Psoriasis and Gut Microbiome—Current State of Art

Psoriasis is a chronic, immune-mediated inflammatory disease that affects around 125 million people worldwide. Several studies concerning the gut microbiota composition and its role in disease pathogenesis recently demonstrated significant alterations among psoriatic patients. Certain parameters such as Firmicutes/Bacteroidetes ratio or Psoriasis Microbiome Index were developed in order to distinguish between psoriatic and healthy individuals. The “leaky gut syndrome” and bacterial translocation is considered by some authors as a triggering factor for the onset of the disease, as it promotes chronic systemic inflammation. The alterations were also found to resemble those in inflammatory bowel diseases, obesity and certain cardiovascular diseases. Microbiota dysbiosis, depletion in SCFAs production, increased amount of produced TMAO, dysregulation of the pathways affecting the balance between lymphocytes populations seem to be the most significant findings concerning gut physiology in psoriatic patients. The gut microbiota may serve as a potential response-to-treatment biomarker in certain cases of biological treatment. Oral probiotics administration as well as fecal microbial transplantation were most reported in bringing health benefits to psoriatic patients. However, the issue of psoriatic bacterial gut composition, its role and healing potential needs further investigation. Here we reviewed the literature on the current state of the relationship between psoriasis and gut microbiome.     

Nitric oxide synthase-immunoreactive neurons in human and porcine respiratory tract

The presence of nitric oxide synthase (NO-synthase), the enzyme responsible for the production of nitric oxide (NO) from L-arginine, is shown immunocytochemically in the intrinsic neurons of the human and porcine respiratory tract. NO-synthase immunoreactivity is demonstrated in a subpopulation of neurons of the microganglia present in the wall of the extra- and intrapulmonary bronchi as well as in the hilar region of the lung in relation to blood vessels. The immunostaining was also found in some nerve fibers of the respiratory nervous system. Human and porcine lung gave similar results. The possible involvement of NO in the nonadrenergic noncholinergic (NANC) nervous regulation of the lung is discussed.     

Autoimmune diabetes induced by the beta-cell toxin STZ. Immunity to the 60-kDa heat shock protein and to insulin

Administered at a suitably low dose, the toxin streptozotocin (STZ) can trigger an autoimmune process leading to destruction of the beta-cells of the pancreatic islets. In this study, we examined specific immunological reactions in mice before and during the development of STZ-induced autoimmune diabetes. We now report that the development of spontaneous autoantibodies to insulin can serve as a marker of susceptibility to a low dose of STZ. Susceptible male mice of the C57BL/KsJ strain manifested such anti-insulin antibodies, and resistant female mice did not. Administration of a low dose of STZ (five daily doses each of 30 mg/kg) induced transient hyperglycemia approximately 20-30 days later, which temporarily remitted but was followed by intractable diabetes approximately 2.5 months later. The diabetogenic process triggered by the low dose of STZ was associated with an increase in the level of anti-insulin antibodies bearing the Dana and Micha (DM) idiotype, later followed by the appearance of anti-idiotypic antibodies that peaked before the onset of diabetes. Antibodies and T-cells reactive to hsp60 (heat shock protein) were triggered by the low-dose STZ administration and persisted throughout the period that preceded clinical diabetes. T-cells reactive to the p277 peptide of hsp60 were also observed. Finally, active immunization to hsp60 caused transient hyperglycemia by itself and also aggravated the hyperglycemia induced by low-dose STZ. Thus, autoantibodies to insulin can indicate susceptibility to a toxic trigger of diabetes, and a low dose of a toxin can activate the insulin and hsp60 autoimmunity that has been detected previously in the spontaneous autoimmune diabetes of NOD strain mice.     

Method of calculating the endurance of specimens with a stress raiser. 2

Dependencies of theoretical values of the endurance of specimens with a stress raiser on the method of determining the theoretical stress concentration factor are normalized. A method is proposed of calculating the endurance of specimens with an allowance made for the gradient of actual stresses in the concentration zone up to the start of formation of a macroscopic fatigue crack. The actual stresses in cyclic elastoplastic loading were determined by the equivalent energy method. The calculated stresses are compared with experimental values.N. E. Zhukovskii Aviation Institute, Khar'kov. Prochnost Regional Scientific Research Institute. Institute of Physical Metallurgy, Czechoslovak Academy of Sciences, Brno. Translated from Problemy Prochnosti, No. 9, pp. 100–103, September, 1989.     

Adenosine Receptor Agonist HE-NECA Enhances Antithrombotic Activities of Cangrelor and Prasugrel in vivo by Decreasing of Fibrinogen Density in Thrombus

Blood platelets’ adenosine receptors (AR) are considered to be a new target for the anti-platelet therapy. This idea is based on in vitro studies which show that signaling mediated by these receptors leads to a decreased platelet response to activating stimuli. In vivo evidence for the antithrombotic activity of AR agonists published to date were limited, however, to the usage of relatively high doses given in bolus. The present study was aimed at verifying if these substances used in lower doses in combination with inhibitors of P2Y₁₂ could serve as components of dual anti-platelet therapy. We have found that a selective A_2A agonist 2-hexynyl-5’-N-ethylcarboxamidoadenosine (HE-NECA) improved the anti-thrombotic properties of either cangrelor or prasugrel in the model of ferric chloride-induced experimental thrombosis in mice. Importantly, HE-NECA was effective not only when applied in bolus as other AR agonists in the up-to-date published studies, but also when given chronically. In vitro thrombus formation under flow conditions revealed that HE-NECA enhanced the ability of P2Y₁₂ inhibitors to decrease fibrinogen content in thrombi, possibly resulting in their lower stability. Adenosine receptor agonists possess a certain hypotensive effect and an ability to increase the blood–brain barrier permeability. Therefore, the effects of anti-thrombotic doses of HE-NECA on blood pressure and the blood–brain barrier permeability in mice were tested. HE-NECA applied in bolus caused a significant hypotension in mice, but the effect was much lower when the substance was given in doses corresponding to that obtained by chronic administration. At the same time, no significant effect of HE-NECA was observed on the blood–brain barrier. We conclude that chronic administration of the A_2A agonist can be considered a potential component of a dual antithrombotic therapy. However, due to the hypotensive effect of the substances, dosage and administration must be elaborated to minimize the side-effects. The total number of animals used in the experiments was 146.     

Short-term prediction of traffic flow using a binary neural network

This paper introduces a binary neural network-based prediction algorithm incorporating both spatial and temporal characteristics into the prediction process. The algorithm is used to predict short-term traffic flow by combining information from multiple traffic sensors (spatial lag) and time series prediction (temporal lag). It extends previously developed Advanced Uncertain Reasoning Architecture (AURA) k-nearest neighbour (k-NN) techniques. Our task was to produce a fast and accurate traffic flow predictor. The AURA k-NN predictor is comparable to other machine learning techniques with respect to recall accuracy but is able to train and predict rapidly. We incorporated consistency evaluations to determine whether the AURA k-NN has an ideal algorithmic configuration or an ideal data configuration or whether the settings needed to be varied for each data set. The results agree with previous research in that settings must be bespoke for each data set. This configuration process requires rapid and scalable learning to allow the predictor to be set-up for new data. The fast processing abilities of the AURA k-NN ensure this combinatorial optimisation will be computationally feasible for real-world applications. We intend to use the predictor to proactively manage traffic by predicting traffic volumes to anticipate traffic network problems.     

Fungal xylanases‐mediated synthesis of silver nanoparticles for catalytic and biomedical applications

Green synthesis of nanoparticles has fuelled the use of biomaterials to synthesise a variety of metallic nanoparticles. The current study investigates the use of xylanases of Aspergillus niger L3 (NEA) and Trichoderma longibrachiatum L2 (TEA) to synthesise silver nanoparticles (AgNPs). Characterisation of AgNPs was carried out using UV–Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), and transmission electron microscopy, while their effectiveness as antimicrobial, antioxidant, catalytic, anticoagulant, and thrombolytic agents were determined. The colloidal AgNPs was brownish with surface plasmon resonance at 402.5 and 410 nm for NEA‐AgNPs and TEA‐AgNPs, respectively; while FTIR indicated that protein molecules were responsible for the capping and stabilisation of the nanoparticles. The spherical nanoparticles had size of 15.21–77.49 nm. The nanoparticles significantly inhibited the growth of tested bacteria (63.20–88.10%) and fungi (82.20–86.10%), and also scavenged DPPH (37.48–79.42%) and hydrogen peroxide (20.50–96.50%). In addition, the AgNPs degraded malachite green (78.97%) and methylene blue (25.30%). Furthermore, the AgNPs displayed excellent anticoagulant and thrombolytic activities using human blood. This study has demonstrated the potential of xylanases to synthesise AgNPs which is to the best of our knowledge the first record of such. The present study underscores the relevance of xylanases in nanobiotechnology.Inspec keywords: visible spectra, catalysis, ultraviolet spectra, silver, microorganisms, antibacterial activity, transmission electron microscopy, surface plasmon resonance, nanoparticles, nanofabrication, colloids, blood, Fourier transform infrared spectra, particle sizeOther keywords: Ag, fungal xylanases‐mediated synthesis, silver nanoparticles, catalytic applications, biomedical applications, green synthesis, metallic nanoparticles, Trichoderma longibrachiatum L2, transmission electron microscopy, antimicrobial agents, antioxidant agents, catalytic agents, thrombolytic agents, surface plasmon resonance, spherical nanoparticles, FTIR spectra, anticoagulant agents, colloidal nanoparticles, biomaterials, Aspergillus niger L3, UV‐vis spectroscopy, Fourier transform infrared spectroscopy, protein molecules, DPPH, hydrogen peroxide, malachite green, methylene blue, human blood, nanobiotechnology     

Reliability-based optimal design using sample average approximations

An algorithm for reliability-based optimal design is developed using sampling techniques for estimating the failure probability. The algorithm applies a new method for sensitivity calculations of the failure probability. Initially, the estimates of the failure probability are coarse. As the algorithm progresses towards an optimal design, the number of sample points is increased in an adaptive way leading to better estimates of the failure probability. The algorithm is proven to converge to an optimal design. The applicability of the algorithm is shown in an example from the area of highway bridge design.     

A novel medical image compression using Ripplet transform

In spite of great advancements in multimedia data storage and communication technologies, compression of medical data remains challenging. This paper presents a novel compression method for the compression of medical images. The proposed method uses Ripplet transform to represent singularities along arbitrarily shaped curves and Set Partitioning in Hierarchical Trees encoder to encode the significant coefficients. The main objective of the proposed method is to provide high quality compressed images by representing images at different scales and directions and to achieve high compression ratio. Experimental results obtained on a set of medical images demonstrate that besides providing multiresolution and high directionality, the proposed method attains high Peak Signal to Noise Ratio and significant compression ratio as compared with conventional and state-of-art compression methods.