Search

Graphite, a key anode material in lithium-ion batteries, primarily relies on the Acheson graphitization furnace (AGF) for production. This research focuses on the power supply module of the AGF, particularly the electrodes and their power transmission clamps. A three-dimensional transient electric-thermal-fluid coupling model was developed to numerically analyze the temperature and electric field distributions during operation. The study revealed that heat conduction through furnace electrodes dominates temperature rise. Notably, clamping plates within transmission clamps exhibit high temperatures and gradients, posing a thermal failure risk. Efficient cooling plate design with liquid-cooled channels is crucial for temperature control. Additionally, maintaining high electrode temperatures reduces resistivity, lowering power consumption in the power supply module. This study provides insights into optimizing AGF power supply module design, emphasizing the importance of effective cooling strategies for clamping plates and the benefits of maintaining elevated electrode temperatures for energy efficiency. [ABSTRACT FROM AUTHOR]

Crop diseases and pests are important factors restricting agricultural production. Traditional pest detection methods are mainly targeted at a single pest species, which is difficult to meet the needs of multi-target identification and rapid response in real scenes. Therefore, this paper improves the YOLOv8n model for efficient multi-target pest detection. Two feature enhancement modules, EMSFEM and AFEM_SIE, are proposed in this paper. The EMSFEM module enriches the model's receptive field through the combination of multi-scale asymmetric convolution kernel and different expansion rates and can better extract the width, height, texture, and edge information of the target. The AFEM_SIE module captures the similarities and differences between upper and lower features through spatial information exchange and enhances feature representation through inter-feature information exchange. In addition, an improved feature fusion operation, Concat_Weighting, is proposed on the basis of Concat. The module uses the learned weights to carry out channel weighting and feature graph weighting for input features, which realizes more flexible and effective feature fusion. The results of experiments conducted on the publicly available large-scale crop pest and disease dataset IP102 show that the performance of the AEC-YOLOv8n model is significantly improved compared with the original YOLOv8n model, with mAP50 increased by 8.9%, accuracy increased by 6.8%, and recall rate increased by 6.3%. The AEC-YOLOv8n model proposed in this study can effectively identify and deal with a variety of crop pests and has achieved the best detection accuracy on the IP102 dataset, which has high application value. [ABSTRACT FROM AUTHOR]

This paper uses an enhanced sparrow search algorithm (SSA) to optimise the support vector machine (SVM) by considering the emission of air pollution sources as the independent variable. Consequently, it establishes a PM2.5 concentration prediction model to improve the prediction accuracy of fine particulate matter PM2.5 concentration. First, the principal component analysis is applied to extract key variables affecting air quality from high-dimensional air data to train the model while removing unnecessary redundant variables. Adaptive dynamic weight factors are introduced to balance the global and local search capabilities and accelerate the convergence of the SSA. Second, the SSA–SVM prediction model is defined using the optimised SSA to continuously update the network parameters and achieve the rapid prediction of atmospheric PM2.5 concentration. The findings demonstrate that the optimised SSA–SVM prediction method can quickly predict atmospheric PM2.5 concentration, using the cyclic search method for the best solution to update the model, proving the method's effectiveness. Compared with other methods, this approach has a small prediction error, a high prediction accuracy and better practical value. [ABSTRACT FROM AUTHOR]

Moringa oleifera leaves are an inexpensive substitute for staple foods. Despite limited data, Moringa oleifera leaf protein (Mo-Pr) may be allergenic in BALB/c mice. In mouse models and allergic patients, dendritic cells (DCs) may be involved in food allergy. In addition, some allergens, including food allergens, can directly activate DCs and induce Th2 polarization. We investigated whether Mo-Pr can modulate the functional profile of murine bone marrow-derived dendritic cells (BMDCs) in vitro. BMDCs were obtained from mouse bone marrow cultured with granulocyte–macrophage colony-stimulating factor (GM-CSF) for 7 days and then treated with lipopolysaccharide (LPS) or Mo-Pr. BMDC phenotypes were evaluated via flow cytometry, cytokine production was assessed using ELISA, the expression of key genes was studied using qRT-PCR, the effects on T-cell differentiation were investigated using mixed lymphocyte reaction (MLR), and transcriptional changes in BMDCs were investigated using RNA-Seq. Mo-Pr-specific IgE was investigated in recipient serum after BMDC transfer. Mo-Pr treatment significantly induced BMDC maturation, increased the expression of CD80/86 and MHC II, resulted in the production of IL-12 and TNF-α, and induced T-cell differentiation. Mo-Pr treatment stimulated BMDCs' expression of the Th2 promoters OX40L and TIM-4, induced the production of the Th2-type chemokines CCL22 and CCL17, and decreased the Th1/Th2 ratio in vitro. Healthy recipients of Mo-Pr-treated BMDCs produced Mo-Pr-specific IgE. [ABSTRACT FROM AUTHOR]

The color of rapeseed (Brassica napus L.) petal is usually yellow but can be milky-white to orange or pink. Thus, the petal color is a popular target in rapeseed breeding programs. In his study, metabolites and RNA were extracted from the yellow (Y), yellow/purple (YP), light purple (LP), and purple (P) rapeseed petals. Ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), RNA-Seq, and quantitative real-time (qRT-PCR) analyses were performed to analyze the expression correlation of differential metabolites and differential genes. A total of 223 metabolites were identified in the petals of the three purple and yellow rapeseed varieties by UPLC-MS/MS. A total of 20511 differentially expressed genes (DEGs) between P, LP, YP, versus Y plant petals were detected. This study focused on the co-regulation of 4898 differential genes in the three comparison groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation and quantitative RT-PCR analysis showed that the expression of BnaA10g23330D (BnF3'H) affects the synthesis of downstream peonidin and delphinidin and is a key gene regulating the purple color of petals in B. napus. L. The gene may play a key role in regulating rapeseed flower color; however, further studies are needed to verify this. These results deepen our understanding of the molecular mechanisms underlying petal color and provide the theoretical and practical basis for flower breeding targeting petal color. [ABSTRACT FROM AUTHOR]

Although many existing noise parameter estimations of image signal-dependent noise have certain denoising effects, most methods are not ideal. There are some problems with these methods, such as poor noise suppression effects, smooth details, lack of flexible denoising ability, etc. To solve these problems, in this study, we propose a deep signal-dependent denoising noise algorithm. The algorithm combines the model method with a convolutional neural network. We use the noise level of the noise image and the noise image together as the input of the convolutional neural network to obtain a wider range of noise levels than the single noise image as the input. In the convolutional neural network, the deep features of the image are extracted by multi-layer residuals, which solves the difficult problem of training. Extensive experiments demonstrate that our noise parameter estimation has good denoising performance. [ABSTRACT FROM AUTHOR]

One of the most important food crops is rice. For this reason, the accurate identification of rice pests is a critical foundation for rice pest control. In this study, we propose an algorithm for automatic rice pest identification and classification based on fully convolutional networks (FCNs) and select 10 rice pests for experiments. First, we introduce a new encoder–decoder in the FCN and a series of sub-networks connected by jump paths that combine long jumps and shortcut connections for accurate and fine-grained insect boundary detection. Secondly, the network also integrates a conditional random field (CRF) module for insect contour refinement and boundary localization, and finally, a novel DenseNet framework that introduces an attention mechanism (ECA) is proposed to focus on extracting insect edge features for effective rice pest classification. The proposed model was tested on the data set collected in this paper, and the final recognition accuracy was 98.28%. Compared with the other four models in the paper, the proposed model in this paper is more accurate, faster, and has good robustness; meanwhile, it can be demonstrated from our results that effective segmentation of insect images before classification can improve the detection performance of deep-learning-based classification systems. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) affects around 1% of children with no effective blood test or cure. Recent studies have suggested that these are neurological disorders with a strong genetic basis and that they are associated with the abnormal formation of dendritic spines. Chromosome microarray (CMA) together with high-throughput sequencing technology has been used as a powerful tool to identify new candidate genes for ASD. In the present study, CMA was first used to scan for genome-wide copy number variants in a proband, and no clinically significant copy number variants were found. Whole-exome sequencing (WES) was used further for genetic testing of the whole quad family affected by ASD, including the proband, his non-autistic sister, and his parents. Sanger sequencing and MassARRAY-based validation were used to identify and confirm variants associated with ASD. WES yielded a 151-fold coverage depth for each sample. A total of 98.65% of the targeted whole-exome region was covered at >20-fold depth. A de novo variant in CTTNBP2, p.M115T, was identified. The CTTNBP2 gene belongs to a family of ankyrin repeat domain-containing proteins associated with dendritic spine formation. Although CTTNBP2 has been associated with ASD, limited studies have been developed to identify clinically relevant de novo mutations of CTTNBP2 in children with ASD; family-based WES successfully identified a clinically relevant mutation in the CTTNBP2 gene in a quad family affected by ASD. Considering the neuron-specific expression of CTTNBP2 and its role in dendritic spine formation, our results suggest a correlation between the CTTNBP2 mutation and ASD, providing genetic evidence for ASD spine pathology. Although the present study is currently insufficient to support the assertion that the de novo mutation M115T in CTTNBP2 directly causes the autism phenotype, our study provides support for the assertion that this mutation is a candidate clinically relevant variant in autism. [ABSTRACT FROM AUTHOR]

To improve the modernization of social governance, the Chinese government has invested a large number of resources and policies into the field of community governance in recent years. This study takes the community proposal in China's Experimental Zone for Community Governance and Service Innovation as research cases, conducts a multi-case comparative analysis, applies social capital theory, summarizes four different community governance models from the differences of emotional and institutional social capital, and individual and collective social capital, and analyzes the process of community governance and proposal operation with the participation of multiple subjects. The study finds that community proposals expand the possibility of public participation, which is an extremely important reference value for the process of urban community governance and social democratization in contemporary China. However, community proposals are still policy-oriented, administrative, and benchmark-oriented, and the participatory roles and functions of multiple subjects remain unbalanced. The key to contemporary urban community governance in China lies in tapping community social capital, expanding the dimensions of social capital, and creating a sustainable mechanism for social capital transformation. [ABSTRACT FROM AUTHOR]

Midu pork roll (MPR), produced in Midu County, Dali Bai Autonomous Prefecture, Yunnan, China, is a traditional fermented meat product with a long history. This study aims to enhance the physical and flavor profile of MPR by improving its process, fermentation conditions and formulations. There were three different formulations, including traditional craft (control group: C), optimization process of Sichuan spicy flavor formula (Test group 1: T1) and optimization process of halogen flavor formula (Test group 2: T2). Higher moisture content, L*, a* and b* values and lower hardness, chewiness and shear force were observed in T1 and T2 compared to C (p < 0.05). A total of 15 free amino acids were detected throughout the fermentation process, during which the content of umami amino acids, sweet amino acids and bitter amino acids underwent significant changes. A total of 88, 85 and 75 volatile compounds were detected in C, T1 and T2, respectively, in which the relative content of alkanes and ketones in T1 and T2 were higher than those in C (p < 0.05). The process and formulas have improved the color, texture characteristics and tenderness of MPR to a certain extent, meanwhile, they have enhanced the flavor of MPR. [ABSTRACT FROM AUTHOR]

The cage-free system has gained a lot of interest in recent years because it can offer chickens more freedom and is easier to manage compared with free-range rearing systems, but few studies have focused on the effect of the cage-free rearing system on meat quality and flavor. In this study, 44 Jianghan chickens were reared in caged or cage-free systems to explore the effect of different rearing systems on meat-eating quality. Sensory evaluation of cooked muscles showed that the leg muscle aroma, juiciness, and flavor intensity significantly improved by the cage-free rearing. The cage-free hens had significantly lower body weight, abdominal fat percentage, and meat fat content, but higher meat moisture content. The cage-free group had brighter breast muscle and redder leg muscle color 24 h after slaughter. Transcriptomic and metabolomic profile analysis of the leg muscle samples showed that the cage-free rearing changed biosynthesis pathways associated with glycogen metabolism, lipid and fatty acid biosynthesis and transport, muscle cellular type, and cellular components, which were related to raw meat quality. Different rearing systems also resulted in differences in glycolipid metabolism, lipid metabolism, and altered levels of intramuscular fat content and other flavor precursors. Pathways such as glycerolipid metabolism, adipocytokine signaling, and metabonomic pathways such as linoleic acid, glycerophospholipid, arginine, proline, and β-alanine metabolism may be responsible for the meat quality and flavor change. [ABSTRACT FROM AUTHOR]

Close-distance coal seams are widely distributed in China, and the mining of overlying coal seams leads to floor damage. To grasp the properties and the fracture spans of the damaged main roof in the underlying coal seam, combining the calculation of the floor damage depth with rock damage theory and the formulas for calculating the first and periodic weighting intervals of the damaged main roof and the instability conditions of the damaged key blocks are obtained. Three interaction stability mechanics models are proposed for key blocks with different properties of the upper and lower main roof, and the instability conditions of the lower damaged key blocks are obtained when the fracture lines overlap. When combined with a specific example, the field monitoring verified the calculation results. The research results are as follows: (1) The first and periodic weighting intervals, horizontal thrust between blocks, and critical load of instability of the damaged main roof are significantly reduced. Still, there are differences in its reduction under different loads, rotation angles, and lumpiness. (2) When the fracture lines of the upper and lower main roofs overlap, the stability of the damaged key blocks is the lowest. There are three linkage stability regions in the critical load curves of the two key blocks. (3) In this case, the damage equivalent of the main roof is 0.397, which belongs to the local damage type. Its first and periodic weighting intervals are 40 m and 16 m, which is 22% and 24% less than when there is no damage. (4) A supporting load of 0.489 MPa is required to maintain the stability of the upper key block, and the lower damaged key block is prone to rotary and sliding instability during the first and periodic weighting, respectively. Thus, the supports need to bear a total of 0.988 MPa and 0.761 MPa to maintain the stability of the two key blocks simultaneously. The ground pressure data monitored on-site is in accord with the calculation results. [ABSTRACT FROM AUTHOR]

Autism spectrum disorder (ASD) affects more than 1% of children, and there is no viable pharmacotherapeutic agent to treat the core symptoms of ASD. Studies have shown that children with ASD show changes in their levels of immune response molecules. Our previous studies have shown that ASD is more common in children with folate receptor autoantibodies. We also found that children with ASD have abnormal gut immune function, which was characterized by a significant increase in the content of immunoglobulin A and an increase in gut-microbiota-associated epitope diversity. These studies suggest that the immune mechanism plays an important role in the occurrence of ASD. The present study aims to systematically assess gene mutations in immune mediators in patients with ASD. We collected genetic samples from 72 children with ASD (2–12 years old) and 107 healthy controls without ASD (20–78 years old). We used our previously-designed immune gene panel, which can capture cytokine and receptor genes, the coding regions of MHC genes, and genes of innate immunity. Target region sequencing (500×) and bioinformatics analytical methods were used to identify variants in immune response genes associated with patients with ASD. A total of 4 rare variants were found to be associated with ASD, including HLA-B: p.A93G, HLA-DQB1: p.S229N, LILRB2: p.R322H, and LILRB2: c.956-4C>T. These variants were present in 44.44% (32/72) of the ASD patients and were detected in 3.74% (4/107) of the healthy controls. We expect these genetic variants will serve as new targets for the clinical genetic assessment of ASD, and our findings suggest that immune abnormalities in children with ASD may have a genetic basis. [ABSTRACT FROM AUTHOR]

Due to the complex operation conditions in a power transformer, an oil-impregnated pressboard (OIP) simultaneously suffers from thermal, electrical, and mechanical stress. Since most research studies have paid much attention to thermal or electrical aging of OIPs, this paper analyzes the effects of long-term mechanical vibrations on cellulose degradation in OIPs under simultaneous multi-stress. The aging experiments were firstly conducted at 130 °C, with a DC electric voltage of +6 kV, vibration amplitude of 10–50 μm, and vibration frequency of 100–300 Hz. The finite element analysis (FEA) of the pressboard vibration model was then performed on Abaqus to investigate the time–frequency domain characteristic parameters of compressive stress on the pressboard under varied vibration frequencies and amplitudes. The FEA results reveal that compressive stress on the pressboard in a multi-stress aging experiment coincided with the axial compressive stress on the insulation spacers in an SZ-50000/110 transformer. Moreover, combined with the degree of polymerization (DP) of cellulose, the effects of long-term vibration on cellulose degradation are reflected in two ways: the increase in compressive stress on the pressboard generates more links available for degradation, while more high frequency harmonic components in compressive stress accelerate the reaction rate in cellulose degradation. [ABSTRACT FROM AUTHOR]

Featured Application: The method proposed in our paper is mainly applied to intelligent driving, driving training and other fields. Our method greatly solves the problems of complex information processing and massive consumption of computing resources in the field of intelligent driving. We can find the area that drivers are most interested in among many items of complicated information. The application of our method can reduce the cost of driverless driving, thereby promoting the early realization of unmanned driving. The method can also be applied to the field of driving training, for example, a novice driver can use our method to judge whether the driver's attention area is correct and ensure driving safety. The current intelligent driving technology based on image data is being widely used. However, the analysis of traffic accidents occurred in intelligent driving vehicles shows that there is an explanatory difference between the intelligent driving system based on image data and the driver's understanding of the target information in the image. In addition, driving behavior is the driver's response based on the analysis of road information, which is not available in the current intelligent driving system. In order to solve this problem, our paper proposes a driver attention area extraction method based on deep network feature visualization. In our method, we construct a Driver Behavior Information Network (DBIN) to map the relation between image information and driving behavior. Then we use the Deep Network Feature Visualization method (DNFV) to determine the driver's attention area. The experimental results show that our method can extract effective road information from a real traffic scene picture and obtain the driver's attention area. Our method can provide a useful theoretical basis and related technology of visual perception for future intelligent driving systems, driving training and assisted driving systems. [ABSTRACT FROM AUTHOR]

Featured Application: The method proposed in our paper can be used in the field of gear fault diagnosis of low-speed and heavy-duty machines. This method uses the stator current signal of the motor for fault diagnosis, and preprocesses the original current to filter the interference of fundamental frequency and the load impact, so as to enhance the gear failure characteristic frequency. The gear failure characteristic frequency can be easily extracted from the preprocessed current. This diagnostic method does not require the installation of sensors and is not affected by environmental factors. Vibration signal is often used in traditional gear fault diagnosis techniques. However, the working face of the scraper conveyor is narrow, harsh and easily explosive, so it is inconvenient to obtain vibration signals by installing sensors. Motor current signature analysis (MCSA) is a fault-diagnosis method without sensor installation, which is easier to realize in the mine. Therefore, a fault diagnosis method for local gear fault, which is based on bispectral analysis (BA) of analytical signal envelope obtained by processing a stator current under time-varying load condition, is proposed in our paper. In this method, the fault frequency component is enhanced by eliminating the interference of fundamental frequency and coal flow impact. Then, the enhanced fault frequency component is extracted by BA, and a quantitative analysis of the fault strength under time-varying load is carried out from the perspective of energy. Finally, the proposed method is verified on the number HB-kpl-75 scraper conveyor reducer, and the results show that this method can successfully diagnose the failure of the scraper conveyor gear under time-varying load conditions. [ABSTRACT FROM AUTHOR]

Fault diagnosis of rolling bearings is essential to ensure the efficient and safe operation of mechanical equipment. The extraction of fault features of the repetitive transient component from noisy vibration signals is key to bearing fault diagnosis. However, the bearing fault-induced transients are often submerged by strong background noise and interference. To effectively detect such fault-related transient components, this paper proposes a probability- and statistics-based method. The maximum-a-posteriori (MAP) estimator combined with probability density functions (pdfs) of the repetitive transient component, which is modeled by a mixture of two Laplace pdfs and noise, were used to derive the fast estimation model of the transient component. Subsequently, the LapGauss pdf was adopted to model the noisy coefficients. The parameters of the model derived could then be estimated quickly using the iterative expectation–maximization (EM) algorithm. The main contributions of the proposed statistic-based method are that: (1) transients and their wavelet coefficients are modeled as mixed Laplace pdfs; (2) LapGauss pdf is used to model noisy signals and their wavelet coefficients, facilitating the computation of the proposed method; and (3) computational complexity changes linearly with the size of the dataset and thus contributing to the fast estimation, indicated by analysis of the computational performance of the proposed method. The simulation and experimental vibration signals of faulty bearings were applied to test the effectiveness of the proposed method for fast fault feature extraction. Comparisons of computational complexity between the proposed method and other transient extraction methods were also conducted, showing that the computational complexity of the proposed method is proportional to the size of the dataset, leading to a high computational efficiency. [ABSTRACT FROM AUTHOR]

Simple Summary: Previous research found that FATP1 plays an important role in the regulation of fatty acid metabolism and lipid accumulation in pig and chicken, but its function has not been explored in bovine adipocyte yet. In this study, we investigated the effect of FATP1 expression on preadipocyte differentiation in Qinchuan cattle using overexpression and interference assays. Our results reveal that FATP1 overexpression promoted preadipocyte differentiation, lipid droplet formation, and the expression of LPL and PPARγ, while FATP1 interference had the opposite effects on adipocyte differentiation and fat deposition. Following FATP1 overexpression and FATP1 interference in adipocytes, RNA-seq analysis identified that SLPI, STC1, SEMA6A, TNFRSF19, SLN, PTGS2, ADCYP1, FADS2, and SCD genes were differentially expressed. Pathway analysis revealed that the PPAR signaling pathway, AMPK signal pathway, and Insulin signaling pathway were enriched with differentially expressed genes. We propose that the FATP1 gene may affect the beef quality by involving adipocyte differentiation and lipid deposition, and may shed new light on the formation mechanisms of adipose tissues. FATP1 plays an important role in the regulation of fatty acid metabolism and lipid accumulation. In this study, we investigated the patterns of FATP1 expression in various tissues obtained from calf and adult Qinchuan cattle, and in differentiating adipocytes. Next, we investigated the effect of FATP1 expression on preadipocyte differentiation in Qinchuan cattle using overexpression and interference assays. We also identified the differentially expressed genes (DEGs) and pathways associated with FATP1 overexpression/interference. Our results reveal that FATP1 was broadly expressed in heart, kidney, muscle, small intestine, large intestine, and perirenal fat tissues. While FATP1 overexpression promoted preadipocyte differentiation, fat deposition, and the expression of several genes involved in fat metabolism, FATP1 interference had the opposite effects on adipocyte differentiation. Following FATP1 overexpression and FATP1 interference in adipocytes, RNA-seq analysis was performed to identify DEGs related to fat metabolism. The DEGs identified include SLPI, STC1, SEMA6A, TNFRSF19, SLN, PTGS2, ADCYP1, FADS2, and SCD. Pathway analysis revealed that the DEGs were enriched in the PPAR signaling pathway, AMPK signal pathway, and Insulin signaling pathway. Our results provide an in-depth understanding of the function and regulation mechanism of FAPT1 in fat metabolism. [ABSTRACT FROM AUTHOR]

To date, breakdown voltage is an underlying risk to the epoxy-based electrical high voltage (HV) equipment. To improve the breakdown strength of epoxy resin and to explore the formation of charge traps, in this study, two types of polyhedral oligomeric silsesquioxane (POSS) fillers are doped into epoxy resin. The breakdown voltage test is performed to investigate the breakdown strength of neat epoxy and epoxy/POSS composites. Electron traps that play an important role in breakdown strength are characterized by thermally stimulated depolarized current (TSDC) measurement. A quantum chemical calculation tool identifies the source of traps. It is found that adding octa-glycidyl POSS (OG-POSS) to epoxy enhances the breakdown strength than that of neat epoxy and epoxycyclohexyl POSS (ECH-POSS) incorporated epoxy. Moreover, side groups of OG-POSS possess higher electron affinity (EA) and large electronegativity that introduces deep-level traps into epoxy resin and restrain the electron transport. In this work, the origin of traps has been investigated by the simulation method. It is revealed that the functional properties of POSS side group can tailor an extensive network of deep traps in the interfacial region with epoxy and enhance the breakdown strength of the epoxy/POSS nanocomposite. [ABSTRACT FROM AUTHOR]

Recently, metal-coordinated orthogonal self-assembly has been used as a feasible and efficient method in the construction of polymeric materials, which can also provide supramolecular self-assembly complexes with different topologies. Herein, a cryptand with a rigid pyridyl group on the third arm derived from BMP32C10 was synthesized. Through coordination-driven self-assembly with a bidentate organoplatinum(II) acceptor or tetradentate Pd(BF4)2•4CH3CN, a di-cryptand complex and tetra-cryptand complex were prepared, respectively. Subsequently, through the addition of a di-paraquat guest, linear and cross-linked supramolecular polymers were constructed through orthogonal self-assembly, respectively. By comparing their proton nuclear magnetic resonance (1H NMR) and diffusion-ordered spectroscopy (DOSY) spectra, it was found that the degrees of polymerization were dependent not only on the concentrations of the monomers but also on the topologies of the supramolecular polymers. [ABSTRACT FROM AUTHOR]

Simple Summary: In bovine preadipocytes, the overexpression of the PLIN1 gene promotes the expression of FASN, PPARγ, ACC, LPL, FABP4, DGAT2, and C/EBPβ at the mRNA level, inhibiting the expression of fat metabolism genes such as PLIN2 and ATGL. Furthermore, after overexpression of PLIN1, the oil red O-staining results showed that the number of lipid droplets (LDs) in fat cells, their volume and triglyceride content were increased. The elevation in triglyceride content indicates that PLIN1 can promote the accumulation of triglyceride in bovine preadipocytes and has an important regulatory role in fat metabolism. After transfection with the adenovirues Ad-PLIN1 and Ad-NC (empty virus), RNA-seq was used to analyze the differentially expressed genes in bovine preadipocytes. A total of 1923 differentially expressed genes were detected, and GO and KEGG signaling pathways were analyzed for differentially expressed genes. Perilipin 1 (PLIN1) is a protein encoded by the PLIN1 gene in eukaryotes. PLIN1 is a member of the PAT protein family, a family of proteins related to lipid droplet (LD) surface proteins. PLIN1 phosphorylation plays a vital role during fat metabolism of adipose tissue lipolysis and fat storage in adipocytes. However, to further explore the regulation of the PLIN1 gene on the proliferation, differentiation and lipid metabolism of bovine adipocytes. In this study, the mRNA expression of PLIN1, at day six, was the highest during bovine adipocyte differentiation. Moreover, PLIN1 can promote the proliferation and differentiation of preadipocytes in cattle. On the sixth day, after transfection with, and overexpression of, the PLIN1 gene in bovine preadipocytes via adenovirus, cell samples were collected, and transcriptome sequencing was performed. A total of 1923 differentially expressed genes were detected. Through GO and KEGG pathway analysis, the differentially expressed genes were established to be mainly enriched in the AMPK, Wnt, and PPAR signaling pathways related to fat proliferation and differentiation. In conclusion, at the transcriptional level, PLIN1 plays an important role in regulating fat proliferation and metabolism. Additionally, the sequencing results screened new differentially expressed genes related to fat metabolism, providing theoretical support for molecular breeding of Qinchuan beef cattle. [ABSTRACT FROM AUTHOR]

Cerebral hernia in crested chicken has been characterized as the protrusion of cerebral hemispheres into the unsealed skull for hundreds of years, since Charles Darwin. The development of deformed forebrain (telencephalon) of cerebral hernia remains largely unknown. Here, the unsealed frontal skull combined with misplaced sphenoid bone was observed and potentially associated with brain protuberance. The shifted pallidum, elongated hippocampus, expanded mesopallium and nidopallium, and reduced hyperpallium were observed in seven regions of the malformed telencephalon. The neurons were detected with nuclear pyknosis and decreased density. Astrocytes showed uneven distribution and disordered protuberances in hyperpallium and hippocampus. Transcriptome analyses of chicken telencephalon (cerebral hernia vs. control) revealed 547 differentially expressed genes (DEGs), mainly related to nervous system development, and immune system processes, including astrocyte marker gene GFAP, and neuron and astrocyte developmental gene S100A6. The upregulation of GFAP and S100A6 genes in abnormal telencephalon was correlated with reduced DNA methylation levels in the promoter regions. The morphological, cellular, and molecular variations in the shape, regional specification, and cellular states of malformed telencephalon potentially participate in brain plasticity and previously reported behavior changes. Chickens with cerebral hernia might be an interesting and valuable disease model to further explore the recognition, diagnosis, and therapy of cerebral hernia development of crested chickens and other species. [ABSTRACT FROM AUTHOR]

Simple Summary: Broad-spectrum antibiotics have been a cornerstone in the treatment of bacterial diseases. However, growing evidence suggests that antibiotics have effects on host-associated gut microbiota communities. In this study, we report persistent significant changes in the abundance of gut microbiota and their functional metabolite pathways in chickens due to enrofloxacin and diclazuril exposure. These changes may affect the taxonomic, genomic, and functional capacity of the chicken gut microbiota, reducing bacterial diversity while expanding and collapsing membership of specific indigenous taxa. Understanding the biology of competitive exclusion of adaptive functions during antibiotic exposure in the gut may inform the design of new strategies to treat infections, while preserving the ecology of chicken-beneficial constituents. The dynamic microbiota in chickens can be affected by exposure to antibiotics, which may alter the composition and substrate availability of functional pathways. Here, 120 Jing Hong chicks at 30 days of age were randomly divided into four treatments totaling seven experimental groups: control chicks not exposed to antibiotics; and chicks exposed to enrofloxacin, diclazuril, and their mixture at 1:1 for 14 days and then not exposed for a withdrawal period of 15 days. Fecal samples were collected from the 7 groups at 8 time-points (exposure to 4 antibiotics and 4 withdrawal periods) to perform in-depth 16S rRNA sequencing of the gut microbiota. Taxon-independent analysis showed that the groups had significantly distinct microbial compositions (p < 0.01). Based on the microbial composition, as compared with the control group, the abundances of the phyla Firmicutes, Actinobacteria, Thermi, and Verrucomicrobia, as well as the families Lactobacillus, Lactococcus, S24-7, and Corynebacterium, were decreased in the antibiotic-exposed chicks (p < 0.01). Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analyses revealed significant differences in microbiota metabolite pathways due to the genera of the antibiotic-responsive microbes (p < 0.01), especially the pathways relating to cell growth and death, immune system diseases, carbohydrate metabolism, and nucleotide metabolism. Oral treatment with enrofloxacin, diclazuril, and their mixture modified the gut microbiota composition and the microbial metabolic profiles in chickens, with persistent effects (during the withdrawal period) that prevented the return to the original community and led to the formation of a new community. [ABSTRACT FROM AUTHOR]

Aiming at the problems that current predicting models are incapable of extracting the inner rule of the traffic flow sequence in traffic big data, and unable to make full use of the spatio-temporal relationship of the traffic flow to improve the accuracy of prediction, a Bi-directional Regression Neural Network (BRNN) is proposed in this paper, which can fully apply the context information of road intersections both in the past and the future to predict the traffic volume, and further to make up the deficiency that the current models can only predict the next-moment output according to the time series information in the previous moment. Meanwhile, a vectorized code to screen out the intersections related to the predicting point in the road network and to train and predict through inputting the track data of the selected intersections into BRNN, is designed. In addition, the model is testified through the true traffic data in partial area of Shen Zhen. The results indicate that, compared with current traffic predicting models, the model in this paper is capable of providing the necessary evidence for traffic guidance and control due to its excellent performance in extracting the spatio-temporal feature of the traffic flow series, which can enhance the accuracy by 16.298% on average. [ABSTRACT FROM AUTHOR]

The improvement of egg production is of vital importance in the chicken industry to maintain optimum output throughout the laying period. Because of the elongation of the egg-laying cycle, a drop in egg-laying rates in the late laying period has provoked great concern in the poultry industry. In this study, we calculated the egg-laying rate at weeks 61–69 (60 days) of Jing Hong chickens parent generation as the phenotype, and the genotype were detected by the chicken 600K Affymetrix Axiom High Density (HD) Single Nucleotide Polymorphisms (SNP)-array. The Genome-Wide Association Study (GWAS) result showed that the egg production trait is significantly associated with five SNPs (AX-75745366, AX-75745380, AX-75745340, AX-75745388, and AX-75745341), which are in the rap guanine nucleotide exchange factor 6 (RAPGEF6) gene on chicken chromosome 13. A total of 1676 Chinese commercial Jing Hong laying hens—including two populations, P1 population (858 hens) and P2 population (818 hens)—were genotyped using the Polymerase Chain Reaction-Restriction Fragments Length Polymorphisms (PCR-RFLP) method for the association analysis of egg-laying rates for the verification of the GWAS results. Genotypic and allelic frequencies of five SNPs were inconsistent with Hardy–Weinberg equilibrium, and the average population genetics parameters considering all the SNP values; i.e., gene homozygosity (Ho), gene heterozygosity (He), the effective number of alleles (Ne), and the polymorphism information content (PIC) were 0.75, 0.25, 1.40, and 0.20 in P1; 0.71, 0.29, 1.46, and 0.24 in P2; and 0.73, 0.27, 1.43, and 0.22 in P1 + P2 populations, respectively. The association analysis results revealed that out of the five polymorphisms, three of them (AX-75745366, AX-75745340, and AX-75745341; Patent applying No: 201810428916.5) had highly significant effects on egg-laying rates according to the GWAS results. Population-specific association analyses also showed similar significant association effects with this trait. Four haplotypes (AAGG, AAAG, AGGG, and AGAG) were inferred based on significant loci (AX-75745340 and AX-75745341) and also showed significant associations with the egg-laying rate, where haplotype AAGG had the highest egg-laying rate, with the exception of the egg-laying rate in P1 population, followed by other haplotypes. Furthermore, genotypes TT, AA, and GG showed the highest egg-laying rate compared to the corresponding genotypes at AX-75745366, AX-75745340, and AX-75745341 SNP loci in P1+P2, respectively. A similar result was found in the population-specific analysis except for the P1 population, in which TC genotype showed the highest egg-laying rate. No significant association was found in the egg-laying rate during the 60 days laying period for the SNPs (AX-75745380 and AX-75745388) in any group of population (p ≥ 0.05). Collectively, we report for the first time that 3 SNPs in the RAPGEF6 gene were significantly associated with the egg-laying rate during the later stage of egg production, which could be used as the potential candidate molecular genetic markers that would be able to facilitate in the selection and improvement of egg production traits through chicken breeding. [ABSTRACT FROM AUTHOR]

Establishing a heterojunction for two kinds of semiconductor catalysts is a promising way to enhance photocatalytic activity. In this study, nanodiamond (ND) and CuFe-layered double hydroxide (LDH) were hybridized by a simple coprecipitation method as a novel heterojunction to photoactivate H2O2. The ND/LDH possessed a hydrotalcite-like structure, large specific surface area (SBET = 99.16 m2/g), strong absorption of visible-light and low band gap (Eg = 0.94 eV). Under the conditions of ND/LDH dosage 0.0667 g/L, H2O2 concentration 19.6 mmol/L, and without initial pH adjustment, 93.5% of 10 mg/L methylene blue (MB) was degraded within 120 min, while only 78.3% of MB was degraded in the presence of LDH instead of ND/LDH. The ND/LDH exhibited excellent stability and maintained relatively high activity, sufficient to photoactivate H2O2 even after five recycles. The mechanism study revealed that in the heterojunction of ND/LDH, the photoelectrons transferred from the valence band of LDH (Cu/Fe 3d t2g) to the conduction band of LDH (Cu/Fe 3d eg) could spontaneously migrate onto the conduction band of ND, promoting the separation of photo-induced charges. Thus, the photoelectrons had sufficient time to accelerate the redox cycles of Cu3+/Cu2+ and Fe3+/Fe2+ to photoactivate H2O2 to produce hydroxyl radicals, resulting in excellent photo-Fenton efficiency on MB degradation. [ABSTRACT FROM AUTHOR]

Adipose tissue is the most important energy metabolism and secretion organ, and these functions are conferred during the adipogenesis process. However, the cause and the molecular events underlying adipogenesis are still unclear. In this study, we performed integrated bioinformatics analyses to identify vital genes involved in adipogenesis and reveal potential molecular mechanisms. Five mouse high-throughput expression profile datasets were downloaded from the Gene Expression Omnibus (GEO) database; these datasets contained 24 samples of 3T3-L1 cells during adipogenesis, including 12 undifferentiated samples and 12 differentiated samples. The five datasets were reanalyzed and integrated to select differentially expressed genes (DEGs) during adipogenesis via the robust rank aggregation (RRA) method. Functional annotation of these DEGs and mining of key genes were then performed. We also verified the expression levels of some potential key genes during adipogenesis. A total of 386 consistent DEGs were identified, with 230 upregulated genes and 156 downregulated genes. Gene Ontology (GO) analysis showed that the biological functions of the DEGs primarily included fat cell differentiation, lipid metabolic processes, and cell adhesion. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these DEGs were mainly associated with metabolic pathways, the peroxisome proliferator-activated receptor (PPAR) signaling pathway, regulation of lipolysis in adipocytes, the tumor necrosis factor (TNF) signaling pathway, and the FoxO signaling pathway. The 30 most closely related genes among the DEGs were identified from the protein–protein interaction (PPI) network and verified by real-time quantification during 3T3-L1 preadipocyte differentiation. In conclusion, we obtained a list of consistent DEGs during adipogenesis through integrated analysis, which may offer potential targets for the regulation of adipogenesis and treatment of adipose dysfunction. [ABSTRACT FROM AUTHOR]

In this study, tunable diode laser absorption spectroscopy (TDLAS) combined with wavelength modulation spectroscopy (WMS) was used to develop a trace C2H2 sensor based on the principle of gas absorption spectroscopy. The core of this sensor is an interband cascade laser that releases wavelength locks to the best absorption line of C2H2 at 3305 cm−1 (3026 nm) using a driving current and a working temperature control. As the detected result was influenced by 1/f noise caused by the laser or external environmental factors, the TDLAS-WMS technology was used to suppress the 1/f noise effectively, to obtain a better minimum detection limit (MDL) performance. The experimental results using C2H2 gas with five different concentrations show a good linear relationship between the peak value of the second harmonic signal and the gas concentration, with a linearity of 0.9987 and detection accuracy of 0.4%. In total, 1 ppmv of C2H2 gas sample was used for a 2 h observation experiment. The data show that the MDL is low as 1 ppbv at an integration time of 63 s. In addition, the sensor can be realized by changing the wavelength of the laser to detect a variety of gases, which shows the flexibility and practicability of the proposed sensor. [ABSTRACT FROM AUTHOR]

With the development and application of next-generation sequencing (NGS) and target capture technology, the demand for an effective analysis method to accurately detect gene fusion from high-throughput data is growing. Hence, we developed a novel fusion gene analyzing method called single-end gene fusion (SEGF) by starting with single-end DNA-seq data. This approach takes raw sequencing data as input, and integrates the commonly used alignment approach basic local alignment search tool (BLAST) and short oligonucleotide analysis package (SOAP) with stringent passing filters to achieve successful fusion gene detection. To evaluate SEGF, we compared it with four other fusion gene discovery analysis methods by analyzing sequencing results of 23 standard DNA samples and DNA extracted from 286 lung cancer formalin fixed paraffin embedded (FFPE) samples. The results generated by SEGF indicated that it not only detected the fusion genes from standard samples and clinical samples, but also had the highest accuracy and sensitivity among the five compared methods. In addition, SEGF was capable of detecting complex gene fusion types from single-end NGS sequencing data compared with other methods. By using SEGF to acquire gene fusion information at DNA level, more useful information can be retrieved from the DNA panel or other DNA sequencing methods without generating RNA sequencing information to benefit clinical diagnosis or medication instruction. It was a timely and cost-effective measure with regard to research or diagnosis. Considering all the above, SEGF is a straightforward method without manipulating complicated arguments, providing a useful approach for the precise detection of gene fusion variation. [ABSTRACT FROM AUTHOR]