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.     

Synthesis and crosslinking properties of phenolphtalein dimethacrylate

Summary By reacting esterification of phenolphtalein with methacrylate chloride, phenolphtalein dimethacrylate was obtained. Based on the results of elemental analysis, FTIR, ¹H-NMR and ¹³C-NMR spectra, the structure of the product was proposed. The dimethacrylate was used as new crosslinker to crosslink poly(methyl methacrylate) (PMMA). The influence of the amount dimethacrylate on the crosslink density and some properties of the crosslinked polymers networks such as swelling, mechanical properties (tensile strength and elongation at break) and thermal stability were examined.     

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.     

Towards language-to-language transformation

This paper proposes a simplicity-oriented approach and framework for language-to-language transformation of, in particular, graphical languages. Key to simplicity is the decomposition of the transformation specification into sub-rule systems that separately specify purpose-specific aspects. We illustrate this approach by employing a variation of Plotkin’s Structural Operational Semantics (SOS) for pattern-based transformations of typed graphs in order to address the aspect ‘computation’ in a graph rewriting fashion. Key to our approach are two generalizations of Plotkin’s structural rules: the use of graph patterns as the matching concept in the rules, and the introduction of node and edge types. Types do not only allow one to easily distinguish between different kinds of dependencies, like control, data, and priority, but may also be used to define a hierarchical layering structure. The resulting Type-based Structural Operational Semantics (TSOS) supports a well-structured and intuitive specification and realization of semantically involved language-to-language transformations adequate for the generation of purpose-specific views or input formats for certain tools, like, e.g., model checkers. A comparison with the general-purpose transformation frameworks ATL and Groove, illustrates along the educational setting of our graphical WebStory language that TSOS provides quite a flexible format for the definition of a family of purpose-specific transformation languages that are easy to use and come with clear guarantees.