Search results for: Monica Saifi

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

Procedia PDF Downloads 46

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

Abstract:

The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

Procedia PDF Downloads 111

Authors: Diana Santiago, Tania Lisboa, Sophie Lee, Alexander P. Demos, Monica C. S. Vasconcelos

Abstract:

Memorization has long been recognized as an arduous and anxiety-evoking task for musicians, and yet, it is an essential aspect of performance. Research shows that musicians are often not taught how to memorize. While memorization and practice strategies of professionals have been studied, little research has been done to examine how student musicians learn to practice and memorize music in different cultural settings. We present the process of developing and testing a questionnaire of music memorization and musical practice for student musicians in the UK and Brazil. A survey was developed for a cross-cultural research project aiming at examining how young orchestral musicians (aged 7–18 years) in different learning environments and cultures engage in instrumental practice and memorization. The questionnaire development included members of a UK/US/Brazil research team of music educators and performance science researchers. A pool of items was developed for each aspect of practice and memorization identified, based on literature, personal experiences, and adapted from existing questionnaires. Item development took the varying levels of cognitive and social development of the target populations into consideration. It also considered the diverse target learning environments. Items were initially grouped in accordance with a single underlying construct/behavior. The questionnaire comprised three sections: a demographics section, a section on practice (containing 29 items), and a section on memorization (containing 40 items). Next, the response process was considered and a 5-point Likert scale ranging from ‘always’ to ‘never’ with a verbal label and an image assigned to each response option was selected, following effective questionnaire design for children and youths. Finally, a pilot study was conducted with young orchestral musicians from diverse learning environments in Brazil and the United Kingdom. Data collection took place in either one-to-one or group settings to facilitate the participants. Cognitive interviews were utilized to establish response process validity by confirming the readability and accurate comprehension of the questionnaire items or highlighting the need for item revision. Internal reliability was investigated by measuring the consistency of the item groups using the statistical test Cronbach’s alpha. The pilot study successfully relied on the questionnaire to generate data about the engagement of young musicians of different levels and instruments, across different learning and cultural environments, in instrumental practice and memorization. Interaction analysis of the cognitive interviews undertaken with these participants, however, exposed the fact that certain items, and the response scale, could be interpreted in multiple ways. The questionnaire text was, therefore, revised accordingly. The low Cronbach’s Alpha scores of many item groups indicated another issue with the original questionnaire: its low level of internal reliability. Several reasons for each poor reliability can be suggested, including the issues with item interpretation revealed through interaction analysis of the cognitive interviews, the small number of participants (34), and the elusive nature of the construct in question. The revised questionnaire measures 78 specific behaviors or opinions. It can be seen to provide an efficient means of gathering information about the engagement of young musicians in practice and memorization on a large scale.

Keywords: cross-cultural, memorization, practice, questionnaire, young musicians

Procedia PDF Downloads 101

Authors: Andreea Campu, Ilinica Muresan, Simona Cainap, Simion Astilean, Monica Focsan

Abstract:

Acute myocardial infarction (AMI) is the most severe cardiovascular disease, which has threatened human lives for decades, thus a continuous interest is directed towards the detection of cardiac biomarkers such as cardiac troponin I (cTnI) in order to predict risk and, implicitly, fulfill the early diagnosis requirements in AMI settings. Microfluidics is a major technology involved in the development of efficient sensing devices with real-time fast responses and on-site applicability. Microfluidic devices have gathered a lot of attention recently due to their advantageous features such as high sensitivity and specificity, miniaturization and portability, ease-of-use, low-cost, facile fabrication, and reduced sample manipulation. The integration of gold nanoparticles into the structure of microfluidic sensors has led to the development of highly effective detection systems, considering the unique properties of the metallic nanostructures, specifically the Localized Surface Plasmon Resonance (LSPR), which makes them highly sensitive to their microenvironment. In this scientific context, herein, we propose the implementation of a novel detection device, which successfully combines the efficiency of gold bipyramids (AuBPs) as signal transducers and thermal generators with the sample-driven advantages of the microfluidic channels into a miniaturized, portable, low-cost, specific, and sensitive test for the dual LSPR-thermographic cTnI detection. Specifically, AuBPs with longitudinal LSPR response at 830 nm were chemically synthesized using the seed-mediated growth approach and characterized in terms of optical and morphological properties. Further, the colloidal AuBPs were deposited onto pre-treated silanized glass substrates thus, a uniform nanoparticle coverage of the substrate was obtained and confirmed by extinction measurements showing a 43 nm blue-shift of the LSPR response as a consequence of the refractive index change. The as-obtained plasmonic substrate was then integrated into a microfluidic “Y”-shaped polydimethylsiloxane (PDMS) channel, fabricated using a Laser Cutter system. Both plasmonic and microfluidic elements were plasma treated in order to achieve a permanent bond. The as-developed microfluidic plasmonic chip was further coupled to an automated syringe pump system. The proposed biosensing protocol implicates the successive injection inside the microfluidic channel as follows: p-aminothiophenol and glutaraldehyde, to achieve a covalent bond between the metallic surface and cTnI antibody, anti-cTnI, as a recognition element, and target cTnI biomarker. The successful functionalization and capture of cTnI was monitored by LSPR detection thus, after each step, a red-shift of the optical response was recorded. Furthermore, as an innovative detection technique, thermal determinations were made after each injection by exposing the microfluidic plasmonic chip to 785 nm laser excitation, considering that the AuBPs exhibit high light-to-heat conversion performances. By the analysis of the thermographic images, thermal curves were obtained, showing a decrease in the thermal efficiency after the anti-cTnI-cTnI reaction was realized. Thus, we developed a microfluidic plasmonic chip able to operate as both LSPR and thermal sensor for the detection of the cardiac troponin I biomarker, leading thus to the progress of diagnostic devices.

Keywords: gold nanobipyramids, microfluidic device, localized surface plasmon resonance detection, thermographic detection

Procedia PDF Downloads 104