Effects of High Functional Resistance Training on Parameters of Arterial Stiffness- Pilot Study

poste

Surface plasmon enhanced light scattering biosensing: Size dependence on the gold nanoparticle tag

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. Surface plasmon enhanced light scattering (SP-LS) is a powerful new sensing SPR modality that yields excellent sensitivity in sandwich immunoassay using spherical gold nanoparticle (AuNP) tags. Towards further improving the performance of SP-LS, we systematically investigated the AuNP size effect. Simulation results indicated an AuNP size-dependent scattered power, and predicted the optimized AuNPs sizes (i.e., 100 and 130 nm) that afford extremely high signal enhancement in SP-LS. The maximum scattered power from a 130 nm AuNP is about 1700-fold higher than that obtained from a 17 nm AuNP. Experimentally, a bio-conjugation protocol was developed by coating the AuNPs with mixture of low and high molecular weight PEG molecules. Optimal IgG antibody bioconjugation conditions were identified using physicochemical characterization and a model dot-blot assay. Aggregation prevented the use of the larger AuNPs in SP-LS experiments. As predicted by simulation, AuNPs with diameters of 50 and 64 nm yielded significantly higher SP-LS signal enhancement in comparison to the smaller particles. Finally, we demonstrated the feasibility of a two-step SP-LS protocol based on a gold enhancement step, aimed at enlarging 36 nm AuNPs tags. This study provides a blue-print for the further development of SP-LS biosensing and its translation in the bioanalytical field

Fields Annihilation and Particles Creation in DBI inflation

We consider a model of DBI inflation where two stacks of mobile branes are moving ultra relativistically in a warped throat. The stack closer to the tip of the throat is annihilated with the background anti-branes while inflation proceeds by the second stack. The effects of branes annihilation and particles creation during DBI inflation on the curvature perturbations power spectrum and the scalar spectral index are studied. We show that for super-horizon scales, modes which are outside the sound horizon at the time of branes collision, the spectral index has a shift to blue spectrum compared to the standard DBI inflation. For small scales the power spectrum approaches to its background DBI inflation value with the decaying superimposed oscillatory modulations.Comment: First revision: minor changes, the background spectral index is corrected, new references are added. Second revision: minor changes, new references are added, accepted for publication in JCA

Subanesthetic ketamine treatment promotes abnormal interactions between neural subsystems and alters the properties of functional brain networks

Acute treatment with subanesthetic ketamine, a non-competitive N-methyl-D-aspartic acid (NMDA) receptor antagonist, is widely utilized as a translational model for schizophrenia. However, how acute NMDA receptor blockade impacts on brain functioning at a systems level, to elicit translationally relevant symptomatology and behavioral deficits, has not yet been determined. Here, for the first time, we apply established and recently validated topological measures from network science to brain imaging data gained from ketamine-treated mice to elucidate how acute NMDA receptor blockade impacts on the properties of functional brain networks. We show that the effects of acute ketamine treatment on the global properties of these networks are divergent from those widely reported in schizophrenia. Where acute NMDA receptor blockade promotes hyperconnectivity in functional brain networks, pronounced dysconnectivity is found in schizophrenia. We also show that acute ketamine treatment increases the connectivity and importance of prefrontal and thalamic brain regions in brain networks, a finding also divergent to alterations seen in schizophrenia. In addition, we characterize how ketamine impacts on bipartite functional interactions between neural subsystems. A key feature includes the enhancement of prefrontal cortex (PFC)-neuromodulatory subsystem connectivity in ketamine-treated animals, a finding consistent with the known effects of ketamine on PFC neurotransmitter levels. Overall, our data suggest that, at a systems level, acute ketamine-induced alterations in brain network connectivity do not parallel those seen in chronic schizophrenia. Hence, the mechanisms through which acute ketamine treatment induces translationally relevant symptomatology may differ from those in chronic schizophrenia. Future effort should therefore be dedicated to resolve the conflicting observations between this putative translational model and schizophrenia

Bone morphogenetic proteins − 7 and − 2 in the treatment of delayed osseous union secondary to bacterial osteitis in a rat model

Background: Bone infections due to trauma and subsequent delayed or impaired fracture healing represent a great challenge in orthopedics and trauma surgery. The prevalence of such bacterial infection-related types of delayed non-union is high in complex fractures, particularly in open fractures with additional extensive soft-tissue damage. The aim of this study was to establish a rat model of delayed osseous union secondary to bacterial osteitis and investigate the impact of rhBMP-7 and rhBMP-2 on fracture healing in the situation of an ongoing infection. Methods: After randomization to four groups 72 Sprague-Dawley rats underwent a transverse fracture of the midshaft tibia stabilized by intramedullary titanium K-wires. Three groups received an intramedullary inoculation with Staphylococcus aureus (103 colony-forming units) before stabilization and the group without bacteria inoculation served as healing control. After 5 weeks, a second surgery was performed with irrigation of the medullary canal and local rhBMP-7 and rhBMP-2 treatment whereas control group and infected control group received sterile saline. After further 5 weeks rats were sacrificed and underwent biomechanical testing to assess the mechanical stability of the fractured bone. Additional micro-CT analysis, histological, and histomorphometric analysis were done to evaluate bone consolidation or delayed union, respectively, and to quantify callus formation and the mineralized area of the callus. Results: Biomechanical testing showed a significantly higher fracture torque in the non-infected control group and the infected rhBMP-7- and rhBMP-2 group compared with the infected control group (p < 0.001). RhBMP-7 and rhBMP-2 groups did not show statistically significant differences (p = 0.57). Histological findings supported improved bone-healing after rhBMP treatment but quantitative micro-CT and histomorphometric results still showed significantly more hypertrophic callus tissue in all three infected groups compared to the non-infected group. Results from a semiquantitative bone-healing-score revealed best bone-healing in the non-infected control group. The expected chronic infection was confirmed in all infected groups. Conclusions: In delayed bone healing secondary to infection rhBMP treatment promotes bone healing with no significant differences in the healing efficacy of rhBMP-2 and rhBMP-7 being noted. Further new therapeutic bone substitutes should be analyzed with the present rat model for delayed osseous union secondary to bacterial osteitis

Applications of deep learning in severity prediction of traffic accidents

This study investigates the power of deep learning in predicting the severity of injuries when accidents occur due to traffic on Malaysian highways. Three network architectures based on a simple feedforward Neural Networks (NN), Recurrent Neural Networks (RNN), and Convolutional Neural Networks (CNN) were proposed and optimized through a grid search optimization to fine tune the hyperparameters of the models that can best predict the outputs with less computational costs. The results showed that among the tested algorithms, the RNN model with an average accuracy of 73.76% outperformed the NN model (68.79%) and the CNN (70.30%) model based on a 10-fold cross-validation approach. On the other hand, the sensitivity analysis indicated that the best optimization algorithm is “Nadam” in all the three network architectures. In addition, the best batch size for the NN and RNN was determined to be 4 and 8 for CNN. The dropout with keep probability of 0.2 and 0.5 was found critical for the CNN and RNN models, respectively. This research has shown that deep learning models such as CNN and RNN provide additional information inherent in the raw data such as temporal and spatial correlations that outperform the traditional NN model in terms of both accuracy and stability

Cellular Automata Applications in Shortest Path Problem

Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

Social representations and the politics of participation

Recent work has called for the integration of different perspectives into the field of political psychology (Haste, 2012). This chapter suggests that one possible direction that such efforts can take is studying the role that social representations theory (SRT) can play in understanding political participation and social change. Social representations are systems of common-sense knowledge and social practice; they provide the lens through which to view and create social and political realities, mediate people's relations with these sociopolitical worlds and defend cultural and political identities. Social representations are therefore key for conceptualising participation as the activity that locates individuals and social groups in their sociopolitical world. Political participation is generally seen as conditional to membership of sociopolitical groups and therefore is often linked to citizenship. To be a citizen of a society or a member of any social group one has to participate as such. Often political participation is defined as the ability to communicate one's views to the political elite or to the political establishment (Uhlaner, 2001), or simply explicit involvement in politics and electoral processes (Milbrath, 1965). However, following scholars on ideology (Eagleton, 1991; Thompson, 1990) and social knowledge (Jovchelovitch, 2007), we extend our understanding of political participation to all social relations and also develop a more agentic model where individuals and groups construct, develop and resist their own views, ideas and beliefs. We thus adopt a broader approach to participation in comparison to other political-psychological approaches, such as personality approaches (e.g. Mondak and Halperin, 2008) and cognitive approaches or, more recently, neuropsychological approaches (Hatemi and McDermott, 2012). We move away from a focus on the individual's political behaviour and its antecedents and outline an approach that focuses on the interaction between psychological and political phenomena (Deutsch and Kinnvall, 2002) through examining the politics of social knowledge

Pretreatment with a novel aquaporin 4 inhibitor, TGN-020, significantly reduces ischemic cerebral edema

We investigated the in vivo effects of a novel aquaporin 4 (AQP4) inhibitor 2-(nicotinamide)-1,3,4-thiadiazole, TGN-020, in a mouse model of focal cerebral ischemia using 7.0-T magnetic resonance imaging (MRI). Pretreatment with TGN-020 significantly reduced brain edema associated with brain ischemia, as reflected by percentage of brain swelling volume (%BSV), 12.1 ± 6.3% in the treated group, compared to (20.8 ± 5.9%) in the control group (p < 0.05), and in the size of cortical infarction as reflected by the percentage of hemispheric lesion volume (%HLV), 20.0 ± 7.6% in the treated group, compared to 30.0 ± 9.1% in the control group (p < 0.05). The study indicated the potential pharmacological use of AQP4 inhibition in reducing brain edema associated with focal ischemia

Neutrophils in cancer: neutral no more

Neutrophils are indispensable antagonists of microbial infection and facilitators of wound healing. In the cancer setting, a newfound appreciation for neutrophils has come into view. The traditionally held belief that neutrophils are inert bystanders is being challenged by the recent literature. Emerging evidence indicates that tumours manipulate neutrophils, sometimes early in their differentiation process, to create diverse phenotypic and functional polarization states able to alter tumour behaviour. In this Review, we discuss the involvement of neutrophils in cancer initiation and progression, and their potential as clinical biomarkers and therapeutic targets