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Conventional paint spraying processes often use small molecule organic solvents and emit a large amount of volatile organic compounds (VOCs) that are highly toxic, flammable, and explosive. Alternatively, the spraying technology using supercritical CO2 (scCO2) as a solvent has attracted
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Conventional paint spraying processes often use small molecule organic solvents and emit a large amount of volatile organic compounds (VOCs) that are highly toxic, flammable, and explosive. Alternatively, the spraying technology using supercritical CO2 (scCO2) as a solvent has attracted attention because of its ability to reduce VOC emissions, but the flow characteristics of coatings have not been thoroughly studied. Therefore, we numerically simulate the spraying process based on the actual process of scCO2 spraying polyurethane coatings by computational fluid dynamics (CFD). The effects of inlet pressure and volume fraction of scCO2 on the fluid motion parameters inside the nozzle as well as the atomization effect of droplets outside the nozzle are investigated. The simulated results show that a fluid with a large volume fraction of scCO2 will obtain a smaller density, resulting in a larger velocity and a larger distance for the spray to effectively spray. Higher coating content and bigger inlet pressures will result in higher discrete phase model (DPM) concentrations, and thus a bigger inlet pressure should be used to make the droplets more uniform across the 30° spray range. This study can provide theoretical guidance for the process of scCO2-sprayed polyurethane resin.
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A lifelong gluten-free diet (GFD) is the only treatment for celiac disease and other gluten-related disorders. Nevertheless, strict adherence to the GFD is often challenging due to concerns about social isolation, risk of gluten contaminations, high cost, poor quality and the taste of
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A lifelong gluten-free diet (GFD) is the only treatment for celiac disease and other gluten-related disorders. Nevertheless, strict adherence to the GFD is often challenging due to concerns about social isolation, risk of gluten contaminations, high cost, poor quality and the taste of gluten-free products. Moreover, although the GFD is effective in achieving mucosal healing, it may lead to dietary imbalances due to nutrient deficiencies over a long period of time. To overcome these issues, several gluten-free wheat flours have been developed to create products that closely resemble their gluten-containing counterparts. Furthermore, given the critical importance of adhering to the GFD, it becomes essential to promote adherence and monitor possible voluntary or involuntary transgressions. Various methods, including clinical assessment, questionnaires, serology for celiac disease, duodenal biopsies and the detection of Gluten Immunogenic Peptides (GIPs) are employed for this purpose, but none are considered entirely satisfactory. Since adherence to the GFD poses challenges, alternative therapies should be implemented in the coming years to improve treatment efficacy and the quality of life of patients with celiac disease. The aim of this narrative review is to explore current knowledge of the GFD and investigate its future perspectives, focusing on technology advancements, follow-up strategies and insights into a rapidly changing future.
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In general, energy loss reduction via the interaction of tires with the ground improves tractor traction performance when a drawbar pull is generated. This paper is examines the driving wheels with steel spikes for a tractor equipped with modern radial tires. An improved
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In general, energy loss reduction via the interaction of tires with the ground improves tractor traction performance when a drawbar pull is generated. This paper is examines the driving wheels with steel spikes for a tractor equipped with modern radial tires. An improved design of the spike device that allows for the change between an active and inactive position of the spikes is presented. The traction performance of a compact articulated tractor with the spike device was tested on a grass plot with two soil moisture contents (SMC). The highest difference in the drawbar pull in the range from 14.2% to 40.5% and from 17.1% to 36.8% was reached by the spikes in the active position in comparison with the tires without spikes, which were at the slip range from 45% to 5% in the case of the low SMC when the test tractor was in the 3rd and 1st gear. The motion resistance difference between the spikes in the active position and the tires without spikes was 11.8% and 2.5% at the low and medium SMC, respectively. At the low and medium SMC, the highest tractive efficiency of 0.765 (0.721) and 0.757 (0.731) was reached by the spikes in the active position when the test tractor was in the 1st (3rd) gear in comparison with 0.736 (0.7) and 0.723 (0.708) in the case of the tires without spikes. The results indicated that the spike device allowed for the improvement of tractor tractive performance.
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Polycyclic aromatic hydrocarbons (PAHs) and arsenic (As) are common pollutants co-existing in the environment, causing potential hazards to the ecosystem and human health. How their behaviors are affected by micro/nano particles in the environment are still not very clear. Through a series of
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Polycyclic aromatic hydrocarbons (PAHs) and arsenic (As) are common pollutants co-existing in the environment, causing potential hazards to the ecosystem and human health. How their behaviors are affected by micro/nano particles in the environment are still not very clear. Through a series of static adsorption experiments, this study investigated the adsorption of pyrene and arsenite (As (III)) using micro/nano carbon black and iron oxide under different conditions. The objectives were to determine the kinetics and isotherms of the adsorption of pyrene and As (III) using micro/nano carbon black and iron oxide and evaluate the impact of co-existing conditions on the adsorption. The microstructure of micro/nano carbon black (C 94.03%) is spherical-like, with a diameter of 100–200 nm. The micro/nano iron oxide (hematite) has irregular rod-shaped structures, mostly about 1 µm long and 100–200 nm wide. The results show that the micro/nano black carbon easily adsorbed the pyrene, with a pseudo-second-order rate constant of 0.016 mg/(g·h) and an adsorption capacity of 283.23 μg/g at 24 h. The micro/nano iron oxide easily adsorbed As (III), with a pseudo-second-order rate constant of 0.814 mg/(g·h) and an adsorption capacity of 3.45 mg/g at 24 h. The mechanisms of adsorption were mainly chemical reactions. Micro/nano carbon black hardly adsorbed As (III), but its adsorption capability for pyrene was reduced by the presence of As (III), and this effect increased with an increase in the As (III) concentration. The adsorbed pyrene on the micro/nano black carbon could hardly be desorbed. On the other hand, the micro/nano iron oxide could hardly adsorb the pyrene, but its adsorption capability for As (III) was increased by the presence of pyrene, and this effect increased with an increase in the pyrene concentration. The results of this study provide guidance for the risk management and remediation of the environment when there is combined pollution of PAHs and As.
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A new type of single–conversion–step wide–input–range versatile step–up/down three–voltage–level power–factor correction stage is presented in this manuscript. The rectifier can operate both in continuous–conduction mode and discontinuous–conduction mode. First, the rectifier’s principle of operation is described, and then the innovative rectifier is analyzed
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A new type of single–conversion–step wide–input–range versatile step–up/down three–voltage–level power–factor correction stage is presented in this manuscript. The rectifier can operate both in continuous–conduction mode and discontinuous–conduction mode. First, the rectifier’s principle of operation is described, and then the innovative rectifier is analyzed in continuous and discontinuous–conduction modes. After, an average model for the innovative rectifier is developed. Lastly, the proposed theory is experimentally validated using a multiplier–less dual–control–loop mode at discontinuous–conduction modes. It is shown that although no multiplier is used in the control circuitry, the power factor is near unity. It is revealed that the rectifier can swing the output voltage from 50 V to 900 V while the input voltage is 230 Vrms. Although the rectifier output has a split DC bus with three voltage levels, the required control effort is low, and the output voltage is balanced. The innovative topology suits any standard power–factor correction rectifier application, dual–stage low–voltage power supply, and three–level voltage supplement for low–harmonic inverters. Since the rectifier’s output–voltage swing is extremely wide, energy storage systems and electric vehicle batteries are suitable applications.
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Pure shear tests of textured magnesium AZ31B sheet samples were carried out using a 5 kN Kammrath & Weiss in situ tension-compression stage in a scanning electron microscope in combination with real-time electron backscatter diffraction lattice orientation mapping. The sample design was optimized
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Pure shear tests of textured magnesium AZ31B sheet samples were carried out using a 5 kN Kammrath & Weiss in situ tension-compression stage in a scanning electron microscope in combination with real-time electron backscatter diffraction lattice orientation mapping. The sample design was optimized to produce a pure shear stress in the central gauge zone. Distributions of the deformation twins were correlated with finite element simulations using a linear-elastic constitutive law considering large deformations to show that twins form in areas where the principal compressive stress is a maximum and that they form normal to the trajectories of that minor principal stress. Mappings of the same area at different load values revealed the formation and growth of individual twins and their relationship to the internal elastic strain of individual grains as indicated by the internal grain disorientation. All twins observed were of the extension type, with an 86.3° disorientation with respect to the parent grains. A more detailed study was conducted using transmission electron microscopy to correlate with the EBSD observations and to further elucidate the twin structures within samples.
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Breast cancer is the most common cause of mortality due to cancer for women both in Lithuania and worldwide. The chances of survival after diagnosis differ significantly depending on the stage of disease at the time of diagnosis and other factors. One way
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Breast cancer is the most common cause of mortality due to cancer for women both in Lithuania and worldwide. The chances of survival after diagnosis differ significantly depending on the stage of disease at the time of diagnosis and other factors. One way to estimate survival is to construct a Kaplan–Meier estimate for each factor value separately. However, in cases when it is impossible to observe a large number of patients (for example, in the case of countries with lower numbers of inhabitants), dividing the data into subsets, say, by stage at diagnosis, may lead to results where some subsets contain too few data, thus causing the results of a Kaplan–Meier (or any other) method to become statistically incredible. The problem may become even more acute if researchers want to use more risk factors, such as stage at diagnosis, sex, place of living, treatment method, etc. Alternatively, Cox models can be used to analyse survival data with covariates, and they do not require the data to be divided into subsets according to chosen risks factors (hazards). We estimate the chances of survival for up to 5 years after a breast cancer diagnosis for Lithuanian females during the period of 1995–2016. Firstly, we construct Kaplan-Meier estimates for each stage separately; then, we apply a (stratified) Cox model using stage, circumstance of diagnosis, and year of diagnosis as (potential) hazards. Some directions of further research are provided in the last section of the paper.
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The aim of this study was to examine patterns of social media use across age groups in four countries (Norway, USA, UK, and Australia) two years after the COVID-19 pandemic outbreak, and whether types of use and time spent using social media was
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The aim of this study was to examine patterns of social media use across age groups in four countries (Norway, USA, UK, and Australia) two years after the COVID-19 pandemic outbreak, and whether types of use and time spent using social media was related to health worries. A cross-sectional online survey was completed by 1578 adult participants. The data were analysed with one-way analyses of variance and a linear regression analysis. Younger people spent more time on and were more likely to be passive users of social media than older people. Motives for social media use, and perceived effects of using social media, varied by participants’ age. Passive social media use and more time spent using social media were related to higher levels of health worries. Thus, an age perspective is relevant for understanding patterns of social media use, and different types of social media use appear to be differently related to health worries.
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Classical machine learning techniques have dominated Music Emotion Recognition. However, improvements have slowed down due to the complex and time-consuming task of handcrafting new emotionally relevant audio features. Deep learning methods have recently gained popularity in the field because of their ability to
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Classical machine learning techniques have dominated Music Emotion Recognition. However, improvements have slowed down due to the complex and time-consuming task of handcrafting new emotionally relevant audio features. Deep learning methods have recently gained popularity in the field because of their ability to automatically learn relevant features from spectral representations of songs, eliminating such necessity. Nonetheless, there are limitations, such as the need for large amounts of quality labeled data, a common problem in MER research. To understand the effectiveness of these techniques, a comparison study using various classical machine learning and deep learning methods was conducted. The results showed that using an ensemble of a Dense Neural Network and a Convolutional Neural Network architecture resulted in a state-of-the-art 80.20% F1 score, an improvement of around 5% considering the best baseline results, concluding that future research should take advantage of both paradigms, that is, combining handcrafted features with feature learning.
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Magnetic resonance imaging (MRI) is used pervasively in veterinary practice for the antemortem diagnosis of intracranial tumors. Here, we provide an illustrated summary of the published MRI features of primary and secondary intracranial tumors of dogs and cats, following PRISMA scoping review guidelines.
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Magnetic resonance imaging (MRI) is used pervasively in veterinary practice for the antemortem diagnosis of intracranial tumors. Here, we provide an illustrated summary of the published MRI features of primary and secondary intracranial tumors of dogs and cats, following PRISMA scoping review guidelines. The PubMed and Web of Science databases were searched for relevant records, and input from stakeholders was solicited to select data for extraction. Sixty-seven studies of moderate to low-level evidence quality describing the MRI features of pathologically confirmed canine and feline brain tumors met inclusion criteria. Considerable variability in data inclusion and reporting, as well as low case numbers, prohibited comparative data analyses. Available data support a holistic MRI approach incorporating lesion number, location within the brain, shape, intrinsic signal appearances on multiparametric sequences, patterns of contrast enhancement, and associated secondary changes in the brain to prioritize differential imaging diagnoses, and often allows for accurate presumptive diagnosis of common intracranial tumors. Quantitative MRI techniques show promise for improving discrimination of neoplastic from non-neoplastic brain lesions, as well as differentiating brain tumor types and grades, but sample size limitations will likely remain a significant practical obstacle to the design of robustly powered radiomic studies. For many brain tumor variants, particularly in cats, there remains a need for standardized studies that correlate clinicopathologic and neuroimaging data.
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In this paper, ordinary Portland cement, ultrafine cement, polyurethane, and epoxy resin were selected as typical grouting materials. Grouting simulation tests were first conducted to prepare the grouted concrete crack sample. The effect of concrete crack parameters (i.e., crack aperture and roughness), grout
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In this paper, ordinary Portland cement, ultrafine cement, polyurethane, and epoxy resin were selected as typical grouting materials. Grouting simulation tests were first conducted to prepare the grouted concrete crack sample. The effect of concrete crack parameters (i.e., crack aperture and roughness), grout water–cement ratio, and grouting pressure on the water-plugging performance of different grouting materials was explored through the impermeability test. The microstructure of grouted concrete cracks was analyzed by means of scanning electron microscopy (SEM) and computed tomography (CT), and the difference in water-plugging performance of different grouting materials was explained at the micro level. The results show that the impermeability of the four grouting materials was ranked as follows: Epoxy resin > polyurethane > ultra-fine cement > ordinary Portland cement. The concrete cracks grouted by epoxy resin have the highest plugging failure water pressure and the lowest permeability, which is the optimal grouting material. The effectiveness of crack grouting in water-plugging was directly proportional to the grouting pressure, provided the pressure did not exceed a certain value. When the pressure surpassed the threshold, the increase in pressure did not have a significant impact on the water plugging performance. For the two cement-based materials, the threshold pressure was 1 MPa, while for the other two chemical grouts, it was 2 MPa. The two cement-based grouts with a water–cement ratio of 0.8 showed optimal water-plugging performance. The water-plugging performance of ordinary Portland cement paste, ultra-fine cement pastes, and polyurethane grout was negatively correlated with crack aperture and positively correlated with crack roughness. However, the water-plugging performance of epoxy resin grout was not affected by crack aperture or roughness.
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The constant monitoring and control of various health, infrastructure, and natural factors have led to the design and development of technological devices in a wide range of fields. This has resulted in the creation of different types of sensors that can be used
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The constant monitoring and control of various health, infrastructure, and natural factors have led to the design and development of technological devices in a wide range of fields. This has resulted in the creation of different types of sensors that can be used to monitor and control different environments, such as fire, water, temperature, and movement, among others. These sensors detect anomalies in the input data to the system, allowing alerts to be generated for early risk detection. The advancement of artificial intelligence has led to improved sensor systems and networks, resulting in devices with better performance and more precise results by incorporating various features. The aim of this work is to conduct a bibliometric analysis using the PRISMA 2020 set to identify research trends in the development of machine learning applications in fiber optic sensors. This methodology facilitates the analysis of a dataset comprised of documents obtained from Scopus and Web of Science databases. It enables the evaluation of both the quantity and quality of publications in the study area based on specific criteria, such as trends, key concepts, and advances in concepts over time. The study found that deep learning techniques and fiber Bragg gratings have been extensively researched in infrastructure, with a focus on using fiber optic sensors for structural health monitoring in future research. One of the main limitations is the lack of research on the use of novel materials, such as graphite, for designing fiber optic sensors. One of the main limitations is the lack of research on the use of novel materials, such as graphite, for designing fiber optic sensors. This presents an opportunity for future studies.
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We consider the two- and n-body problems on the two-dimensional conformal sphere , with a radius . We employ an alternative potential free of singularities at antipodal points. We study the limit of relative equilibria under
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We consider the two- and n-body problems on the two-dimensional conformal sphere , with a radius . We employ an alternative potential free of singularities at antipodal points. We study the limit of relative equilibria under the SO(2) symmetry; we examine the specific conditions under which a pair of positive-mass particles, situated at antipodal points, can maintain a state of relative equilibrium as they traverse along a geodesic. It is identified that, under an appropriate radius–mass relationship, these particles experience an unrestricted and free movement in alignment with the geodesic of the canonical Killing vector field in . An even number of bodies with pairwise conjugated positions, arranged in a regular n-gon, all with the same mass m, move freely on a geodesic with suitable velocities, where this geodesic motion behaves like a relative equilibrium. Also, a center of mass formula is included. A relation is found for the relative equilibrium in the two-body problem in the sphere similar to the Snell law.
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To investigate the mechanical behavior and design methodology of column-free QRST (quasi-rectangular segmental tunnel) structures, a theoretical analysis based on prototype experiments and simulation models is conducted. Initially, a prototype experimental investigation is conducted to reveal the structural behavior at the service stage.
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To investigate the mechanical behavior and design methodology of column-free QRST (quasi-rectangular segmental tunnel) structures, a theoretical analysis based on prototype experiments and simulation models is conducted. Initially, a prototype experimental investigation is conducted to reveal the structural behavior at the service stage. Subsequently, the ESHR model (Equivalent Stiffness Homogeneous Ring), the BS model (Beam Spring), and the MBS model (Modified Beam Spring) are used to simulate structural behavior. For design purposes, the design methodology is explored based on the ESHR model, followed by a sensitivity analysis of several key load parameters. Based on the experimental results, weak parts of the column-free QRST structure are found to include several joints (Joint 1, Joint 5, Joint 3, and Joint 8), and corresponding optimization measures are proposed. By comparing the test results, the above-mentioned three models demonstrate their applicability in structural simulation, with the ESHR model having sufficient design accuracy. A model-based deformation mechanism analysis found that joints contribute approximately 2/3 of the structural deformation. For the structural design of the column-free QRST using the ESHR model, amplifying the calculated results of structures directly subjected to the service stage by 10% suffices to meet engineering requirements. Based on the test and study, special attention should be paid to the negative bending moment regions at the waists of the structure during both the design and service stages.
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Lynn Pulliam, Bing Sun, Erin McCafferty, Steven A. Soper, Malgorzata A. Witek, Mengjia Hu, Judith M. Ford, Sarah Song, Dimitrios Kapogiannis, Marshall J. Glesby, Daniel Merenstein, Phyllis C. Tien, Heather Freasier, Audrey French, Heather McKay, Monica M. Diaz, Igho Ofotokun, Jordan E. Lake, Joseph B. Margolick, Eun-Young Kim, Steven R. Levine, Margaret A. Fischl, Wei Li, Jeremy Martinson and Norina Tangadd
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Int. J. Mol. Sci.2024, 25(7), 3830; https://doi.org/10.3390/ijms25073830 (registering DOI) - 29 Mar 2024
Long COVID (LongC) is associated with a myriad of symptoms including cognitive impairment. We reported at the beginning of the COVID-19 pandemic that neuronal-enriched or L1CAM+ extracellular vesicles (nEVs) from people with LongC contained proteins associated with Alzheimer’s disease (AD). Since that time,
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Long COVID (LongC) is associated with a myriad of symptoms including cognitive impairment. We reported at the beginning of the COVID-19 pandemic that neuronal-enriched or L1CAM+ extracellular vesicles (nEVs) from people with LongC contained proteins associated with Alzheimer’s disease (AD). Since that time, a subset of people with prior COVID infection continue to report neurological problems more than three months after infection. Blood markers to better characterize LongC are elusive. To further identify neuronal proteins associated with LongC, we maximized the number of nEVs isolated from plasma by developing a hybrid EV Microfluidic Affinity Purification (EV-MAP) technique. We isolated nEVs from people with LongC and neurological complaints, AD, and HIV infection with mild cognitive impairment. Using the OLINK platform that assesses 384 neurological proteins, we identified 11 significant proteins increased in LongC and 2 decreased (BST1, GGT1). Fourteen proteins were increased in AD and forty proteins associated with HIV cognitive impairment were elevated with one decreased (IVD). One common protein (BST1) was decreased in LongC and increased in HIV. Six proteins (MIF, ENO1, MESD, NUDT5, TNFSF14 and FYB1) were expressed in both LongC and AD and no proteins were common to HIV and AD. This study begins to identify differences and similarities in the neuronal response to LongC versus AD and HIV infection.
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With the integration of clean energy and new power electronic devices into the power grid, the superposition of harmonic sources has become increasingly apparent and common. There is an urgent need to effectively identify composite harmonic sources in the new energy grid. This
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With the integration of clean energy and new power electronic devices into the power grid, the superposition of harmonic sources has become increasingly apparent and common. There is an urgent need to effectively identify composite harmonic sources in the new energy grid. This article proposes a multi-label composite harmonic source classification method that integrates knowledge representation with the transformer model. First, triplets from harmonic monitoring data are extracted and TransR models are used to train time-frequency feature representation vectors. Then, the transformer model is trained to learn the data features of different harmonic sources. Finally, based on the multi-label classification method, composite harmonic sources are identified. This article integrates the semantic information of time-frequency features into the data samples, increasing the interpretability of the model while expanding the inter-class features, which is conducive to the classification and recognition of the model. Compared with other deep learning recognition methods, verification based on simulation data and measured data shows that this method has low training complexity and higher recognition accuracy.
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Salmonella enterica subspecies enterica serovar 4,[5],12:i:- is a monophasic variant of S. Typhimurium which has emerged as a world-wide distributed pathogen in the last decades. Several clones have been identified within this variant, the European clone, the Spanish clone, the Southern European
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Salmonella enterica subspecies enterica serovar 4,[5],12:i:- is a monophasic variant of S. Typhimurium which has emerged as a world-wide distributed pathogen in the last decades. Several clones have been identified within this variant, the European clone, the Spanish clone, the Southern European clone and the U.S./American clone. The present study focused on isolates of the Southern European clone that were obtained from clinical samples at Spanish hospitals. The selected isolates were multidrug resistant, with most resistance genes residing on IncR plasmids that also carried virulence genes. These plasmids had a mosaic structure, comprising a highly reduced IncR backbone, which has acquired a large amount of exogenous DNA mostly derived from pSLT and IncI1-I(alfa) plasmids. Although composed of approximately the same elements, the investigated plasmids displayed a high diversity, consistent with active evolution driven by a wealth of mobile genetic elements. They comprise multiple intact or truncated insertion sequences, transposons, pseudo-compound transposons and integrons. Particularly relevant was the role of IS26 (with six to nine copies per plasmid) in generating insertions, deletions and inversions, with many of the rearrangements uncovered by tracking the patterns of eight bp target site duplications. Most of the resistance genes detected in the analyzed isolates have been previously associated with the Southern European clone. However, erm(B), lnu(G) and blaTEM-1B are novel, with the last two carried by a second resistance plasmid found in one of the IncR-positive isolates. Thus, evolution of resistance in the Southern European clone is not only mediated by diversification of the IncR plasmids, but also through acquisition of additional plasmids. All isolates investigated in the present study have the large deletion affecting the fljBA region previously found to justify the monophasic phenotype in the Southern European and U.S./American clones. An SNP-based phylogenetic analysis revealed the close relationship amongst our isolates, and support that those sharing the large fljBA deletion could be more heterogeneous than previously anticipated.
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Samah Maaloul, Maher Mahmoudi, Hédi Mighri, Imen Ghzaiel, Talel Bouhamda, Fay?al Boughalleb, Adil El Midaoui, Anne Vejux, Gérard Lizard and Raoudha Abdellaoui
Plants2024, 13(7), 989; https://doi.org/10.3390/plants13070989 (registering DOI) - 29 Mar 2024
Silybum marianum and Silybum eburneum are wild edible Mediterranean plants used in the human diet. This study presents the initial findings on the phytochemical characterization of Tunisian S. marianum and S. eburneum organs. It examined their mineral, sugar, organic acid, polyphenolic, and seed
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Silybum marianum and Silybum eburneum are wild edible Mediterranean plants used in the human diet. This study presents the initial findings on the phytochemical characterization of Tunisian S. marianum and S. eburneum organs. It examined their mineral, sugar, organic acid, polyphenolic, and seed storage protein contents, as well as their antioxidant potential. In S. marianum, stems had high sodium and potassium contents, while the immature and mature seeds were rich in calcium and magnesium. However, S. eburneum had high potassium levels in stems and high sodium and calcium levels in the flowers. S. marianum showed substantial fructose variation among its organs. Conversely, S. eburneum exhibited significant heterogeneity in glucose, sucrose, and maltose levels across its organs, with maltose exclusively detected in the immature seeds. A notable organ-dependent distribution of organic acids was observed among the two species. Higher levels of phenolic contents were detected in both mature and immature seeds in both species compared to the other plant parts. The seeds possessed higher antioxidant activities than other plant organs. In both S. marianum and S. eburneum seeds, albumins and globulins were the predominant protein fractions. This study brings evidence supporting the important potential of Silybum organs as sources of nutrients with antioxidant properties for producing functional food.
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Frameworks for human activity recognition (HAR) can be applied in the clinical environment for monitoring patients’ motor and functional abilities either remotely or within a rehabilitation program. Deep Learning (DL) models can be exploited to perform HAR by means of raw data, thus
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Frameworks for human activity recognition (HAR) can be applied in the clinical environment for monitoring patients’ motor and functional abilities either remotely or within a rehabilitation program. Deep Learning (DL) models can be exploited to perform HAR by means of raw data, thus avoiding time-demanding feature engineering operations. Most works targeting HAR with DL-based architectures have tested the workflow performance on data related to a separate execution of the tasks. Hence, a paucity in the literature has been found with regard to frameworks aimed at recognizing continuously executed motor actions. In this article, the authors present the design, development, and testing of a DL-based workflow targeting continuous human activity recognition (CHAR). The model was trained on the data recorded from ten healthy subjects and tested on eight different subjects. Despite the limited sample size, the authors claim the capability of the proposed framework to accurately classify motor actions within a feasible time, thus making it potentially useful in a clinical scenario.
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This article draws on a twenty-year relationship of short-term interventions with Dalit communities living in informal settlements, sub-cities and urban villages in Mumbai, that have sought to create public theatre events based on research by and with communities that celebrate, problematise and interrogate
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This article draws on a twenty-year relationship of short-term interventions with Dalit communities living in informal settlements, sub-cities and urban villages in Mumbai, that have sought to create public theatre events based on research by and with communities that celebrate, problematise and interrogate sustainable urban living. In looking back over the developments and changes to our working methods in Mumbai, I explore how the projects priorities the roles of the community as both researchers and artists. I consider where a specific applied theatre project, which focuses on site specific storytelling with Dalit communities in Worli Koliwada and Dharavi, functions on a continuum of interactive, participatory, and emancipatory practice, research and performance. Applied Theatre practices should not and cannot remain static, they need to be constantly reformed and as practitioners and researchers we need to constantly re-examine the ways in which we work. This chapter poses two central questions: firstly, can this long-term partnership between practitioners, researchers and artists from the UK and India working with community members genuinely be a space for co-creating knowledge and theatre? And secondly, if so, is this Theatre-based Research or Research Based Theatre? I interrogate Applied Theatre’s potential to create a space of cognitive justice, which must be the next step for applied theatre, along-side its more widely accepted aims of searching for social and spatial justice and which places the community as both artists and researchers. The Dalit social reality is one of oppression, based on three axes: social, economic and gender. The chapter explores how working as co-researchers and the public performance of their stories has been a form of ‘active citizenship’ for these participants and is a key part of their strategy in their demand for policy changes. In looking forward I ask how working in international partnerships with community members can promote cognitive justice and go beyond a merely participatory practice. I consider why it is vital for the field that applied theatre practice includes partners from both the global south and north working together to co-create knowledge, new methods of practice to ensure an applied theatre knowledge democracy. In doing so I will discuss if and how this work might be considered to be Theatre-based Research.
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A wide range of nano-objects is found in many applications of our everyday life. Recognition of their peculiar properties and ease of functionalization has prompted their engineering into multifunctional platforms that are supposed to afford efficient tools for the development of biomedical applications.
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A wide range of nano-objects is found in many applications of our everyday life. Recognition of their peculiar properties and ease of functionalization has prompted their engineering into multifunctional platforms that are supposed to afford efficient tools for the development of biomedical applications. However, bridging the gap between bench to bedside cannot be expected without a good knowledge of their behaviour in vivo, which can be obtained through non-invasive imaging techniques, such as positron emission tomography (PET). Their radiolabelling with [18F]-fluorine, a technique already well established and widely used routinely for PET imaging, with [18F]-FDG for example, and in preclinical investigation using [18F]-radiolabelled biological macromolecules, has, therefore, been developed. In this context, this review highlights the various nano-objects studied so far, the reasons behind their radiolabelling, and main in vitro and/or in vivo results obtained thereof. Then, the methods developed to introduce the radioelement are presented. Detailed indications on the chemical steps involved are provided, and the stability of the radiolabelling is discussed. Emphasis is then made on the techniques used to purify and analyse the radiolabelled nano-objects, a point that is rarely discussed despite its technical relevance and importance for accurate imaging. The pros and cons of the different methods developed are finally discussed from which future work can develop.
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Glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are incretins that regulate postprandial glucose regulation, stimulating insulin secretion from pancreatic β-cells in response to food ingestion. Modified GLP-1 receptor agonists (GLP-1RAs) are being administered for the treatment of obesity and type 2
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Glucagon-like peptide 1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are incretins that regulate postprandial glucose regulation, stimulating insulin secretion from pancreatic β-cells in response to food ingestion. Modified GLP-1 receptor agonists (GLP-1RAs) are being administered for the treatment of obesity and type 2 diabetes mellitus (T2DM). Strongly related to those disorders, metabolic dysfunction-associated steatotic liver disease (MASLD), especially its aggressive form, defined as metabolic dysfunction-associated steatohepatitis (MASH), is a major healthcare burden associated with high morbidity and extrahepatic complications. GLP-1RAs have been explored in MASH patients with evident improvement in liver dysfunction enzymes, glycemic control, and weight loss. Importantly, the combination of GLP-1RAs with GIP and/or glucagon RAs may be even more effective via synergistic mechanisms in amelioration of metabolic, biochemical, and histological parameters of MASLD but also has a beneficial impact on MASLD-related complications. In this current review, we aim to provide an overview of incretins’ physiology, action, and signaling. Furthermore, we provide insight into the key pathophysiological mechanisms through which they impact MASLD aspects, as well as we analyze clinical data from human interventional studies. Finally, we discuss the current challenges and future perspectives pertinent to this growing area of research and clinical medicine.
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Background and Objectives: The escalating prevalence of gestational diabetes mellitus (GDM) and the limitations associated with utilizing body mass index (BMI) as a predictive measure underscore the imperative need for identifying an optimal early pregnancy predictor. Such a predictor not only mitigates
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Background and Objectives: The escalating prevalence of gestational diabetes mellitus (GDM) and the limitations associated with utilizing body mass index (BMI) as a predictive measure underscore the imperative need for identifying an optimal early pregnancy predictor. Such a predictor not only mitigates the risk of GDM but also allows for timely implementation of interventions. Materials and Methods: This meta-analysis aimed to explore the association between visceral adipose tissue (VAT) depth and the risk of GDM. A thorough search of PubMed, Embase, and Web of Science databases was conducted up to 30 September 2023. The analysis employed a random-effects model to assess the relationship between VAT depth and the likelihood of GDM. Results: The inclusion criteria encompassed seven studies involving 1315 women, including 225 diagnosed with GDM. Significantly lower VAT depth was observed in the non-GDM group in comparison to the GDM group (Standardized Mean Difference [SMD]: 0.84; 95% Confidence Interval [CI]: 0.52–1.15; p < 0.001). Substantial statistical heterogeneity was noted among studies (I2 = 72.88%, p = 0.001). Through meticulous sensitivity and subgroup analyses, the source of heterogeneity was identified and thoroughly discussed. Subgroup analyses suggest that different GDM diagnostic criteria and VAT definitions all indicate higher VAT depth in GDM patients during early pregnancy. Conclusions: Our findings propose that, during the first trimester, GDM patients exhibit higher VAT depth compared to non-GDM women, highlighting VAT depth as a potential predictive factor for GDM in early pregnancy. This study contributes valuable evidence to the growing body of knowledge surrounding novel predictors for GDM, emphasizing the importance of early intervention strategies.
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