The blood brain barrier consisting of astrocytes, pericytes and brain microvascular endothelial cells plays a vital role in the pathogenesis of neurotropic viruses by controlling the access of ...circulating molecules, immune cells or viruses into the central nervous system (CNS). However, this barrier is not impenetrable and neuroviruses have evolved to disrupt and evade it. This review aims to describe the underlying entry mechanisms of several neuroviruses such as (Japanese encephalitis virus (JEV), West Nile virus (WNV), Zika virus (ZIKV), Nipah virus (NiV), Rabies virus (RABV), Herpes simplex virus (HSV) and Human immunodeficiency virus (HIV)) into the CNS through BBB disruption. The mechanisms, through which neurotropic viruses enter the BBB, are being studied and are becoming clearer, however, some aspects still remain unknown. Some of these viruses are able to invade the brain parenchyma by a 'Trojan horse' mechanism, through diapedesis of infected immune cells that either cross the BBB paracellularly or transcellularly. Important mechanisms of BBB disruption associated with paracellular entry of viruses include alterations in expression or phosphorylation of tight junction proteins, disruption of the basal lamina and disruption of the actin cytoskeleton. In the absence of such mechanisms, indirect effects of viruses on the immune system are likely causes of barrier disruption.
A fundamental computer vision task called semantic segmentation has significant uses in the understanding of medical pictures, including the segmentation of tumors in the brain. The G-Shaped Net ...architecture appears in this context as an innovative and promising design that combines components from many models to attain improved accuracy and efficiency. In order to improve efficiency, the G-Shaped Net architecture synergistically incorporates four fundamental components: the Self-Attention, Squeeze Excitation, Fusion, and Spatial Pyramid Pooling block structures. These factors work together to improve the precision and effectiveness of brain tumor segmentation. Self-Attention, a crucial component of G-Shaped architecture, gives the model the ability to concentrate on the image’s most informative areas, enabling accurate localization of tumor boundaries. By adjusting channel-wise feature maps, Squeeze Excitation completes this by improving the model’s capacity to capture fine-grained information in the medical pictures. Since the G-Shaped model’s Spatial Pyramid Pooling component provides multi-scale contextual information, the model is capable of handling tumors of various sizes and complexity levels. Additionally, the Fusion block architectures combine characteristics from many sources, enabling a thorough comprehension of the image and improving the segmentation outcomes. The G-Shaped Net architecture is an asset for medical imaging and diagnostics and represents a substantial development in semantic segmentation, which is needed more and more for accurate brain tumor segmentation.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Abstract Brain tumors, often referred to as intracranial tumors, are abnormal tissue masses that arise from rapidly multiplying cells. During medical imaging, it is essential to separate brain tumors ...from healthy tissue. The goal of this paper is to improve the accuracy of separating tumorous regions from healthy tissues in medical imaging, specifically for brain tumors in MRI images which is difficult in the field of medical image analysis. In our research work, we propose IC-Net (Inverted-C), a novel semantic segmentation architecture that combines elements from various models to provide effective and precise results. The architecture includes Multi-Attention (MA) blocks, Feature Concatenation Networks (FCN), Attention-blocks which performs crucial tasks in improving brain tumor segmentation. MA-block aggregates multi-attention features to adapt to different tumor sizes and shapes. Attention-block is focusing on key regions, resulting in more effective segmentation in complex images. FCN-block captures diverse features, making the model more robust to various characteristics of brain tumor images. Our proposed architecture is used to accelerate the training process and also to address the challenges posed by the diverse nature of brain tumor images, ultimately leads to potentially improved segmentation performance. IC-Net significantly outperforms the typical U-Net architecture and other contemporary effective segmentation techniques. On the BraTS 2020 dataset, our IC-Net design obtained notable outcomes in Accuracy, Loss, Specificity, Sensitivity as 99.65, 0.0159, 99.44, 99.86 and DSC (core, whole, and enhancing tumors as 0.998717, 0.888930, 0.866183) respectively.
We propose a methodological framework to perform forward asteroseismic modeling of stars with a convective core, based on gravity-mode oscillations. These probe the near-core region in the deep ...stellar interior. The modeling relies on a set of observed high-precision oscillation frequencies of low-degree coherent gravity modes with long lifetimes and their observational uncertainties. Identification of the mode degree and azimuthal order is assumed to be achieved from rotational splitting and/or from period spacing patterns. This paper has two major outcomes. The first is a comprehensive list and discussion of the major uncertainties of theoretically predicted gravity-mode oscillation frequencies based on linear pulsation theory, caused by fixing choices of the input physics for evolutionary models. Guided by a hierarchy among these uncertainties of theoretical frequencies, we subsequently provide a global methodological scheme to achieve forward asteroseismic modeling. We properly take into account correlations among the free parameters included in stellar models. Aside from the stellar mass, metallicity, and age, the major parameters to be estimated are the near-core rotation rate, the amount of convective core overshooting, and the level of chemical mixing in the radiative zones. This modeling scheme allows for maximum likelihood estimation of the stellar parameters for fixed input physics of the equilibrium models, followed by stellar model selection considering various choices of the input physics. Our approach uses the Mahalanobis distance instead of the often-used χ2 statistic and includes heteroscedasticity. It provides estimation of the unknown variance of the theoretically predicted oscillation frequencies.
The present paper aims at to produce the building vulnerability and its spatial distribution in mountainous regions of the Nilgiris District in the Western Ghats, India. The landslide-susceptible ...areas were identified based on the existing landslide-susceptible maps. The landslide-prone slope was identified based on the historical and recent landslide information’s collected from various authenticated sources as well as the field investigations made on the recent landslides. The high-to-severe landslide hazard-prone areas were selected for the present study of building vulnerability analysis. The areas were divided into ten segments based on the landslide inventory, built-up areas, and transportation corridors in the vicinity of landslide locations. Building foot print map was prepared for each segments using ArcGIS software visual interpretation for 1627 buildings and infrastructures. Different thematic layers viz, building type/material, surrounding wall, sloping side details, warning, and number of floors which contribute to landslide vulnerability in vector formats are used for the present study. Using the formula proposed by Papathoma-Köhle et al. (Nat Hazards Earth Syst Sci 7:765–779,
2007
) the vulnerability score were calculated by scripting in ArcGIS software. Based on the vulnerability score, the buildings were grouped under three categories viz, low, medium, and high vulnerability. The spatial distribution of vulnerability of buildings was prepared and presented. The present study can be useful data for preparation of regional landuse plan as well as evacuation plans and warning systems to safeguard measure for population living in the vulnerable buildings in The Nilgiris District of Western Ghats in India.
Exploration of reinforcing alkaline oxide modifiers into the nominal composition of 40P2O5+(30‒X)CaO+XMgO+9SiO2+6Sr2F+6LiF+6BaF+2.5Ce2O3+0.5Sm2O3 (where X= 0, 5, 10, 15, 20, 25 in wt%) has been ...performed. Oxides from the same alkaline group (CaO and MgO) have been chosen as a modifier. Glasses were made through the customary melt-quench technique. Successful glass formation was confirmed by XRD and functional group and compositional analysis via FTIR. Electronic structures of the proposed poly-component glasses are visualized by absorption spectra in the three prominent regions of the (electromagnetic) EM spectrum. Auxiliary physical, structural, and elastic properties were scrutinized for the approval of glasses as an obedient shielding material and evaluation of some other attenuating factors of EM wave by poly-component glasses in the gamma-ray region. The linear attenuation coefficient (LAC) was reported in the energy range of 0.284–1.333 MeV. The LAC results demonstrated that the interaction of the photons with the prepared specimens is high at lower photon energies and the shielding provided by the samples is relatively high when the energy level is low. The addition of MgO results in an improvement in the LAC values, and as a consequence, PS0Mg and PS25Mg had the lowest and highest LAC, respectively. The highest transmission factor values were reported for a thickness of 0.3 cm and equal to 0.87 at 0.284 MeV, 0.91 at 0.551 MeV, and 0.93 at 0.826 MeV (this is for PS0Mg sample).
•Concentration dependent alkali modifiers were prepared via melt quench technique for shielding applications.•Physical, structural and elastic properties of all the prepared glasses were examined in detail.•PS25Mg glass exhibits higher LAC value, 1.333 MeV.•Radiation protection efficiency increases by increasing the wt% of MgO into the glass composition.
As the demand for higher data rate is exponentially growing, spectral efficiency improving methods can be adopted in recent day’s wireless communication systems. If the cognitive radio network can ...forecast the channel to be sensed, instead of sensing all channels sequentially, then reasonable increase in throughput can be achieved. In this research, we forecast not only the channel that can be sensed, but we also predict how long the channel remains usable for secondary users. This process can reduce the sensing time. We use a deep deterministic policy gradient method to optimally select the channel and also the duration for sensing. Doing this way, we can minimise the energy spent on sensing and make the cognitive radio energy efficient. Through simulation, we show that the number of operations invested on sensing is minimised. We also show in our result that the higher throughput is achieved.
Dengue, an arboviral disease is a global threat to public health as the number of Dengue cases increases through the decades and this trend is predicted to continue. Non-communicable diseases such as ...diabetes and obesity are also on an upward trend. Moreover, past clinical studies have shown comorbidities worsen the clinical manifestation of especially Severe Dengue. However, discussion regarding the underlying mechanisms regarding the association between these comorbidities and dengue are lacking. The hallmark of Severe Dengue is plasma leakage which is due to several factors including presence of pro-inflammatory cytokines and dysregulation of endothelial barrier protein expression. The key factors of diabetes affecting endothelial functions are Th1 skewed responses and junctional-related proteins expression. Additionally, obesity alters the lipid metabolism and immune response causing increased viral replication and inflammation. The similarity between diabetes and obesity individuals is in having chronic inflammation resulting in endothelial dysfunction. This review outlines the roles of diabetes and obesity in severe dengue and gives some insights into the plausible mechanisms of comorbidities in Severe Dengue. Keywords: Diabetes, Obesity, Dengue, Endothelium, Th-1 cytokines, Junctional proteins, Adhesion molecules
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