Search Results (8)

During the last few years, nuclear energy has received great attention due to the increase in climate change awareness. According to the Paris agreement, global temperature is to be kept below 2 °C and preferably below 1.5 °C by 2050. This approach has been substantially confirmed in the recent COP 26 in Glasgow. This research investigates the effects of integrating SMR nuclear power plants (small modular reactors) into the Nordhaus Dynamic Integrated Climate Economy (DICE) model for reducing the CO₂ emissions in the atmosphere by substituting all existing fossil-fueled power plants (FPPP). The software is based on the VENSIM dynamic systems modeling platform. Simulations were carried out from the year 2019 to 2100 using 10-year increments. Several scenarios were thus simulated replacing roughly 70,000 FPPPs operating at this time in the world. Simulations indicate a CO₂ reduction of approximately 12.63% relative to the initial conditions used and using 87,830 SMR core units of 80 MWe electric each to meet such demand. The DICE model further predicts the cost of climate damage impacting the upper ocean and atmospheric temperatures, and the deep ocean temperature as USD 1.515 trillion (US Dollar; (US) trillion = 1,000,000,000,000 (1 × 10¹²)) by the end of this century. From a modified section of the model, a cost of USD 1.073 trillion is predicted as the toll on human health costs. This is thus equal to a USD 2.59 trillion loss in the economy. Full article

Artemisinin (also known as Qinghaosu), an active component of the Qinghao extract, is widely used as antimalarial drug. Previous studies reveal that artemisinin and its derivatives also have effective anti-inflammatory and immunomodulatory properties, but the direct molecular target remains unknown. Recently, several reports mentioned that myeloid differentiation factor 2 (MD-2, also known as lymphocyte antigen 96) may be the endogenous target of artemisinin in the inhibition of lipopolysaccharide signaling. However, the exact interaction between artemisinin and MD-2 is still not fully understood. Here, experimental and computational methods were employed to elucidate the relationship between the artemisinin and its inhibition mechanism. Experimental results showed that artemether exhibit higher anti-inflammatory activity performance than artemisinin and artesunate. Molecular docking results showed that artemisinin, artesunate, and artemether had similar binding poses, and all complexes remained stable throughout the whole molecular dynamics simulations, whereas the binding of artemisinin and its derivatives to MD-2 decreased the TLR4(Toll-Like Receptor 4)/MD-2 stability. Moreover, artemether exhibited lower binding energy as compared to artemisinin and artesunate, which is in good agreement with the experimental results. Leu61, Leu78, and Ile117 are indeed key residues that contribute to the binding free energy. Binding free energy analysis further confirmed that hydrophobic interactions were critical to maintain the binding mode of artemisinin and its derivatives with MD-2. Full article

Since the use of protein hydrolysates (PHs) enhances overall plant performance and quality of vegetables, they might be considered as a toll to face a number of concerns essentially associated to the growing request of premium quality foodstuff realized in agreement with eco-friendly agriculture practices. Molybdenum (Mo) is considered a fundamental trace element for human body. Thus, its shortage determines several disorders mainly related to neurological lesion and esophageal cancer. Biofortification of fruiting and leafy vegetables is a promising tool to prevent Mo deficiency in the human diet. The current study was carried out to assess the interactive effect of plant-derived PHs and Mo dosage (0.0, 0.5, 3.0, and 6.0 µmol L⁻¹) on yield, morphology, nutritional and functional features, and nitrogen indices of ‘Canasta’ lettuce. Head fresh weight (HFW), head height (HH), ascorbic acid, K, Mg, total chlorophyll, as well as nitrogen use efficiency (NUE) index were positively correlated to PHs application. Furthermore, ascorbic acid and total chlorophyll were also improved by Mo supply. A great improvement in terms of soluble solid content (SSC), total sugars, total phenolic, carotenoids, Mo and N concentrations, nitrogen uptake efficiency (UE), and nitrogen physiological efficiency (PUE) indices was recorded when PHs application was combined with the highest Mo dosage (6.0 µmol L⁻¹). Consequently, our results suggest that Mo-biofortification and PHs application can positively modulate ‘Canasta’ lettuce plant performance and quality. Full article

Objective: Cluster of differentiation (CD14) is an important protein involved in activating toll-like receptors by bacterial components. It exists as either a transmembrane or soluble protein, called mCD14 or sCD14, respectively. Several studies show that CD14 regulates the inflammatory response to periodontal pathogens, and its expression is altered in periodontitis, an inflammatory disease of tooth-supporting tissues. It is the intent of this review to investigate the levels of expression of mCD14 and sCD14 in peripheral blood monocytes, saliva, gingival crevicular fluid, and gingival tissue biopsies in periodontitis patients. Methods: PubMed, Scopus, Ovid/Medline, Embase, and the Cochrane Library were consulted for the online literature search. To ensure methodical quality, titles and abstracts were reviewed in accordance to the PRISMA guidelines. Data extraction and evaluation of the full texts were executed in agreement with the GRADE approach. Results: This systematic review shows that mCD14 levels are decreased in peripheral blood monocytes of periodontitis patients in comparison to healthy patients, while sCD14 levels in sera, gingival crevicular fluid (GCF), and biopsies of periodontitis patients have a tendency to be increased in comparison to healthy controls. The evaluation of CD14 in gingival biopsies and periodontal tissues elucidated the fact that interpretation of the data obtained with qPCR, ELISA, and flow cytometry is questionable. Full article

In a short time, the COVID-19 pandemic has left the world with over 25 million cases and staggering death tolls that are still rising. Treatments for SARS-CoV-2 infection are desperately needed as there are currently no approved drug therapies. With limited knowledge of viral mechanisms, a network controllability method of prioritizing existing drugs for repurposing efforts is optimal for quickly moving through the drug approval pipeline using limited, available, virus-specific data. Based on network topology and controllability, 16 proteins involved in translation, cellular transport, cellular stress, and host immune response are predicted as regulators of the SARS-CoV-2 infected cell. Of the 16, eight are prioritized as possible drug targets where two, PVR and SCARB1, are previously unexplored. Known compounds targeting these genes are suggested for viral inhibition study. Prioritized proteins in agreement with previous analysis and viral inhibition studies verify the ability of network controllability to predict biologically relevant candidates. Full article

Acute respiratory distress syndrome (ARDS) is a clinical syndrome that inflicts a considerably heavy toll in terms of morbidity and mortality. While there are multitudes of conditions that can lead to ARDS, the vast majority of ARDS cases are caused by a relatively small number of diseases, especially sepsis and pneumonia. Currently, there is no clinically agreed upon reliable diagnostic test for ARDS, and the detection or diagnosis of ARDS is based on a constellation of laboratory and radiological tests in the absence of evidence of left ventricular dysfunction, as specified by the Berlin definition of ARDS. Virtually all the ARDS biomarkers to date have been proven to be of very limited clinical utility. Given the heterogeneity of ARDS due to the wide variation in etiology, clinical and molecular manifestations, there is a current scientific consensus agreement that ARDS is not just a single entity but rather a spectrum of conditions that need further study for proper classification, the identification of reliable biomarkers and the adequate institution of therapeutic targets. This scoping review aims to elucidate ARDS omics research, focusing on metabolomics and how metabolomics can boost the study of ARDS biomarkers and help to facilitate the identification of ARDS subpopulations. Full article

Road infrastructures represent a key point in the development of smart cities. In any case, the environmental impact of road traffic should be carefully assessed. Acoustic noise is one of the most important issues to be monitored by means of sound level measurements. When a large measurement campaign is not possible, road traffic noise predictive models (RTNMs) can be used. Standard RTNMs present in literature usually require in input several information about the traffic, such as flows of vehicles, percentage of heavy vehicles, average speed, etc. Many times, the lack of information about this large set of inputs is a limitation to the application of predictive models on a large scale. In this paper, a new methodology, easy to be implemented in a sensor concept, based on video processing and object detection tools, is proposed: the Equivalent Acoustic Level Estimator (EAgLE). The input parameters of EAgLE are detected analyzing video images of the area under study. Once the number of vehicles, the typology (light or heavy vehicle), and the speeds are recorded, the sound power level of each vehicle is computed, according to the EU recommended standard model (CNOSSOS-EU), and the Sound Exposure Level (SEL) of each transit is estimated at the receiver. Finally, summing up the contributions of all the vehicles, the continuous equivalent level, L_eq, on a given time range can be assessed. A preliminary test of the EAgLE technique is proposed in this paper on two sample measurements performed in proximity of an Italian highway. The results will show excellent performances in terms of agreement with the measured L_eq and comparing with other RTNMs. These satisfying results, once confirmed by a larger validation test, will open the way to the development of a dedicated sensor, embedding the EAgLE model, with possible interesting applications in smart cities and road infrastructures monitoring. These sites, in fact, are often equipped (or can be equipped) with a network of monitoring video cameras for safety purposes or for fining/tolling, that, once the model is properly calibrated and validated, can be turned in a large scale network of noise estimators. Full article

To overcome profitability deterioration in executing steel price projects, companies are seeking overseas expansion, which increases market size while reducing profit certainty. Special purpose companies (SPCs) have been found to better manage these risks through tolling agreements which transfer the local pricing volatility risks (raw material, steel sales, licensing and income tax) to the project sponsor. The energy market has benefited from policy changes allowing the use of the tolling model, finding an increase in profitability for both project sponsors and SPCs through more effective risk sharing. While successes have been published in the energy, gas, and highway sectors, the tolling model’s efficacy has yet to be tested on the steel sector. As such, this research adds to the existing body of knowledge by testing the financial feasibility of using the tolling model on three million ton/year capacity steel projects. The data analyzed has been collected from “Company A”, a company with 50 years of domestic and 20 years international steel-iron plant project execution and operation experience. An economic analysis is performed on the best, most likely, and worst-case cost/revenue scenarios of a virtual project (which represents the average of all Company A projects) and two Company A projects under construction/operation. The findings support the use of the tolling model in volatile markets, showing a net present value (NPV) profitability increase of up to $940 versus the traditional project company model under worst case market conditions. However, the traditional project company model was found to be superior in best case market conditions. With these findings, international steel companies are able to consider alternative financing structures when executing projects in volatile markets, potentially resulting in greater project sponsor and SPC profit. Full article