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Abstract The majority of existing face inpainting methods primarily focus on generating a single result that visually resembles the original image. The generation of diverse and plausible results has emerged as a new branch in image restoration, often referred to as “Pluralistic Image Completion”. However, most diversity methods simply use random latent vectors to generate multiple results, leading to uncontrollable outcomes. To overcome these limitations, we introduce a novel architecture known as the Reference-Guided Directional Diverse Face Inpainting Network. In this paper, instead of using a background image as reference, which is typically used in image restoration, we have used a face image, which can have many different characteristics from the original image, including but not limited to gender and age, to serve as a reference face style. Our network firstly infers the semantic information of the masked face, i.e., the face parsing map, based on the partial image and its mask, which subsequently guides and constrains directional diverse generator network. The network will learn the distribution of face images from different domains in a low-dimensional manifold space. To validate our method, we conducted extensive experiments on the CelebAMask-HQ dataset. Our method not only produces high-quality oriented diverse results but also complements the images with the style of the reference face image. Additionally, our diverse results maintain correct facial feature distribution and sizes, rather than being random. Our network has achieved SOTA results in face diverse inpainting when writing. Code will is available at https://github.com/nothingwithyou/RDFINet .

Abstract Background Dysregulation of zinc homeostasis is widely recognized as a hallmark feature of prostate cancer (PCa) based on the compelling clinical and experimental evidence. Nevertheless, the implications of zinc dyshomeostasis in PCa remains largely unexplored. Methods In this research, the zinc homeostasis pattern subtype (ZHPS) was constructed according to the profile of zinc homeostasis genes. The identified subtypes were assessed for their immune functions, mutational landscapes, biological peculiarities and drug susceptibility. Subsequently, we developed the optimal signature, known as the zinc homeostasis-related risk score (ZHRRS), using the approach won out in multifariously machine learning algorithms. Eventually, clinical specimens, Bayesian network inference and single-cell sequencing were used to excavate the underlying mechanisms of MT1A in PCa. Results The zinc dyshomeostasis subgroup, ZHPS2, possessed a markedly worse prognosis than ZHPS1. Moreover, ZHPS2 demonstrated a more conspicuous genomic instability and better therapeutic responses to docetaxel and olaparib than ZHPS1. Compared with traditional clinicopathological characteristics and 35 published signatures, ZHRRS displayed a significantly improved accuracy in prognosis prediction. The diagnostic value of MT1A in PCa was substantiated through analysis of clinical samples. Additionally, we inferred and established the regulatory network of MT1A to elucidate its biological mechanisms. Conclusions The ZHPS classifier and ZHRRS model hold great potential as clinical applications for improving outcomes of PCa patients.

BackgroundPrevious studies have shown an association between lipid-lowering drugs, circulating inflammatory factors, and atrial fibrillation (AF), but the specific effects of lipid-lowering drugs on AF and whether they can be mediated by circulating inflammatory factors remain unclear.MethodsWe collected 10 genetic variants encoding lipid-lowering drug targets (LDLR, HMGCR, PCSK9, NPC1L1, APOB, APOB, ABCG5, ABCG8, LPL, APOC3, and PPARA) and AF based on genome-wide association study (GWAS) summary statistics. Drug target Mendelian randomization (MR) was used to explore the causal relationship between lipid-lowering drugs and AF. In addition, we performed a mediation analysis of 91 circulating inflammatory factors to explore potential mediators. Sensitivity analyses were performed to verify the reliability of the MR Results by MR-Egger intercept test, Cochran's Q test and leave-one-out test.ResultsThe results of IVW method showed that LPL agonist had a protective effect on AF(OR = 0. 854, 95%CI: 0.816–0.894, P = 1.844E-11). However, the other nine lipid-lowering drug targets had no significant effect on AF. Notably, we found a mediator role of Fibroblast Growth Factor 5 (FGF5) in the protective effect of LPL agonist on AF with a mediator ratio of 9.22%. Sensitivity analyses supported the robustness of our findings, indicating a possible mediating pathway by which LPL agonists affect the risk of AF.ConclusionOur study provides new insights into the complex interactions among lipid-lowering agents, circulating inflammatory factors and AF, and also identified a potential mediating role of FGF5 in the pathogenesis of AF. Our findings highlight the potential of LPL agonists and targeting specific inflammatory factors for therapeutic intervention in AF, providing promising avenues for future research and clinical strategies for the management and prevention of AF.

BackgroundChronic heart failure (CHF) patients exhibit alterations in cerebral cortical structure and cognitive function. However, the mechanisms by which CHF affects cortical structure and functional regions remain unknown. This study aims to investigate potential causal relationship between CHF and cerebral cortical structure through Mendelian randomization (MR).MethodsThe research utilized genome-wide association studies (GWAS) to explore the causal association between CHF and cerebral cortical structure. The results were primarily analyzed using the inverse-variance weighted (IVW). The reliability of the data was verified through horizontal pleiotropy and heterogeneity analysis by MR-Egger intercept test and Cochran's Q-test, respectively. Replication analysis was conducted in the Integrative Epidemiology Unit (IEU) OpenGWAS project for further validation. In addition, we collected mediator genes that mediate causality to reveal potential mechanisms. Integrated bioinformatics analysis was conducted using the Open Target Genetics platform, the STRING database, and Cytoscape software.ResultsThe IVW results did not reveal any significant causal association between genetically predicted CHF and the overall structure of the cerebral cortex or the surface area (SA) of the 34 functional regions of the cerebral cortex (P > 0.05). However, the results revealed that CHF increased the thickness (TH) of pars opercularis (IVW: β = 0.015, 95% CI: 0.005–0.025, P = 3.16E-03). Replication analysis supported the causal association between CHF and pars opercularis TH (IVW: β = 0.02, 95% CI: 0.010–0.033, P = 1.84E-04). We examined the degree centrality values of the top 10 mediator genes, namely CDKN1A, CELSR2, NME5, SURF4, PSMA5, TSC1, RPL7A, SURF6, PRDX3, and FTO.ConclusionGenetic evidence indicates a positive correlation between CHF and pars opercularis TH.

BackgroundSome occupational and environmental exposures could increase the risk of chronic obstructive pulmonary disease (COPD) and hypertension in various work and living environments. However, the effect of exposure to multiple exogenous harmful substances on COPD and hypertension co-morbidities remains unclear.MethodsParticipants were selected from eight hospitals in five provinces in China using a multistage cluster sampling procedure. Participants' demographic, exposure, and disease information were collected through questionnaires, spirometry, and blood pressure examinations. Demographic data were used as matching factors, and 1:1 matching between the exposed and non-exposed groups was performed by employing propensity score matching (PSM) to minimize the influence on the results. A one-way chi-squared analysis and multifactorial logistic regression were used to analyze the association between the exposure to exogenous harmful substances (metals and their compound dust, inorganic mineral dust, organic chemicals, and livestock by-products) and the co-morbidity of COPD and hypertension.ResultsThere were 6,610 eligible participants in the final analysis, of whom 2,045 (30.9%) were exposed to exogenous harmful substances. The prevalence of co-morbidities of COPD and hypertension (6.0%) in the exposure group was higher than their prevalence in the total population (4.6%). After PSM, exogenous harmful substance exposure was found to be a risk factor for the co-morbidity of COPD and hypertension [odds ratio (OR) = 1.347, 95% confidence interval (CI): 1.011–1.794], which was not statistically significant before PSM (OR = 1.094, 95% CI: 0.852–1.405). Meanwhile, the results of different outcomes showed that the association between hypertension and exogenous harmful substance exposure was not statistically significant (OR = 0.965, 95% CI: 0.846–1.101). Smoking (OR = 4.702, 95% CI: 3.321–6.656), history of a respiratory disease during childhood (OR = 2.830, 95% CI: 1.600–5.006), and history of respiratory symptoms (OR = 1.897, 95% CI: 1.331–2.704) were also identified as risk factors for the co-morbidity of COPD and hypertension.ConclusionThe distribution of exogenous harmful substance exposure varies in the population, and the prevalence of co-morbidities is generally higher in susceptible populations. Exposure to exogenous harmful substances was found to be a key risk factor after adjusting for demographic confounders.

With the increasingly widespread application of large-scale energy storage battery systems, the demand for battery safety is rising. Research on how to detect battery anomalies early and reduce the occurrence of thermal runaway (TR) accidents has become particularly important. Existing research on battery TR warning algorithms can be mainly divided into two categories: model-driven and data-driven methods. However, the common model-driven methods are often of high complexity, with poor versatility and low early warning capability; and the common data-driven methods are mostly based on neural networks, requiring substantial training costs, with better early warning capabilities but higher false alarm probabilities. To address the limitations of existing works, this paper proposes a combined data-driven and model-based algorithm for accurate battery TR warnings. Specifically, the K-Means algorithm serves as the data-driven module, capturing outliers in battery data, and the Bernardi equation serves as the model-driven module used to evaluate battery temperature. Ultimately, the outputs of the weighted model-driven module and data-driven module are combined to comprehensively assess whether the battery is abnormal. The proposed algorithm combines the advantages of model-driven and data-driven approaches, achieving a 25 min advance warning for thermal runaway, with a significantly reduced probability of false alarms.

N6-methyladenosine (m6A) RNA modification is the most prevalent form of RNA methylation and plays a crucial role in plant development. However, our understanding of m6A modification in Masson pine (Pinus massoniana Lamb.) remains limited. In this study, a complete analysis of m6A writers, erasers, and readers in Masson pine was performed, and 22 m6A regulatory genes were identified in total, including 7 m6A writers, 7 m6A erases, and 8 readers. Phylogenetic analysis revealed that all m6A regulators involved in Masson pine could be classified into three distinct groups based on their domains and motifs. The tissue expression analysis revealed that the m6A regulatory gene may exert a significant influence on the development of reproductive organs and leaves in Masson pine. Moreover, the results from stress and hormone expression analysis indicated that the m6A regulatory gene in Masson pine might be involved in drought stress response, ABA-signaling-pathway activation, as well as resistance to Monochamus alternatus. This study provided valuable and anticipated insights into the regulatory genes of m6A modification and their potential epigenetic regulatory mechanisms in Masson pine.

Abstract Super-enhancers (SEs) consist of multiple typical enhancers enriched at high density with transcription factors, histone-modifying enzymes and cofactors. Oncogenic SEs promote tumorigenesis and malignancy by altering protein-coding gene expression and noncoding regulatory element function. Therefore, they play central roles in the treatment of cancer. Here, we review the structural characteristics, organization, identification, and functions of SEs and the underlying molecular mechanism by which SEs drive oncogenic transcription in tumor cells. We then summarize abnormal SE complexes, SE-driven coding genes, and noncoding RNAs involved in tumor development. In summary, we believe that SEs show great potential as biomarkers and therapeutic targets.

With high aerodynamic efficiency and low observable design for flying wing configuration, the control ability decreases and the flying risk increases, especially during the takeoff and landing processes for unmanned aerial vehicle (UAV). To solve the nonlinear characteristic problem of the flying wing configuration at a high angle of attack (AoA) for a low aspect ratio flying wing UAV, a controllable region and stability analysis method is proposed in the paper. Firstly, the aerodynamic characteristics and static stability of a flying wing UAV are analyzed. Secondly, according to the characteristics of aerodynamic data, an efficient longitudinal trim state calculation method under the low-speed range is proposed. The trim state contour map can be used effectively with the proposed trim state calculation method, which can further analyze the constraint relationship between different trim states and the controllable region of the UAV. Thirdly, the stability of different trim states is analyzed through the phase portrait between AoA and airspeed. With the analysis result, longitudinal attitude and AoA decoupling control laws are designed based on the incremental nonlinear dynamic inversion (INDI) method. The effectiveness and adaptability of the designed control methods are verified through simulation at high AoA.

Nickel oxide nanoparticles (NiONPs) are toxic heavy metal compounds that induce liver fibrosis and metabolic disorders. Current research shows that the intestinal microbiota regulates liver metabolism through the gut-liver axis. However, it is unclear whether NiONPs affect the intestinal microbiota and the relationship between microbiota and liver metabolic disorders. Therefore, in this study, we established liver fibrosis model by administering 0.015, 0.06 and 0.24 mg/mL NiONPs through tracheal instillation twice a week for 9 weeks in rats, then we collected serum and fecal sample for whole metabolomics and metagenomic sequencing. As the result of sequencing, we screened out seven metabolites (beta-D-glucuronide, methylmalonic acid, linoleic acid, phosphotidylcholine, lysophosphatidylinositol, docosapentaenoic acid and progesterone) that related to functional alterations (p

Melanoma differentiation-associated gene-5 (MDA5) acts as a cytoplasmic RNA sensor to detect viral dsRNA and mediates antiviral innate immune responses to infection by RNA viruses. Upon recognition of viral dsRNA, MDA5 is activated with K63-linked polyubiquitination and then triggers the recruitment of MAVS and activation of TBK1 and IKKα/β, subsequently leading to IRF3 and NF-κB phosphorylation. However, the specific E3 ubiquitin ligase for MDA5 K63-polyubiquitination has not been well characterized. Great numbers of symptomatic and severe infections of SARS-CoV-2 are spreading worldwide, and the poor efficacy of treatment with type I interferon and antiviral immune agents indicates that SARS-CoV-2 escapes from antiviral immune responses via several unknown mechanisms. Here, we report that SARS-CoV-2 nonstructural protein 8 (nsp8) acts as a suppressor of antiviral innate immune and inflammatory responses to promote infection of SARS-CoV-2. It downregulates the expression of type I interferon, IFN-stimulated genes and proinflammatory cytokines by binding to MDA5 and TRIM4 and impairing TRIM4-mediated MDA5 K63-linked polyubiquitination. Our findings reveal that nsp8 mediates innate immune evasion during SARS-CoV-2 infection and may serve as a potential target for future therapeutics for SARS-CoV-2 infectious diseases.

To investigate the effect of excessive stacking loadings on the deformation of raw-water pipelines, a model test was designed based on the analogous theory in this paper. The design of the model box, selection of pipeline material, and preparation of remolded soil were conducted, respectively. A theoretical formula was derived to convert the results of the model test into actual ones. Then, the field test data and three-dimensional numerical values were employed to verify the correctness of the model test results. Finally, the stresses of pipelines were discussed under different loading conditions, pipe diameters, buried depths, and compactness of underlying soils, and the guidelines for pipeline protection were proposed based on the results of the model tests. It can lay a solid theoretical and practical foundation for the protection of buried pipelines.

To enhance the path following ability for fixed-wing unmanned aerial vehicles, and solve the stability and high-accuracy tracking problems due to inappropriate route switchover time during intense maneuvers, an improved nonlinear path following method with on-line transition trajectory generation was proposed in the article. Firstly, the influence of the guidance distance to the nonlinear path following method was verified through a flight experiment, and the importance of the critical time for route switchover was deduced. The on-line transition trajectory generation was expected to realize the automation of the switchover process, including the computation of the critical switchover time and desired paths. Secondly, to generate the on-line transition trajectory, the computation method was derived for typical intense maneuvers, such as the turning maneuver for square trajectory, or the converging maneuver to the expected trajectory under initial numerous errors (such as modifying the waypoint during a flight mission). Finally, to solve the situations in which the transition trajectory does not exist, an adaptive guidance distance algorithm was proposed to improve the flight stability and accuracy. From the simulation and flight experiment results, stability and high accuracy can be guaranteed for different situations with the proposed methods. The path following error is smaller than 1.0 m when it is converged (in downwind or upwind situations), which is important for the method to be used widely.

Conformational changes are fundamental events in the transport mechanism. The serotonin transporter (SERT) catalyzes reuptake of the neurotransmitter serotonin after its release by serotonergic neurons and is the molecular target for antidepressant drugs and psychostimulants. Despite significant progress in characterizing the structure–function relationship of SERT, its conformational mechanism has not been fully understood. We present here a cell-based method for determining conformational changes in SERT with its fluorescent substrates by fluorescence imaging analysis. This method fluorometrically measures accessibility of strategically positioned cysteine residues in the substrate permeation pathway to calculate the rate constants of reactivity with MTS reagents in live or permeabilized cells. We validated this method by investigating ligand and ion-induced conformational changes in both the extracellular and cytoplasmic pathways of SERT. Furthermore, we applied this method for examining the influence of Cl− binding and vilazodone inhibition on SERT conformation. Our results showed that Cl− ion, in the presence of Na+, facilitates the conformational conversion from outward to inward open states, and that vilazodone binding stabilizes SERT in an outward open and inward-closed conformation. The present work provided insights into the conformational mechanism of SERT and also indicated that the cell-based fluorometric method is robust, straightforward to perform, and potentially applicable to any monoamine transporters in exploring the transport mechanism and mechanism of action of therapeutic agents for the treatment of several psychiatric disorders.

Ulmus parvifolia Jacq is a kind of landscape tree endemic to East Asia. In this study, the complete chloroplast genome of U. parvifolia was sequenced. The genome was 159,259 bp in length, with a large single-copy (LSC) region of 88,451 bp, a small single-copy (SSC) region of 19,598 bp, and two inverted repeat (IR) regions of 25,605 bp, each. The genome consisted of 121 genes, including 77 protein-coding genes, 36 tRNA genes, and 8 rRNA genes. The phylogenetic results indicated that Ulmus is not monophyletic and U. parvifolia constitute a well-supported clade sister to U. Sect. Ulmus. The complete chloroplast genome of U. parvifolia will provide important information for phylogenetic and evolutionary studies in Ulmaceae, as well as the other closely related families.

This paper presents a preliminary design methodology for small unmanned battery powered tailsitters. Subsystem models, including takeoff weight, power and energy consumption models, and battery discharge model, were investigated, respectively. Feasible design space was given by simulation with mission and weight constraints, while the influences of wing loading and battery ratio were analyzed. Case study was carried out according to the design process, and the results were validated by previous designs. The design methodology can be used to determine key parameters and make necessary preparations for detailed design and vehicle realization of small battery powered tailsitters.

Fracture tests of postfire normal concrete with ten temperatures up to 600°C are implemented. Residual fracture toughness using analytical method is determined. Two situations are divided at critical load when calculating the cohesive fracture toughness. The initial and critical fracture toughness could be calculated from the complete load-crack opening displacement curves. Finally, the validation of double-K fracture model to the postfire concrete specimens is proved.

Background: Renal fibrosis is an important process in the development of chronic kidney disease. Understanding the pathogenesis and finding effective treatments for renal fibrosis is crucial. This study aims to investigate whether a newly discovered long non-coding RNA (lncRNA) called LOC103694972 could be a potential target for treating fibrosis of NRK-49F cells. Methods: LncRNA Chip was used to identify differentially expressed lncRNAs between TGF-β1-induced NRK-49F cells and normal cells. The dual-luciferase assay confirmed the binding between miR-29c-3p and signal transducer and activator of transcription (STAT3), as well as between miR29c-3p and lncRNA LOC103694972. Si-LOC103694972 and miR-29c-3p mimic were then transfected into TGF-β1- induced NRK-49F cells. Results: The study found that LOC103694972 was highly expressed in TGF-β1-induced NRK-49F cells. These cells exhibited increased cell length and activity compared to the control group. The expression levels of Collagen I, α-Smooth muscle actin (α-SMA), and tissue inhibitor of metalloproteinase (TIMP-1) were increased, while matrix Metalloproteinase 2 (MMP2) and matrix Metalloproteinase 9 (MMP9) expression was decreased. However, transfection with si-LOC103694972 and miR-29c-3p mimics restored cell morphology and reduced cell viability. This led to a decrease in the levels of Collagen I, α-SMA, and TIMP-1, as well as an increase in MMP2 and MMP9 expression. Additionally, TGF-β1-induced NRK-49F cells transfected with miR-29c-3p mimics activated the STAT3-Smad3/CTGF pathway. Conclusion: Based on these findings, lncRNA LOC103694972 shows promise as a target for treating renal fibrosis. It negatively regulates miR-29c-3p and activates the STAT3-Smad3/CTGF pathway. [ABSTRACT FROM AUTHOR]