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Selenoprotein P (SeP; encoded by SELENOP in humans, Selenop in rodents) is a hepatokine that is upregulated in the liver of humans with type 2 diabetes. Excess SeP contributes to the onset of insulin resistance and various type 2 diabetes-related complications. We have previously reported that the long-chain saturated fatty acid, palmitic acid, upregulates Selenop expression, whereas the polyunsaturated fatty acids (PUFAs) downregulate it in hepatocytes. However, the effect of medium-chain fatty acids (MCFAs) on Selenop is unknown. Here we report novel mechanisms that underlie the lauric acid-mediated Selenop gene regulation in hepatocytes. Lauric acid upregulated Selenop expression in Hepa1-6 hepatocytes and mice liver. A luciferase promoter assay and computational analysis of transcription factor-binding sites identified the hepatic nuclear factor 4α (HNF4α) binding site in the SELENOP promoter. A chromatin immunoprecipitation (ChIP) assay showed that lauric acid increased the binding of HNF4α to the SELENOP promoter. The knockdown of Hnf4α using siRNA canceled the upregulation of lauric acid-induced Selenop. Thus, the lauric acid-induced impairment of Akt phosphorylation brought about by insulin was rescued by the knockdown of either Hnf4α or Selenop. These results provide new insights into the regulation of SeP by fatty acids and suggest that SeP may mediate MCFA-induced hepatic insulin signal reduction.

Muscle atrophy is the cause and consequence of obesity. Proteasome dysfunction mediates obesity-induced endoplasmic reticulum (ER) stress and insulin resistance in the liver and adipose tissues. However, obesity-associated regulation of proteasome function and its role in the skeletal muscles remains underinvestigated. Here, we established skeletal muscle-specific 20S proteasome assembly chaperone-1 (PAC1) knockout (mPAC1KO) mice. A high-fat diet (HFD) activated proteasome function by ∼8-fold in the skeletal muscles, which was reduced by 50% in mPAC1KO mice. mPAC1KO induced unfolded protein responses in the skeletal muscles, which were reduced by HFD. Although the skeletal muscle mass and functions were not different between the genotypes, genes involved in the ubiquitin proteasome complex, immune response, endoplasmic stress, and myogenesis were coordinately upregulated in the skeletal muscles of mPAC1KO mice. Therefore, we introduced an immobilization-induced muscle atrophy model in obesity by combining HFD and immobilization. mPAC1KO downregulated atrogin-1 and MuRF1, together with their upstream Foxo1 and Klf15, and protected against disused skeletal muscle mass reduction. In conclusion, obesity elevates proteasome functions in the skeletal muscles. PAC1 deficiency protects mice from immobilization-induced muscle atrophy in obesity. These findings suggest obesity-induced proteasome activation as a possible therapeutic target for immobilization-induced muscle atrophy.

We report for the first time using zinc hydroxyfluoride (ZnOHF) for efficient NO2 gas detection. The prepared ZnOHF had a unique flower-like architecture self-assembled by nanorods with a diameter of 150 nm and length of 2-3 μm. The sensing performance toward NO2 detection indicated that the prepared ZnOHF exhibited high response (82.71), short response/recovery time (13 s/35 s) to 10 ppm of NO2, and excellent selectivity at 200 °C, greatly outperforming the ZnO raw material. ZnOHF could work in a wide detection window ranging from 100 ppb to 50 ppm, implying its practical application prospects in both industry and daily life. The excellent sensing behavior of ZnOHF originated mainly from the negligible oxygen ions adsorbed on the material surface, which was caused by the higher work function of ZnOHF. Therefore, almost all conduction band electrons can be used in the NO2 gas sensing.

Cyclosporine A (CsA) is a worldwide applied immunosuppressant for preventing graft rejection and autoimmune diseases. However, CsA elevates oxidative stress leading to liver injuries. The present study aimed to clarify the mechanisms underlying the CsA-mediated oxidative stress. Among the redox proteins, CsA concentration-dependently downregulated

Selenoprotein P is upregulated in type 2 diabetes, causing insulin and exercise resistance. We have previously reported that eicosapentaenoic acid (EPA) negatively regulates Selenop expression by suppressing Srebf1 in H4IIEC3 hepatocytes. However, EPA downregulated Srebf1 long before downregulating Selenop. Here, we report additional novel mechanisms for the Selenop gene regulation by EPA. EPA upregulated Foxo1 mRNA expression, which was canceled with the ERK1/2 inhibitor, but not with the PKA inhibitor. Foxo1 knockdown by siRNA initiated early suppression of Selenop, but not Srebf1, by EPA. However, EPA did not affect the nuclear translocation of the FoxO1 protein. Neither ERK1/2 nor PKA inhibitor affected FoxO1 nuclear translocation. In summary, FoxO1 knockdown accelerates the EPA-mediated Selenop downregulation independent of SREBP-1c in hepatocytes. EPA upregulates Foxo1 mRNA via the ERK1/2 pathway without altering its protein and nuclear translocation. These findings suggest redundant and conflicting transcriptional networks in the lipid-induced redox regulation.

MgAl2O4 ceramics with high porosity and performance were fabricated via foam gel casting at 1673–1823 K using MgAl2O4 as the raw material and a small amount of V2O5 (0.25 wt%) as a sintering additive. The variations in the physical properties of the final porous MgAl2O4 samples at ambient temperature demonstrated that their flexural, compressive, and specific strength increased with the addition of a small amount of V2O5 as a sintering aid. However, the thermal insulation properties of the as-fabricated MgAl2O4 ceramics exhibited an inverse tendency. A porous MgAl2O4 ceramic containing 0.25 wt% of V2O5 and fired at 1823 K had flexural and specific strength values of 4.2 MPa and 14.0 (MPa cm3)/g, respectively, representing improvements over those reported in the literature at a similar porosity (72.0%). Moreover, a low thermal conductivity of approximately 0.24 W/(m·K) was measured at 473 K, which may be attributed to the relatively high porosity and high proportion of small pores with diameters less than 50 μm.

Pyrroline-5-carboxylate reductase 1 (PYCR1) upregulation contributes to the progression of gastric cancer (GC) and indicates poor survival. However, PYCR1 expression profile in GC subtypes and the mechanism behind its upregulation are not well-studied.PYCR1 expression profiles in GC subtypes and different stages of gastric carcinogenesis were assessed in different GC cohorts. Genetic alterations and epigenetic modulation in PYCR1 regulation were further investigated using bioinformatics analysis and in vitro experiments.PYCR1 expression was significantly higher in intestinal-type GC and associated molecular subtypes in TCGA and ACRG GC cohorts. During the cascade of intestinal-type GC, PYCR1 was continuously increased from normal gastric tissues through to atrophic gastritis, to intraepithelial neoplasia, and to GC. Copy number alterations in PYCR1 were associated with PYCR1 transcript expression. One CpG island was observed in PYCR1 promoter region, and the hypomethylation occurred at this region could contribute to PYCR1 transcriptional activation in GC. Besides, H3K27ac combination was found in PYCR1 promoter, and acetyltransferase p300 induced H3K27ac could promote PYCR1 expression in GC.PYCR1 expression varies across GC subtypes, with intestinal-type GC and associated molecular subtypes having the highest expression. Hypomethylation at CpG sites and p300-induced H3K27ac modification within PYCR1 promoter could contribute to maintaining PYCR1 overexpression in GC. These results provide us with a new insight into epigenetic modulation in mitochondrial proline metabolism.

The Fiber Bragg grating sensor (FBG) is a kind of optical fiber sensor, compared with the electric sensor, it has many irreplaceable advantages for aerospace applications. The challenge of FBG for cryogenic application is how to increase the sensitivity of bare FBG and reduce nonlinear error. Two different thermosetting epoxy materials were studied to recoat bare FBG and presented a specific packaging method for thermosetting coatings. The verification of the accuracy of the model that is used to describe the FBG coated with thermosetting polymers by comparing the calculated results with the warming-up experiment conducted in the temperature range of 120K-328K using epoxy coated FBGs and bare FBG has been conducted. The results show a great improvement of sensitivity and good linearity, and the model can also be used to predict the characteristics of FBG coated with epoxy resins at cryogenic temperature and determine the stability of the epoxy.

Background Bismuth-based drugs are used to treat Helicobacter pylori infection; however, the antibacterial activity of bismuth, especially against H. pylori, has not been fully elucidated. In this study, the mechanisms by which bismuth exerts its detrimental effects on H. pylori were evaluated. Methods Six H. pylori strains isolated from different patients were cultured with or without bismuth; proteins and metabolites differentially expressed in these two sets of bacteria were detected via data independent acquisition proteomic and gas chromatography-mass spectrometry metabolic approaches, respectively. Gene ontology functional analysis and Kyoto Encyclopedia of Genes and Genomes database were used to identity pathway enrichment. Results Bismuth inhibited H. pylori growth in vitro via the following mechanisms: downregulation of virulence proteins CagA and VacA; disruption of flagella assembly responsible for bacterial colonization; and inhibition of antioxidant enzymes, including catalase, catalase-related peroxidase, and superoxide dismutase. Diverse metabolic pathways related to growth and RNA translation in H. pylori were disrupted by bismuth. Bismuth treatment impaired many biological processes in H. pylori, including antioxidant response and purine, pyrimidine, amino acid, and carbon metabolism. Conclusions The findings of this study suggest that motility, virulence factors CagA and VacA, antioxidant defense system, and many important metabolic pathways associated with bacterial growth, including nucleotide and amino acid metabolism and translation in H. pylori, are inhibited by bismuth. This study provides novel insights into the mechanism by which bismuth eradicates H. pylori upon being incorporated into quadruple therapy.

We report for the first time using zinc hydroxyfluoride (ZnOHF) for efficient NO

Network representation learning (NRL) technique has been successfully adopted in various data mining and machine learning applications. Random walk based NRL is one popular paradigm, which uses a set of random walks to capture the network structural information, and then employs word2vec models to learn the low-dimensional representations. However, until now there is lack of a framework, which unifies existing random walk based NRL models and supports to efficiently learn from large networks. The main obstacle comes from the diverse random walk models and the inefficient sampling method for the random walk generation. In this paper, we first introduce a new and efficient edge sampler based on Metropolis-Hastings sampling technique, and theoretically show the convergence property of the edge sampler to arbitrary discrete probability distributions. Then we propose a random walk model abstraction, in which users can easily define different transition probability by specifying dynamic edge weights and random walk states. The abstraction is efficiently supported by our edge sampler, since our sampler can draw samples from unnormalized probability distribution in constant time complexity. Finally, with the new edge sampler and random walk model abstraction, we carefully implement a scalable NRL framework called UniNet. We conduct comprehensive experiments with five random walk based NRL models over eleven real-world datasets, and the results clearly demonstrate the efficiency of UniNet over billion-edge networks.

To establish accurate finite element (FE) model of bolted joint structures of aeroengine stator system (casings), this work implements the parametric FE modeling and updating of bolted joints of aeroengine stator system with multi-characteristic responses (multi-object). Firstly, the parametric FE modeling approach of bolted joint structure was developed based on the thin layer element method. And then the FE model updating thought of aeroengine stator system was developed based on the probabilistic analysis method. Finally, the parametric modeling and updating of the bolted joints of aeroengine stator system with multi-characteristic responses was completed by the optimization iteration calculation of objective function based on the proposed methods and the static stiffness testing data. Through the parametric modeling of bolted joint structures based on the thin layer method, the complexity of FE model of aeroengine casings with many bolted joint structures is reduced. As shown in the FE model updating of casings with multi-characteristic responses analysis, the static stiffness from the updated model are very close to the test data, in which the maximum relative error decreases to 3.9% from 30.52% and the others are less than 3%, so that the design precision of aeroengine stator system with the many and wide variety of bolted joints gets a great improvement. Moreover, the proposed methods of parametric modeling and model updating for multi-characteristic responses are validated to be effective in the simulation and equivalent of the mechanical characteristics of bolted joints in complex systems like aeroengine stator system.

A new dynamic modeling method called the improved thin-layer element method is proposed to apply to the aero-engine bolted joints. The thin-layer elements are partitioned based on the interface contact stress distribution. In addition, the material parameters of the partitioned thin-layer elements are determined by the bolted joints stiffness technique and the fractal contact theory without the experimental results, which allows the engineer to estimate the dynamic characteristics of whole structure before the physical prototype is available. First, the modeling principles of the improved thin-layer element method are studied and the bolted joints stiffness is analyzed. Next, the material parameters of the partitioned thin-layer elements are determined on the basis of the interface contact stress distribution characteristics of the bolted joints. Finally, this method is applied to the simulative casing bolted joints structure and the results are compared with the experimental results in order to verify the proposed method. The results indicate that the improved thin-layer element method is more accurate than the thin-layer elements method, and the material parameters of the partitioned thin-layer elements can be expressed by the structural parameters of the aero-engine bolted joints without updating based on the experiment.

Many face recognition tasks encounter the problem of having only one sample for each subject, which is known as the single sample per person (SSPP) problem. To tackle the problem, we propose a strategy of sparse representation with dense matching method. First, an external training set is used to form an intra-class variation dictionary. Then, noting that captured facial features will vary with facial expression and pose, dense matching is applied to preprocess facial patches. This offers a courtesy way to overcome this obstacle and improves coherence of facial features. Finally, we make decision by extended sparse representation based classification (ESRC) based on the learned dictionary. Experiments on AR, Extended Y ale B, CMU PIE and FERET datasets demonstrate that our proposed method outperforms many state-of-the-art methods on face recognition with SSPP.

A method of selecting master degrees of freedom (DOFs) for rotating substructure is presented in this paper to obtain reduced 3D rotor models. Fixed modes of the substructure below thrice the operating frequency are analyzed. According to each mode shape, the DOFs at where main kinetic energy locates are selected as master DOFs to decrease missing of dynamic coupling. Additional DOFs may be selected based on traditional substructure method. In the stationary reference frame, frequency-dependent gyroscopic effects can be included as damping matrices changing with spin speed. Besides, by selecting appropriate substructure, localized damping and key parts of the rotor for analysis can be kept the same as the original model. A reduced model of a high pressure rotor amply demonstrated the capability of the method in reducing the model size and increasing the computational efficiency with less than two percent error.Copyright © 2014 by ASME