MicroRNA and Cardiac Stem Cell Therapy

Cardiac Progenitor Cells (CPCs) are multipotent cells of the myocardium. They are located inside niches of the heart muscle, can be isolated, characterized and used for cardiac regeneration in stem cell therapy. Actually, CPCs may be isolated by tissue digestion with or without cell sorting, but it is difficult to achieve the maximum level of differentiation when these cells are implanted into a damaged myocardium. The knowledge recently acquired on small molecules of non-coding RNAs, microRNA (miRNA), may improve the use of these cells in stem cell therapy. In fact, these small molecules may be attached to devices or adminstered as they are or in combination with nanoparticles in order to drive the correct differentiation of stem cells. Regarding heart regeneration, we can acquire knowledge from the role of miRNAs in heart development and use it to reprogram CPCs to gain the correct three-dimensional structure of the cardiac muscle

Control of DNA minor groove width and Fis protein binding by the purine 2-amino group.

The width of the DNA minor groove varies with sequence and can be a major determinant of DNA shape recognition by proteins. For example, the minor groove within the center of the Fis-DNA complex narrows to about half the mean minor groove width of canonical B-form DNA to fit onto the protein surface. G/C base pairs within this segment, which is not contacted by the Fis protein, reduce binding affinities up to 2000-fold over A/T-rich sequences. We show here through multiple X-ray structures and binding properties of Fis-DNA complexes containing base analogs that the 2-amino group on guanine is the primary molecular determinant controlling minor groove widths. Molecular dynamics simulations of free-DNA targets with canonical and modified bases further demonstrate that sequence-dependent narrowing of minor groove widths is modulated almost entirely by the presence of purine 2-amino groups. We also provide evidence that protein-mediated phosphate neutralization facilitates minor groove compression and is particularly important for binding to non-optimally shaped DNA duplexes

Artificial Neural Network for Predicting Silicon Content in the Hot Metal Produced in a Blast Furnace Fueled by Metallurgical Coke

The main production route for cast iron and steel is through the blast furnace. The silicon content in cast iron is an important indicator of the thermal condition of a blast furnace. High silicon contents indicate an increase in the furnace\u2019s thermal input and, in some cases, may indicate an excess of coke in the reactor. As coke costs predominate in the production of cast iron, tighter control of the silicon content therefore has economic advantages. The main objective of this article was to design an artificial neural network to predict the silicon content in hot metal, varying the number of neurons in the hidden layer by 10, 20, 25, 30, 40, 50, 75, 100, 125, 150, 170 and 200 neurons. In general, all neural networks showed excellent results, with the network with 30 neurons showing the best results among the 12 modeled networks. The validation of the models was confirmed using the Mean Square Error (MSE) and Pearson\u2019s correlation coefficient. The cross-validation technique was used to re-evaluate the performance of neural networks. In short, neural networks can be used in practical operations due to the excellent correlations between the real values and those calculated by the neural network

Quantitative Storytelling: Science, Narratives, and Uncertainty in Nexus Innovations

Innovations are central instruments of sustainability policies. They project future visions onto technological solutions and enable win-win framings of complex sustainability issues. Yet, they also create new problems by interconnecting different resources such as water, food, and energy, what is known as the â WEF nexus.â In this paper, we apply a new approach called Quantitative Storytelling (QST) to the assessment of four innovations with a strong nexus component in EU policy: biofuels, shale gas, electric vehicles, and alternative water resources. Recognizing irreducible pluralism and uncertainties, QST inspects the relationships between the narratives used to frame sustainability issues and the evidence on those issues. Our experiences outlined two rationales for implementing QST. First, QST can be used to question dominant narratives that promote certain innovations despite evidence against their effectiveness. Second, QST can offer avenues for pluralistic processes of co-creation of alternative narratives and imaginaries. We reflect on the implementation of QST and on the role played by different uncertainties throughout these processes. Our experiences suggest that while the role of nexus assessments using both numbers and narratives may not be instrumental in directly inducing policy change, they are valuable means to open discussions on innovations outside of dominant nexus imaginaries. © The Author(s) 2021.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research has been funded by the European Union’s H2020 project MAGIC: Moving towards Adaptive Governance in Complexity (MAGIC GA No. 689669); European Union’s FP7 project IANEX: Integrated Assessment of the Nexus: The Case of Hydraulic Fracturing, Marie Curie International Outgoing Fellowship GA No. 623593; and Spanish Ministry of Science’s Juan de la Cierva Fellowship (IJC2019-038847-I/AEI/10.13039/501100011033)

Efficacy and toxicity of bevacizumab in recurrent ovarian disease: an update meta-analysis on phase III trials

Background: To analyze the efficacy and toxicity of bevacizumab on survival outcomes in recurrent ovarian cancer. Results: Bevacizumab was associated with significant improvement of PFS and OS compared with standard treatment with HRs of 0.53 (95% CI 0.44 - 0.63; p < 0.00001) and 0.87 (95% CI, 0.77 to 0.99; p = 0.03), respectively. Bevacizumab increased the incidence of G3/G4 hypertension (RR 19.01, 95% CI 7.77 - 46.55; p < 0.00001), proteinuria (RR 17.31, 95% CI 5.42 - 55.25; p < 0.00001), arterial thromboembolic events (ATE) (RR 4.99, 95% CI 1.29 - 19.27; p = 0.02) and bleeding (RR 3.14, 95% CI 1.35 - 7.32; p = 0.008). Materials and Methods: Three randomized phase III trials representing 1502 patients were identified. Pooled hazard ratio (HR), odd ratio (OR), risk ratio (RR) with 95% confidence interval (CI) were calculated using fixed or random effects model. Conclusions: Adding bevacizumab to standard chemotherapy improved ORR, PFS and OS, and it had a higher, but manageable, incidence of toxicities graded 3 to 4

Interoperability in Open IoT Platforms: WoT-FIWARE Comparison and Integration

The rapid and exponential growth of the Internet of Things (IoT) has been generating a new breed of technologies that introduce several different protocols and interfaces. The Web of Things (WoT) architecture stands out as an emerging and poten- tial solution to improve interoperability across IoT platforms by describing well-defined software interfaces. However, few studies analyze and compare WoT to other interoperability solutions proposed in the IoT literature. In this paper, we attempt to bridge the gap by three main contributions. First, we qualitative compare the WoT approach with the well-known FIWARE- based interoperability solution.Second, based on the previous analysis, we design and implement a connector to bridge the WoT architecture to the FIWARE ecosystem. Third, we conduct a performance analysis emulating a real IoT-based environment to understand scalability, response time, and computer resource usage of the two interoperability solutions. The results reveal that conceptual design choices impact the applications’ performance: the WoT architecture effectively enables interoperability across IoT Platforms, though it incorporates several characteristics that hinder the implementation of applications. On the other hand, the FIWARE IoT Agent solution is platform-specific. Hence new implementations are needed for each different IoT data model

Pd-based membranes performance under hydrocarbon exposure for propane dehydrogenation processes: Experimental and modeling

In this work, a novel Pd–Ag double-skinned (DS-) membrane is used for the first time in conditions typical of propane dehydrogenation (PDH). This membrane presents a protective layer on top of the H2-selective one, which acts as shield against chemical deactivation and mechanical erosion under reaction conditions. While the protective layer is already been proven as an efficient barrier against membrane erosion in fluidized beds, there is no validation yet under PDH reaction. The DS- membrane performance is compared with a conventional (C-) Pd–Ag membrane under alkane/alkene exposure, at 400–500 °C and 3 bar, to investigate whether the incorporation of the protective layer would be suited for H2 separation in PDH systems, and if coking rate would be affected. The novel membrane shows a H2 permeance of 2.28 × 10−6 mol∙m−2 s−1∙Pa−1 at 500 ᵒC and 4 bar of pressure difference, overcoming the performance of the conventional PdAg one (1.56x∙10−6 mol m−2 s−1∙Pa−1). Both membranes present a stable H2 flux under alkane exposure, while deactivation occurs under exposure to alkenes. A model able to describe the H2 flux through Pd-based membranes is presented to fit the experimental data and predict membrane performance. The model includes mass transfer limitations in the retentate and a corrective inhibition factor to account for the competitive adsorption of hydrocarbon species in the H2 selective layer. The experimental results obtained under alkene exposure deviates from model predictions; this can be attributed to carbon deposition on the surface of the selective layer, as further detected on the DS-membrane by Scanning Electron Microscopy (SEM)/Energy Dispersive X-Ray Analysis (EDX), which is the main factor for membrane deactivation.European Union´s Horizon 2020 research and innovation program under grant agreement No 814671 (BiZeolCat

Joint Power Control and Structural Health Monitoring in Industry 4.0 Scenarios using Eclipse Arrowhead and Web of Things

The integration of legacy IoT ecosystems in Industry 4.0 scenarios requires human effort to adapt single devices. This process would highly benefit from features like device lookup, loose coupling and late binding. In this paper, we tackle the issue of integrating legacy monitoring systems and actuation systems in an industrial scenario, by looking into the Web of Things (WoT) as a communication standard and the Eclipse Arrowhead Framework (AHF) as a service orchestrator. More specifically, we propose a general architectural approach to enable closed-loop automation between the above mentioned legacy systems by leveraging the adaptation of the WoT to the AHF. Then, we develop a rule-based engine that enables the control of the actuation based on sensor values. Finally, we present a proof-of-concept use case where we integrate a Structural Health Monitoring (SHM) scenario with a power control actuation subsystem using the developed component