Out-of-Field Hippocampus from Partial-Body Irradiated Mice Displays Changes in Multi-Omics Profile and Defects in Neurogenesis

The brain undergoes ionizing radiation exposure in many clinical situations, particularly during radiotherapy for brain tumors. The critical role of the hippocampus in the pathogenesis of radiation-induced neurocognitive dysfunction is well recognized. The goal of this study is to test the potential contribution of non-targeted effects in the detrimental response of the hippocampus to irradiation and to elucidate the mechanisms involved. C57Bl/6 mice were whole body (WBI) or partial body (PBI) irradiated with 0.1 or 2.0 Gy of X-rays or sham irradiated. PBI consisted of the exposure of the lower third of the mouse body, whilst the upper two thirds were shielded. Hippocampi were collected 15 days or 6 months post-irradiation and a multi-omics approach was adopted to assess the molecular changes in non-coding RNAs, proteins and metabolic levels, as well as histological changes in the rate of hippocampal neurogenesis. Notably, at 2.0 Gy the pattern of early molecular and histopathological changes induced in the hippocampus at 15 days following PBI were similar in quality and quantity to the effects induced by WBI, thus providing a proof of principle of the existence of out-of-target radiation response in the hippocampus of conventional mice. We detected major alterations in DAG/IP3 and TGF-β signaling pathways as well as in the expression of proteins involved in the regulation of long-term neuronal synaptic plasticity and synapse organization, coupled with defects in neural stem cells self-renewal in the hippocampal dentate gyrus. However, compared to the persistence of the WBI effects, most of the PBI effects were only transient and tended to decrease at 6 months post-irradiation, indicating important mechanistic difference. On the contrary, at low dose we identified a progressive accumulation of molecular defects that tended to manifest at later post-irradiation times. These data, indicating that both targeted and non-targeted radiation effects might contribute to the pathogenesis of hippocampal radiation-damage, have general implications for human health.     

Connectionist simulation of quantification skills

The study of numerical abilities, and how they are acquired, is being used to explore the continuity between ontogenesis and environmental learning. One technique that proves useful in this exploration is the artificial simulation of numerical abilities with neural networks, using different learning paradigms to explore development. A neural network simulation of subitization, sometimes referred to as visual enumeration, and of counting, a recurrent operation, has been developed using the so-called multi-net architecture. Our numerical ability simulations use two or more neural networks combining supervised and unsupervised learning techniques to model subitization and counting. Subitization has been simulated using networks employing unsupervised self-organizing learning, the results of which agree with infant subitization experiments and are comparable with supervised neural network simulations of subitization reported in the literature. Counting has been simulated using a multi-net system of supervised static and recurrent backpropagation networks that learn their individual tasks within an unsupervised, competitive framework. The developmental profile of the counting simulation shows similarities to that of children learning to count and demonstrates how neural networks can learn how to be combined together in a process modelling development.     

Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures

In this research, we work with data of futures contracts on foreign exchange rates for British pound (BP), Canadian dollar (CD), and Japanese yen (JY) that are traded at the Chicago Mercantile Exchange (CME) against US dollars. We model relationships between exchange rates in these currencies using linear models, feed forward artificial neural networks (ANN), and three versions of recurrent neural networks (RNN1, RNN2 and RNN3) for predicting exchange rates in these currencies against the US dollar. Our results on forecast evaluations based on AGS test the tests of forecast equivalence between any two competing models among the entire models employed for each of the series show that ANN and the three versions of RNN models offer superior forecasts for predicting BP, CD and JY exchange rates although the forecast evaluations based on MGN test are in sharp contrast. On the other hand forecast based on SIGN test shows that ANN and all the versions of RNN models offer superior forecasts for BP and CD in exception of JY exchange rates. The results for forecast evaluation for all the models for each of the series based on summary measures of forecast evaluations show that RNN3 model appears to offer the most accurate predictions of BP and RNN1 for JP exchange rates. However, none of the RNN models appear to be statistically superior to the benchmark (i.e., linear model) for predicting CD exchange rates.      

Numerical solution of second‐order,two‐point boundary value problems using continuous genetic algorithms

Second‐order, two‐point boundary‐value problems are encountered in many engineering applications including the study of beam deflections, heat flow, and various dynamic systems. Two classical numerical techniques are widely used in the engineering community for the solution of such problems; the shooting method and finite difference method. These methods are suited for linear problems. However, when solving the non‐linear problems, these methods require some major modifications that include the use of some root‐finding technique. Furthermore, they require the use of other basic numerical techniques in order to obtain the solution. In this paper, the author introduces a novel method based on continuous genetic algorithms for numerically approximating a solution to this problem. The new method has the following characteristics; first, it does not require any modification while switching from the linear to the non‐linear case; as a result, it is of versatile nature. Second, this approach does not resort to more advanced mathematical tools and is thus easily accepted in the engineering application field. Third, the proposed methodology has an implicit parallel nature which points to its implementation on parallel machines. However, being a variant of the finite difference scheme with truncation error of the order O(h²), the method provides solutions with moderate accuracy. Numerical examples presented in the paper illustrate the applicability and generality of the proposed method. Copyright © 2004 John Wiley & Sons, Ltd.     

Storage and permeation of hydrogen molecule,atom and ions (H+ and H−) through silicon carbide nanotube; a DFT approach

The barriers for the encapsulation and decapsulation of hydrogen ions (cationic hydrogen and hydride), atom, and molecule through silicon carbide nanotube are thoroughly studied. DFT method is selected to measure the kinetic barriers for the passage of hydrogen atom, ions and molecule through nanotube via scanning potential energy surface. The kinetic barriers for the passage (encapsulation and decapsulation) of hydrogen are very important to understand the mechanism of hydrogen storage and release. The barriers for the permeation of H, H⁺ and H^? across SiC nanosheet are lower compared to hydrogen molecule (H₂). The exohedral and endohedral adsorption of hydrogen ions (cation and anion), atom and exohedral hydrogen molecule on silicon carbide are exothermic in nature. Whereas the encapsulation of hydrogen molecule in silicon carbide is endothermic. Electronic properties are analyzed through measurement of energy gap between highest occupied and lowest unoccupied molecular orbitals gap (G_H-L) and the density of state (DOS) spectra. The G_H-L analysis reveals that endohedral complexes have more pronounced effect on electronic properties compared to exohedral complexes. The SiC nanotube has highly favorable properties for storage and release of hydrogen ions, and atom.     

Micro-RNA and Proteomic Profiles of Plasma-Derived Exosomes from Irradiated Mice Reveal Molecular Changes Preventing Apoptosis in Neonatal Cerebellum

Cell communication via exosomes is capable of influencing cell fate in stress situations such as exposure to ionizing radiation. In vitro and in vivo studies have shown that exosomes might play a role in out-of-target radiation effects by carrying molecular signaling mediators of radiation damage, as well as opposite protective functions resulting in resistance to radiotherapy. However, a global understanding of exosomes and their radiation-induced regulation, especially within the context of an intact mammalian organism, has been lacking. In this in vivo study, we demonstrate that, compared to sham-irradiated (SI) mice, a distinct pattern of proteins and miRNAs is found packaged into circulating plasma exosomes after whole-body and partial-body irradiation (WBI and PBI) with 2 Gy X-rays. A high number of deregulated proteins (59% of WBI and 67% of PBI) was found in the exosomes of irradiated mice. In total, 57 and 13 miRNAs were deregulated in WBI and PBI groups, respectively, suggesting that the miRNA cargo is influenced by the tissue volume exposed to radiation. In addition, five miRNAs (miR-99b-3p, miR-200a-3p, miR-200a, miR-182-5p, miR-182) were commonly overexpressed in the exosomes from the WBI and PBI groups. In this study, particular emphasis was also given to the determination of the in vivo effect of exosome transfer by intracranial injection in the highly radiosensitive neonatal cerebellum at postnatal day 3. In accordance with a major overall anti-apoptotic function of the commonly deregulated miRNAs, here, we report that exosomes from the plasma of irradiated mice, especially in the case of WBI, prevent radiation-induced apoptosis, thus holding promise for exosome-based future therapeutic applications against radiation injury.     

The multiaxial weld root fatigue of butt welded joints subjected to uniaxial loading

In this study, the fatigue strength of inclined butt welds subjected to a proportional multiaxial stress state generated by uniaxial loading is studied in nominal and local stress concepts. The local methodologies studied included principal stress hypothesis, von Mises stress hypothesis and modified Wöhler curve method. Nominal methodologies included modified Gough–Pollard interaction equation, the design equation in Eurocode3 and the interaction equation in DNV standard. Results are evaluated along with data published in relevant literature. It is observed that both local and nominal stress assessment methods are able to estimate multiaxial fatigue strength. No obvious difference in fatigue strength is observed in the nominal stress concept, but the notch stress concept is able to capture a decrease in fatigue strength in shear‐dominated joints. It is concluded that modified Wöhler curve method is a suitable tool for the evaluation of fatigue strength in joints dominated by both normal and shear stresses.     

Differences between t‐norms in fuzzy control

The application of conjunctive aggregation functions in fuzzy control systems with n inputs is discussed, and the effect of the choice of a continuous t‐norm in the inference phase for Takagi–Sugeno–Kang (TSK) systems is computed. A continuous t‐norm modeling AND connective in antecedent part of fuzzy rules can be reduced just to strict or nilpotent t‐norm. The isomorphism of strict (nilpotent) t‐norms enables simpler fitting of TSK fuzzy system parameters and reduces the computational complexity. Similar principle can also be used in the case of some noncommutative conjunctive aggregation functions modeling AND connective. The effect of the choice of a continuous t‐norm is then evaluated on well‐known case studies in fuzzy control, the Sinc function, and the urban traffic noise control system.     

Bacteriological Evaluation of Gingival Crevicular Fluid in Teeth Restored Using Fixed Dental Prostheses: An In Vivo Study

The present in vivo study determined the microbiological counts of the gingival crevicular fluid (GCF) among patients with fixed dental prostheses fabricated using three different techniques. A total of 129 subjects were divided into three study groups: first, cobalt-chrome-based, metal-ceramic prostheses fabricated by the conventional method (MC, n = 35); the second group consisted of cobalt-chrome-based, metal-ceramic prostheses fabricated by the computer-aided design and computer-aided manufacturing (CAD/CAM) technique (CC-MC, n = 35); the third group comprised zirconia-based ceramic prostheses fabricated using the CAD/CAM technique (CC-Zr, n = 35). The control consisted of 24 patients using prostheses fabricated with either MC, CC-MC, or CC-Zr. The GCF was obtained from the subjects before treatment, and 6 and 12 months after the prosthetic treatment. Bacteriological and bacterioscopic analysis of the GCF was performed to analyze the patients’ GCF. The data were analyzed using SPSS V20 (IBM Company, Chicago, IL, USA). The number of microorganisms of the gingival crevicular fluid in all groups at 12 months of prosthetic treatment reduced dramatically compared with the data obtained before prosthetic treatment. Inflammatory processes in the periodontium occurred slowly in the case of zirconium oxide-based ceramic constructions due to their biocompatibility with the mucous membranes and tissues of the oral cavity as well as a reduced risk of dental biofilm formation. This should be considered by dentists and prosthodontists when choosing restoration materials for subjects with periodontal pathology.