Abnormal expression of oxylipins and related synthesizing/signaling pathways in inflammatory bowel diseases.

We investigated selected oxylipins and related synthesizing/signaling pathways in 28 patients with Crohn's disease (CD), 19 patients with ulcerative colitis (UC), and 39 controls. Plasma and mucosal PUFA/oxylipin profiles were analyzed by LC-MS/MS. mRNA expression of 5, 12 and 15-lipooxygenases, FPR2/ALXR, FFAR4/GPR120, annexin A1, and interleukin-10 were analyzed by qRT-PCR. Oxylipin profile and related metabolic pathways were altered in both CD and UC patients. The patterns were characterized by increased prostaglandins, leukotrienes, and lipoxins and overexpression of 5-lipoxygenase, FPR2/ALXR, annexin A1, and interleukin-10 genes, but decreased n-3 PUFAs and 18-hydroxyeisapentaenoic acid. The gene of 15-lipoxygenase was under-expressed mainly in UC patients. CD and UC are associated with unbalanced n-6 ​​and n-3 derivatives and pro-inflammatory and anti-inflammatory/pro-resolving mediators favoring the former compounds. The findings suggest that oxylipins engage in the pathophysiology of the diseases. Targeting oxylipin's metabolic pathways would be a promising therapy for inflammatory bowel diseases.

Raising nurse educators' awareness regarding caring pedagogical relationships' barriers to foster inclusive simulation settings: Insights from a phenomenological study.

AIM: The purpose of this paper was to shed light on the main barriers to caring pedagogical relationships within simulation centers from the perspective of nursing students and offer targeted strategies to reduce these barriers. BACKGROUND: A caring pedagogical relationship is a powerful strategy to foster students' learning within simulation settings. However, the development of this relationship could be hindered if nurse educators are not aware of its barriers. Hence, this could affect students' learning and well-being within this academic context. According to our knowledge, no previous research has addressed the question of the barriers to caring pedagogical relationships within the context of simulation. DESIGN: This study employed a descriptive phenomenological method, entitled Relational Caring Inquiry, to collect and analyze data gathered from 19 students enrolled in an undergraduate nursing program. RESULTS: This paper focuses on one eidos-theme that emerged from our data analysis and interpretation entitled "Educator's conscientization regarding barriers to the development of a caring pedagogical relationship". According to data analysis and interpretation, this eidos-theme was the most emphasized by research participants. It emerged from the following themes: (a) educators' dehumanizing practices, (b) disruptive and stressful academic context, (c) lack of educators' experiences and (d) educators' disinterest in students' learning. CONCLUSIONS: Leaving caring pedagogical relationships' barriers unaddressed has shown adverse impacts on students' learning process and their mental and physical well-being. This paper brings to light the main barriers to caring pedagogical relationships and invites educators, managers and nurse leaders to be aware of these obstacles and collectively engage in humanizing nursing education. In other words, we emphasize the impact of these barriers on students' apprenticeship and suggest political actions to build caring and inclusive simulation environments. STUDY REGISTRATION NUMBER: CERSES-19-050-D.

Cultivating a psychological health and safety culture for interprofessional primary care teams through a co-created evidence-informed toolkit.

The psychological health and safety of healthcare workers workplaces and learning environments impacts the quality of healthcare services. To facilitate the psychological health and safety of interprofessional primary care teams, we curated a bilingual toolkit of 122 psychological health and safety resources comprising a multi-level categorization addressing individual, team, organization, and system-level interventions. The resources in the toolkit are organized by 7 themes, based on a clustering of the 15 psychosocial factors. Adopting the framework built on the 7 themes, this article describes the toolkit development process and how it addresses the key factors for psychologically healthy and safe workplaces to foster interprofessional collaboration. Implementation of the interventions in the toolkit is an important next step for which health system leadership is critical. Additionally, we identify several gaps and call on researchers, educators, and health leaders to address them in their future work.

Assessing the spillover effects of various forms of energy on CO2 emissions - An empirical study based on dynamic spatial Durbin model.

Previous studies ignored the geospatial dynamics spillover effects of energy consumption on CO2 emissions while assessing such impacts in developed and developing countries. Moreover, most studies wrongfully assess spillover effects in its aggregated format rather than decomposing by its components. This is important as not all energy sources share the same characteristics. We fill these gaps in the literature by investigating the spillover effects of various forms of energy, including fossil fuels, renewable energy, and nuclear power, on CO2 emissions in 135 developed and developing countries from 2000 to 2019. We used the Dynamic Spatial Durbin Model (DSDM) to better understand the results. A series of indicative tests confirmed using the DSDM model and including spatial interaction of CO2 emissions in the analysis. Our findings show evidence of indirect spillover effects of the various energy sources on CO2 emissions. Further considering the spillover effects of the energy sources of neighbouring countries, the paper finds that the driving increase in CO2 emissions mainly came from the energy consumption of the country itself and neighbouring countries' energy consumption. Nevertheless, the results indicate that the direct effects of energy consumption often exceed its indirect effects. The results also confirm that total and fossil energy consumption harms the environment, whereas adopting renewable and nuclear energy sources reduces CO2 emissions. Lastly, we find nuclear energy is the most environmentally sustainable energy source. The study concludes that the Dynamic Spatial Durbin Model is paramount in estimating the environmental impact of energy consumption in our sample. The practical policy implications drawn from this study could be used to promote increased collaboration to hasten the energy transition process and address global warming and climate change.

A novel approach to designing viral precision vaccines applied to SARS-CoV-2.

Efficient precision vaccines against several highly pathogenic zoonotic viruses are currently lacking. Proteolytic activation is instrumental for a number of these viruses to gain host-cell entry and develop infectivity. For SARS-CoV-2, this process is enhanced by the insertion of a furin cleavage site at the junction of the spike protein S1/S2 subunits upstream of the metalloprotease TMPRSS2 common proteolytic site. Here, we describe a new approach based on specific epitopes selection from the region involved in proteolytic activation and infectivity for the engineering of precision candidate vaccinating antigens. This approach was developed through its application to the design of SARS-CoV-2 cross-variant candidates vaccinating antigens. It includes an in silico structural analysis of the viral region involved in infectivity, the identification of conserved immunogenic epitopes and the selection of those eliciting specific immune responses in infected people. The following step consists of engineering vaccinating antigens that carry the selected epitopes and mimic their 3D native structure. Using this approach, we demonstrated through a Covid-19 patient-centered study of a 500 patients' cohort, that the epitopes selected from SARS-CoV-2 protein S1/S2 junction elicited a neutralizing antibody response significantly associated with mild and asymptomatic COVID-19 (p<0.001), which strongly suggests protective immunity. Engineered antigens containing the SARS-CoV-2 selected epitopes and mimicking the native epitopes 3D structure generated neutralizing antibody response in mice. Our data show the potential of this combined computational and experimental approach for designing precision vaccines against viruses whose pathogenicity is contingent upon proteolytic activation.

The Trajectory of Agency-Employed Nurses in Ontario, Canada: A Longitudinal Analysis (2011-2021).

In Canada, reports of nursing staff shortages, job vacancies and the use of private agency nurses, especially in hospitals, have increased since the start of the COVID-19 pandemic. Media reports suggest the pandemic exacerbated nursing shortages among other issues, and nurses are leaving their traditional positions to work at such agencies. Public spending on agency nurses has increased appreciably. Using 2011 to 2021 regulatory college data on all registered nurses (RNs) and registered practical nurses (RPNs) in the province of Ontario, Canada, we investigated trends in the count and share of nurses working for employment agencies. We also examined the rate at which previously non-agency employed nurses transition to employment in at least one agency job. We found the prevalence of RNs and RPNs reporting agency employment was relatively stable from 2011 to 2019, and decreased slightly in 2020 and 2021. However, there was a small increase in transitions from non-agency employment to working at an agency job. We also found the mean hours of practice in all jobs reported by agency and non-agency nurses increased during the pandemic. Based on these findings, an increase in hours and/or prices for agency nurses may explain the increase in public funding for agency nurses, but it was not driven by an increasing share of nurses working for employment agencies. To fully understand employment agency activity, policymakers may need to monitor hours of work and hourly costs rather than only costs. Further research is required to investigate any long-term effects the pandemic may have had on agency-employment.

Investigating the fundamental levels of a signature pedagogy in nursing education: A scoping review.

BACKGROUND: A signature pedagogy is a unique approach that provides a blueprint for curricular decision-making, as it reflects how we teach (surface structures), why we teach (deep structures), and what we believe are vital concepts or values all learners should embody (implicit structures). OBJECTIVE: To investigate what is known from the existing literature about a signature pedagogy to support undergraduate nursing education. DESIGN: This scoping review adopted Arksey and O'Malley's framework to guide the analysis of data. Two electronic databases were used to explore studies on educational strategies, content, and values published in Arabic, English, Filipino, French, Portuguese, and Spanish between 1972 and 2022. RESULTS: A total of 258 articles were included in this review. The analysis revealed that the majority of articles were at the surface (n = 189), followed by the deep (n = 123), with the least number examining the implicit level (n = 90) associated with signature pedagogy levels. Results reflect a limited focus on implicit level; the core concepts and values that all learners should understand and grasp for their future practice to construct their professional identity and engage in healthcare transformation. CONCLUSIONS: The findings from this scoping review, should not be an isolated movement within nursing education. The first step is to engage in discourse amongst all stakeholders, educational and healthcare nurse leaders, regarding the state of the profession. As a profession we need to understand what is the preferred future of nursing and what are the necessary educational processes to ensure the profession is actualizing their mandate. A call to action to develop a unique signature pedagogy should provide synergy between education and practice to enhance learner's competencies as a future professional.

Short-term effect of COVID-19 pandemic on cryptocurrency markets: A DCC-GARCH model analysis.

This research examines the impact of the coronavirus index on the returns and volatility of ten major cryptocurrencies during the COVID-19 pandemic. For this purpose, we applied a multivariate volatility GARCH model with an integrated dynamic conditional correlation (DCC) approach to daily cryptocurrency values observed data during the January-December, 2020 period. Moreover, we used the Granger causality test to study return-volume correlations. The findings indicate that cryptocurrency volatility declined after the World Health Organization declared on March 11, 2020, that the coronavirus was a pandemic. Unlike most of the relevant previous studies, we found that the COVID-19 crisis did not have a long-term effect on cryptocurrency returns and volatility but only presented a short-term effect. Our results have implications for investors who need to determine an optimal portfolio for a scenario other than the base.

Managing the COVID-19 pandemic in thirty-two policy measures in Saudi Arabia: A mixed-methods analysis.

BACKGROUND: The Kingdom of Saudi Arabia has developed rigorous strategies to control and prevent the spread of COVID-19. However, the effectiveness of these measures in containing and mitigating the epidemic has yet to be studied. This paper aims to assess the efficiency of preventive policy initiatives that Saudi Arabia has taken to reduce the spread of COVID-19, which was rapid and progressive in nature. Information on the effectiveness of measures applies to help the Saudi government adjust policy responses when considering which measures to relax once the epidemic is controlled. METHODS: Data for this study were retrieved via publicly available data sources such as the Saudi Arabia Ministry of Health and the government's official news agency-Saudi Press Agency (SPA) websites. Other datasets, such as prevention measures, were gathered from the Country Policy Tracker website. Our dataset's time component extends over 590 consecutive days from 20 January 2020-31 August 2021. Moreover, a mixed-method approach combining COVID-19 data and prevention measures was adopted to assess preventative measures practice. We compiled the dataset used in this study in a Microsoft Excel database. The significance of observed differences among implementing effective strategies was determined using ANOVA and Mixed methods approach. Noticeably, the statistical analysis was performed using the open-source statistical system R version 4.2 (available at http://cran.r-project.org). RESULTS: Our analysis showed that only three out of the 32 (9.4%) measures significantly reduced the spread of COVID-19. Our results also show substantial variations in the spread of COVID-19 associated with preventive measures in Saudi Arabia. There was a significant positive correlation between activating and massive testing in communities and cases of COVID-19 (measure effect = 923.086 and p < 0.05). A similar result was found for complete curfew across the Kingdom and cases of COVID-19 (measure effect = 621.389 and p < 0.10). Removing slum areas interrupted the spread of Covid-19 (measure effect = 305.689 and p < 0.01). The other preventive measures did not significantly affect the COVID-19 pandemic distribution. These findings consistently concluded that activating and massive testing in communities, complete curfew across the Kingdom, and removal of slum areas were the most effective measures for reducing the impact of the COVID-19 pandemic. CONCLUSION: Only by understanding these correlations will it be possible to control and reduce the rate of COVID-19 spread and, therefore, suggest a possible exit strategy once the epidemic is controlled.

Sustaining the Canadian Nursing Workforce: Targeted Evidence-Based Reactive Solutions in Response to the Ongoing Crisis.

Inadequate staffing, excessive workloads, endemic violence and unhealthy workplaces are some of the challenges facing Canadian nurses. Leaving these issues unaddressed has had pernicious impacts on the nursing workforce: thousands of nurses across Canada have been suffering from extreme stress, anxiety and burnout, leading many of them to leave their current jobs and, for some, the profession of nursing altogether. We conducted a comprehensive yet rapid review of evidence-based solutions from the peer-reviewed and policy literature, stakeholder dialogues and member surveys commissioned by the Canadian Federation of Nurses Unions that could be implemented and scaled across Canada. Our findings support coordinated series of collectively planned, carefully sequenced and evidence-based interventions to retain, return, integrate and recruit nurses targeted to support the nursing workforce from training to early-, mid- and late-career stages. The implementation of these reactive solution bundles will also enhance the quality of healthcare services and, more broadly, the healthcare system.

Attention-guided neural network for early dementia detection using MRS data.

Imaging bio-markers have been widely used for Computer-Aided Diagnosis (CAD) of Alzheimer's Disease (AD) with Deep Learning (DL). However, the structural brain atrophy is not detectable at an early stage of the disease (namely for Mild Cognitive Impairment (MCI) and Mild Alzheimer's Disease (MAD)). Indeed, potential biological bio-markers have been proved their ability to early detect brain abnormalities related to AD before brain structural damage and clinical manifestation. Proton Magnetic Resonance Spectroscopy (1H-MRS) provides a promising solution for biological brain changes detection in a no invasive manner. In this paper, we propose an attention-guided supervised DL framework for early AD detection using 1H-MRS data. In the early stages of AD, features may be closely related and often complex to delineate between subjects. Hence, we develop a 1D attention mechanism that explicitly guides the classifier to focus on diagnostically relevant metabolites for classes discrimination. Synthetic data are used to tackle the lack of data problem and to help in learning the feature space. Data used in this paper are collected in the University Hospital of Poitiers, which contained 111 1H-MRS samples extracted from the Posterior Cingulate Cortex (PCC) brain region. The data contain 33 Normal Control (NC), 49 MCI due to AD, and 29 MAD subjects. The proposed model achieves an average classification accuracy of 95.23%. Our framework outperforms state of the art imaging-based approaches, proving the robustness of learning metabolites features against traditional imaging bio-markers for early AD detection.

COVID-19 impact on digital companies' stock return: A dynamic data analysis.

The coronavirus crisis impact on the digital sector is undoubtedly an important issue that deserves to be studied. Researchers mostly focused on specific sectors such as tourism, healthcare sector, or the economy. This paper used a dynamic panel model to examine the COVID-19 crisis impact on the digital companiesfl stock return. The findings indicate that both of the monthly growth in total infected cases and total death cases caused by COVID-19 have significant positive effects on stock returns across digital companies. This novel results contradicts previous research findings and highlights that this crisis is slowing down all the economic sectors.

Root Reinforcement Improved Performance, Productivity, and Grain Bioactive Quality of Field-Droughted Quinoa (Chenopodium quinoa).

Modern agriculture is facing multiple and complex challenges and has to produce more food and fiber to feed a growing population. Increasingly volatile weather and more extreme events such as droughts can reduce crop productivity. This implies the need for significant increases in production and the adoption of more efficient and sustainable production methods and adaptation to climate change. A new technological and environment-friendly management technique to improve the tolerance of quinoa grown to maturity is proposed using native microbial biostimulants (arbuscular mycorrhizal fungi; AMF) alone, in the consortium, or in combination with compost (Comp) as an organic matter source under two water treatments (normal irrigation and drought stress (DS)). Compared with controls, growth, grain yield, and all physiological traits under DS were significantly decreased while hydrogen peroxide, malondialdehyde, and antioxidative enzymatic functions were significantly increased. Under DS, biofertilizer application reverted physiological activities to normal levels and potentially strengthened quinoa's adaptability to water shortage as compared to untreated plants. The dual combination yielded a 97% improvement in grain dry weight. Moreover, the effectiveness of microbial and compost biostimulants as a biological tool improves grain quality and limits soil degradation under DS. Elemental concentrations, particularly macronutrients, antioxidant potential (1,1-diphenyl-2-picrylhydrazyl radical scavenging activity), and bioactive compounds (phenol and flavonoid content), were accumulated at higher levels in biofertilizer-treated quinoa grain than in untreated controls. The effects of AMF + Comp on post-harvest soil fertility traits were the most positive, with significant increases in total phosphorus (47%) and organic matter (200%) content under drought conditions. Taken together, our data demonstrate that drought stress strongly influences the physiological traits, yield, and quality of quinoa. Microbial and compost biostimulation could be an effective alternative to ensure greater recovery capability, thereby maintaining relatively high levels of grain production. Our study shows that aboveground stress responses in quinoa can be modulated by signals from the microbial/compost-treated root. Further, quinoa grains are generally of higher nutritive quality when amended and inoculated with AMF as compared to non-inoculated and compost-free plants.

Assessment of fenestrated Anaconda stent graft design by numerical simulation: Results of a European prospective multicenter study.

OBJECTIVE: A crucial step in designing fenestrated stent grafts for treatment of complex aortic abdominal aneurysms is the accurate positioning of the fenestrations. The deployment of a fenestrated stent graft prototype in a patient-specific rigid aortic model can be used for design verification in vitro, but is time and human resources consuming. Numerical simulation (NS) of fenestrated stent graft deployment using the finite element analysis has recently been developed; the aim of this study was to compare the accuracy of fenestration positioning by NS and in vitro. METHODS: All consecutive cases of complex aortic abdominal aneurysm treated with the Fenestrated Anaconda (Terumo Aortic) in six European centers were included in a prospective, observational study. To compare fenestration positioning, the distance from the center of the fenestration to the proximal end of the stent graft (L) and the angular distance from the 0° position (C) were measured and compared between in vitro testing (L1, C1) and NS (L2, C2). The primary hypothesis was that ΔL (|L2 - L1|) and ΔC (|C2 - C1|) would be 2.5 or less mm in more than 80% of the cases. The duration of both processes was also compared. RESULTS: Between May 2018 and January 2019, 50 patients with complex aortic abdominal aneurysms received a fenestrated stent graft with a total of 176 fenestrations. The ΔL and ΔC was 2.5 mm or less for 173 (98%) and 174 (99%) fenestrations, respectively. The NS process duration was significantly shorter than the in vitro (2.1 days [range, 1.0-5.2 days] vs 20.6 days [range, 9-82 days]; P < .001). CONCLUSIONS: Positioning of fenestrations using NS is as accurate as in vitro and could significantly decrease delivery time of fenestrated stent grafts.

Childhood visceral leishmaniasis in Tunisia: A cross-sectional study in local spatial analysis.

This paper describes spatial distribution of Visceral Leishmaniasis (VL) and determines its correlation with climatic factors in an endemic focus in northern and central Tunisia. Data on VL cases in children under five years of age were obtained by consulting medical reports from all Tunisian Pediatric Departments (TPD) during 2006-2016. Three key climatic factors, namely precipitation, continentality index and pluviometric coefficient of Emberger were used as predictor variables to model the VL geographical distribution. Data handling and statistical analysis were performed using R and Arcview GIS software systems. Bayesian local spatial model was employed to analyse the data. The results show a progressive increase in the VL incidence rates in regions with high levels of precipitation, but with low values of both continentality index and pluviometric coefficient of Emberger. A likely explanation of these findings arises from the opposite local effects of climatic factors which tend to cancel each other out in the calculation of the mean parameter estimate over the whole study area. We conclude that using non-local spatial analysis approach leads to misleading epidemiological interpretations, which in turn are of relevance for more efficient and cost-effective resource allocation for control and well manage the spread of VL in the study region and elsewhere in Tunisia.

Rare splicing defects of FAS underly severe recessive autoimmune lymphoproliferative syndrome.

Autoimmune lymphoproliferative syndrome (ALPS) is a prototypic disorder of impaired apoptosis characterized by autoimmune features and lymphoproliferation. Heterozygous germline or somatic FAS mutations associated with preserved protein expression have been described. Very rare cases of homozygous germline FAS mutations causing severe autosomal recessive form of ALPS with a complete defect of Fas expression have been reported. We report two unrelated patients from highly inbred North African population showing a severe ALPS phenotype and an undetectable Fas surface expression. Two novel homozygous mutations have been identified underlying rare splicing defects mechanisms. The first mutation breaks a branch point sequence and the second alters a regulatory exonic splicing site. These splicing defects induce the skipping of exon 6 encoding the transmembrane domain of CD95. Our findings highlight the requirement of tight regulation of FAS exon 6 splicing for balanced alternative splicing and illustrate the importance of such studies in highly consanguineous populations.

Ticlopidine and clopidogrel, sometimes combined with aspirin, only minimally increase the surgical risk in renal transplantation: a case-control study.

BACKGROUND: Patients undergoing kidney transplantation are sometimes being treated with antiplatelet agents such as ticlopidine or clopidogrel. Some teams refuse to wait-list these patients for fear of bleeding during transplant surgery. METHODS: We retrospectively reviewed the records of 702 adult patients with a kidney transplant alone between 2000 and 2010. Nineteen (2.7%) patients were taking clopidogrel or ticlopidine when called in for transplantation. Furthermore, 10 of these 19 patients were also taking low-dose aspirin (ASA). We compared the risk of bleeding peri- and postoperatively, and the occurrence of cardiovascular complications within 30 days after renal transplantation between 19 cases and 39 controls randomly selected within the cohort. RESULTS: Platelets were administered to 7 cases (37%) versus 0 controls (P<0.001). A single case (5.3%) presented with significant bleeding during surgery following an implantation biopsy, and required 4 red bood cell (RBC) units. During the first day, 3 of the 19 cases (16%) and 1 of the 39 controls required RBC (P=0.1). No reoperation was performed for bleeding. After the transplant, clopidogrel or ticlopidine was resumed in only two patients. The platelet count and haemoglobin were similar between cases and controls at Day 30. No cardiovascular event occurred in cases or controls during the first month post-transplantation. At 5 years, graft and patient survival was similar in cases and controls. CONCLUSIONS: Clopidogrel and ticlopidine, sometimes in combination with ASA, are associated with a low risk of bleeding during renal transplantation and does not seem to be a contraindication for renal transplant surgery.

Visceral leishmaniasis in Tunisia: spatial distribution and association with climatic factors.

Visceral leishmaniasis (VL) cases in children less than five years of age were recorded from 1996 through 2006 from Tunisian pediatric departments. Mean incidence rates were calculated for each of the 215 districts in the study area. Averages of annual rainfall and extreme values of low temperatures in winter and high temperatures in summer were used to characterize the climate of each district according to its continentality index and bioclimatic zone. A geographic information system and a local indicator of spatial association were used to summarize the spatial properties of VL distribution. Poisson spatial regression was performed to study the relationship between VL incidence rates and climatic parameters. We identified one hot-spot region of 35 inland districts located mostly in the semi-arid bioclimatic zone and two cold-spots located in coastal regions of the northeastern sub-humid zone and the southeastern arid zone. The incidence rate of VL was positively correlated with mean yearly rainfall and continentality index.