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Metformin is still being investigated due to its potential use as a therapeutic agent for managing overweight or obesity. However, the underlying mechanisms are not fully understood. Inhibiting the adipogenesis of adipocyte precursors may be a new therapeutic opportunity for obesity treatments. It is still not fully elucidated whether adipogenesis is also involved in the weight loss mechanisms by metformin. We therefore used adipose-derived stem cells (ADSCs) from inguinal and epididymal fat pads to investigate the effects and mechanisms of metformin on adipogenesis in vitro. Our results demonstrate the similar effect of metformin inhibition on lipid accumulation, lipid droplets fusion, and growth in adipose-derived stem cells from epididymal fat pads (Epi-ADSCs) and adipose-derived stem cells from inguinal fat pads (Ing-ADSCs) cultures. We identified that cell death-inducing DFFA-like effector c (Cidec), Perilipin1, and ras-related protein 8a (Rab8a) expression increased ADSCs differentiation. In addition, we found that metformin inhibits lipid droplets fusion and growth by decreasing the expression of Cidec, Perilipin1, and Rab8a. Activation of AMPK pathway signaling in part involves metformin inhibition on Cidec, Perilipin1, and Rab8a expression. Collectively, our study reveals that metformin inhibits lipid storage, fusion, and growth of lipid droplets via reduction in Cidec and its regulatory factors in ADSCs cultures. Our study supports the development of clinical trials on metformin-based therapy for patients with overweight and obesity. [ABSTRACT FROM AUTHOR]

Simple Summary: Mycoplasma gallisepticum (MG) can induce chronic respiratory disease (CRD) in chickens. Glycyrrhizic acid (GA) is the major ingredient of licorice and shows excellent anti-pathogenic microorganism and anti-inflammatory properties. Based on above, this study has evaluated the therapeutic effects and safety of GA in MG-infected broilers. Study results showed that GA could inhibit the proliferation of MG in vitro and expression of MG adhesion protein (pMGA1.2) in broiler lungs. GA restored production performances and attenuated MG-induced organ damage and abnormal biochemical indicator changes in MG-infected broilers. In conclusion, GA displayed significant therapeutic efficacy regarding MG infection and had no adverse effects on broilers (100 mg/kg/d). This study was conducted to evaluate the therapeutic effects and safety of GA in MG-infected broilers. Our results showed that the minimum inhibitory concentration of GA was 31.25 μg/mL. Moreover, GA inhibited the expression of MG adhesion protein (pMGA1.2) in the broilers' lungs. GA treatment clearly decreased the morbidity of CRD and mortality in the MG-infected broilers. Compared with the model group, GA treatment significantly decreased gross air sac lesion scores and increased average weight gain and feed conversion rate in the MG-infected broilers. Histopathological examination showed GA treatment attenuated MG-induced trachea, immune organ and liver damage in the broilers. Moreover, GA treatment alone did not induce abnormal morphological changes in these organs in the healthy broilers. Compared with the model group, serum biochemical results showed GA treatment significantly decreased the content of total protein, albumin, globulin, alanine aminotransferase, aspartate aminotransferase, total bilirubin, creatinine, uric acid, total cholesterol, and increased the content of albumin/globulin, alkaline phosphatase, apolipoprotein B and apolipoprotein A-I. In conclusion, GA displayed a significant therapeutic efficacy regarding MG infection and had no adverse effects on the broilers (100 mg/kg/d). [ABSTRACT FROM AUTHOR]

The lateral organ boundary domain (LBD) gene is a plant-specific transcription factor that plays a crucial role in plant growth and development, including the development of lateral vegetative organs such as leaf and root development, as well as floral organs such as sepal, petal, and pollen development. Passion fruit is a tropical fruit with important agricultural, economic and ornamental value. However, there is no systematic research report available on the LBD gene family of passion fruit. In this study, a genome-wide analysis of passion fruit LBD genes identified 33 PeLBDs that were unevenly distributed across nine chromosomes. According to phylogenetic and gene structure analysis, PeLBDs were divided into two categories: Class I (27) and Class II (6). Homologous protein modeling results showed that the gene members of the two subfamilies were structurally and functionally similar. Cis-acting element and target gene prediction analysis suggested that PeLBDs might participate in various biological processes by regulating diverse target genes involved in growth and development, metabolism, hormones and stress response. Collinearity analysis indicated that the expansion of the PeLBD gene family likely took place mainly by segmental duplication, and some duplicated gene pairs such as PeLBD13/15 might show functional redundancy, while most duplicated gene pairs such as PeLBD8/12 showed different expression profiles indicating their functional diversification. After filtering low expressed genes, all Class Id PeLBDs were more highly expressed during pollen development. At the same, all Class Ic and many other PeLBDs were relatively highly expressed during ovule development, similar with their homologous LBD genes in Arabidopsis, indicating their potential regulatory roles in reproductive tissue development in passion fruit. PeLBDs that were highly expressed in floral tissues were also expressed at a higher level in tendrils with some differences, indicating the close relationships of tendrils to floral tissues. Some genes such as PeLBD23/25 might be simultaneously related to floral development and leaf early formation in passion fruit, while other PeLBDs showed a strong tissue-specific expression. For example, PeLBD17/27/29 were specifically expressed in floral tissues, while PeLBD11 were only highly expressed in fruit, suggesting their specific function in the development of certain tissues. A qRT-PCR was conducted to verify the expression levels of six PeLBDs in different tissues. Our analysis provides a basis for the functional analysis of LBD genes and new insights into their regulatory roles in floral and vegetative tissue development. [ABSTRACT FROM AUTHOR]

A quad-element multiple-input-multiple-output (MIMO) antenna with ultra-wideband (UWB) performance is presented in this paper. The MIMO antenna consists of four orthogonally arranged microstrip line-fed hexagonal monopole radiators and a modified ground plane. In addition, E-shaped and G-shaped stubs are added to the radiator to achieve additional resonances at 1.5 GHz and 2.45 GHz. The reliability of the antenna in the automotive environment is investigated, with housing effects taken into account. The housing effects show that the antenna performs consistently even in the presence of a large metal object. The proposed MIMO antenna has potential for various automotive applications, including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-everything (V2X), intelligent transport system (ITS), automatic vehicle identifier, and RFID-based electronic toll collection. [ABSTRACT FROM AUTHOR]

Here, 22-carbon tricarboxylic acid (C22TA) and its ester (C22TAE) were prepared via the Diels–Alder reaction of polyunsaturated fatty acids (PUFAs) and their esters (PUFAEs) as dienes with fumaric acid (FA) and dimethyl fumarate (DF) as dienophiles, respectively. The role of an iodine catalyst for the synthesis of C22TA and C22TAE in the Diels–Alder type reaction was investigated using a spectroscopic approach. The chemical structures of the products were characterized using proton nuclear magnetic resonance (1H-NMR) and electrospray ionization mass spectrometry (ESI-MS) analysis. Results showed that nonconjugated dienes can react with dienophiles through a Diels–Alder reaction with an iodine catalyst, and that iodine transformed the nonconjugated double bonds of dienes into conjugated double bonds via a radical process. DF was more favorable for the Diels–Alder reaction than FA. This was mainly because the dienophile DF contained an electron-withdrawing substituent, which reduced the highest and lowest occupied molecular orbital (HOMO–LUMO) energy gap and accelerated the Diels–Alder reaction. By transforming nonconjugated double bonds into conjugated double bonds, iodine as a Lewis acid increased the electron-withdrawing effect of the carbonyl group on the carbon–carbon double bond and reduced the energy difference between the HOMO of diene and the LUMO of dienophile, thus facilitating the Diels–Alder reaction. [ABSTRACT FROM AUTHOR]

The aircraft auxiliary power unit (APU) is responsible for environmental control in the cabin and the main engines starting the aircraft. The prediction of its performance sensing data is significant for condition-based maintenance. As a complex system, its performance sensing data have a typically nonlinear feature. In order to monitor this process, a model with strong nonlinear fitting ability needs to be formulated. A neural network has advantages of solving a nonlinear problem. Compared with the traditional back propagation neural network algorithm, an extreme learning machine (ELM) has features of a faster learning speed and better generalization performance. To enhance the training of the neural network with a back propagation algorithm, an ELM is employed to predict the performance sensing data of the APU in this study. However, the randomly generated weights and thresholds of the ELM often may result in unstable prediction results. To address this problem, a restricted Boltzmann machine (RBM) is utilized to optimize the ELM. In this way, a stable performance parameter prediction model of the APU can be obtained and better performance parameter prediction results can be achieved. The proposed method is evaluated by the real APU sensing data of China Southern Airlines Company Limited Shenyang Maintenance Base. Experimental results show that the optimized ELM with an RBM is more stable and can obtain more accurate prediction results. [ABSTRACT FROM AUTHOR]

This article presents a quad-band multiple-input-multiple-output (MIMO) antenna for the Internet of Things (IoT) applications. The proposed antenna consists of four quarter-wavelength asymmetrical meandered radiators, microstrip feed lines, and modified ground planes. The antenna elements are arranged in a chiral pattern to improve isolation between them, with two radiators and two ground planes placed on the front side of the substrate and the other two on the back side. The MIMO antenna has an operating bandwidth (S11 ≤ −10 dB) of 1.76–1.84 GHz, 2.37–2.56 GHz, 3.23–3.68 GHz, and 5.34–5.84 GHz, covering GSM, WLAN, WiMAX, and 5G frequency bands. The isolation between the radiating elements is greater than 18 dB in the operating bands. The peak gain of the antenna is 3.6 dBi, and the envelope correlation coefficient (ECC) is less than 0.04. Furthermore, the proposed antenna is validated for IoT-based smart home (SH) applications. The prototype MIMO antenna is integrated with a commercially available ZigBee device, and the measured values are found to be consistent with the expected results. The proposed MIMO antenna could be a good candidate for IoT systems/modules due to its low profile, compact size, lightweight, and easy integration with wireless communication devices. [ABSTRACT FROM AUTHOR]

A steel-batten ribbed cable dome structural system is proposed. By replacing the upper flexible cables with semi-rigid steel battens, rigid roofing materials were conveniently installed overhead via non-bracket or less-bracket technology. Additionally, an 8 m diameter test model was designed, and a 'ω' shaped less-bracket consequent hoist-dragging system was adopted. Finally, the test model was tested under symmetric and asymmetric uniform loading arrangements, while a finite element model was established to verify the test values. The results indicate that the measured values are basically consistent with the finite element values. In the early steps of hoisting and dragging, the structure establishes a prestress, accumulates stiffness, and found its internal force balance, while the entire structure keeps a "ω" shape to guarantee stability. As the internal forces of the components increase, the structure turns from "ω" to "m" and finally reached its designed shape. With increasing symmetric uniform load, the internal forces of the cables decrease, the bending stresses of the steel battens increase, and the steel battens remain in the elastic stage. Under an asymmetric uniform load, the high loaded area is displaced downward, and the low loaded area behaves upward, twisting the overall structure. [ABSTRACT FROM AUTHOR]

Simple Summary: The inv(16)/t(16;16) AML is a disease that is considered relatively easy and straightforward to be diagnosed in the clinical laboratories. Up to date, CBFB FISH and/or CBFB-MYH11 RT-PCR are still the major diagnostic assays utilized in the clinical laboratories. However, incidental CBFB FISH findings and their implication in clinical laboratory diagnostics and management, especially in the era of next-generation sequencing (NGS)-based methods, have not been systemically investigated. In this study, we systemically studied over 1600 AML cases tested with CBFB FISH. Over 5% of cases with a confirmed CBFB rearrangement were challenging, including those with discrepant FISH and RT-PCR results and/or atypical FISH findings. Meanwhile, atypical FISH findings usually indicate additional chromosome 16 aberrations (AC16As) overlooked by other methods including RT-PCR and almost all NGS-based methods if following the published parameters. The information revealed in this study will be useful for further workup and interpreting atypical CBFB FISH findings and confirmation of inv(16)/t(16;16) AML diagnosis and related treatment, as well as selection of samples to better validate NGS-based new diagnostic methods. Fluorescence in situ hybridization (FISH) is a confirmatory test to establish a diagnosis of inv(16)/t(16;16) AML. However, incidental findings and their clinical diagnostic implication have not been systemically studied. We studied 1629 CBFB FISH cases performed in our institution, 262 (16.1%), 1234 (75.7%), and 133 (8.2%) were reported as positive, normal, and abnormal, respectively. The last included CBFB copy number changes (n = 120) and atypical findings such as 3′CBFB deletion (n = 11), 5′CBFB deletion (n = 1), and 5′CBFB gain (n = 1). Correlating with CBFB-MYH11 RT-PCR results, totally 271 CBFB rearrangement cases were identified, including five with discrepancies between FISH and RT-PCR due to new partner genes (n = 3), insertion (n = 1), or rare CBFB-MYH11 variant (n = 1) and eight with 3′CBFB deletion. All cases with atypical findings and/or discrepancies presented clinical diagnostic challenges. Correlating FISH signal patterns and karyotypes, additional chromosome 16 aberrations (AC16As) show impacts on the re-definition of a complex karyotype and prognostic prediction. The CBFB rearrangement but not all AC16As will be detected by NGS-based methods. Therefore, FISH testing is currently still needed to provide a quick and straightforward confirmatory inv(16)/t(16;16) AML diagnosis and additional information related to clinical management. [ABSTRACT FROM AUTHOR]

Most of the existing laser welding process monitoring technologies focus on the detection of post-engineering defects, but in the mass production of electronic equipment, such as laser welding metal plates, the real-time identification of defect detection has more important practical significance. The data set of laser welding process is often difficult to build and there is not enough experimental data, which hinder the applications of the data-driven laser welding defect detection method. In this paper, an intelligent welding defect diagnosis method based on auxiliary classifier generative adversarial networks (ACGAN) has been proposed. Firstly, a ten-class dataset consisting of 6467 samples, was constructed, which originate from the optical and thermal sensory parameters in the welding process. A new structured ACGAN network model is proposed to generate fake data similar to the true defect feature distributions. In addition, in order to make the difference between different defects categories more obvious after data expansion, a data filtering and data purification scheme was proposed based on ensemble learning and an SVM (support vector machine), which is used to filter the bad generated data. In the experiments, the classification accuracy can reach 96.83% and 85.13%, for the CNN (convolutional neural network) algorithm model and ACGAN model, respectively. However, the accuracy can further improve to 97.86% and 98.37% for the fusion models of ACGAN-CNN and ACGAN-SVM-CNN models, respectively. The results show that ACGAN can not only be used as an algorithm model for classification, but also be used to achieve superior real-time classification and recognition through data enhancement and multi-model fusion. [ABSTRACT FROM AUTHOR]

Excess sulfur has become a global problem in petrochemical industry. Inexpensive and easily available cottonseed oil (CSO) is still underutilized. To resolve these issues, bio-based polysulfide composites were prepared via inverse vulcanization of sulfur and CSO. The density of polysulfide composites was adjusted by fillers. The results showed that Elm and cattail as the fillers had no effects on the thermal properties and chemical structures of polysulfide composites. However, the morphologies of polysulfide composites were significantly influenced by the fillers. Different types and amounts of fillers produced significantly different holes and folds in the composites. The fillers were embedded in polysulfide composites by physical filling. This study provides an alternative and promising approach for preparing affordable density-adjustable bio-based polysulfide composite. [ABSTRACT FROM AUTHOR]

Glutamine synthetase (GS), the key enzyme in plant nitrogen assimilation, is strictly regulated at multiple levels, but the most relevant reports focus on the mRNA level. Using specific antibodies as probes, the effects of nitrogen on the expression and localization of individual wheat GS (TaGS) isoforms were studied. In addition to TaGS2, TaGS1;1 with high affinity to substrate and TaGS1;3 with high catalytic activity were also localized in mesophyll, and may participate in cytoplasmic assimilation of ammonium (NH4+) released from photorespiration or absorbed by roots; TaGS1;2 was localized in xylem of leaves. In roots, although there were hundreds of times more TaGS1;1 than TaGS1;2 transcripts, the amount of TaGS1;1 subunit was not higher than that of TaGS1;2; NH4+ inhibited TaGS1;1 expression but stimulated TaGS1;3 expression. In root tips, nitrate stimulated TaGS1;1, TaGS1;3, and TaGS2 expression in meristem, while NH4+ promoted tissue differentiation and TaGS1;2 expression in endodermis and vascular tissue. Only TaGS1;2 was located in vascular tissue of leaves and roots, and was activated by glutamine, suggesting a role in nitrogen transport. TaGS1;3 was induced by NH4+ in root endodermis and mesophyll, suggesting a function in relieving NH4+ toxicity. Thus, TaGS isoforms play distinct roles in nitrogen assimilation for their different kinetic properties, tissue locations, and response to nitrogen regimes. [ABSTRACT FROM AUTHOR]

Traditional methods for identifying naming ignore the correlation between named entities and lose hierarchical structural information between the named entities in a given text. Although traditional named-entity methods are effective for conventional datasets that have simple structures, they are not as effective for sports texts. This paper proposes a Chinese sports text named-entity recognition method based on a character graph convolutional neural network (Char GCN) with a self-attention mechanism model. In this method, each Chinese character in the sports text is regarded as a node. The edge between the nodes is constructed using a similar character position and the character feature of the named-entity in the sports text. The internal structural information of the entity is extracted using a character map convolutional neural network. The hierarchical semantic information of the sports text is captured by the self-attention model to enhance the relationship between the named entities and capture the relevance and dependency between the characters. The conditional random fields classification function can accurately identify the named entities in the Chinese sports text. The results conducted on four datasets demonstrate that the proposed method improves the F-Score values significantly to 92.51%, 91.91%, 93.98%, and 95.01%, respectively, in comparison to the traditional naming methods. [ABSTRACT FROM AUTHOR]

The application of trimellitate (TMT) in the lubricating oil industry was seriously restricted because of its low viscosity index. In the work reported here, polycaprolactone (PCL) soft chain was embedded into the structure of TMT in order to improve the viscosity index. Characterization of the polymers was done by proton nuclear magnetic resonance (1H-NMR), Fourier transform infrared spectroscopy (FT-IR) and thermogravimetric analysis (TG). Results supported our design and were consistent with the target product structure. Performance of the prepared materials was evaluated by standard ASTM methods. Noticeably, the viscosity index of the modified TMT increased from 8 to above 100, which greatly improved its viscosity-temperature performance. As the initiator, tetrabutyl titanate (TBT) can not only complete the ring-opening polymerization of caprolactam (ε-CL) at room temperature, but also generate nano-TiO2 by-products with excellent anti-wear properties during the synthesis. Characterization of the nano-TiO2 was done by scanning electron microscopy (SEM), FT-IR, TG and X-ray diffractometry (XRD). The friction and wear tests were conducted on a four-ball friction tester and the surface morphologies of worn surfaces were investigated by SEM. The experimental results clearly showed that the modified TMT showed better viscosity index and thermal stability as compared to the unmodified one. The modified nano-TMT base oil features excellent lubricant performance with good viscosity–temperature properties, thermal stability and anti-wear properties. [ABSTRACT FROM AUTHOR]

Distributed multiple input multiple output (MIMO) radar has attracted much attention for its improved detection and estimation performance as well as enhanced electronic counter-counter measures (ECCM) ability. To protect the target from being detected and tracked by such radar, we consider a barrage jamming strategy towards a distributed MIMO. We first derive the Cramer–Rao bound (CRB) of target parameters estimation using a distributed MIMO under barrage jamming environments. We then set maximizing the CRB as the criterion for jamming resource allocation, aiming at degrading the accuracy of target parameters estimation. Due to the non-convexity of the CRB maximizing problem, particle swarm optimization is used to solve the problem. Simulation results demonstrate the advantages of the proposed strategy over traditional jamming methods. [ABSTRACT FROM AUTHOR]