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The purchasing behaviors of the Tunisian consumers have changed during these recent years. Now, he purchases and values more local goods, especially handicrafts ones. This new mindset come out because of the emergence of new Tunisian crafts companies that sell updated products that combine both traditional and modern styles. Our objective consists first, to outline the evolution of the Tunisian artisanal product. Therefore, this theoretical advancement will enable us to empirically study the new consumer perspective on this long-trivialized commodity in Tunisia. We were initially motivated to address our issue based on the work of Schumpeter (1930). The purpose of this article is to draw attention to the innovations that the artisanal product has to deal with, by discussing organizational innovation, product innovation, innovation by breaking into new markets, innovation through commercialization, and innovation by the use of new raw material sources. The second method involved a qualitative study in which we performed 21 non-directive one-to-one interviews with consumers. Our findings demonstrate that Tunisian consumer is actually attracted by the handcrafted brand that considered it fashionable. This discovery runs counter to prior research's findings regarding a product that has long been associated with a basic and archaic appearance. This research demonstrates also the relationship between current consumer trends and the revisited artisanal product, confirming that the new version of the artisanal product satisfies perfectly the needs of the postmodern consumer, namely the quest for erasure of boundaries, the quest for authenticity and nostalgia, the thirst for achievement, and the quest for reassurance. Our results will help experts in the sector, such as craftspeople, creators and designers to understand consumer perceptions regarding the product, to reconsider their strategies. However, this study has a few limitations. We specially point out the data collection technique, which was carried out for the sake of convenience and led to a significant representation of students at the expense of other socio-professional classes. Therefore, it will be interesting to perform a study with a more diverse sample, possibly including industry professionals in order to determine whether there is a perception gap between consumers and artisans.

Nuclear power plants (NPPs) rely on critical, complex systems that require continuous monitoring to ensure safe operation under both normal and abnormal conditions. Despite the potential of artificial intelligence (AI) to enhance predictive capabilities in these systems, limited research has been conducted on the application of AI algorithms within NPPs. This presents a knowledge gap in the integration of AI for improving safety, reliability, and decision making in NPP. In this study, we explore the use of AI methods, including machine learning and real-time data analytics, applied to NPP components to address the nonlinearity and dynamic behavior inherent in reactor operations. Through the implementation of AI and Internet of Things (IoT) devices, we propose a system that enables early warning and real-time data transmission to regulatory authorities and decision-makers, ensuring better coordination during incidents. Lessons from past nuclear accidents, such as Chernobyl, emphasize the importance of timely information dissemination to mitigate risks. However, this integration also presents challenges, including cybersecurity risks and the need for updated regulations to address AI use in safety-critical environments. The results of this study highlight the urgent need for further research on the application of AI in NPPs, with a particular focus on addressing these challenges to ensure safe implementation.

The efficacy of available treatments for melanoma is limited by side effects and the rapidly emerging resistance to treatment. In this context, the decavanadate compounds represent promising tools to design efficient therapeutic agents. In our study, we synthesized a dimagnesium disodium decavanadate icosahydrate compound (Mg2Na2V10O28·20H2O) and investigated its structure stability as well as its antimelanoma effects. Results showed that the Mg2Na2V10O28·20H2O compound is structured in a monoclinic system with the space group C2/c, stabilized by oxygen vertices, hydrogen bonds, and van der Waals interactions. Interestingly, we found that this newly synthesized compound reduced the viability of human (IGR39, IGR37, and SKMEL28) and murine (B16-F10) melanoma cells in a dose-dependent manner. The IC50 values ranged from 7.3 to 18 μM after 24 h and decreased to 1.4 μM after 72 h of treatment. Notably, this effect was more important than that of cisplatin (IC50 = 3 μM after 72 h of treatment), a chemotherapeutic agent, commonly used in the treatment of malignant melanoma. Furthermore, the cytotoxicity of the decavanadate compound was relatively weak on normal human keratinocytes (HaCaT), with a light effect (IC50 >> 70 μM) observed after 24 h of treatment. Thus, the Mg2Na2V10O28·20H2O compound displayed an advantage over cisplatin, which was reported to be much more aggressive to the keratinocyte cell line (IC50 = 23.9 μM). Moreover, it inhibited dose-dependently the adhesion of IGR39 cells to collagen (IC50 = 2.67 μM) and fibronectin, as well as their migration with an IC50 value of 2.23 μM. More interestingly, its in vivo administration to B16-F10 allografted mice, at the nontoxic dose of 50 μg (2.5 mg/kg), prevented and suppressed by 70% the tumor growth, compared to the nontreated mice. Moreover, this compound has also allowed a recovery against inflammation induced in mice by a mixture of DMBA and croton oil. Thus, all our results showed the potential of the Mg2Na2V10O28·20H2O compound to prevent and efficiently treat the growth and metastasis of melanoma.

Summary: Background: Adrenocortical tumours (ACT) in children are part of the Li-Fraumeni cancer spectrum and are frequently associated with a germline TP53 pathogenic variant. TP53 p.R337H is highly prevalent in the south and southeast of Brazil and predisposes to ACT with low penetrance. Thus, we aimed to investigate whether genetic variants exist which are associated with an increased risk of developing ACT in TP53 p.R337H carrier children. Methods: A genetic association study was conducted in trios of children (14 girls, 7 boys) from southern Brazil carriers of TP53 p.R337H with (n = 18) or without (n = 3) ACT and their parents, one of whom also carries this pathogenic variant (discovery cohort). Results were confirmed in a validation cohort of TP53 p.R337H carriers with (n = 90; 68 girls, 22 boys) or without ACT (n = 302; 165 women, 137 men). Findings: We analysed genomic data from whole exome sequencing of blood DNA from the trios. Using deep learning algorithms, according to a model where the affected child inherits from the non-carrier parent variant(s) increasing the risk of developing ACT, we found a significantly enriched representation of non-coding variants in genes involved in the cyclic AMP (cAMP) pathway known to be involved in adrenocortical tumorigenesis. One among those variants (rs2278986 in the SCARB1 gene) was confirmed to be significantly enriched in the validation cohort of TP53 p.R337H carriers with ACT compared to carriers without ACT (OR 1.858; 95% CI 1.146, 3.042, p = 0.01). Interpretation: Profiling of the variant rs2278986 is a candidate for future confirmation and possible use as a tool for ACT risk stratification in TP53 p.R337H carriers. Funding: Centre National de la Recherche Scientifique (CNRS), Behring Foundation, Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).

Dialysis machines operate in an uncertain environment with several sources of disturbances; therefore, it is necessary to take account of the uncertainties during all their life phases. This paper presents a study of the random reliability of the dialysis machine in a stochastic environment through the two-parameter for Weibull distribution. The shape and scale parameters were estimated through analytical and graphical methods based on the failure history of the devices. The formulation of the analytical methods and their exploitation using numerical simulations was one of the objectives of this work. The uncertainties in the stochastic environment of the machines are related to variability in physical and geometric parameters, fluctuations in load conditions, stress boundary conditions, and also to physical laws and simplifying assumptions used in the modeling process. The Weibull parameters introduced these uncertainties, and their effect on the device's reliability was studied. The main contribution is the study of the effect of the uncertainties in Weibull parameters on the reliability of the dialysis machine. The question of the uncertainties in the Weibull parameters was treated. The involved parameters were considered a Gaussian variable, and their means and standard deviations were calculated in several configurations of the dialysis devices. The random failure rate and reliability were treated and discussed. The random systematic inspection period is studied to install an efficient preventive maintenance program.

IntroductionIn systemic sclerosis (SSc), B-cells are activated and present in the skin and lung of patients where they can interact with fibroblasts. The precise impact and mechanisms of the interaction of B-cells and fibroblasts at the tissular level are poorly studied.ObjectiveWe investigated the impact and mechanisms of B-cell/fibroblast interactions in cocultures between B-cells from patients with SSc and 3-dimensional reconstituted healthy skin model including fibroblasts, keratinocytes and extracellular matrix.MethodsThe quantification and description of the B-cell infiltration in 3D cocultures were performed using cells imagery strategy and cytometry. The effect of coculture on the transcriptome of B-cells and fibroblasts was studied with bulk and single-cell RNA sequencing approaches. The mechanisms of this interaction were studied by blocking key cytokines like IL-6 and TNF.ResultsWe showed a significant infiltration of B-cells in the 3D healthy skin model. The amount but not the depth of infiltration was higher with B-cells from SSc patients and with activated B-cells. B-cell infiltrates were mainly composed of naïve and memory cells, whose frequencies differed depending on B-cells origin and activation state: infiltrated B-cells from patients with SSc showed an activated profile and an overexpression of immunoglobulin genes compared to circulating B-cells before infiltration. Our study has shown for the first time that activated B-cells modified the transcriptomic profile of both healthy and SSc fibroblasts, toward a pro-inflammatory (TNF and IL-17 signaling) and interferon profile, with a key role of the TNF pathway.ConclusionB-cells and 3D skin cocultures allowed the modelization of B-cells infiltration in tissues observed in SSc, uncovering an influence of the underlying disease and the activation state of B-cells. We showed a pro-inflammatory effect on skin fibroblasts and pro-activation effect on infiltrating B-cells during coculture. This reinforces the role of B-cells in SSc and provide potential targets for future therapeutic approach in this disease.

Background Brain injury is one of the most serious complications after cardiac arrest (CA). To prevent this phenomenon, rapid cooling with total liquid ventilation (TLV) has been proposed in small animal models of CA (rabbits and piglets). Here, we aimed to determine whether hypothermic TLV can also offer neuroprotection and mitigate cerebral inflammatory response in large animals. Methods and Results Anesthetized pigs were subjected to 14 minutes of ventricular fibrillation followed by cardiopulmonary resuscitation. After return of spontaneous circulation, animals were randomly subjected to normothermia (control group, n=8) or ultrafast cooling with TLV (TLV group, n=8). In the latter group, TLV was initiated within a window of 15 minutes after return of spontaneous circulation and allowed to reduce tympanic, esophageal, and bladder temperature to the 32 to 34 °C range within 30 minutes. After 45 minutes of TLV, gas ventilation was resumed, and hypothermia was maintained externally until 3 hours after CA, before rewarming using heat pads (0.5 °C–1 °C/h). After an additional period of progressive rewarming for 3 hours, animals were euthanized for brain withdrawal and histological analysis. At the end of the follow‐up (ie, 6 hours after CA), histology showed reduced brain injury as witnessed by the reduced number of Fluroro‐Jade C‐positive cerebral degenerating neurons in TLV versus control. IL (interleukin)‐1ra and IL‐8 levels were also significantly reduced in the cerebrospinal fluid in TLV versus control along with cerebral infiltration by CD3+ cells. Conversely, circulating levels of cytokines were not different among groups, suggesting a discrepancy between local and systemic inflammatory levels. Conclusions Ultrafast cooling with TLV mitigates neuroinflammation and attenuates acute brain lesions in the early phase following resuscitation in large animals subjected to CA.

Traffic-related pollution significantly contributes to environmental degradation. The escalating demand for vehicles, coupled with consumer preferences for larger utility vehicles, poses a challenge to achieving targeted carbon emission reductions in common fleet vehicles. To address the inefficiencies in existing route planning methods, this paper introduces a novel eco-routing approach known as Visual Eco-Routing (VER). VER is designed to understand the non-linear relationships between road scenes and emissions data, providing a comprehensive insight into the real-time dynamics of roads and their influence on vehicle performance characteristics. On-road experimental cycles are conducted to gather data, creating a new dataset called the Vehicle Activity Dataset (VAD). To assess viability of the VER approach, a model named VER-XGB based on eXtreme Gradient Boosting (XGBoost) is proposed. Performance comparisons are made by individual training and benchmarking three selected models, both without VER association and separately with VER association. The comparison reveals significantly lower prediction errors in models with VER, with VER-XGB exhibiting enhanced reliability, yielding MAPE of 4.83% with VAD. Additionally, an aggregate factor termed the emission factor is introduced to explore the correlation between emission gases and distinct groups of visual features defined in the study. The analysis indicates a high correlation between infrastructure features such as traffic signals and stop signs on the road and vehicle emissions. Concluding the study, a qualitative examination is undertaken to evaluate the real-world applicability of the model by predicting an eco-route for a given origin and destination pair. The MAPE for this route for predictions from VER-XGB is found to be 6.21%, affirming the practical utility of the proposed VER-XGB model in real-world scenarios.

Abstract Background The spread of COVID-19 has brought challenges to health, social and economic systems around the world. With little to no prior immunity in the global population, transmission has been driven primarily by human interaction. However, as with common respiratory illnesses such as influenza some authors have suggested COVID-19 may become seasonal as immunity grows. Despite this, the effects of meteorological conditions on the spread of COVID-19 are poorly understood. Previous studies have produced contrasting results, due in part to limited and inconsistent study designs. Methods This study investigates the effects of meteorological conditions on COVID-19 infections in England using a Bayesian conditional auto-regressive spatio-temporal model. Our data consists of daily case counts from local authorities in England during the first lockdown from March–May 2020. During this period, legal restrictions limiting human interaction remained consistent, minimising the impact of changes in human interaction. We introduce a lag from weather conditions to daily cases to accommodate an incubation period and delays in obtaining test results. By modelling spatio-temporal random effects we account for the nature of a human transmissible virus, allowing the model to isolate meteorological effects. Results Our analysis considers cases across England’s 312 local authorities for a 55-day period. We find relative humidity is negatively associated with COVID-19 cases, with a 1% increase in relative humidity corresponding to a reduction in relative risk of 0.2% [95% highest posterior density (HPD): 0.1–0.3%]. However, we find no evidence for temperature, wind speed, precipitation or solar radiation being associated with COVID-19 spread. The inclusion of weekdays highlights systematic under reporting of cases on weekends with between 27.2–43.7% fewer cases reported on Saturdays and 26.3–44.8% fewer cases on Sundays respectively (based on 95% HPDs). Conclusion By applying a Bayesian conditional auto-regressive model to COVID-19 case data we capture the underlying spatio-temporal trends present in the data. This enables us to isolate the main meteorological effects and make robust claims about the association of weather variables to COVID-19 incidence. Overall, we find no strong association between meteorological factors and COVID-19 transmission.

Abstract Systemic sclerosis (SSc) is the most severe systemic autoimmune disease with currently no cure. Intravenous immunoglobulins (IVIg) are an attractive candidate in this disease to counteract inflammation and fibrosis but data are scarce and conflicting. This study, assessed the effects of IVIg in a murine HOCl-induced model of SSc. We showed that IVIg prevented skin inflammation and fibrosis, by mitigating the immune cell infiltration (p = 0.04), proinflammatory cytokines gene overexpression (IL1β, p = 0.04; TNFα, p = 0.04; IL6, p = 0.05), skin and dermal thickening (p = 0.003 at d21 and p = 0.0003 at d42), the expression markers of fibrosis, such as αSMA (p = 0.031 for mRNA and p = 0.05 for protein), collagen (p = 0.05 for mRNA and p = 0.04 for protein, p = 0.05 for the hydroxyproline content) and fibronectin (p = 0.033 for mRNA). Moreover, IVIg prevented HOCl-induced alterations in splenic cell homeostasis. When administered in curative mode, despite their ability to reduce skin and dermal thickness (p

Abstract Systemic sclerosis (SSc) is an autoimmune, inflammatory and fibrotic disease with limited treatment options. Developing new therapies is therefore crucial to address patient needs. To this end, we focused on galectin-3 (Gal-3), a lectin known to be associated with several pathological processes seen in SSc. Using RNA sequencing of whole-blood samples in a cross-sectional cohort of 249 patients with SSc, Gal-3 and its interactants defined a strong transcriptomic fingerprint associated with disease severity, pulmonary and cardiac malfunctions, neutrophilia and lymphopenia. We developed new Gal-3 neutralizing monoclonal antibodies (mAb), which were then evaluated in a mouse model of hypochlorous acid (HOCl)-induced SSc. We show that two of these antibodies, D11 and E07, reduced pathological skin thickening, lung and skin collagen deposition, pulmonary macrophage content, and plasma interleukin-5 and -6 levels. Moreover, E07 changed the transcriptional profiles of HOCl-treated mice, resulting in a gene expression pattern that resembled that of control mice. Similarly, pathological pathways engaged in patients with SSc were counteracted by E07 in mice. Collectively, these findings demonstrate the translational potential of Gal-3 blockade as a therapeutic option for SSc.

We report a case of a 16-year-old man in cardiogenic shock secondary to On-X mitral prosthesis dysfunction due to leaflet embolization through aortic mechanical prosthesis. He underwent an emergency redo mitral valve replacement and, a few days later, leaflet removal by open aortic surgery with full recovery.

In the field of smart mobility, Artificial Intelligence (AI) approaches are influential and can make a highly beneficial contribution. Our project aims to develop a real-time ecological map of road traffic. This map will allow electric vehicles (EVs) and thermal vehicles (TVs) to display the cost of energy consumption and CO2 emissions on different road sections. In urban environments, road traffic emissions are a significant contributor to environmental pollution, with vehicle emissions being a major component. Addressing these impacts requires a thorough understanding of the operational behavior of vehicles on different road infrastructures within the region. This paper presents a novel, comprehensive dataset, the Vehicle Activity Dataset (VAD), designed to assess the emissions and fuel consumption characteristics of vehicles about their actual operating environment. Constructed from a large number of real-world driving scenarios, VAD incorporates emission data collected by an industrial Portable Emission Measurement System (PEMS), road scenes captured by an RGB camera, and the detection of different object classes within these images. The primary objective of VAD is to provide a comprehensive understanding of the relationship between vehicle emissions and the diverse range of objects present on the road. Experimental results in real road traffic environments through different studies demonstrate the robustness of the developed dataset.

Nuclear power plants (NPPs) rely on critical, complex systems that require continuous monitoring to ensure safe operation under both normal and abnormal conditions. Despite the potential of artificial intelligence (AI) to enhance predictive capabilities in these systems, limited research has been conducted on the application of AI algorithms within NPPs. This presents a knowledge gap in the integration of AI for improving safety, reliability, and decision making in NPP. In this study, we explore the use of AI methods, including machine learning and real-time data analytics, applied to NPP components to address the nonlinearity and dynamic behavior inherent in reactor operations. Through the implementation of AI and Internet of Things (IoT) devices, we propose a system that enables early warning and real-time data transmission to regulatory authorities and decision-makers, ensuring better coordination during incidents. Lessons from past nuclear accidents, such as Chernobyl, emphasize the importance of timely information dissemination to mitigate risks. However, this integration also presents challenges, including cybersecurity risks and the need for updated regulations to address AI use in safety-critical environments. The results of this study highlight the urgent need for further research on the application of AI in NPPs, with a particular focus on addressing these challenges to ensure safe implementation. [ABSTRACT FROM AUTHOR]

Colorectal intussusception is a rare entity in adults presenting an acute abdomen. The authors present a case of a 73-year-old female who presented with an acute large bowel obstruction. Abdominal computed tomography (CT) scan reveals a colorectal intussusception with a colonic distension upstream. Laparoscopy founds out a stenotic tumor on colorectal junction corresponding with an adenocarcinoma on histopathological exam. CT scan is the most specific diagnostic test for intussusception and is superior to ultrasonography and endoscopy and thus should be performed preferentially.

De plus en plus d’initiatives de développement rural au Maghreb affichent une volonté d’adopter des approches participatives. Or, pour les agents de l’administration, la mise en œuvre de ces approches implique souvent un changement de posture et l’acquisition de connaissances et de compétences spécifiques. Comme tous les agents ne peuvent pas être formés à la participation, bon nombre d’initiatives adoptent une stratégie reposant sur une hypothèse de partage de compétences et de posture entre un petit groupe d’agents de l’administration qui sont formés à la participation et leurs collègues. Cet article vise à analyser dans quelle mesure ce partage de compétences et de posture est effectif ou non dans le cas d’une démarche participative mise en œuvre sur un territoire rural en Tunisie. Notre analyse repose sur 12 entretiens individuels réalisés auprès d’agents de l’administration. Notre analyse montre qu’il y a eu un partage partiel entre les facilitateurs de la démarche et les agents de l’administration qui ont été impliqués. Les personnes interrogées ont notamment acquis des compétences sur les outils participatifs et pour l’une d’entre elles au moins un changement de posture est envisagé. On ne peut pas dire pour autant que leur implication dans la démarche, quel que soit son degré, ait changé leur vision sur la participation. Le partage de compétences et de posture pourrait être renforcé par une réflexion plus poussée sur la distribution des rôles et des responsabilités entre agents de l’administration lors de l’ingénierie de la démarche.

Abstract Background Mastocytosis is a rare disease characterised by the accumulation and/or proliferation of abnormal mast cells (MCs) in one or several organs. It may present with a number of different symptoms that involve various organ systems. The current study aims to assess the prevalence of MC mediator-related symptoms in a cohort of mastocytosis patients with a specific focus on neurological, psychiatric, cognitive and sexual symptoms. We also assessed the impact of the disease on patients’ professional lives. Patients were administered a validated multidimensional questionnaire to collect information on patients’ perception of the severity of their symptoms. From the questionnaires we extracted the neurological, cognitive, psychiatric and sexual symptoms and the impact of the disease on patients’ professional lives as well as their grading. The affective status was assessed using the 17-item version of the Hamilton Depression Rating Scale. Results We included 139 patients. Mastocytosis was classified as systemic in 113 patients and cutaneous in 26 patients. The prevalence of MC mediator-related systemic symptoms was as follows: cutaneous (71%), gastro-intestinal (48%), cardio-vascular (36%), musculoskeletal (26.6%), fatigue (24%), urinary (14.4%) and respiratory (10%). Headaches and vertigo were noted in respectively 55% and 32% of patients. Irritability, episodes of memory loss and difficulty concentrating were reported in 54%, 52% and 40% of cases, respectively. Sexual impairment was noted in 24% of patients. No associations were found between neuropsychiatric/cognitive impairment and age, gender, diagnostic delay, disease form, the presence of cutaneous lesions, the level of serum and bone marrow tryptase and the presence of KIT mutation in bone marrow and/or skin. Depression was noted in 49% of patients. One in four patients reported a negative impact of the disease on their professional lives. Conclusion This current study provides some insights regarding symptoms related to mastocytosis and their impact on patients’ professional lives.