Characterization of Maga Expression and Iron Uptake in P19 Cells: Implications for Use as a Gene-Based Contrast Agent

Magnetic resonance imaging (MRI) is one of the non-invasive imaging modalities used in longitudinal cell tracking. Previous studies suggest that MagA, a putative iron transport protein from magnetotactic bacteria, is a useful gene-based magnetic resonance contrast agent. Hemagglutinin (HA)-tagged MagA was stably expressed in undifferentiated embryonic mouse teratocarcinoma, multipotent P19 stem cells to provide a suitable model for tracking these cells during differentiation. Western blot and immunocytochemistry confirmed the expression and membrane localization of MagA-HA in P19 cells. Elemental iron analysis using inductively-coupled plasma mass spectrometry revealed significant iron uptake in both parental and MagA-HA-expressing P19 cells, cultured in the presence of iron-supplemented medium. Withdrawal of this extracellular iron supplement revealed unexpected iron export activity in P19 cells, which MagA-HA expression attenuated. The influence of iron supplementation on parental and MagA-HA-expressing cells was not reflected by longitudinal relaxation rates. Measurement of transverse relaxation rates (R2* and R2) reflected changes in total cellular iron content. In particular, the reversible component R2′ (R2* ‒ R2) provided a moderately strong correlation to amount of cellular iron, normalized to amount of protein

L2L^2-Wasserstein contraction for Euler schemes of elliptic diffusions and interacting particle systems

We show the $L^2$-Wasserstein contraction for the transition kernel of a discretised diffusion process, under a contractivity at infinity condition on the drift and a sufficiently high diffusivity requirement. This extends recent results that, under similar assumptions on the drift but without the diffusivity restrictions, showed the $L^1$-Wasserstein contraction, or $L^p$-Wasserstein bounds for $p > 1$ that were, however, not true contractions. We explain how showing the true $L^2$-Wasserstein contraction is crucial for obtaining the local Poincar\'{e} inequality for the transition kernel of the Euler scheme of a diffusion. Moreover, we discuss other consequences of our contraction results, such as concentration inequalities and convergence rates in KL-divergence and total variation. We also study the corresponding $L^2$-Wasserstein contraction for discretisations of interacting diffusions. As a particular application, this allows us to analyse the behaviour of particle systems that can be used to approximate a class of McKean-Vlasov SDEs that were recently studied in the mean-field optimization literature.Comment: 28 page

Protective effect of S-allyl cysteine against cerebral ischemia/reperfusion injury in experimental rats

Purpose: To investigate the protective effect of S-allyl cysteine (SAC) against cerebral ischemiareperfusion injury (CRI) in rats.Methods: The protective effect of SAC was determined in a male Wistar rat model of middle cerebral artery occlusion (MCAO)-stimulated transient focal ischemia, followed by reperfusion. Cerebral ischemia reperfusion injury was induced via 90 min of MCAO, followed by 24-h reperfusion. The cerebral infarct size was determined by staining with 2,3,5- triphenyl tetrazolium chloride. The onset of cellular derangement, neurological deficit score and neuronal oedema were determined. In addition, the expressions of CRI markers and inflammatory cytokines were measured by enzyme-linked immunosorbent assay (ELISA).Results: Rats subjected to CRI showed marked increases in cellular oxidative stress, as evidenced by significant increase in the levels of inflammatory markers, including MDA (p < 0.05), MPO (p < 0.05) and nitric oxide (p < 0.01). In addition, CRI increased the mRNA expression levels of the marker genes TLR4, syndecan-1, CSF, aquaporin-1, OCT3, and RFX1. In contrast, rats pre-treated with SAC prior to CRI displayed reduced levels of inflammatory cytokines, with a near-normal cellular arrangement. SAC treatment significantly reduced the mRNA expression levels of the marker genes in CRI rats.Conclusion: These findings suggest that SAC may protect the brain of rats from cerebral ischemiareperfusion injury caused by amplification of oxidative stress and inflammatory signaling. Thus, S-allyl cysteine is a potential therapy for the management of CRI

STKE: Temporal Knowledge Graph Embedding in the Spherical Coordinate System

Knowledge graph embedding (KGE) aims to learn the representation of entities and predicates in low-dimensional vector spaces which can complete the missing parts of the Knowledge Graphs (KGs). Nevertheless, temporal knowledge graphs (TKGs) that include time information are more consistent with real-world application scenarios. Meanwhile, the facts with time constraints make the results of reasoning over time more accurate. Because of these, we propose a novel temporal knowledge graph embedding (TKGE) model, namely Spherical Temporal Knowledge Graph Embedding (STKE), which embeds facts into a spherical coordinate system. We treat each fact as a rotation from the subject to the object. The entities and predicates in STKE are divided into three parts--the radial part, the azimuth part, and the polar part. The radial part aims to resize the modulus between two entities. The azimuth part is mainly used to distinguish entities with the same module length and the polar part aims to represent the transformation of the time embedding with the change of polar angle. We evaluate the proposed model via the link prediction task on four typical temporal datasets. Experiments demonstrate that STKE achieves a significant surpass compared with the state-of-the-art static knowledge graph embedding (SKGE) model and TKGE model. In addition, we analyze the representation ability of different facts in the spherical coordinate system and confirm that our model can better represent time-constrained facts

Facile Preparation of g-C3N4-WO3 Composite Gas Sensing Materials with Enhanced Gas Sensing Selectivity to Acetone

In this paper, g-C3N4-WO3 composite materials were prepared by hydrothermal processing. The composites were characterized by means of X-ray powder diffraction (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and N2 adsorption-desorption, respectively. The gas sensing properties of the composites were investigated. The results indicated that the addition of appropriate amount of g-C3N4 to WO3 could improve the response and selectivity to acetone. The sensor based on 2 wt% g-C3N4-WO3 composite showed the best gas sensing performances. When operating at optimum temperature of 310°C, the responses to 1000 ppm and 0.5 ppm acetone were 58.2 and 1.6, respectively, and the ratio of the S1000 ppm acetone to S1000 ppm ethanol reached 3.7

Influences of planetary gear parameters on the dynamic characteristics – a review

Planetary gear trains (PGTs) are widely used in the field of mechanical transmission. PGTs significantly differ from fixed-axis gear trains and exhibit unique dynamic behavior. Dynamic characteristics of PGTs are popular research topic, particularly when attempting to solve the problem of vibration noise. Moreover, the effects of the planetary gear parameters on the dynamic characteristics are paramount important. And significant researches have been conducted in this field. However, few reviews regarding these studies have been published. In this paper, the effects of certain parameters, which include mesh phase difference, geometric errors (tooth profile error, eccentricity error and misalignment), tooth profile modification, mesh stiffness, and etc., on the dynamic characteristics of PGTs are summarized. Several conclusions obtained can be used for the PGTs design and dynamic characteristics analysis. Finally, the potential research trends are pointed out

The analysis and fabrication of a novel tin-nickel mixed salt electrolytic coloured processing and the performance of coloured films for Al-12.7Si-0.7Mg alloy in acidic and alkali corrosive environments.

We present for the first time the analysis and fabrication of a novel Tin-Nickel mixed salt electrolytic coloured processing and the performance of coloured films for Al-12.7Si-0.7Mg alloy. This alloy is a novel alloy containing high silicon aluminum alloy extrusion profile which presents excellent mechanical properties as well as broad market prospects. Nevertheless, this kind of material is urgent in need of surface treatment technology. The orthogonal design and single factor tests were applied to optimize for electrolytic coloured technological conditions. By controlling operation conditions, the uniform electrolytic coloured films with different color were obtained. Analysis of microstructure showed that tin particles had been deposited in the coloured film. The coloured films, about 10 mu m thick, were uniform, dense and firmly attached to the substrate. After the coloured samples were maintained at 400AC for 1 h, or quenched from 300AC to room temperature, the coloured films did not change, demonstrating excellent thermostability and thermal shock resistance. Acid and alkali corrosion tests and potentiodynamic polarization showed that corrosion resistance of coloured sample was much better than those of untreated samples. After 240 h neutral salt spray test, protection ratings and appearance ratings of coloured films were Grade 9

Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices

Home appliance manufacturers strive to obtain feedback from users to improve their products and services to build a smart home system. To help manufacturers develop a smart home system, we design a federated learning (FL) system leveraging the reputation mechanism to assist home appliance manufacturers to train a machine learning model based on customers' data. Then, manufacturers can predict customers' requirements and consumption behaviors in the future. The working flow of the system includes two stages: in the first stage, customers train the initial model provided by the manufacturer using both the mobile phone and the mobile edge computing (MEC) server. Customers collect data from various home appliances using phones, and then they download and train the initial model with their local data. After deriving local models, customers sign on their models and send them to the blockchain. In case customers or manufacturers are malicious, we use the blockchain to replace the centralized aggregator in the traditional FL system. Since records on the blockchain are untampered, malicious customers or manufacturers' activities are traceable. In the second stage, manufacturers select customers or organizations as miners for calculating the averaged model using received models from customers. By the end of the crowdsourcing task, one of the miners, who is selected as the temporary leader, uploads the model to the blockchain. To protect customers' privacy and improve the test accuracy, we enforce differential privacy on the extracted features and propose a new normalization technique. We experimentally demonstrate that our normalization technique outperforms batch normalization when features are under differential privacy protection. In addition, to attract more customers to participate in the crowdsourcing FL task, we design an incentive mechanism to award participants.Comment: This paper appears in IEEE Internet of Things Journal (IoT-J

Spatial and temporal variability in net primary production (NPP) of alpine grassland on Tibetan Plateau from 1982 to 2009

Abstract HKT-ISTP 2013 B