Bright solitons in a spin-orbit-coupled dipolar Bose-Einstein condensate trapped within a double-lattice.

By effectively controlling the dipole-dipole interaction, we investigate the characteristics of the ground state of bright solitons in a spin-orbit coupled dipolar Bose-Einstein condensate. The dipolar atoms are trapped within a double-lattice which consists of a linear and a nonlinear lattice. We derive the motion equations of the different spin components, taking the controlling mechanisms of the dipole-dipole interaction into account. An analytical expression of dipole-dipole interaction is derived. By adjusting the dipole polarization angle, the dipole interaction can be adjusted from attraction to repulsion. On this basis, we study the generation and manipulation of the bright solitons using both the analytical variational method and numerical imaginary time evolution. The stability of the bright solitons is also analyzed and we map out the stability phase diagram. By adjusting the long-range dipole-dipole interaction, one can achieve manipulation of bright solitons in all aspects, including the existence, width, nodes, and stability. Considering the complexity of our system, our results will have enormous potential applications in quantum simulation of complex systems.

Electron beam irradiation induced aggregation, structural and functional changes of soybean 11S globulin.

This study investigated the effects of different irradiation doses of an electron beam (e-beam) (0, 2, 4, 6, 8, and 10 kGy) on the structure, emulsification, foaming, and rheological and gel properties of soybean 11S globulin. The irradiation treatment at 4 and 6 kGy significantly increased the solubility, surface hydrophobicity, disulfide bonding, and ζ-potential of 11S globulin, decreased the particle size of the protein solution, and effectively improved the emulsifying activity and foaming stability of the protein solution. Moreover, irradiation induced moderate cross-linking and aggregation of the proteins, thereby increasing the apparent viscosity and shear stress of the protein solution. In addition, the low-field NMR and microstructure analysis results revealed that protein gels formed a dense and homogeneous three-dimensional mesh structure after irradiation (6 kGy), along with increased content of bound water (T2b) and water not readily flowable (T21) and a decrease content of free water (T22). Overall, our results confirmed that e-beam irradiation could significantly improve the physicochemical properties of soybean 11S globulin. Our study thus provides a new technical means for the application of electron beam irradiation technology toward protein modification and broadens the high-value utilization of soybean 11S globulin in the food processing industry.

Effect of electron beam irradiation on the structural characteristics and functional properties of goat's milk casein.

The effects of electron beam irradiation (EBI) at different doses (0, 2, 4, 6, 8, and 10 kGy) were investigated on the structural and functional properties of casein, including their interrelationship. A gradual reduction in the α-helix content of the secondary structure (as a stable structure) indicates that casein under EBI treatment mainly undergoes fragmentation and aggregation from a structural perspective. Furthermore, the hydrophobic group and tryptophan in the tertiary structure were exposed, which opened up the internal structure of the protein. In addition, a continuously increasing irradiation dose led to casein aggregation, as confirmed by electron microscopy. The structural changes affected its functional properties, such as solubility, emulsification, foaming, and rheological properties, all of which increased first and subsequently decreased. Finally, at irradiation doses of 4-6 kGy, casein was modified to exhibit optimal functional properties, which enhanced its food processing value and performance.

Chitosan/konjac glucomannan bilayer films: Physical, structural, and thermal properties.

To overcome the limitations of chitosan (CS) and konjac glucomannan (KGM), the bilayer films of CS and KGM were prepared by layer-by-layer (LBL) casting method, and the effects of different mass ratios (i.e., C5: K0, C4:K1, C3:K2, C1:K1, C2:K3, C1:K4, and C0:K5) on the microstructures and physicochemical properties of bilayer films were examined to evaluate their applicability in food packaging. The results revealed that the bilayer films had uniform microstructures. When compared with pure films, the bilayer films displayed lower swelling degrees and water vapor permeability. However, the tensile tests revealed a reduction in the mechanical properties of the bilayer films, which was nonetheless superior to that of the pure KGM film. In addition, the intermolecular interactions between the CS and KGM layers were observed through FTIR and XRD analyses. Finally, TGA and DSC analyses demonstrated a decrease in the thermal stability of the bilayer films. Our cumulative results verified that CS-KGM bilayer films may be a promising material for use in food packaging and further properties of the bilayer films can be supplemented in the future through layer-by-layer modification and the addition of active ingredients.

A circRNA-miRNA-mRNA network analysis underlying pathogenesis of human heart failure.

BACKGROUND: The molecular mechanisms of heart failure (HF) are still poorly understood. Circular RNA (circRNA) has been discovered in the heart in increasing numbers of studies. The goal of this research is to learn more about the potential roles of circRNAs in HF. METHODS & RESULTS: We used RNA sequencing data to identify the characteristics of circRNAs expressed in the heart and discovered that the majority of circRNAs screened were less than 2000 nt. Additionally, chromosomes One and Y had the most and least number of circRNAs, respectively. After excluding duplicate host genes and intergenic circRNAs, a total of 238 differentially expressed circRNAs (DECs) and 203 host genes were discovered. However, only four of the 203 host genes of DECs were examined in HF differentially expressed genes. Another study used Gene Oncology analysis of DECs host genes to elucidate the underlying pathogenesis of HF, and it found that binding and catalytic activity accounted for a large portion of DECs. Immune system, metabolism, and signal transduction pathways were significantly enriched. Furthermore, 1052 potentially regulated miRNAs from the top 40 DECs were collected to build a circRNA-miRNA network, and it was discovered that 470 miRNAs can be regulated by multiple circRNAs, while others are regulated by a single circRNA. In addition, a comparison of the top 10 mRNAs in HF and their targeted miRNAs revealed that DDX3Y and UTY were regulated by the most and least circRNA, respectively. CONCLUSION: These findings demonstrated circRNAs have species and tissue specific expression patterns; while circRNA expression is independent on host genes, the same types of genes in DECs and DEGs worked in HF. Our findings would contribute to a better understanding of the critical roles of circRNAs and lay the groundwork for future studies of HF molecular functions.

A Soft Sensor Model of Sintering Process Quality Index Based on Multi-Source Data Fusion.

In complex industrial processes such as sintering, key quality variables are difficult to measure online and it takes a long time to obtain quality variables through offline testing. Moreover, due to the limitations of testing frequency, quality variable data are too scarce. To solve this problem, this paper proposes a sintering quality prediction model based on multi-source data fusion and introduces video data collected by industrial cameras. Firstly, video information of the end of the sintering machine is obtained via the keyframe extraction method based on the feature height. Secondly, using the shallow layer feature construction method based on sinter stratification and the deep layer feature extraction method based on ResNet, the feature information of the image is extracted at multi-scale of the deep layer and the shallow layer. Then, combining industrial time series data, a sintering quality soft sensor model based on multi-source data fusion is proposed, which makes full use of multi-source data from various sources. The experimental results show that the method effectively improves the accuracy of the sinter quality prediction model.

Biological Characteristics and Pathogenicity Analysis of a Low Virulence G2a Porcine Epidemic Diarrhea Virus.

Since the outbreak caused by a porcine epidemic diarrhea virus (PEDV) variant in 2010, the current epidemic of PEDV genotype 2 (G2) has caused huge economic losses to the pig industry in China. In order to better understand the biological characteristics and pathogenicity of the current PEDV field strains, 12 PEDV isolates were collected and plaque purified during 2017 to 2018 in Guangxi, China. The neutralizing epitopes of the spike proteins and the ORF3 proteins were analyzed to evaluate genetic variations, and they were compared with the reported G2a and G2b strains. Phylogenetic analysis of the S protein showed that the 12 isolates were clustered into the G2 subgroup (with 5 and 7 strains in G2a and G2b, respectively) and that they shared 97.4 to 99.9% amino acid identities. Among them, one of the G2a strains, CH/GXNN-1/2018, which had a titer of 106.15 PFU/mL, was selected for pathogenicity analysis. Although piglets infected with the CH/GXNN-1/2018 strain exhibited severe clinical signs and the highest level of virus shedding within 24 h postinfection (hpi), recovery and decreased virus shedding were seen after 48 hpi, and no piglets died during the whole process. Thus, the CH/GXNN-1/2018 strain had low virulence in suckling piglets. Virus neutralizing antibody analysis showed that the CH/GXNN-1/2018 strain induced cross-protection against both homologous G2a and heterologous G2b PEDV strains as early as 72 hpi. These results are of great significance for understanding PEDV in Guangxi, China, and they provide a promising naturally occurring low-virulent vaccine candidate for further study. IMPORTANCE The current epidemic of porcine epidemic diarrhea virus (PEDV) G2 has caused huge economic losses to the pig industry. Evaluation for low virulence of the PEDV strains of subgroup G2a would be useful for the future development of effective vaccines. In this study, 12 field strains of PEDV were obtained successfully, and they were characterized from Guangxi, China. The neutralizing epitopes of the spike proteins and the ORF3 proteins were analyzed to evaluate antigenic variations. One of the G2a strains, CH/GXNN-1/2018, was selected for pathogenicity analysis, and it showed that the CH/GXNN-1/2018 strain had low virulence in suckling piglets. These results provide a promising naturally occurring low-virulent vaccine candidate for further study.

[Visual analysis of research on traditional Chinese medicine treatment of Alzheimer's disease in recent ten years].

This study employed bibliometrics tools to review the studies of traditional Chinese medicine(TCM) treatment of Alzheimer's disease(AD) in recent ten years, aiming to explore the research status, hotspots, and future trends in this field at home and abroad. The relevant literature published from January 1, 2012 to August 15, 2022 was retrieved from Web of Science and CNKI. CiteSpace 6.1R2 and VOSviewer 1.6.15 were used for the visual analysis of authors, countries, institutions, keywords, journals, etc. A total of 2 254 Chinese articles and 545 English articles were included. The annual number of articles published showed a rising trend with fluctuations. The country with the largest number of relevant articles published and the largest centrality was China. SUN Guo-jie and WANG Qi were the authors publishing the most Chinese articles and English articles, respectively. Hubei University of Chinese Medicine and Beijing University of Chinese Medicine published the most articles in Chinese and English, respectively. Journal of Ethnopharmacology and Neuroscience Letters published the articles with the highest cited frequency and the highest centrality. According to the keywords, the research on TCM treatment of AD mainly focused on the mechanism of action and treatment methods. Metabolomics, intestinal flora, oxidative stress, tau hyperphosphorylation, ß-amyloid(Aß), inflammatory cytokines, and autophagy were the focuses of the research on mechanism of action. Acupuncture, clinical effect, kidney deficiency and phlegm stasis, and dredging governor vessel to revitalize mind were the hotspots of clinical research. This research field is still in the stage of exploration and development. Exchanges and cooperation among institutions should be encouraged to carry out more high-quality basic research on TCM treatment of AD, obtain high-level evidence, and clarify the pathogenesis and prescription mechanism.

Integrated proteomics and metabolomics analysis revealed the mechanisms underlying the effect of irradiation on the fat quality of Chinese bacon.

Irradiation increases the security and storage period of preserved Chinese bacon; nevertheless, the biological mechanisms underlying the changes in fat quality caused by irradiation are unknown. We investigated the influence of irradiation on Chinese bacon by proteomic and metabolomic. We identified 24 proteins that participated in metabolism and 40 common differential metabolites enriched in 16 signalling pathways. Correlation analysis revealed that irradiation altered 11 pathways shared between the proteome and metabolome, including two lipid metabolism pathways. Acetyl-CoA carboxylase, ACSL, octanoic acid, decanoic acid, palmitic acid, and oleic acid participated in fatty acid biosynthesis. Acyl-CoA thioesterase 1/2/4, enoyl-CoA reductase, acetyl-CoA acyltransferase 1, enoyl-CoA hydratase 2, palmitic acid, and oleic acid participated in unsaturated fatty acid biosynthesis. These findings lay the groundwork for multi-omics research on the effects of irradiation on Chinese bacon quality, assisting in assessing irradiated Chinese bacon quality, and developing effective strategies to standardise quality parameters.

Cannabinoid Receptor 2-Centric Molecular Feedback Loop Drives Necroptosis in Diabetic Heart Injuries.

BACKGROUND: Diabetic heart dysfunction is a common complication of diabetes. Cell death is a core event that leads to diabetic heart dysfunction. However, the time sequence of cell death pathways and the precise time to intervene of particular cell death type remain largely unknown in the diabetic heart. This study aims to identify the particular cell death type that is responsible for diabetic heart dysfunction and to propose a promising therapeutic strategy by intervening in the cell death pathway. METHODS: Type 2 diabetes models were established using db/db leptin receptor-deficient mice and high-fat diet/streptozotocin-induced mice. The type 1 diabetes model was established in streptozotocin-induced mice. Apoptosis and programmed cell necrosis (necroptosis) were detected in diabetic mouse hearts at different ages. G protein-coupled receptor-targeted drug library was searched to identify potential receptors regulating the key cell death pathway. Pharmacological and genetic approaches that modulate the expression of targets were used. Stable cell lines and a homemade phosphorylation antibody were prepared to conduct mechanistic studies. RESULTS: Necroptosis was activated after apoptosis at later stages of diabetes and was functionally responsible for cardiac dysfunction. Cannabinoid receptor 2 (CB2R) was a key regulator of necroptosis. Mechanically, during normal glucose levels, CB2R inhibited S6 kinase-mediated phosphorylation of BACH2 at serine 520, thereby leading to BACH2 translocation to the nucleus, where BACH2 transcriptionally repressed the necroptosis genes Rip1, Rip3, and Mlkl. Under hyperglycemic conditions, high glucose induced CB2R internalization in a ß-arrestin 2-dependent manner; thereafter, MLKL (mixed lineage kinase domain-like), but not receptor-interacting protein kinase 1 or 3, phosphorylated CB2R at serine 352 and promoted CB2R degradation by ubiquitin modification. Cardiac re-expression of CB2R rescued diabetes-induced cardiomyocyte necroptosis and heart dysfunction, whereas cardiac knockout of Bach2 diminished CB2R-mediated beneficial effects. In human diabetic hearts, both CB2R and BACH2 were negatively associated with diabetes-induced myocardial injuries. CONCLUSIONS: CB2R transcriptionally repressed necroptosis through interaction with BACH2; in turn, MLKL formed a negative feedback to phosphorylate CB2R. Our study provides the integrative view of a novel molecular mechanism loop for regulation of necroptosis centered by CB2R, which represents a promising alternative strategy for controlling diabetic heart dysfunction.

Evaluation of the Influence of Flavor Characteristics of Cooked Bacon with Different Sterilization Methods by GC-IMS Combined with HS-SPME-GC-MS and Electronic Nose.

This study investigated the impact of high pressure and temperature (HTHP) and electron-beam irradiations (3, 5, 7, and 9 kGy) using differences in two sterilization methods on the volatile compounds and sensory characteristics of cooked bacon. It showed that 7 and 9 kGy of irradiation caused a significant reduction in species of volatile compounds and sensory features, but the concentration of total ketones, alcohols, aldehydes, acids and aromatic hydrocarbons significantly increased at 9 kGy. Samples treated with a dose of less than 5 kGy did not change volatile compounds and sensory properties. High-temperature-high-pressure conditions could greatly impact the concentrations of volatile compound species and sensory traits. The electronic nose effectively detected the flavor difference in different sterilization methods. Fingerprinting showed that HTHP and 9-kGy-treated groups were significantly different from other treatments. This study inferred that 5 kGy might be optimal for maintaining the original flavor and sensory properties of cooked bacon.

Protections of transcription factor BACH2 and natural product myricetin against pathological cardiac hypertrophy and dysfunction.

Pathological hypertrophic myocardium under consistent adverse stimuli eventually can cause heart failure. This study aims to explore the role of BACH2, a member of the basic region leucine zipper transcription factor family, in cardiac hypertrophy and failure. Transverse aortic constriction surgery was operated to induce cardiac hypertrophy and failure in mice. BACH2 was overexpressed in mice through tail vein injection of AAV9-Bach2. Mice with systemic or cardiac-specific knockdown of Bach2 were adopted. Neonatal rat ventricular myocytes (NRVMs) were isolated and infected with lentivirus to overexpress Bach2 or transfected with siRNA to knock down Bach2. Our data showed that overexpression of BACH2 ameliorated TAC-induced cardiac hypertrophy and failure in mice and decreased isoproterenol (ISO)-triggered myocyte hypertrophy in NRVMs. Systemic or cardiac-specific knockdown of Bach2 worsened the cardiac hypertrophy and failure phenotype in mice. Further assays showed that BACH2 bound to the promotor region of Akap6 at the -600 to -587 site and repressed its expression, which functioned as a crucial scaffold for cardiac hypertrophy and failure signaling pathways. Small molecular natural product library screening suggested that myricetin could up-regulate expression of Bach2 and simultaneously suppress the transcriptional levels of hypertrophic marker genes Bnp and Myh7. Further studies showed that myricetin exerted a BACH2-dependent protective effect against cardiac hypertrophy in vivo and in vitro. Taken together, our findings demonstrated that BACH2 plays a crucial role in the regulation of cardiac hypertrophy and failure and can be a potential therapeutic target in the future.

Surgically Induced Cardiac Volume Overload by Aortic Regurgitation in Mouse.

Aortic regurgitation (AR) is a common valvular heart disease that exerts volume overload on the heart and represents a global public health problem. Although mice are widely applied to shed light on the mechanisms of cardiovascular disease, mouse models of AR, especially those induced by surgery, are still paucity. Here, a mouse model of AR was described in detail which is surgically induced by disruption of the aortic valves under high-resolution echocardiography. In accordance with regurgitated blood flow, AR mouse hearts present a distinctive and clinically relevant volume overload phenotype, which is characterized by eccentric hypertrophy and cardiac dysfunction, as evidenced by echocardiographic and invasive hemodynamic evaluation. Our proposal, in a reliable and reproducible manner, provides a practical guide on the establishment and assessment of a mouse model of AR for future studies on molecular mechanisms and therapeutic targets of volume overload cardiomyopathy.

N4-acetylcytidine regulates the replication and pathogenicity of enterovirus 71.

Chemical modifications are important for RNA function and metabolism. N4-acetylcytidine (ac4C) is critical for the translation and stability of mRNA. Although ac4C is found in RNA viruses, the detailed mechanisms through which ac4C affects viral replication are unclear. Here, we reported that the 5' untranslated region of the enterovirus 71 (EV71) genome was ac4C modified by the host acetyltransferase NAT10. Inhibition of NAT10 and mutation of the ac4C sites within the internal ribosomal entry site (IRES) suppressed EV71 replication. ac4C enhanced viral RNA translation via selective recruitment of PCBP2 to the IRES and boosted RNA stability. Additionally, ac4C increased the binding of RNA-dependent RNA polymerase (3D) to viral RNA. Notably, ac4C-deficient mutant EV71 showed reduced pathogenicity in vivo. Our findings highlighted the essential role of ac4C in EV71 infection and provided insights into potential antiviral treatments.

Sintering Quality Prediction Model Based on Semi-Supervised Dynamic Time Feature Extraction Framework.

In the sintering process, it is difficult to obtain the key quality variables in real time, so there is lack of real-time information to guide the production process. Furthermore, these labeled data are too few, resulting in poor performance of conventional soft sensor models. Therefore, a novel semi-supervised dynamic feature extraction framework (SS-DTFEE) based on sequence pre-training and fine-tuning is proposed in this paper. Firstly, based on the DTFEE model, the time features of the sequences are extended and extracted. Secondly, a novel weighted bidirectional LSTM unit (BiLSTM) is designed to extract the latent variables of original sequence data. Based on improved BiLSTM, an encoder-decoder model is designed as a pre-training model with unsupervised learning to obtain the hidden information in the process. Next, through model migration and fine-tuning strategy, the prediction performance of labeled datasets is improved. The proposed method is applied in the actual sintering process to estimate the FeO content, which shows a significant improvement of the prediction accuracy, compared to traditional methods.

Predicting Tumor Mutational Burden From Lung Adenocarcinoma Histopathological Images Using Deep Learning.

Tumor mutation burden (TMB) is an important biomarker for tumor immunotherapy. It plays an important role in the clinical treatment process, but the gold standard measurement of TMB is based on whole exome sequencing (WES). WES cannot be done in most hospitals due to its high cost, long turnaround times and operational complexity. To seek out a better method to evaluate TMB, we divided the patients with lung adenocarcinoma (LUAD) in TCGA into two groups according to the TMB value, then analyzed the differences of clinical characteristics and gene expression between the two groups. We further explored the possibility of using histopathological images to predict TMB status, and developed a deep learning model to predict TMB based on histopathological images of LUAD. In the 5-fold cross-validation, the area under the receiver operating characteristic (ROC) curve (AUC) of the model was 0.64. This study showed that it is possible to use deep learning to predict genomic features from histopathological images, though the prediction accuracy was relatively low. The study opens up a new way to explore the relationship between genes and phenotypes.

Consistent Optimization of Blast Furnace Ironmaking Process Based on Controllability Assurance Soft Sensor Modeling.

The blast furnace ironmaking process is the core of steel manufacturing, and the optimization of this process can bring enormous economic and environmental benefits. However, previous data-driven optimization methods neglect the uncontrollability of part of the variables in the predictive modeling process, which brings great uncertainty to the optimization results and adversely affects the optimization effect. To address this problem, a consistency optimization framework based on controllability assurance soft sensor modeling is proposed. The method achieves the information extraction of uncontrollable variables in a process-supervised way, and improves the posterior distribution prediction accuracy. The method also proposes an integrated self-encoder regression module, which uses the regression to guide the encoding, realize the construction of latent features, and further improve the prediction accuracy of the model. Integrating the prediction module and the multi-objective gray wolf optimizer, the proposed model achieves the optimization of the blast furnace ironmaking process with only controllable variables as prediction model inputs while being capable of giving uncertainty estimates of the solutions. Empirical data validated the optimization model and demonstrated the effectiveness of the proposed algorithm.

Fault Detection and Isolation of Non-Gaussian and Nonlinear Processes Based on Statistics Pattern Analysis and the k-Nearest Neighbor Method.

Only low-order information of process data (i.e., mean, variance, and covariance) was considered in the principal component analysis (PCA)-based process monitoring method. Consequently, it cannot deal with continuous processes with strong dynamics, nonlinearity, and non-Gaussianity. To this aim, the statistics pattern analysis (SPA)-based process monitoring method achieves better monitoring results by extracting higher-order statistics (HOS) of the process variables. However, the extracted statistics do not strictly follow a Gaussian distribution, making the estimated control limits in Hotelling-T 2 and squared prediction error (SPE) charts inaccurate, resulting in unsatisfactory monitoring performance. In order to solve this problem, this paper presents a novel process monitoring method using SPA and the k-nearest neighbor algorithm. In the proposed method, first, the statistics of process variables are calculated through SPA. Then, the k-nearest neighbor (kNN) method is used to monitor the extracted statistics. The kNN method only uses the paired distance of samples to perform fault detection. It has no strict requirements for data distribution. Hence, the proposed method can overcome the problems caused by the non-Gaussianity and nonlinearity of statistics. In addition, the potential of the proposed method in early fault detection or safety alarm and fault isolation is explored. The proposed method can isolate which variable or its statistic is faulty. Finally, the numerical examples and Tennessee Eastman benchmark process illustrate the effectiveness of the proposed method.

Erratum: Cardiomyocyte-Restricted Low Density Lipoprotein Receptor-Related Protein 6 (LRP6) Deletion Leads to Lethal Dilated Cardiomyopathy Partly Through Drp1 Signaling: Erratum.

[This corrects the article DOI: 10.7150/thno.22177.].