Spinal Excitatory Dynorphinergic Interneurons Contribute to Burn Injury-Induced Nociception Mediated by Phosphorylated Histone 3 at Serine 10 in Rodents

The phosphorylation of serine 10 in histone 3 (p-S10H3) has recently been demonstrated to participate in spinal nociceptive processing. However, superficial dorsal horn (SDH) neurons involved in p-S10H3-mediated nociception have not been fully characterized. In the present work, we combined immunohistochemistry, in situ hybridization with the retrograde labeling of projection neurons to reveal the subset of dorsal horn neurons presenting an elevated level of p-S10H3 in response to noxious heat (60 °C), causing burn injury. Projection neurons only represented a small percentage (5%) of p-S10H3-positive cells, while the greater part of them belonged to excitatory SDH interneurons. The combined immunolabeling of p-S10H3 with markers of already established interneuronal classes of the SDH revealed that the largest subset of neurons with burn injury-induced p-S10H3 expression was dynorphin immunopositive in mice. Furthermore, the majority of p-S10H3-expressing dynorphinergic neurons proved to be excitatory, as they lacked Pax-2 and showed Lmx1b-immunopositivity. Thus, we showed that neurochemically heterogeneous SDH neurons exhibit the upregulation of p-S10H3 shortly after noxious heat-induced burn injury and consequential tissue damage, and that a dedicated subset of excitatory dynorphinergic neurons is likely a key player in the development of central sensitization via the p-S10H3 mediated pathway.     

Performance of RSS Based Cooperative Localization in Millimeter Wave Wireless Sensor Networks

Wireless Personal Communications - Localization in wireless sensor networks (WSNs) is a necessity as there is a vital need to have location information combined with the measured quantities. The...     

Identification of Host Cellular Protein Substrates of SARS-COV-2 Main Protease

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease-19 (COVID-19) being associated with severe pneumonia. Like with other viruses, the interaction of SARS-CoV-2 with host cell proteins is necessary for successful replication, and cleavage of cellular targets by the viral protease also may contribute to the pathogenesis, but knowledge about the human proteins that are processed by the main protease (3CLpro) of SARS-CoV-2 is still limited. We tested the prediction potentials of two different in silico methods for the identification of SARS-CoV-2 3CLpro cleavage sites in human proteins. Short stretches of homologous host-pathogen protein sequences (SSHHPS) that are present in SARS-CoV-2 polyprotein and human proteins were identified using BLAST analysis, and the NetCorona 1.0 webserver was used to successfully predict cleavage sites, although this method was primarily developed for SARS-CoV. Human C-terminal-binding protein 1 (CTBP1) was found to be cleaved in vitro by SARS-CoV-2 3CLpro, the existence of the cleavage site was proved experimentally by using a His₆-MBP-mEYFP recombinant substrate containing the predicted target sequence. Our results highlight both potentials and limitations of the tested algorithms. The identification of candidate host substrates of 3CLpro may help better develop an understanding of the molecular mechanisms behind the replication and pathogenesis of SARS-CoV-2.     

Estimation of the Stress-Strength Reliability for Exponentiated Pareto Distribution Using Median and Ranked Set Sampling Methods

In reliability analysis, the stress-strength model is often used to describe the life of a component which has a random strength (X) and is subjected to a random stress (Y). In this paper, we considered the problem of estimating the reliability R=P [Y<X] when the distributions of both stress and strength are independent and follow exponentiated Pareto distribution. The maximum likelihood estimator of the stress strength reliability is calculated under simple random sample, ranked set sampling and median ranked set sampling methods. Four different reliability estimators under median ranked set sampling are derived. Two estimators are obtained when both strength and stress have an odd or an even set size. The two other estimators are obtained when the strength has an odd size and the stress has an even set size and vice versa. The performances of the suggested estimators are compared with their competitors under simple random sample via a simulation study. The simulation study revealed that the stress strength reliability estimates based on ranked set sampling and median ranked set sampling are more efficient than their competitors via simple random sample. In general, the stress strength reliability estimates based on median ranked set sampling are smaller than the corresponding estimates under ranked set sampling and simple random sample methods.     

Effects of microelements on soil nematode assemblages seven years after contaminating an agricultural field

Long-term effects of Cd, Cr, Cu, Se and Zn were studied 7 years after artificially contaminating plots of an agricultural field on a calcareous chernozem soil. Effects of three to four different contamination levels (originally 10, 30, 90 and 270 mg kg⁻¹) were studied. Nematode density was significantly reduced by 90 and 270 mg kg⁻¹ Se as well as by 270 mg kg⁻¹ Cr, while 90 and 270 mg kg⁻¹ Se also reduced nematode generic richness. Maturity Index values (calculated for c-p 2–5 nematodes) consistently decreased with increasing Cr and Se concentration and to a lesser extent in Zn plots as well. Structure Index showed decreasing trends in increasing Cr, Se and (to a lesser extent) in Zn treatments, while in Cd it shows a moderate increase. Distribution of c-p groups was negatively affected by the increasing Cr and Se concentration, while in Zn plots, this decrease was not significant. Response of feeding groups to pollutions was similar to other parameters: Cr and Se caused significant changes toward the loss of variability. The proportion of the most sensitive omnivorous and predatory nematodes decreased clearly as a consequence of Cr and Se treatments. Zn pollution also resulted in a slight decrease in this group, while Cd caused an increase. Nematode diversity profiles showed a significant decrease in the plots of increased Cr and Se concentrations, while increased concentrations of Cu and Zn resulted in ambiguous effects. Besides providing evidence on the harmful effects of Cr and Se on a soil nematode assemblage, our results suggest that simultaneous analysis of Maturity Index, Structure Index and diversity profiles provide a promising tool in nematological indication of soil pollution.     

Experimental Investigations on Microstructure,Properties and Workability Behavior of Zinc Oxide Reinforced Al–Si–Mg Matrix Composites

Silicon - Al-Si based alloy matrix composites are now broadly utilized by the industrial sectors like automobile, structural, aerospace and more practical industrial applications due to its...     

Kinetic parameter estimation for cooling crystallization process based on cell average technique and automatic differentiation

In this paper, a cell average technique(CAT) based parameter estimation method is proposed for cooling crystallization involved with particle growth, aggregation and breakage, by establishing a more efficient and accurate solution in terms of the automatic differentiation(AD) algorithm. To overcome the deficiency of CAT that demands high computation cost for implementation, a set of ordinary differential equations(ODEs) entailed from CAT based discretized population balance equation(PBE) are solved by using the AD based high-order Taylor expansion. Moreover, an AD based trust-region reflective(TRR) algorithm and another interior-point(IP) algorithm are established for estimating the kinetic parameters associated with particle growth, aggregation and breakage. As a result, the estimation accuracy can be further improved while the computation cost can be significantly reduced, compared to the existing algorithms. Benchmark examples from the literature are used to illustrate the accuracy and efficiency of the AD-based CAT, TRR and IP algorithms in comparison with the existing algorithms. Moreover, seeded batch cooling crystallization experiments of β form L-glutamic acid are performed to validate the proposed method.     

Experimental and numerical evaluation of electromagnetic acoustic transducer performance on steel materials

Electromagnetic Acoustic Transducers (EMATs) are an attractive alternative to standard piezoelectric probes in a number of applications thanks to their contactless nature. EMATs do not require any couplant liquid and are able to generate a wide range of wave-modes; however these positive features are partly counterbalanced by a relatively low signal-to-noise ratio and by the dependence of EMAT performance on the material properties of the test object. A wide variety of steel materials is employed in many industrial applications, so it is important to assess the material-dependent behaviour of EMATs when used in the inspection of different types of steel. Experimental data showing the performance of bulk shear wave EMATs on a wide range of steels is presented, showing the typical range of physical properties encountered in practice. A previously validated Finite Element model, including the main transduction mechanisms, the Lorentz force and magnetostriction, is used to evaluate the experimental data. The main conclusion is that the Lorentz force is the dominant transduction effect, regardless of the magnitude and direction of the bias magnetic field. Differently from magnetostriction, the Lorentz force is not significantly sensitive to the typical range of physical properties of steels, as a consequence the same EMAT sensor can be used on different grades of ferritic steel.