Optimization of the wavesax device: numerical modelling and ocean wave basin tests

The Wavesax device has been conceived to be installed in ports and harbours, in the Mediterranean sea. Therefore, two aspects are quite important: flexibility of the device to fit in different structural configurations and replication in a large number of units. Preliminary numerical modelling of the fixed component of the device has been performed using Computational Fluid Dynamics analysis (RANS-CFD model) and considering four regular wave conditions typical of the Mediterranean sea. Main issues to be considered in the first stage scale modelling analysis are the effective functionality of the device conception (scale 1:20), the optimization of the design and position of the device in terms of generated velocity gradients in the working section where the turbine blades are installed. The main parameters to be investigated, both with numerical modelling and ocean wave basin tests, are the pressure field in different sections of the device, water levels for different wave conditions and device sinking. Following the scale model test, the numerical model was calibrated and validated. The paper presents the results of the numerical simulations related to different configurations of the device, under typical Mediterranean wave climates

Heterogeneity of neuroinflammatory responses in amyotrophic lateral sclerosis: A challenge or an opportunity?

Amyotrophic Lateral Sclerosis (ALS) is a complex pathology: (i) the neurodegeneration is chronic and progressive; it starts focally in specific central nervous system (CNS) areas and spreads to different districts; (ii) multiple cell types further than motor neurons (i.e., glial/immune system cells) are actively involved in the disease; (iii) both neurosupportive and neurotoxic neuroinflammatory responses were identified. Microglia cells (a key player of neuroinflammation in the CNS) attracted great interest as potential target cell population that could be modulated to counteract disease progression, at least in preclinical ALS models. However, the heterogeneous/multifaceted microglia cell responses occurring in different CNS districts during the disease represent a hurdle for clinical translation of single-drug therapies. To address this issue, over the past ten years, several studies attempted to dissect the complexity of microglia responses in ALS. In this review, we shall summarize these results highlighting how the heterogeneous signature displayed by ALS microglia reflects not only the extent of neuronal demise in different regions of the CNS, but also variable engagement in the attempts to cope with the neuronal damage. We shall discuss novel avenues opened by the advent of single-cell and spatial transcriptomics technologies, underlining the potential for discovery of novel therapeutic targets, as well as more specific diagnostic/prognostic not-invasive markers of neuroinflammation

Fast deep learning reconstruction techniques for preclinical magnetic resonance fingerprinting

We propose a deep learning (DL) model and a hyperparameter optimization strategy to reconstruct T1 and T2 maps acquired with the magnetic resonance fingerprinting (MRF) methodology. We applied two different MRF sequence routines to acquire images of ex vivo rat brain phantoms using a 7-T preclinical scanner. Subsequently, the DL model was trained using experimental data, completely excluding the use of any theoretical MRI signal simulator. The best combination of the DL parameters was implemented by an automatic hyperparameter optimization strategy, whose key aspect is to include all the parameters to the fit, allowing the simultaneous optimization of the neural network architecture, the structure of the DL model, and the supervised learning algorithm. By comparing the reconstruction performances of the DL technique with those achieved from the traditional dictionary-based method on an independent dataset, the DL approach was shown to reduce the mean percentage relative error by a factor of 3 for T1 and by a factor of 2 for T2, and to improve the computational time by at least a factor of 37. Furthermore, the proposed DL method enables maintaining comparable reconstruction performance, even with a lower number of MRF images and a reduced k-space sampling percentage, with respect to the dictionary-based method. Our results suggest that the proposed DL methodology may offer an improvement in reconstruction accuracy, as well as speeding up MRF for preclinical, and in prospective clinical, investigations

Alteration in Superoxide Dismutase 1 Causes Oxidative Stress and p38 MAPK Activation Following RVFV Infection

Rift Valley fever (RVF) is a zoonotic disease caused by Rift Valley fever virus (RVFV). RVFV is a category A pathogen that belongs to the genus Phlebovirus, family Bunyaviridae. Understanding early host events to an infectious exposure to RVFV will be of significant use in the development of effective therapeutics that not only control pathogen multiplication, but also contribute to cell survival. In this study, we have carried out infections of human cells with a vaccine strain (MP12) and virulent strain (ZH501) of RVFV and determined host responses to viral infection. We demonstrate that the cellular antioxidant enzyme superoxide dismutase 1 (SOD1) displays altered abundances at early time points following exposure to the virus. We show that the enzyme is down regulated in cases of both a virulent (ZH501) and a vaccine strain (MP12) exposure. Our data demonstrates that the down regulation of SOD1 is likely to be due to post transcriptional processes and may be related to up regulation of TNFα following infection. We also provide evidence for extensive oxidative stress in the MP12 infected cells. Concomitantly, there is an increase in the activation of the p38 MAPK stress response, which our earlier published study demonstrated to be an essential cell survival strategy. Our data suggests that the viral anti-apoptotic protein NSm may play a role in the regulation of the cellular p38 MAPK response. Alterations in the host protein SOD1 following RVFV infection appears to be an early event that occurs in multiple cell types. Activation of the cellular stress response p38 MAPK pathway can be observed in all cell types tested. Our data implies that maintaining oxidative homeostasis in the infected cells may play an important role in improving survival of infected cells

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Longitudinal Associations among Adolescent Socioeconomic Status, Delay Discounting, and Substance Use

Adolescence is a period of heightened risk for substance use and heightened vulnerability to substance exposure. Yet, little is known about how socioeconomic status (SES) influences adolescent decision making and behavior across development to add to these risks. This prospective longitudinal study used latent growth curve modeling (GCM) to examine the contributions of SES on adolescent delay discounting and substance use in a sample of 167 adolescents (52% male). Confirmatory factor analysis (CFA) was used to compute SES factor scores across three waves using a composite of parent and spouse education years and combined annual household income. Adolescent delay discounting and substance use were measured annually across three waves. The main goal of this study is to examine how SES may explain individual differences in growth trajectories of delay discounting and substance use. We used parallel process growth curve modeling with SES as a time-varying and time-invariant covariate to examine the associations between adolescent SES, delay discounting, and substance use onset as well as frequency. These results reveal that delay discounting exhibits a declining linear trend across adolescent development whereas cigarette, alcohol, marijuana, and polysubstance use exhibit increasing linear trends across adolescent development. Furthermore, low SES (as a time-invariant covariate) may lead to earlier onset adolescent alcohol and polysubstance use by way of heightened levels of delay discounting. These findings suggest that delay discounting interventions may be a promising avenue for reducing socioeconomic disparities in early onset alcohol and polysubstance use, while delay discounting development is still underway.Master of ScienceAdolescence is a period of heightened risk for substance use and heightened vulnerability to the effects of substances. Yet, little is known about how socioeconomic status (SES) influences adolescent decision making and behavior to add to these risks. This study used latent growth curve modeling (GCM) to examine the role of SES on adolescent decision making and substance use in a sample of 167 adolescents (52% male). Confirmatory factor analysis (CFA) was used to compute SES factor scores across three time points using an average of parent and spouse education years and income. Adolescent delay discounting and substance use were measured annually across three time points. The main goal of this study is to examine how SES may explain individual differences in delay discounting and substance use across adolescence. We used parallel process growth curve modeling with SES as a time-varying and time-invariant covariate to examine the links between adolescent SES, delay discounting, and substance use age of onset and frequency. These results reveal that delay discounting shows linear decreases in growth across adolescence whereas cigarette, alcohol, marijuana, and polysubstance use show increasing linear growth across adolescence. Additionally, low SES may lead to earlier onset adolescent alcohol and polysubstance use by way of heightened levels of delay discounting. These findings suggest that delay discounting interventions may help reduce socioeconomic differences in early onset alcohol and polysubstance use, while delay discounting development is still in progress