard of a DJI Phantom 4, a Mavic 2 Pro PPK Drone and an X91 GNSS receiver to collect the precised position of selected points were employed to detail mapping. Satellite images enabled a first knowledge approach of watershed areas on a more regional scale, yet very current, and drone images were essential in mapping details of catchment basins. The drone multispectral image mosaics, the digital elevation model, the contour lines and geomorphometric parameters were generated using OpenDroneMap/ODM and QGis softwares. The drone images generated facilitated the location, understanding and mapping of watersheds, recharge areas and first-order ephemeral watercourses on an adequate scale and will be used in the following project’s phases: watershed management planning, recovery and environmental protection of Rio's springs Guajiru. Environmental degradation is being analyzed from the perspective of the availability and quality of surface water supply.

Keywords: imaging, relief, UAV, water

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