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The pattern and scale of commerce worldwide have been greatly transformed by the Fourth Industrial Revolution and technological advancement; digital trade has become the primary form of trade in the digital economy. On the basis of information network infrastructure, information technology level, digital industrialization level, and industrial digitalization level, this study establishes a comprehensive assessment system that applies an entropy–TOPSIS model to evaluate digital trade development level in China. The results indicate that digital trade in China was steadily growing between 2010 and 2019. A principal component analysis is conducted to identify factors affecting the digital trade development level in China. The analysis results suggest that Internet development, population income, industrial structure, payment convenience level, fixed asset investment, online transaction scale, and economic development all have positive effects on the digital trade development level in China, with payment convenience level having the greatest influence. By contrast, state intervention and degree of dependence on foreign trade have a negative effect on digital trade development.

To date, the underlying mechanisms involved intervertebral disc degeneration (IDD) remain unclear, which has hindered the development of molecular biological therapy for IDD. Autophagy is vital for intracellular quality control and metabolic balance in intervertebral disc cells. Hence, autophagy homeostasis is important. Emerging evidence has implicated vitamin D (VD) and the vitamin D receptor (VDR) in IDD progression because of their effects on different autophagy steps. However, the results of clinical trials in which VD supplementation was assessed as a treatment for IDD are controversial. Furthermore, experimental studies on the interplay between VD/VDR and autophagy are still in their infancy. In view of the significance of the crosstalk between VD/VDR and autophagy components, this review focuses on the latest research on VD/VDR modulation in autophagy and investigates the possible regulatory mechanisms. This article will deepen our understanding of the relationship between VD/VDR and autophagy and suggests novel strategies for IDD prevention and treatment.

Summary: Background: Childhood neurodevelopmental disorders, including autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD), and Tourette syndrome (TS), comprise a major cause of health-related disabilities in children. However, biomarkers towards pathogenesis or novel drug targets are still limited. Our study aims to provide a comprehensive investigation of the causal effects of the plasma proteome on ASD, ADHD, and TS using the two-sample Mendelian Randomization (MR) approach. Methods: Genetic associations with 2994 plasma proteins were selected as exposures and genome-wide association data of ASD, ADHD, TS were utilized as outcomes. MR analyses were carried out using the inverse-variance weighted method, and the MR-Egger and weighted median methods were used for sensitivity analysis. Findings: Using single-nucleotide polymorphisms as instruments, the study suggested increased levels of MAPKAPK3 (OR: 1.09; 95% CI: 1.05–1.13; P = 1.43 × 10−6) and MRPL33 (OR: 1.07; 95% CI: 1.04–1.11; P = 5.37 × 10−6) were causally associated with a higher risk of ASD, and increased MANBA level was associated with a lower risk of ADHD (OR: 0.91; 95% CI: 0.88–0.95; P = 8.97 × 10−6). The causal associations were robust in sensitivity analysis, leave-one-out analysis and Multivariable MR, and no pleiotropy was observed. No significant risk protein was identified for TS. Interpretation: The study findings support the idea that the MAPK/ERK signaling pathway and mitochondrial dysfunction are involved in the pathogenesis of ASD, while a deficiency in beta-mannosidase might play a role in the development of ADHD.

We present a comprehensive analysis of the loop induced top quark FCNC signals at the LHC within one class of the simplified model. The loop level FCNC interactions are well motivated to avoid the hierarchy of the top quark couplings from the new physics and standard model. Such a theory will posit a Majorana dark matter candidate and could be tested through dark matter relic density, direct detection experiments (the scattering between dark matter and heavy nuclei), and the collider signals at the LHC. We find that the spin-independent (SI) scattering between Majorana dark matter and nuclei will vanish at the leading order, while the next-to-leading order correction to the SI scattering becomes significant to constrain the parameter space of the model. A detailed comparison between direct detection experiments and LHC searches is also discussed and both of them are very important to fully constrain the model.

Objectives:The purpose of our study was to investigate the effect of objective sleep characteristics on the incidence of depression.MethodsThe participants of our study (1,595 men and 1,780 women with 63.1 ± 10.7 years) were selected from the Sleep Heart Health Study (SHHS) datasets. Depression was defined as the first occurrence between SHHS visit 1 and visit 2. Objective sleep characteristics, including sleep efficiency (SE), wake after sleep onset (WASO), sleep fragmentation index (SFI) and arousal index (ArI), were monitored by polysomnography. Multivariable logistic regression was used to explore the relationship between sleep characteristics and depression.ResultsA total of 248 patients with depression (7.3%) were observed between SHHS visits 1 and 2. After adjusting for covariates, SE (odds ratio [OR], 0.891; 95% confidence interval [CI] 0.811–0.978; P = 0.016) and WASO (OR, 1.021; 95% CI 1.002–1.039; P = 0.026) were associated with the incidence of depression. Moreover, the relationship between SE and depression was more pronounced in men (OR, 0.820; 95% CI 0.711–0.946; P = 0.007) than in women (OR, 0.950; 95% CI 0.838–1.078; P = 0.429) in subgroup analysis (Pinteraction < 0.05).ConclusionsSE and WASO may be markers for the incidence of depression. The association between SE and depression was intensified in men.

ObjectiveAberrant activation of Wnt/β-catenin signaling contributes to the maintenance of cancer stem cells and chemoresistance in colorectal cancer (CRC). Retinoic acid-induced 2 (RAI2) was proved to be a tumor suppressor in CRC in our previous report. In this study, the role of RAI2 in Wnt/β-catenin signaling was further investigated.MethodsAs a transcriptional co-regulator, C-terminal Binding Protein 2 (CtBP2) was reported to be involved in Wnt signaling in multiple and complex ways. The correlation of RAI2 and CtBP2 in CRC was analyzed by TCGA dataset, and the interaction between RAI2 and CtBP2 was explored by co-immunoprecipitation (Co-IP) in CRC cells. The effect of RAI2 on the activity of Wnt signaling and the location of β-catenin was detected by Dual-Luciferase reporter assay and Immunofluorescence respectively. Western blotting analysis was performed to detect the expression of target genes involved in Wnt signaling. Sphere formation assay was employed to detect the effect of RAI2 on stem cell like properties. Cell viability assay was used to detect the chemosensitivity of cells before and after transfection of RAI2.ResultsThe interaction between RAI2 and CtBP2 was confirmed by Co-IP in CRC cells. Besides, the negative correlation of RAI2 and CtBP2 in CRC was found by analyzing the TCGA dataset. Re-expression of RAI2 in human colon cancer cells (HCT116 and LoVo) suppressed the fluorescent activity of Wnt signaling, increased the phosphorylation and inhibited nuclear translocation of β-catenin, with down-regulation of target genes like c-Myc, CyclinD1, ASCL2, and LGR5. In contrast, the mutated RAI2, which can’t interact with CtBP2, has no above effects. We observed low expression of RAI2 in 33.89% (101/298) of CRC patients, which was significantly associated with reduced phosphorylation of β-catenin (r=0.8866, P

Schizophrenia (SCZ) is associated with several immune dysfunctions, including elevated levels of pro-inflammatory cytokines. Microorganisms and their metabolites have been found to regulate the immune system, and that intestinal microbiota is significantly disturbed in schizophrenic patients. To systematically investigate aberrant gut-metabolome-immune network in schizophrenia, we performed an integrative analysis of intestinal microbiota, serum metabolome, and serum inflammatory cytokines in 63 SCZ patients and 57 healthy controls using a multi-omics strategy. Eighteen differentially abundant metabolite clusters were altered in patients displayed higher cytokine levels, with a significant increase in pro-inflammatory metabolites and a significant decrease in anti-inflammatory metabolites (such as oleic acid and linolenic acid). The bacterial co-abundance groups in the gut displayed more numerous and stronger correlations with circulating metabolites than with cytokines. By integrating these data, we identified that certain bacteria might affect inflammatory cytokines by modulating host metabolites, such as amino acids and fatty acids. A random forest model was constructed based on omics data, and seven serum metabolites significantly associated with cytokines and α-diversity of intestinal microbiota were able to accurately distinguish the cases from the controls with an area under the receiver operating characteristic curve of 0.99. Our results indicated aberrant gut-metabolome-immune network in SCZ and gut microbiota may influence immune responses by regulating host metabolic processes. These findings suggest a mechanism by which microbial-derived metabolites regulated inflammatory cytokines and insights into the diagnosis and treatment of mental disorders from the microbial-immune system in the future.

Pancreatic ductal adenocarcinoma (PDAC) is among the leading causes of cancer mortality, and new therapeutic options are urgently needed. Long noncoding RNA H19 (H19) is known to promote PDAC progression, but the downstream genes of H19 are largely unknown. Five PDAC cell lines, nonmalignant pancreatic cells, TCGA, GEO-derived pancreatic tissues (malignant, n=413; nonmalignant, n=234), a pancreatic tissue array (n=96), and pancreatic tissues from our clinic (malignant, n=20; nonmalignant, n=20) were examined by a gene array, RT-qPCR, Western blotting, MTT, colony formation, wound-healing, siRNA-mediated gene silencing, bioinformatics, xenotransplantation, and immunohistochemistry assays. The cell cycle inhibitor, UHMK1, was identified to have the strongest correlation with H19. UHMK1 expression was enhanced in PDAC, and high UHMK1 expression correlated with tumor stage, and lower overall survival. siRNA-mediated UHMK1 downregulation inhibited progression signaling. siRNA-mediated downregulation of H19 or UHMK1 inhibited tumor proliferation and xenograft growth. Based on the correlation between UHMK1 expression and clinical parameters, we developed a nomogram that reliably predicts patient prognosis and overall survival. Together, we characterized UHMK1 as an H19-induced oncogene and verified it as a novel PDAC prognostic marker for overall survival.

Many epidemiological reports have indicated an increase in the incidence of breast cancer among psychotic patients, suggesting that the targets of antipsychotics, neurotransmitter receptors, may have a role in tumorigenesis. However, the functions of neurotransmitter receptors in cancer are barely known. Here, we analyzed 44 neurotransmitter receptors in breast cancer and revealed that the expression of 34 receptors was positively correlated with relapse-free survival rates (RFS) of patients using the public database (n = 3951). Among all these receptors, we revealed decreased expression of HTR6 in human advanced breast cancer versus tumors in situ using our original data (n = 44). After a pan-cancer analysis including 22 cancers (n = 11262), we disclosed that HTR6 was expressed in 12 tumors and uncovered its influence on survival in seven tumors. Using multi-omics datasets from Linkedomics, we revealed a potential regulatory role of HTR6 in MAPK, JUN, and leukocyte-differentiation pathways through enriching 294 co-expressed phosphorylated proteins of HTR6. Furthermore, we proclaimed a close association of HTR6 expression with the immune microenvironment. Finally, we uncovered two possible reasons for HTR6 down-regulation in breast cancer, including deep deletion in the genome and the up-regulation of FOXA1 in breast cancer, which was a potential negatively regulatory transcription factor of HTR6. Taken together, we revealed a new function of neurotransmitter receptors in breast cancer and identified HTR6 as a survival-related gene potentially regulating the immune microenvironment. The findings in our study would improve our understanding of the pathogenesis of breast cancer and provided a theoretical basis for personalized medication in psychotic patients.

Purpose: To investigate the role of the mouse double minute 2 (MDM2) gene single-nucleotide polymorphism (SNP) T309G in the development of epimacular membranes (EMMs) by analyzing the genotype distribution and consistency of the polymorphism in paired membrane-blood samples.Methods: This was a cross–sectional genetic association study of patients with proliferative vitreoretinopathy (PVR) or EMMs. PVR membranes (PVRMs), internal limiting membranes (ILMs) (PVR-ILMs) and blood samples (PVR-blood) from patients with PVR, and EMMs, EMM-ILMs and EMM-blood from patients with EMMs were collected. The genotype of all samples was determined by Sanger sequencing. Sex composition, mean age, the genotype distribution of MDM2 T309G, the allelic frequency of the MDM2 SNP309 G allele (% G) and the somatic mutation rate at the MDM2 T309G locus (% M) were analyzed and compared. The PVR and healthy Chinese donor groups were used as controls for different comparisons.Results: The EMM group of 62 patients was older than the PVR group of 61 patients by an average of 8.87 years (p < 0.0001), but the two groups were statistically similar in the sex composition (p = 0.1754). Importantly, G allele carriers were at a higher risk of developing EMMs than non-G allele carriers (p = 0.0479; OR = 2.047). Moreover, EMM-blood exhibited a significantly higher % G than blood samples from healthy Chinese donors (EMM-blood: 56.78%, donors: 45.61%; p = 0.0256; OR = 1.567). Regarding membrane-blood consistency, % M was significantly different between PVRMs and EMMs (PVRMs: 2.63%, EMMs: 21.57%; p = 0.0097; OR = 10.18) but not between different types of ILMs (PVR-ILMs: 18.18%, EMM-ILMs: 29.17%; p = 0.6855). Furthermore, EMMs (p = 0.0053; OR = 8.250) and EMM-ILMs (p = 0.0233; OR = 14.40) from patients with preoperative macular holes were more predisposed toward somatic mutations at the MDM2 T309G locus than those from patients without preoperative macular holes.Conclusions:MDM2 T309G is associated with the development of EMMs. Herein, the MDM2 SNP309 G allele is first reported as an associated factor of EMMs in a Chinese population. In addition, EMMs and ILMs are genetically unstable at the MDM2 T309G locus, especially when complicated with preoperative macular holes.

Inefficient differentiation and insufficient maturation are barriers to the application of human pluripotent stem cell (hPSC)-derived cardiomyocytes (CMs) for research and therapy. Great strides have been made to the former, and multiple groups have reported cardiac differentiation protocol that can generate hPSC-CMs at high efficiency. Although many such protocols are based on the modulation of the WNT signaling pathway, they differ in their timing and in the WNT inhibitors used. Little is currently known about whether and how conditions of differentiation affect cardiac maturation. Here we adapted multiple cardiac differentiation protocols to improve cost-effectiveness and consistency, and compared the properties of the hPSC-CMs generated. Our results showed that the schedule of differentiation, but not the choice of WNT inhibitors, was a critical determinant not only of differentiation efficiency, which was expected, but also CM maturation. Among cultures with comparable purity, hPSC-CMs generated with different differentiation schedules vary in the expression of genes which are important for developmental maturation, and in their structural, metabolic, calcium transient and proliferative properties. In summary, we demonstrated that simple changes in the schedule of cardiac differentiation could promote maturation. To this end, we have optimized a cardiac differentiation protocol that can simultaneously achieve high differentiation efficiency and enhanced developmental maturation. Our findings would advance the production of hPSC-CMs for research and therapy.

ObjectivesRapid eye movement (REM) sleep is closely related to all-cause mortality. The aim of this study is to explore the role of REM sleep on the incident heart failure (HF).MethodsWe selected 4490 participants (2480 women and 2010 men; mean age, 63.2 ± 11.0 years) from the Sleep Heart Health Study. HF was identified as the first occurrence during a mean follow-up period of 10.9 years. REM sleep including percentage of REM sleep and total REM sleep time were monitored using in-home polysomnography at baseline. Multivariable Cox regression analysis was utilized to explore the relationship between REM sleep and HF.ResultsIn total, 436 (9.7%) cases of HF were observed during the entire follow-up period. After adjusting for potential covariates, an increased percentage of REM sleep (per 5%) was independently associated with a reduced incidence of HF [hazard ratio (HR) 0.88, 95% confidence interval (CI) 0.82–0.94, P < 0.001]. A similar result was also found between total REM sleep time (increased per 5 min) and incident HF (HR 0.97, 95% CI 0.95–0.99, P < 0.001). Moreover, the fourth quartile of both percentage of REM sleep (HR 0.65, 95% CI 0.48–0.88, P = 0.005) and total REM sleep time (HR 0.64, 95% CI 0.45–0.90, P = 0.010) had lower risk of incident HF when compared with the first quartile.ConclusionAn increased percentage of REM sleep and total REM sleep time were associated with a reduced risk of HF. REM sleep may be a predictor of the incident HF.Clinical Trial Registration[ClinicalTrials.gov], identifier [NCT00005275].

Abstract Genetic heterogeneity of tumor is closely related to its clonal evolution, phenotypic diversity and treatment resistance, and such heterogeneity has only been characterized at single-cell sub-chromosomal scale in liver cancer. Here we reconstructed the single-variant resolution clonal evolution in human liver cancer based on single-cell mutational profiles. The results indicated that key genetic events occurred early during tumorigenesis, and an early metastasis followed by independent evolution was observed in primary liver tumor and intrahepatic metastatic portal vein tumor thrombus. By parallel single-cell RNA-Seq, the transcriptomic phenotype of HCC was found to be related with genetic heterogeneity. For the first time we reconstructed the single-cell and single-variant clonal evolution in human liver cancer, and dissection of both genetic and phenotypic heterogeneity will facilitate better understanding of their relationship.

Abstract Intelligence predicts important life and health outcomes, but the biological mechanisms underlying differences in intelligence are not yet understood. The use of genetically determined metabotypes (GDMs) to understand the role of genetic and environmental factors, and their interactions, in human complex traits has been recently proposed. However, this strategy has not been applied to human intelligence. Here we implemented a two-sample Mendelian randomization (MR) analysis using GDMs to assess the causal relationships between genetically determined metabolites and human intelligence. The standard inverse-variance weighted (IVW) method was used for the primary MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Using 25 genetic variants as instrumental variables (IVs), our study found that 5-oxoproline was associated with better performance in human intelligence tests (PIVW = 9.25 × 10–5). The causal relationship was robust when sensitivity analyses were applied (PMR-Egger = 0.0001, PWeighted median = 6.29 × 10–6, PMR-PRESSO = 0.0007), and repeated analysis yielded consistent result (PIVW = 0.0087). Similarly, also dihomo-linoleate (20:2n6) and p-acetamidophenylglucuronide showed robust association with intelligence. Our study provides novel insight by integrating genomics and metabolomics to estimate causal effects of genetically determined metabolites on human intelligence, which help to understanding of the biological mechanisms related to human intelligence.

Abstract Macroautophagy/autophagy is a highly conserved self-digestion pathway that plays an important role in cytoprotection under stress conditions. Autophagy is involved in hepatotoxicity induced by acetaminophen (APAP) in experimental animals and in humans. APAP also causes ototoxicity. However, the role of autophagy in APAP-induced auditory hair cell damage is unclear. In the present study, we investigated autophagy mechanisms during APAP-induced cell death in a mouse auditory cell line (HEI-OC1) and mouse cochlear explant culture. We found that the expression of LC3-II protein and autophagic structures was increased in APAP-treated HEI-OC1 cells; however, the degradation of SQSTM1/p62 protein, the yellow puncta of mRFP-GFP-LC3 fluorescence, and the activity of lysosomal enzymes decreased in APAP-treated HEI-OC1 cells. The degradation of p62 protein and the expression of lysosomal enzymes also decreased in APAP-treated mouse cochlear explants. These data indicate that APAP treatment compromises autophagic degradation and causes lysosomal dysfunction. We suggest that lysosomal dysfunction may be directly responsible for APAP-induced autophagy impairment. Treatment with antioxidant N-acetylcysteine (NAC) partially alleviated APAP-induced autophagy impairment and apoptotic cell death, suggesting the involvement of oxidative stress in APAP-induced autophagy impairment. Inhibition of autophagy by knocking down of Atg5 and Atg7 aggravated APAP-induced ER and oxidative stress and increased apoptotic cell death. This study provides a better understanding of the mechanism responsible for APAP ototoxicity, which is important for future exploration of treatment strategies for the prevention of hearing loss caused by ototoxic medications.

Tracking trajectory with high precision under wind perturbations is a difficult problem of a quadrotor. In response to this problem, a novel wind perturbation estimator using neural network is proposed. The structure of wind estimator is designed based on deep understanding of a quadrotor, and training process is optimized to solve overfitting problem in the presence of sensor noise. With the consideration of wind perturbations and rotor dynamics, cascaded Lyapunov functions are used to derive full backstepping controller. Compared with traditional wind estimator, the proposed estimator is simple to be carried out and shows better robustness to sensor noise. To the best of our knowledge, the proposed controller is more robust to wind with less power cost than existing controllers. A series of simulations show the process to optimize wind estimator, and comparison between different controllers demonstrates that the proposed controller is robust to wind and energy-efficient. Finally, experiments have strengthened the effectiveness of our proposed method.

We present the development of an As2S3 fiber-based reusable inline optical connector; and, for the first time to the best of our knowledge, integrated it into a 2 μm chirped pulse amplification system as the pulse stretcher. By this mechanism, a near 20 times pulse stretching ratio was achieved in 0.5 m-long this As2S3 fiber and the introduction of insertion loss as low as 2.84 dB while it was connected with silica fiber. After the follow-up fiber amplification and self-compression mechanism, the laser average output power was boosted to 1.97 W and pulse duration was optimized to 2.53 ps. Moreover, to further inspect the laser pulse property, the pulses were then delivered into a 5.3 m-long ZrF4-BaF2-LaF3-AlF3-NaF (ZBLAN) fiber which was fusion spliced to SM1950 fiber. Thanks to the 0.4-dB low fusion splice loss between these fibers, a 1.56-W supercontinuum source with bandwidth of 1.93-3.50 μm is obtained. The measured two hours of root-mean-square value of power fluctuation of this laser source is 0.13%, indicating an ultra-high long-term power stability. This work will lay a solid foundation in the realization of the all-fiber structured high-power thulium-doped fiber amplifier with high compactness.

The spatiotemporal scan statistics proposed by Kulldorff have been applied to detect numerous disease clusters, and scan statistics based on heuristic algorithm optimization have also been utilized for disease cluster detection. The gravitational search algorithm (GSA) and the recent human mental search (HMS) possess superior performance in comparison with several heuristic algorithms, and neither algorithm has yet been applied in spatiotemporal scan statistics. However, the size of the spatiotemporal scanning window utilized in disease applications is constant in the time dimension, and it is difficult to detect changes in the size of an anomalous cluster over time. In this study, we proposed a dynamic cylinder with a variable radius as a spatiotemporal scanning window. In addition, we proposed an improved GSA based on mental search (MSGSA), and the MSGSA was utilized to optimize the dynamic scanning window to detect spatiotemporally anomalous clusters. The performance of the MSGSA was verified on 23 benchmark functions in comparison with the GSA and HMS. Simulated experiments based on the MSGSA and SaTScan showed that the MSGSA-optimized dynamic window yielded better performance based on the obtained accuracies and error rates. Finally, we utilized the MSGSA-optimized dynamic window and other methods to detect spatiotemporally anomalous clusters of hand-foot-and-mouth disease (HFMD) in China (2016) and Guangdong (2009), and the MSGSA-optimized dynamic window yielded better performance on both HFMD datasets. Moreover, the conclusions obtained with the MSGSA-optimized dynamic window were consistent with those of relevant researchers, indicating that the MSGSA possesses certain disease outbreak detection ability.

Abstract Mesenchymal stem cell (MSC)-based therapy has emerged as a novel strategy to treat many degenerative diseases. Accumulating evidence shows that the function of MSCs declines with age, thus limiting their regenerative capacity. Nonetheless, the underlying mechanisms that control MSC ageing are not well understood. We show that compared with bone marrow-MSCs (BM-MSCs) isolated from young and aged samples, NADH dehydrogenase (ubiquinone) iron-sulfur protein 6 (Ndufs6) is depressed in aged MSCs. Similar to that of Ndufs6 knockout (Ndufs6−/−) mice, MSCs exhibited a reduced self-renewal and differentiation capacity with a tendency to senescence in the presence of an increased p53/p21 level. Downregulation of Ndufs6 by siRNA also accelerated progression of wild-type BM-MSCs to an aged state. In contrast, replenishment of Ndufs6 in Ndufs6−/−-BM-MSCs significantly rejuvenated senescent cells and restored their proliferative ability. Compared with BM-MSCs, Ndufs6−/−-BM-MSCs displayed increased intracellular and mitochondrial reactive oxygen species (ROS), and decreased mitochondrial membrane potential. Treatment of Ndufs6−/−-BM-MSCs with mitochondrial ROS inhibitor Mito-TEMPO notably reversed the cellular senescence and reduced the increased p53/p21 level. We provide direct evidence that impairment of mitochondrial Ndufs6 is a putative accelerator of adult stem cell ageing that is associated with excessive ROS accumulation and upregulation of p53/p21. It also indicates that manipulation of mitochondrial function is critical and can effectively protect adult stem cells against senescence.

Hexagonal boron nitride (h-BN) flakes have been widely used due to their excellent physical and chemical properties. Here, thermal-induced wrinkles of thin h-BN flakes deposited on silicon dioxide substrate were investigated through a combination of atomic force microscopy (AFM) and Raman spectroscopy. The experimental results indicated that the wrinkles did not occur at relatively low annealing temperatures and were detected at temperatures as high as 500 °C or even 600 °C. When repeatedly annealed at high temperatures, the number and positions of the wrinkles also changed. From the Raman spectra, the wrinkles were caused by the fact that the h-BN contraction rate was faster than that of the substrate at the cooling stage due to the interfacial sliding between the flake and the substrate and the h-BN flake of 7 nm thickness recovered to the original length at 150 °C. Further cooling introduced the compressive stress and then the wrinkles appeared. Moreover, it was found that if there was a crack in the h-BN flake, the wrinkle always appeared at the crack. Our findings appeal the mechanism of thermal-induced wrinkles of h-BN flakes and help us to research their applications as substrate materials in electronic devices in a high-temperature environment.

Inspired by the bamboo growth process, Chu et al. proposed the Bamboo Forest Growth Optimization (BFGO) algorithm. It incorporates bamboo whip extension and bamboo shoot growth into the optimization process. It can be applied very well to classical engineering problems. However, binary values can only take 0 or 1, and for some binary optimization problems, the standard BFGO is not applicable. This paper firstly proposes a binary version of BFGO, called BBFGO. By analyzing the search space of BFGO under binary conditions, the new curve V-shaped and Taper-shaped transfer function for converting continuous values into binary BFGO is proposed for the first time. A long-mutation strategy with a new mutation approach is presented to solve the algorithmic stagnation problem. Binary BFGO and the long-mutation strategy with a new mutation are tested on 23 benchmark test functions. The experimental results show that binary BFGO achieves better results in solving the optimal values and convergence speed, and the variation strategy can significantly enhance the algorithm’s performance. In terms of application, 12 data sets derived from the UCI machine learning repository are selected for feature-selection implementation and compared with the transfer functions used by BGWO-a, BPSO-TVMS and BQUATRE, which demonstrates binary BFGO algorithm’s potential to explore the attribute space and choose the most significant features for classification issues.

In this study, the mitochondrial genome of Luperomorpha xanthodera was assembled and annotated, which is a circular DNA molecule including 13 protein-coding genes (PCGs), 22 transfer RNA (tRNA) genes, 2 ribosomal RNA genes (12S rRNA and 16S rRNA), and 1388 bp non-coding regions (A + T rich region), measuring 16,021 bp in length. The nucleotide composition of the mitochondrial genome is 41.3% adenine (A), 38.7% thymine (T), 8.4% guanine (G), and 11.6% cytosine (C). Most of the protein-coding genes presented a typical ATN start codon (ATA, ATT, ATC, ATG), except for ND1, which showed the start codon TTG. Three-quarters of the protein-coding genes showed the complete stop codon TAR (TAA, TAG), except the genes COI, COII, ND4, and ND5, which showed incomplete stop codons (T- or TA-). All the tRNA genes have the typical clover-leaf structure, except tRNASer1 (AGN), which has a missing dihydrouridine arm (DHU). The phylogenetic results determined by both maximum likelihood and Bayesian inference methods consistently supported the monophyly of the subfamily Galerucinae and revealed that the subtribe Luperina and genus Monolepta are polyphyletic groups. Meanwhile, the classification status of the genus Luperomorpha is controversial.

In recent years, atomic force microscopes have been used for cell transfection because of their high-precision micro-indentation mode; however, the insertion efficiency of the tip of AFM into cells is extremely low. In this study, NIH3T3 mouse fibroblast cells cultured on a flexible dish with micro-groove patterns were subjected to various substrate strains at 5%, 10%, 15%, and 20%. It was found that the cell stiffness depends on the prestress of the cell membrane, and that the insertion rate of AFM tips into the cell membrane is proportional to the stiffness through the AFM indentation experiment. The finite element analysis proves that prestress increases the bending stiffness of the cytoskeleton, allowing it to better support the cell membrane, which realizes the stress concentration in the contact area between the AFM tip and the cell membrane. The results indicate that the prestress contributes to the mechanical properties of the cell and suggest that the insertion efficiency could be greatly improved with an increase of the prestress of the cell membrane.

The heuristic optimization algorithm is a popular optimization method for solving optimization problems. A novel meta-heuristic algorithm was proposed in this paper, which is called the Willow Catkin Optimization (WCO) algorithm. It mainly consists of two processes: spreading seeds and aggregating seeds. In the first process, WCO tries to make the seeds explore the solution space to find the local optimal solutions. In the second process, it works to develop each optimal local solution and find the optimal global solution. In the experimental section, the performance of WCO is tested with 30 test functions from CEC 2017. WCO was applied in the Time Difference of Arrival and Frequency Difference of Arrival (TDOA-FDOA) co-localization problem of moving nodes in Wireless Sensor Networks (WSNs). Experimental results show the performance and applicability of the WCO algorithm.

Spodoptera litura is an important pest that seriously affects Asparagus officinalis production. To clarify the population characteristics and feeding preference of S. litura on different asparagus tissues, asparagus stems and leaves were selected as the research objects, related studies were conducted by constructing the life table and the feeding preference experiment. The results showed that S. litura could complete its development and reproduction normally on asparagus stems or leaves. Although the adult longevity and fecundity of S. litura on the two types of tissues were not significantly different, the development duration of larvae and pupae, and total preoviposition period on leaves were significantly longer than those raised on stems. The intrinsic rate of increase and finite rate of increase were 0.186 d−1 and 1.204 d−1 on stems, which were significantly higher than those fed on leaves (0.161 d−1 and 1.175 d−1). The mean generation time on stems (32.88 d) was significantly lower than on leaves (36.88 d). It indicated that stems were more suitable for its population growth. In the feeding preference, the third and fifth instar larvae preferred to feed on leaves, and other instar larvae (except for the sixth instar of 2.5 h) had no significant difference. These results will provide a theoretical reference for further research and forecasting and integrated control.

Increasing water shortages and environmental pollution from excess chemical nitrogen fertilizer use necessitate the development of irrigation-nitrogen conservation technology in oilseed flax production. Therefore, a two-year split-plot design experiment (2017–2018) was conducted with three types of irrigation (I) levels (no irrigation (I0), irrigation of 1200 m3 ha−1 (I1200), and 1800 m3 ha−1 (I1800)) as the main plot and three nitrogen (N) application rates (0 (N0), 60 (N60) and 120 (N120) kg N ha−1) as the subplot in Northwest China to determine the effects of irrigation and N rates on oilseed flax grain yield, yield components, water-use efficiency (WUE), and N partial factor productivity (NPFP). The results show that I1800 optimized the farmland water storage and water storage efficiency (WSE), which gave rise to greater above-ground biomass. Under I1800, the effective capsule (EC) number increased significantly with increasing irrigation amounts, which increased significantly with increasing nitrogen application rate (0–120 kg ha−1). Both irrigation and nitrogen indirectly affect GY by affecting EC; the highest grain yield was observed at the I1800N60 treatment, which increased by 69.04% and 22.80% in 2017 and 2018 compared with the I0N0 treatment, respectively. As a result, both irrigation and N affect grain yield by affecting soil water status, improving above-ground biomass, and finally affecting yield components. In addition, I1800N60 also obtained a higher WUE and the highest NPFP due to a higher grain yield and a lower N application rate. Hence, our study recommends that irrigation with 1800 m3 ha−1 coupled with 60 kg N ha−1 could be a promising strategy for synergistically improving oilseed flax WUE, grain yield and yield components within this semi-arid region.

Fe-based amorphous alloys have advantages of low iron loss and high effective permeability, which are widely used in sensors and actuators. Power efficiency is one of the most important indicators among power conversion applications. We compared the magnetomechancial power conversion factors of metallic glassy ribbons FeCoSiB (Vitrovac 7600) and FeSiB (Metglas 2605SA1). We investigated the crystallization process under different annealing temperatures and tested the magnetomechancial coupling factors (k) and quality factors (Q) by using resonant and anti-resonant methods. We found that the maximum coupling factor of the annealed Vitrovac ribbons was 23% and the figure of merits k2Q was 4–7; however, the maximum coupling factor of the annealed Metglas ribbons was 73% and the maximum value of k2Q was 16. We can observe that the Metglas 2605SA1 ribbons have higher values of the magnetomechanical power efficiency than those of the Vitrovac 7600 ribbons, which means they are better to be used in subsequent research regarding acoustically driven antennas.

Abstract The emergence and transmission of the mobile colistin resistance gene (mcr-1) threatened the extensive use of polymyxin antimicrobials. Accumulated evidence showed that the banning of colistin additive in livestock feed efficiently reduce mcr-1 prevalence, not only in animals but also in humans and environments. However, our previous study has revealed that a small proportion of Escherichia coli could continually carry chromosomally-encoded mcr-1. The chromosomally-encoded events, indicated the existence of stabilized heritage of mcr-1 and revealed a potential threat in the antimicrobial stewardship interventions, are yet to be investigated. In this study, we systematically investigated the genetic basis of chromosomally-encoded mcr-1 in prevalence and potential mechanisms of lineage, plasmid, insertion sequence, and phage. Our results demonstrated that the emergence of chromosomally-encoded mcr-1 could originate from multiple mechanisms, but mainly derived through the recombination of ISApl1/Tn6330. We reported a specific transmission mechanism, which is a phage-like region without lysogenic components, could associate with the emergence and stabilization of chromosomally-encoded mcr-1. These results highlighted the potential origin and risks of chromosomally-encoded mcr-1, which could be a heritable repository and thrive again when confronted with new selective pressures. To the best of our knowledge, this is the first study to systematically reveal the genomic basis of chromosomally-encoded mcr-1, and report a specific transmission pattern involved in phage-like region. Overall, we demonstrate the origin mechanisms and risks of chromosomally-encoded mcr-1. It highlights the need of public attention on chromosome-encoded mcr-1 to prevent from its reemergence.

To investigate the effects of crop rotation on oilseed flax growth and yield, three season experiments were carried out in semi-arid area of Dingxi, Gansu from 2017 to 2019. The designed 6 rotational systems were FFF (flax-flax-flax), PFF (potato-flax-flax), WPF (wheat-potato-flax), FPF (flax-potato-flax), PWF (potato-wheat-flax) and FWF (flax-wheat-flax). Flax growth and yield investigation results showed that crop rotation increased leaf area duration, dry matter accumulation, seed nitrogen accumulation, water and nitrogen used efficiency, compared with continuous cropping of flax. Flaxseed yields in rotation systems were 22.23%–44.11% greater than those of continuous cropping system. Those in wheat and potato stubbles had higher tiller number (21.43% and 29.46%), more branches (14.24% and 6.97%), effective capsules (26.35% and 28.79%), higher water use efficiency (40.26% and 33.5%), higher nitrogen partial factor productivity (33.85% and 31.46%) and dry matter (41.98% and 25.47%) than those in oilseed flax stubble. It concluded that crop rotation system was an effective measure for oilseed flax productivity in semi-arid area by improving yield components and promoting biomass.

Abstract Background Varying degrees of macular ischemia generally occur in diabetic retinopathy (DR). This study aims to evaluate the effect of conbercept with 3+ pro re nata (PRN) on macular perfusion status in patients with diabetic macular edema (DME) and quantitatively assess changes in foveal avascular zone (FAZ) areas and capillary density in macular regions by applying optical coherence tomography angiography (OCTA). Methods Fifty patients were divided into ischemic (n = 31) and non-ischemic (n = 19) groups according to the presence of ischemia on OCTA at baseline. All patients received intravitreal injections of 0.5 mg of conbercept with 3+ PRN principle. The FAZ areas and macular vessel density measured using OCTA were evaluated at baseline, 3 months, and 6 months after treatment in both groups. Results At months 3 and 6, the FAZ area in the ischemic group changed from 0.510 ± 0.171 mm2 to 0.441 ± 0.158 mm2 then to 0.427 ± 0.153 mm2 (p = 0.003, p = 0.296); in the non-ischemic group, it remained stable (p = 0.269, p = 0.926). The superficial vessel density changed from 41.1 ± 4.1 to 42.5% ± 4.7% then to 42.6% ± 4.6% (p = 0.043, p = 0.812), and the deep vessel density changed from 40.7 ± 4.4 to 42.3% ± 3.6% then to 42.3% ± 4.7% (p = 0.072, p = 0.961) in the ischemic group. In the non-ischemic group, the superficial vessel density changed from 44.8 ± 3.2 to 46.0% ± 3.5% then to 45.7% ± 3.3% (p = 0.108, p = 0.666), whereas the deep vessel density changed from 43.6 ± 3.6 to 43.8% ± 3.2% then to 43.5% ± 4.5% (p = 0.882, p = 0.736). Reperfusion in macular nonperfusion areas was observed. Conclusion Anti–vascular endothelial growth factor treatment may have a positive effect on macular perfusion status. Furthermore, OCTA had advantages in quantifying and calculating blood flow index in the study of macular perfusion status.

Abstract Background Intervertebral disc degeneration (IDD) is widely known as the main contributor to low back pain which has a negative socioeconomic impact worldwide. However, the underlying mechanism remains unclear. This study aims to analyze the dataset GSE23130 using bioinformatics methods to identify the pivotal genes and pathways associated with IDD. Material/methods The gene expression data of GSE23130 was downloaded, and differentially expressed genes (DEGs) were extracted from 8 samples and 15 controls. GO and KEGG pathway enrichment analyses were performed. Also, protein–protein interaction (PPI) network was constructed and visualized, followed by identification of hub genes and key module. Results A total of 30 downregulated and 79 upregulated genes were identified. The DEGs were mainly enriched in the regulation of protein catabolic process, extracellular matrix organization, collagen fibril organization, and extracellular structure organization. Meanwhile, we found that most DEGs were primarily enriched in the PI3K-Akt signaling pathway. The top 10 hub genes were FN1, COL1A2, SPARC, COL3A1, CTGF, LUM, TIMP1, THBS2, COL5A2, and TGFB1. Conclusions In summary, key candidate genes and pathways were identified by using integrated bioinformatics analysis, which may provide insights into the underlying mechanisms and offer potential target genes for the treatment of IDD.

During mechanical force-induced alveolar bone remodeling, macrophage-mediated local inflammation plays a critical role. Yet, the detailed heterogeneity of macrophages is still unknown. Single-cell RNA sequencing was used to study the transcriptome heterogeneity of macrophages during alveolar bone remodeling. We identified macrophage subclusters with specific gene expression profiles and functions. CellChat and trajectory analysis revealed a central role of the Ccr2 cluster during development, with the CCL signaling pathway playing a crucial role. We further demonstrated that the Ccr2 cluster modulated bone remodeling associated inflammation through an NF-κB dependent pathway. Blocking CCR2 could significantly reduce the Orthodontic tooth movement (OTM) progression. In addition, we confirmed the variation of CCR2+ macrophages in human periodontal tissues. Our findings reveal that mechanical force-induced functional shift of the Ccr2 macrophages cluster mediated by NF-κB pathway, leading to a pro-inflammatory response and bone remodeling. This macrophage cluster may represent a potential target for the manipulation of OTM.

Electroencephalography (EEG)-based emotion computing has become one of the research hotspots of human-computer interaction (HCI). However, it is difficult to effectively learn the interactions between brain regions in emotional states by using traditional convolutional neural networks because there is information transmission between neurons, which constitutes the brain network structure. In this paper, we proposed a novel model combining graph convolutional network and convolutional neural network, namely MDGCN-SRCNN, aiming to fully extract features of channel connectivity in different receptive fields and deep layer abstract features to distinguish different emotions. Particularly, we add style-based recalibration module to CNN to extract deep layer features, which can better select features that are highly related to emotion. We conducted two individual experiments on SEED data set and SEED-IV data set, respectively, and the experiments proved the effectiveness of MDGCN-SRCNN model. The recognition accuracy on SEED and SEED-IV is 95.08 and 85.52%, respectively. Our model has better performance than other state-of-art methods. In addition, by visualizing the distribution of different layers features, we prove that the combination of shallow layer and deep layer features can effectively improve the recognition performance. Finally, we verified the important brain regions and the connection relationships between channels for emotion generation by analyzing the connection weights between channels after model learning.

Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. UM develops and is sustained by inflammation and immunosuppression from the tumor microenvironment (TME). This study sought to identify a reliable TME-related biomarker that could provide survival prediction and new insight into therapy for UM patients. Based on clinical characteristics and the RNA-seq transcriptome data of 80 samples from The Cancer Genome Atlas (TCGA) database, PRRX1 as a TME- and prognosis-related gene was identified using the ESTIMATE algorithm and the LASSO–Cox regression model. A prognostic model based on PRRX1 was constructed and validated with a Gene Expression Omnibus (GEO) dataset of 63 samples. High PRRX1 expression was associated with poorer overall survival (OS) and metastasis-free survival (MFS) in UM patients. Comprehensive results of the prognostic analysis showed that PRRX1 was an independent and reliable predictor of UM. Then the results of immunological characteristics demonstrated that higher expression of PRRX1 was accompanied by higher expression of immune checkpoint genes, lower tumor mutation burden (TMB), and greater tumor cell infiltration into the TME. Gene set enrichment analysis (GSEA) showed that high PRRX1 expression correlated with angiogenesis, epithelial–mesenchymal transition (EMT), and inflammation. Furthermore, downregulation of PRRX1 weakened the process of EMT, reduced cell invasion and migration of human UM cell line MuM-2B in vitro. Taken together, these findings indicated that increased PRRX1 expression is independently a prognostic factor of poorer OS and MFS in patients with UM, and that PRRX1 promotes malignant progression of UM by facilitating EMT, suggesting that PRRX1 may be a potential target for UM therapy.

With the continuous development of deep-learning technology, ever more advanced face-swapping methods are being proposed. Recently, face-swapping methods based on generative adversarial networks (GANs) have realized many-to-many face exchanges with few samples, which advances the development of this field. However, the images generated by previous GAN-based methods often show instability. The fundamental reason is that the GAN in these frameworks is difficult to converge to the distribution of face space in training completely. To solve this problem, we propose a novel face-swapping method based on pretrained StyleGAN generator with a stronger ability of high-quality face image generation. The critical issue is how to control StyleGAN to generate swapped images accurately. We design the control strategy of the generator based on the idea of encoding and decoding and propose an encoder called ShapeEditor to complete this task. ShapeEditor is a two-step encoder used to generate a set of coding vectors that integrate the identity and attribute of the input faces. In the first step, we extract the identity vector of the source image and the attribute vector of the target image; in the second step, we map the concatenation of the identity vector and attribute vector onto the potential internal space of StyleGAN. Extensive experiments on the test dataset show that the results of the proposed method are not only superior in clarity and authenticity than other state-of-the-art methods but also sufficiently integrate identity and attribute.

Esophageal adenocarcinoma (EAC) is one of the main subtypes of esophageal cancer. The incidence rate of EAC increased progressively while the 5-year relative survival rates were poor in the past two decades. The mechanism of EAC has been studied extensively in relation to genetic factors, but less so with respect to human microbiota. Currently, researches about the relationship between EAC and the human microbiota is a newly emerging field of study. Herein, we present the current state of knowledge linking human microbiota to esophageal adenocarcinoma and its precursor lesion—gastroesophageal reflux disease and Barrett’s esophagus. There are specific human bacterial alternations in the process of esophageal carcinogenesis. And bacterial dysbiosis plays an important role in the process of esophageal carcinogenesis via inflammation, microbial metabolism and genotoxicity. Based on the human microbiota alternation in the EAC cascade, it provides potential microbiome-based clinical application. This review is focused on novel targets in prevention, diagnosis, prognosis, and therapy for esophageal adenocarcinoma.

Broccoli-derived isothiocyanate sulforaphane inhibits inflammation and cancer. Sulforaphane may support healthy aging, but the underlying detailed mechanisms are unclear. We used the C. elegans nematode model to address this question. Wild-type and 4 mutant C. elegans worm strains were fed in the presence or absence of sulforaphane and E. coli food bacteria transfected with RNA interference gene constructs. Kaplan–Meier survival analysis, live imaging of mobility and pharyngeal pumping, fluorescence microscopy, RT–qPCR, and Western blotting were performed. In the wild type, sulforaphane prolonged lifespan and increased mobility and food intake because of sulforaphane-induced upregulation of the sex-determination transcription factor TRA-1, which is the ortholog of the human GLI mediator of sonic hedgehog signaling. In turn, the tra-1 target gene daf-16, which is the ortholog of human FOXO and the major mediator of insulin/IGF-1 and aging signaling, was induced. By contrast, sulforaphane did not prolong lifespan and healthspan when tra-1 or daf-16 was inhibited by RNA interference or when worms with a loss-of-function mutation of the tra-1 or daf-16 genes were used. Conversely, the average lifespan of C. elegans with hyperactive TRA-1 increased by 8.9%, but this longer survival was abolished by RNAi-mediated inhibition of daf-16. Our data suggest the involvement of sulforaphane in regulating healthy aging and prolonging lifespan by inducing the expression and nuclear translocation of TRA-1/GLI and its downstream target DAF-16/FOXO.

One of the greatest limitations in the field of EEG-based emotion recognition is the lack of training samples, which makes it difficult to establish effective models for emotion recognition. Inspired by the excellent achievements of generative models in image processing, we propose a data augmentation model named VAE-D2GAN for EEG-based emotion recognition using a generative adversarial network. EEG features representing different emotions are extracted as topological maps of differential entropy (DE) under five classical frequency bands. The proposed model is designed to learn the distributions of these features for real EEG signals and generate artificial samples for training. The variational auto-encoder (VAE) architecture can learn the spatial distribution of the actual data through a latent vector, and is introduced into the dual discriminator GAN to improve the diversity of the generated artificial samples. To evaluate the performance of this model, we conduct a systematic test on two public emotion EEG datasets, the SEED and the SEED-IV. The obtained recognition accuracy of the method using data augmentation shows as 92.5 and 82.3%, respectively, on the SEED and SEED-IV datasets, which is 1.5 and 3.5% higher than that of methods without using data augmentation. The experimental results show that the artificial samples generated by our model can effectively enhance the performance of the EEG-based emotion recognition.

Deep neural networks (DNNs) are proven vulnerable to attack against adversarial examples. Black-box transfer attacks pose a massive threat to AI applications without accessing target models. At present, the most effective black-box attack methods mainly adopt data enhancement methods, such as input transformation. Previous data enhancement frameworks only work on input transformations that satisfy accuracy or loss invariance. However, it does not work for other transformations that do not meet the above conditions, such as the transformation which will lose information. To solve this problem, we propose a new noise data enhancement framework (NDEF), which only transforms adversarial perturbation to avoid the above issues effectively. In addition, we introduce random erasing under this framework to prevent the over-fitting of adversarial examples. Experimental results show that the black-box attack success rate of our method Random Erasing Iterative Fast Gradient Sign Method (REI-FGSM) is 4.2% higher than DI-FGSM in six models on average and 6.6% higher than DI-FGSM in three defense models. REI-FGSM can combine with other methods to achieve excellent performance. The attack performance of SI-FGSM can be improved by 22.9% on average when combined with REI-FGSM. Besides, our combined version with DI-TI-MI-FGSM, i.e., DI-TI-MI-REI-FGSM can achieve an average attack success rate of 97.0% against three ensemble adversarial training models, which is greater than the current gradient iterative attack method. We also introduce Gaussian blur to prove the compatibility of our framework.

Background: Female breast cancer is currently the most frequently diagnosed cancer in the world. This study aimed to develop and validate a novel hypoxia-related long noncoding RNA (HRL) prognostic model for predicting the overall survival (OS) of patients with breast cancer.Methods: The gene expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 200 hypoxia-related mRNAs were obtained from the Molecular Signatures Database. The co-expression analysis between differentially expressed hypoxia-related mRNAs and lncRNAs based on Spearman’s rank correlation was performed to screen out 166 HRLs. Based on univariate Cox regression and least absolute shrinkage and selection operator Cox regression analysis in the training set, we filtered out 12 optimal prognostic hypoxia-related lncRNAs (PHRLs) to develop a prognostic model. Kaplan–Meier survival analysis, receiver operating characteristic curves, area under the curve, and univariate and multivariate Cox regression analyses were used to test the predictive ability of the risk model in the training, testing, and total sets.Results: A 12-HRL prognostic model was developed to predict the survival outcome of patients with breast cancer. Patients in the high-risk group had significantly shorter median OS, DFS (disease-free survival), and predicted lower chemosensitivity (paclitaxel, docetaxel) compared with those in the low-risk group. Also, the risk score based on the expression of the 12 HRLs acted as an independent prognostic factor. The immune cell infiltration analysis revealed that the immune scores of patients in the high-risk group were lower than those of the patients in the low-risk group. RT-qPCR assays were conducted to verify the expression of the 12 PHRLs in breast cancer tissues and cell lines.Conclusion: Our study uncovered dozens of potential prognostic biomarkers and therapeutic targets related to the hypoxia signaling pathway in breast cancer.

Abstract Cr(VI) containing industrial wastewaters are highly toxic and carcinogenic, and severely threats living creatures and the environment. Therefore, it is highly desired yet challenging to develop an available and economical adsorbent for simultaneously detoxifying Cr(VI) anions to Cr(III) ions and removing them from the wastewater. Here we propose a facile method for rapid removal of Cr(VI) ions from the wastewater by using a synthetic polydopamine microsphere (PPM) adsorbent with hierarchical porosity. The as-prepared PPM exhibits high Cr(VI) removal capacity of 307.7 mg/g and an outstanding removal efficiency. They can effectively decrease the Cr(VI) concentration to lower than 0.05 mg/L well below the limits for drinking water standard of WHO regulations in 60 s at pH 2. More importantly, PPMs can reduce the lethal Cr(VI) anions to Cr(III) ions with low toxicity, and simultaneously immobilize them on the matrices of PPMs. Graphical abstract

Field experiment was arranged in a randomized complete block design to determine effects of nitrogen (N) application levels (J0: 150 ​kg/hm2, J1: 120 ​kg/hm2, J2: 90 ​kg/hm2, J3: 60 ​kg/hm2) on regulating dry biomass accumulation, allocation and translocation, and grain yield of oil flax during 2018 cropping season. Significant promotion was observed in dry matter during accumulation stage of oil flax, when N rate was reduced by 40% (from 150 to 90 ​kg/hm2). Under J2 treatment, translocation of dry matter from vegetative organs to pod increased by 38.46% and 61.54% respectively, when compared with J1 and J0 treatment. Dry matter distribution proportion of pod at maturity increased 4.47%–7.61%, contribution rate of leaf to grain upgraded 5.09%–8.77%, and number of effective pods and grains per pod increased by 27.16%–45.38% and 6.49%–26.59% respectively compared to other treatments. As a result, seed yield of oil flax under J2 treatment was 2.23%–18.21% higher than those of other treatments. Our study recommended 90 ​kg/hm2 as the best N fertilizer level to improve seed yield of oil flax.

In order to identify effects of nitrogen (N) and phosphorus (P) on soil nitrogen morphological characteristics and grain yield of oil flax, a two-factor experiment was conducted in a randomized complete block design in typical semi-arid and hilly-gully area of Loess Plateau with 3 replicates in 2013 and 2014. Two levels of N application included 150 ​kg/hm2 (N2) and 75 ​kg/hm2 (N1). P application included 150 ​kg P2O5/hm2 (P2) and 75 ​kg P2O5/hm2 (P1). Temporal and spatial variation of soil nitrate nitrogen (NO3−-N) and ammonium nitrogen (NH4+-N) contents in 0–60 ​cm soil layer, and relationship between soil NO3−-N accumulation (SNA) and grain yield of oil flax were analyzed. Results showed that SNA increased with evaluated N application rate in different soil layers (0–20 ​cm, 20–40 ​cm and 40–60 ​cm). With the increased P application, SNA increased at N1 level but decreased at N2 level. SNA under N2P1 treatment increased by 73.33% in 2013 and 74.97% in 2014 respectively, compared with control treatment (CK) at maturity stage. Grain yield of oil flax also increased by 44.27% in 2013 and 56.55% in 2014, compared with CK under the same treatment. Correlation analysis showed that SNA in different soil layers were respectively positively correlated with grain yield. In conclusion, this research suggested that the optimal fertilizer application rate was 150 ​kg ​N/hm2 and 75 ​kg P2O5/hm2 in the Northwest of China.

AIM: To conduct a systematic review and Meta-analysis to examine the association between uveitis and psoriatic disease, and to evaluate whether one condition predisposes individuals to the other. METHODS: We performed a comprehensive search of PubMed and EMBASE to identify cohort studies examining the association between uveitis and psoriatic disease [psoriasis and/or psoriatic arthritis (PsA)]. We used a random-effects model to calculate the pooled relative risks (RRs) adjusted for confounders, along with the 95% confidence intervals (CIs). RESULTS: This Meta-analysis included a total of 6 studies and a maximum of 80 178 648 participants. Compared with non-psoriatic controls, uveitis risk was significantly elevated in patients with psoriasis (RR=1.49; 95%CI: 1.08-2.07), and PsA (RR=3.16; 95%CI: 2.16-4.63). Furthermore, pre-existing uveitis was associated with a significantly increased risk of psoriasis (RR=1.62; 95%CI: 1.44-1.83), and PsA (RR=4.44; 95%CI: 3.52-5.60). CONCLUSION: The results of this systematic review and Meta-analysis suggest an overall positive bidirectional association between uveitis and psoriatic disease (psoriasis and PsA), warranting increased awareness among clinicians involved in the management of these two conditions. Therefore, there remains a need for more detailed studies of the possible common pathogenesis of psoriatic disease and uveitis.

Quantum teleportation faithfully transfers the quantum state of a physical system, instead of the system itself, which underlies the proposal of global quantum communication network. In this paper, we propose a faithful multi-hop quantum communication scheme. In a quantum network, different types of Greenberger-Horne-Zeilinger (GHZ) states are previously shared on quantum links. To implement qubits transmission, the sender and intermediate nodes perform quantum measurements in parallel, and then send their measurement results and the types of previously shared GHZ states to the receiver independently. A general formula is deduced for the receiver, who chooses an appropriate unitary operation to perform on the local particle, the original qubit can be retrieved. Our scheme shows advantages in quantum communication delay.

The mutation status of the epidermal growth factor receptor (EGFR) is an important clinical reference indicator for lung cancer diagnosis and treatment. However, the extraction of effective discriminative features for non-invasive computer-aided EGFR mutation prediction still poses a big challenge. In this paper, multiple types of features are designed and analyzed to address this problem. These features include clinical features based on prior medical knowledge and quantitative image features extracted by convolutional neural networks (CNN). A long short-term memory (LSTM) network is also introduced to exploit the dependency between these feature types and then fuse them. In particular, a CNN is constructed to extract quantitative features of computed-tomography (CT) images. Furthermore, a LSTM is utilized to analyze the dependency between these clinical and CT image features and generate a new feature representation for computer-aided diagnosis. For samples from the same category, the proposed method deal with feature representation variabilities arising from interdependencies in multi-type features and patient specificity. The multiple feature types of the collected clinical data are used to assess the proposed approach and other relevant algorithms. Our results demonstrate that the multi-type dependency-based feature representation shows superior performance (Accuracy = 75%, AUC = 0.78) compared to single-type feature representations. The proposed method is reliable to apply for diagnosing of the EGFR mutation status.

Aiming at the attitude control problem of three-axis stabilization gimbal, an algorithm combining interval type-2 fuzzy control and sliding-mode control was designed. Firstly, the mathematical model of the three-axis stabilization gimbal actuator was established after analyzing the mechanical structure of the three-axis stabilization gimbal. Then, a sliding-mode controller was designed based on the position ring of the actuator of three-axis stabilization gimbal. An interval type-2 control was used to reduce chattering in sliding-mode control. The switching function and its derivative are taken as the input of fuzzy control, and the rate of change of the approach law is taken as the output of fuzzy control. Fuzzy control can adjust the gain of sliding-mode surface dynamically, enhance the adaptability on external random disturbance, improve the speed of convergence and weaken chattering. The simulation results show that the output of the controller designed in this paper is more stable, and the tracking of the three-axis stabilization gimbal is more rapid and accurate.

Sliding Mode Control and Adaptive Control are widely studied in the area of Rotor UAV in recent years. Although the performance of Rotor UAV with these controllers show high command tracking ability and good robustness, they are limited by model accuracy so that they cannot take place PID. In this paper, a novel method named State damping control is proposed to be a candidate for the traditional PID method. Our proposed State Damping Control is inspired by the format of air resistance. The method is based on the general idea that resistance will make a system easy to stabilize. State damping control is independent of model accuracy and just uses three parameters to control attitude, so it is easy to realize. Krasovskii Theorem is used to give the evidence that State damping control is asymptotic stable in our considered state space. Finally, simulations are implemented in C++ on VS2017, it demonstrates that State damping control is easy to be tuned and robust to wind attack and inertial parameters. Compared with PID, our proposed method is robust to wind disturbances obviously.