Value of micro-CT for monitoring spinal microvascular changes after chronic spinal cord compression

published_or_final_versio

Correlation effects in the electronic structure of the Ni-based superconducting KNi2S2

published_or_final_versio

Optimization of RAPD-PCR reaction system for genetic relationships analysis of 15 camellia cultivars

With orthogonal analysis by L27(36), the random amplified polymorphic DNA (RAPD)-PCR optimization reaction system for camellia were obtained. Results showed that the optimization system was 10×PCR Buffer (2.5 L), 25 mM MgCl2 (2.5 L), 2.5 mM dNTPs (2.0 L), 20 M primer (1.0 L), Tag (1.5 U), temple DNA (40 ng or so) and added ddH2O to the total volume 25 uL; suitable annealing temperature was 36°C. With the optimized system and fifteen 10 nt random primers, we analyzed 15 camellia cultivars and observed 102 clear amplified loci, in which polymorphic loci were 79 while the percentage of polymorphic loci were 77.54%. Cluster analysis showed that the four groups were divided at the point 0.75 of similarity coefficient, indicating relatively high genetic diversity. We also found that the gene controlling petal color may play an important role in RAPD analysis. Moreover, genetic diversities based on RAPD analysis could be clearly reflected by morphological traits among 15 camellia cultivars. This study showed the RAPD optimization system was suitable and RAPD molecular marker was effective and useful tool for detection of genetic relationships among camellia cultivars

Superconducting ECR ion source: From 24-28 GHz SECRAL to 45 GHz fourth generation ECR.

The development of superconducting ECR source with higher magnetic fields and higher microwave frequency is the most straight forward path to achieve higher beam intensity and higher charge state performance. SECRAL, a superconducting third generation ECR ion source, is designed for 24-28 GHz microwave frequency operation with an innovative magnet configuration of sextupole coils located outside the three solenoids. SECRAL at 24 GHz has already produced a number of record beam intensities, such as 40Ar12+ 1.4 emA, 129Xe26+ 1.1 emA, 129Xe30+ 0.36 emA, and 209Bi31+ 0.68 emA. SECRAL-II, an upgraded version of SECRAL, was built successfully in less than 3 years and has recently been commissioned at full power of a 28 GHz gyrotron and three-frequency heating (28 + 45 + 18 GHz). New record beam intensities for highly charged ion production have been achieved, such as 620 eμA 40Ar16+, 15 eμA 40Ar18+, 146 eμA 86Kr28+, 0.5 eμA 86Kr33+, 53 eμA 129Xe38+, and 17 eμA 129Xe42+. Recent beam test results at SECRAL and SECRAL II have demonstrated that the production of more intense highly charged heavy ion beams needs higher microwave power and higher frequency, as the scaling law predicted. A 45 GHz superconducting ECR ion source FECR (a first fourth generation ECR ion source) is being built at IMP. FECR will be the world's first Nb3Sn superconducting-magnet-based ECR ion source with 6.5 T axial mirror field, 3.5 T sextupole field on the plasma chamber inner wall, and 20 kW at a 45 GHz microwave coupling system. This paper will focus on SECRAL performance studies at 24-28 GHz and technical design of 45 GHz FECR, which demonstrates a technical path for highly charged ion beam production from 24 to 28 GHz SECRAL to 45 GHz FECR

Synergistic Antibacterial Effects of Metallic Nanoparticle Combinations

© The Author(s) 2019.Metallic nanoparticles have unique antimicrobial properties that make them suitable for use within medical and pharmaceutical devices to prevent the spread of infection in healthcare. The use of nanoparticles in healthcare is on the increase with silver being used in many devices. However, not all metallic nanoparticles can target and kill all disease-causing bacteria. To overcome this, a combination of several different metallic nanoparticles were used in this study to compare effects of multiple metallic nanoparticles when in combination than when used singly, as single elemental nanoparticles (SENPs), against two common hospital acquired pathogens (Staphylococcus aureus and Pseudomonas. aeruginosa). Flow cytometry LIVE/DEAD assay was used to determine rates of cell death within a bacterial population when exposed to the nanoparticles. Results were analysed using linear models to compare effectiveness of three different metallic nanoparticles, tungsten carbide (WC), silver (Ag) and copper (Cu), in combination and separately. Results show that when the nanoparticles are placed in combination (NPCs), antimicrobial effects significantly increase than when compared with SENPs (P < 0.01). This study demonstrates that certain metallic nanoparticles can be used in combination to improve the antimicrobial efficiency in destroying morphologically distinct pathogens within the healthcare and pharmaceutical industry.Peer reviewe

Atomic-scale combination of germanium-zinc nanofibers for structural and electrochemical evolution

Alloys are recently receiving considerable attention in the community of rechargeable batteries as possible alternatives to carbonaceous negative electrodes; however, challenges remain for the practical utilization of these materials. Herein, we report the synthesis of germanium-zinc alloy nanofibers through electrospinning and a subsequent calcination step. Evidenced by in situ transmission electron microscopy and electrochemical impedance spectroscopy characterizations, this one-dimensional design possesses unique structures. Both germanium and zinc atoms are homogenously distributed allowing for outstanding electronic conductivity and high available capacity for lithium storage. The as-prepared materials present high rate capability (capacity of similar to 50% at 20 C compared to that at 0.2 C-rate) and cycle retention (73% at 3.0 C-rate) with a retaining capacity of 546 mAh g(-1) even after 1000 cycles. When assembled in a full cell, high energy density can be maintained during 400 cycles, which indicates that the current material has the potential to be used in a large-scale energy storage system

The Goldbeter-Koshland switch in the first-order region and its response to dynamic disorder

In their classical work (Proc. Natl. Acad. Sci. USA, 1981, 78:6840-6844), Goldbeter and Koshland mathematically analyzed a reversible covalent modification system which is highly sensitive to the concentration of effectors. Its signal-response curve appears sigmoidal, constituting a biochemical switch. However, the switch behavior only emerges in the "zero-order region", i.e. when the signal molecule concentration is much lower than that of the substrate it modifies. In this work we showed that the switching behavior can also occur under comparable concentrations of signals and substrates, provided that the signal molecules catalyze the modification reaction in cooperation. We also studied the effect of dynamic disorders on the proposed biochemical switch, in which the enzymatic reaction rates, instead of constant, appear as stochastic functions of time. We showed that the system is robust to dynamic disorder at bulk concentration. But if the dynamic disorder is quasi-static, large fluctuations of the switch response behavior may be observed at low concentrations. Such fluctuation is relevant to many biological functions. It can be reduced by either increasing the conformation interconversion rate of the protein, or correlating the enzymatic reaction rates in the network.Comment: 23 pages, 4 figures, accepted by PLOS ON

Discussion on the thermal conductivity enhancement of nanofluids

Increasing interests have been paid to nanofluids because of the intriguing heat transfer enhancement performances presented by this kind of promising heat transfer media. We produced a series of nanofluids and measured their thermal conductivities. In this article, we discussed the measurements and the enhancements of the thermal conductivity of a variety of nanofluids. The base fluids used included those that are most employed heat transfer fluids, such as deionized water (DW), ethylene glycol (EG), glycerol, silicone oil, and the binary mixture of DW and EG. Various nanoparticles (NPs) involving Al2O3 NPs with different sizes, SiC NPs with different shapes, MgO NPs, ZnO NPs, SiO2 NPs, Fe3O4 NPs, TiO2 NPs, diamond NPs, and carbon nanotubes with different pretreatments were used as additives. Our findings demonstrated that the thermal conductivity enhancements of nanofluids could be influenced by multi-faceted factors including the volume fraction of the dispersed NPs, the tested temperature, the thermal conductivity of the base fluid, the size of the dispersed NPs, the pretreatment process, and the additives of the fluids. The thermal transport mechanisms in nanofluids were further discussed, and the promising approaches for optimizing the thermal conductivity of nanofluids have been proposed

A novel isolator-based system promotes viability of human embryos during laboratory processing

In vitro fertilisation (IVF) and related technologies are arguably the most challenging of all cell culture applications. The starting material is a single cell from which one aims to produce an embryo capable of establishing a pregnancy eventually leading to a live birth. Laboratory processing during IVF treatment requires open manipulations of gametes and embryos, which typically involves exposure to ambient conditions. To reduce the risk of cellular stress, we have developed a totally enclosed system of interlinked isolator-based workstations designed to maintain oocytes and embryos in a physiological environment throughout the IVF process. Comparison of clinical and laboratory data before and after the introduction of the new system revealed that significantly more embryos developed to the blastocyst stage in the enclosed isolator-based system compared with conventional open-fronted laminar flow hoods. Moreover, blastocysts produced in the isolator-based system contained significantly more cells and their development was accelerated. Consistent with this, the introduction of the enclosed system was accompanied by a significant increase in the clinical pregnancy rate and in the proportion of embryos implanting following transfer to the uterus. The data indicate that protection from ambient conditions promotes improved development of human embryos. Importantly, we found that it was entirely feasible to conduct all IVF-related procedures in the isolator-based workstations

Employing machine learning for reliable miRNA target identification in plants

<p>Abstract</p> <p>Background</p> <p>miRNAs are ~21 nucleotide long small noncoding RNA molecules, formed endogenously in most of the eukaryotes, which mainly control their target genes post transcriptionally by interacting and silencing them. While a lot of tools has been developed for animal miRNA target system, plant miRNA target identification system has witnessed limited development. Most of them have been centered around exact complementarity match. Very few of them considered other factors like multiple target sites and role of flanking regions.</p> <p>Result</p> <p>In the present work, a Support Vector Regression (SVR) approach has been implemented for plant miRNA target identification, utilizing position specific dinucleotide density variation information around the target sites, to yield highly reliable result. It has been named as p-TAREF (plant-Target Refiner). Performance comparison for p-TAREF was done with other prediction tools for plants with utmost rigor and where p-TAREF was found better performing in several aspects. Further, p-TAREF was run over the experimentally validated miRNA targets from species like <it>Arabidopsis</it>, <it>Medicago</it>, Rice and Tomato, and detected them accurately, suggesting gross usability of p-TAREF for plant species. Using p-TAREF, target identification was done for the complete Rice transcriptome, supported by expression and degradome based data. miR156 was found as an important component of the Rice regulatory system, where control of genes associated with growth and transcription looked predominant. The entire methodology has been implemented in a multi-threaded parallel architecture in Java, to enable fast processing for web-server version as well as standalone version. This also makes it to run even on a simple desktop computer in concurrent mode. It also provides a facility to gather experimental support for predictions made, through on the spot expression data analysis, in its web-server version.</p> <p>Conclusion</p> <p>A machine learning multivariate feature tool has been implemented in parallel and locally installable form, for plant miRNA target identification. The performance was assessed and compared through comprehensive testing and benchmarking, suggesting a reliable performance and gross usability for transcriptome wide plant miRNA target identification.</p