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Biomarkers are often measured in bulk to diagnose patients, monitor patient conditions, and research novel drug pathways. The measurement of these biomarkers often suffers from detection limits that result in missing and untrustworthy measurements. Frequently, missing biomarkers are imputed so that down‐stream analysis can be conducted with modern statistical methods that cannot normally handle data subject to informative censoring. This work develops an empirical Bayes g$$ g $$‐modeling method for imputing and denoising biomarker measurements. We establish superior estimation properties compared to popular methods in simulations and with real data, providing the useful biomarker measurement estimations for down‐stream analysis. [ABSTRACT FROM AUTHOR]

Wide heterogeneity exists in cancer patients' survival, ranging from a few months to several decades. To accurately predict clinical outcomes, it is vital to build an accurate predictive model that relates the patients' molecular profiles with the patients' survival. With complex relationships between survival and high‐dimensional molecular predictors, it is challenging to conduct nonparametric modeling and irrelevant predictors removing simultaneously. In this article, we build a kernel Cox proportional hazards semi‐parametric model and propose a novel regularized garrotized kernel machine (RegGKM) method to fit the model. We use the kernel machine method to describe the complex relationship between survival and predictors, while automatically removing irrelevant parametric and nonparametric predictors through a LASSO penalty. An efficient high‐dimensional algorithm is developed for the proposed method. Comparison with other competing methods in simulation shows that the proposed method always has better predictive accuracy. We apply this method to analyze a multiple myeloma dataset and predict the patients' death burden based on their gene expressions. Our results can help classify patients into groups with different death risks, facilitating treatment for better clinical outcomes. [ABSTRACT FROM AUTHOR]

The subway alleviates the traffic pressure in the city but also brings the potential risk of land subsidence. The land subsidence caused by the subway is a global problem that seriously affects the safety of subway operations and surrounding buildings. Therefore, it is very important to carry out long-term deformation monitoring on the subway system. StaMPS-PS is a time-series Interferometric Synthetic Aperture Radar (InSAR) technique that serves as an effective means for monitoring urban ground subsidence. However, the accuracy of external (Digital Elevation Models) DEM will affect the accuracy of StaMPS-PS monitoring, and previous studies have mostly used SRTM-1 arc DEM (30 m) as the external DEM. In this study, to obtain a more precise measurement of surface deformation caused by the excavation of the Hohhot subway, a total of 85 scenes of Sentinel-1A data from July 2015 to October 2021, as well as two different resolution digital elevation models (DEMs) (ALOS PALSAR DEM and SRTM-1 arc DEM), were used to calculate and analyze the subsidence along the subway line in Hohhot city. The StaMPS-PS monitoring results showed the ALOS PALSAR DEM, as an external DEM, had higher accuracy, and there was regional subsidence in both the construction processes of Line 1 and Line 2 of the Hohhot subway, with a maximum subsidence rate of −21.1 mm/year. The dynamic changes in subway subsidence were fitted using the Peck formula and the long short-term memory (LSTM) model. The Peck formula results showed the width and maximum subsidence of the settlement troughs gradually expanded during the construction of the subway. The predicted values of the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) of the LSTM model were less than 4 mm and 10%, respectively, consistent with the measured results. Furthermore, we discussed the factors that affect settlement along the subway line and the impact of two external DEMs on StaMPS-PS. The study results provide a scientific method for DEM selection and subsidence analysis calculations in the StaMPS-PS monitoring of urban subway subsidence. [ABSTRACT FROM AUTHOR]

Covariance matrix estimation is a fundamental statistical task in many applications, but the sample covariance matrix is suboptimal when the sample size is comparable to or less than the number of features. Such high‐dimensional settings are common in modern genomics, where covariance matrix estimation is frequently employed as a method for inferring gene networks. To achieve estimation accuracy in these settings, existing methods typically either assume that the population covariance matrix has some particular structure, for example, sparsity, or apply shrinkage to better estimate the population eigenvalues. In this paper, we study a new approach to estimating high‐dimensional covariance matrices. We first frame covariance matrix estimation as a compound decision problem. This motivates defining a class of decision rules and using a nonparametric empirical Bayes g‐modeling approach to estimate the optimal rule in the class. Simulation results and gene network inference in an RNA‐seq experiment in mouse show that our approach is comparable to or can outperform a number of state‐of‐the‐art proposals. [ABSTRACT FROM AUTHOR]

Problems involving the simultaneous estimation of multiple parameters arise in many areas of theoretical and applied statistics. A canonical example is the estimation of a vector of normal means. Frequently, structural information about relationships between the parameters of interest is available. For example, in a gene expression denoising problem, genes with similar functions may have similar expression levels. Despite its importance, structural information has not been well-studied in the simultaneous estimation literature, perhaps in part because it poses challenges to the usual geometric or empirical Bayes shrinkage estimation paradigms. This article proposes that some of these challenges can be resolved by adopting an alternate paradigm, based on regression modeling. This approach can naturally incorporate structural information and also motivates new shrinkage estimation and inference procedures. As an illustration, this regression paradigm is used to develop a class of estimators with asymptotic risk optimality properties that perform well in simulations and in denoising gene expression data from a single cell RNA-sequencing experiment. [ABSTRACT FROM AUTHOR]

Clinical studies examining the effectiveness of a treatment with respect to some primary outcome often require long‐term follow‐up of patients and/or costly or burdensome measurements of the primary outcome of interest. Identifying a surrogate marker for the primary outcome of interest may allow one to evaluate a treatment effect with less follow‐up time, less cost, or less burden. While much clinical and statistical work has focused on identifying and validating surrogate markers, available approaches tend to focus on settings in which only a single surrogate marker is of interest. Limited work has been done to accommodate the high‐dimensional surrogate marker setting where the number of potential surrogates is greater than the sample size. In this article, we develop methods to estimate the proportion of treatment effect explained by high‐dimensional surrogates. We study the asymptotic properties of our proposed estimator, propose inference procedures, and examine finite sample performance via a simulation study. We illustrate our proposed methods using data from a randomized study comparing a novel whey‐based oral nutrition supplement with a standard supplement with respect to change in body fat percentage over 12 weeks, where the surrogate markers of interest are gene expression probesets. [ABSTRACT FROM AUTHOR]

• A self-organized mechanism based consensus framework is presented. • Non-cooperative behaviors are detected and managed at the element level of MAEMs. • A novel distance-based ordinal consensus measurement is proposed. • Simulation analysis is presented to show the effectiveness of our proposals. In consensus-based multi-attribute group decision making (MAGDM) problems, decision makers (DMs) may exhibit non-cooperative behaviors since they usually have different individual interests (sometimes conflicting) or limited knowledge, which strongly affects the efficiency of consensus and the quality of decision outcomes. Additionally, the existing MAGDM studies mainly focus on the cardinal consensus, and the ordinal consensus is ignored. Thus, this paper proposes a self-organized mechanism based framework to manage non-cooperative behaviors and ordinal consensus in MAGDM. First, a dual-membership function based on the basic idea of synergy theory is designed to detect non-cooperative behaviors at the element level of the multiple attribute evaluation matrix (MAEM), and then the weights of elements with non-cooperative behaviors are penalized automatically. In this way, the negative effects of non-cooperative behaviors can be eliminated. Next, a novel preference ranking-based ordinal consensus approach is proposed, which calculates an ordinal consensus based on the preference rankings of alternatives between individuals and the group. If the pre-defined consensus level is not reached, the feedback adjustment is used to help DMs modify their MAEMs to improve the consensus level; otherwise, the selection process is utilized to choose the optimal alternative(s). Finally, detailed simulation experiments and comparative analysis are designed to show the properties and effectiveness of the proposed framework, and an illustrative angel investment case is presented to demonstrate the calculation process and usability. [ABSTRACT FROM AUTHOR]

• We analyze the origin of feedback mechanism with minimum adjustment or cost (FMMA/C). • We review FMMA/C in classical group decision making problems. • We review FMMA/C in complex group decision making problems. • We propose some open problems on FMMA/C. Consensus reaching process is a very powerful decision tool to eliminate the preference conflict in group decision making. In general, the consensus is achieved by the decision makers modifying their preferences (or opinions) toward a point of mutual consent, and the feedback mechanism aims to provide preference-modifications suggestions. In many situations, the preference-modifications mean cost and the resources for the consensus reaching process are limited. So, in the last decade, the feedback mechanism with minimum adjustment or cost (FMMA/C) has been developed and widely used in various group decision making contexts to improve consensus efficiency. In this review, we first analyze the origin and basic research paradigm of the FMMA/C. Then, we review the FMMA/C in two decision contexts: (1) the FMMA/C in classical group decision making problems, and (2) the FMMA/C in complex group decision making problems (e.g., social network, large-scale, and opinion dynamic group decision making problems). Finally, we identify research challenges and propose future research direction. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) and differential expression analyses have had limited success in finding genes that cause complex diseases such as heart failure (HF), a leading cause of death in the United States. This article proposes a new statistical approach that integrates GWAS and expression quantitative trait loci (eQTL) data to identify important HF genes. For such genes, genetic variations that perturb its expression are also likely to influence disease risk. The proposed method thus tests for the presence of simultaneous signals: SNPs that are associated with the gene’s expression as well as with disease. An analytic expression for thep-value is obtained, and the method is shown to be asymptotically adaptively optimal under certain conditions. It also allows the GWAS and eQTL data to be collected from different groups of subjects, enabling investigators to integrate public resources with their own data. Simulation experiments show that it can be more powerful than standard approaches and also robust to linkage disequilibrium between variants. The method is applied to an extensive analysis of HF genomics and identifies several genes with biological evidence for being functionally relevant in the etiology of HF. It is implemented in the R packagessa. Supplementary materials for this article are available online. [ABSTRACT FROM PUBLISHER]

It is frequently of interest to jointly analyze two paired sequences of multiple tests. This paper studies the problem of detecting whether there are more pairs of tests that are significant in both sequences than would be expected by chance. The asymptotic detection boundary is derived in terms of parameters such as the sparsity of non-null cases in each sequence, the effect sizes of the signals, and the magnitude of the dependence between the two sequences. A new test for detecting weak dependence is also proposed, shown to be asymptotically adaptively optimal, studied in simulations, and applied to study genetic pleiotropy in 10 pediatric autoimmune diseases. [ABSTRACT FROM AUTHOR]

Genetic risk prediction is an important component of individualized medicine, but prediction accuracies remain low for many complex diseases. A fundamental limitation is the sample sizes of the studies on which the prediction algorithms are trained. One way to increase the effective sample size is to integrate information from previously existing studies. However, it can be difficult to find existing data that examine the target disease of interest, especially if that disease is rare or poorly studied. Furthermore, individual-level genotype data from these auxiliary studies are typically difficult to obtain. This article proposes a new approach to integrative genetic risk prediction of complex diseases with binary phenotypes. It accommodates possible heterogeneity in the genetic etiologies of the target and auxiliary diseases using a tuning parameter-free non-parametric empirical Bayes procedure, and can be trained using only auxiliary summary statistics. Simulation studies show that the proposed method can provide superior predictive accuracy relative to non-integrative as well as integrative classifiers. The method is applied to a recent study of pediatric autoimmune diseases, where it substantially reduces prediction error for certain target/auxiliary disease combinations. The proposed method is implemented in the R package ssa. [ABSTRACT FROM AUTHOR]

We propose new nonparametric empirical Bayes methods for high-dimensional classification. Our classifiers are designed to approximate the Bayes classifier in a hypothesized hierarchical model, where the prior distributions for the model parameters are estimated nonparametrically from the training data. As is common with nonparametric empirical Bayes, the proposed classifiers are effective in high-dimensional settings even when the underlying model parameters are in fact nonrandom. We use nonparametric maximum likelihood estimates of the prior distributions, following the elegant approach studied by Kiefer & Wolfowitz in the 1950s. However, our implementation is based on a recent convex optimization framework for approximating these estimates that is well-suited for large-scale problems. We derive new theoretical results on the accuracy of the approximate estimator, which help control the misclassification rate of one of our classifiers. We show that our methods outperform several existing methods in simulations and perform well when gene expression microarray data is used to classify cancer patients. [ABSTRACT FROM AUTHOR]

Circulating urotensin II (UII) is involved in the development of atherosclerosis. However, the role of autocrine UII in the development of atherosclerosis remains unclear. Here, we tested the hypothesis that autocrine UII would promote atherosclerosis. Transgenic rabbits were created as a model to study macrophage-specific expressing human UII (hUII) and used to investigate the role of autocrine UII in the development of atherosclerosis. Transgenic rabbits and their nontransgenic littermates were fed a high cholesterol diet to induce atherosclerosis. Comparing the transgenic rabbits with their nontransgenic littermates, it was observed that hUII expression increased the macrophage-positive area in the atherosclerotic lesions by 45% and the positive area ratio by 56% in the transgenic rabbits. Autocrine hUII significantly decreased the smooth muscle cell-positive area ratio in transgenic rabbits (by 54%), without affecting the plasma levels of total cholesterol, triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and glucose and adipose tissue contents. These results elucidated for the first time that autocrine UII plays an important role in the development of atherosclerosis by increasing the accumulation of macrophage-derived foam cell. [ABSTRACT FROM AUTHOR]

Integrative genomics offers a promising approach to more powerful genetic association studies. The hope is that combining outcome and genotype data with other types of genomic information can lead to more powerful SNP detection. We present a new association test based on a statistical model that explicitly assumes that genetic variations affect the outcome through perturbing gene expression levels. It is shown analytically that the proposed approach can have more power to detect SNPs that are associated with the outcome through transcriptional regulation, compared to tests using the outcome and genotype data alone, and simulations show that our method is relatively robust to misspecification. We also provide a strategy for applying our approach to high-dimensional genomic data. We use this strategy to identify a potentially new association between a SNP and a yeast cell's response to the natural product tomatidine, which standard association analysis did not detect. [ABSTRACT FROM AUTHOR]

Variable screening has emerged as a crucial first step in the analysis of high-throughput data, but existing procedures can be computationally cumbersome, difficult to justify theoretically, or inapplicable to certain types of analyses. Motivated by a high-dimensional censored quantile regression problem in multiple myeloma genomics, this article makes three contributions. First, we establish a score test-based screening framework, which is widely applicable, extremely computationally efficient, and relatively simple to justify. Secondly, we propose a resampling-based procedure for selecting the number of variables to retain after screening according to the principle of reproducibility. Finally, we propose a new iterative score test screening method which is closely related to sparse regression. In simulations we apply our methods to four different regression models and show that they can outperform existing procedures. We also apply score test screening to an analysis of gene expression data from multiple myeloma patients using a censored quantile regression model to identify high-risk genes. [ABSTRACT FROM AUTHOR]

Motivation: The successful translation of genomic signatures into clinical settings relies on good discrimination between patient subgroups. Many sophisticated algorithms have been proposed in the statistics and machine learning literature, but in practice simpler algorithms are often used. However, few simple algorithms have been formally described or systematically investigated.Results: We give a precise definition of a popular simple method we refer to as más-o-menos, which calculates prognostic scores for discrimination by summing standardized predictors, weighted by the signs of their marginal associations with the outcome. We study its behavior theoretically, in simulations and in an extensive analysis of 27 independent gene expression studies of bladder, breast and ovarian cancer, altogether totaling 3833 patients with survival outcomes. We find that despite its simplicity, más-o-menos can achieve good discrimination performance. It performs no worse, and sometimes better, than popular and much more CPU-intensive methods for discrimination, including lasso and ridge regression.Availability and Implementation: Más-o-menos is implemented for survival analysis as an option in the survHD package, available from http://www.bitbucket.org/lwaldron/survhd and submitted to Bioconductor.Contact: sdzhao@illinois.edu [ABSTRACT FROM AUTHOR]

It is often of interest to understand how the structure of a genetic network differs between two conditions. In this paper, each condition-specific network is modelled using the precision matrix of a multivariate normal random vector, and a method is proposed to directly estimate the difference of the precision matrices. In contrast to other approaches, such as separate or joint estimation of the individual matrices, direct estimation does not require those matrices to be sparse, and thus can allow the individual networks to contain hub nodes. Under the assumption that the true differential network is sparse, the direct estimator is shown to be consistent in support recovery and estimation. It is also shown to outperform existing methods in simulations, and its properties are illustrated on gene expression data from late-stage ovarian cancer patients. [ABSTRACT FROM PUBLISHER]

Urotensin II (UII) is a vasoactive peptide composed of 11 amino acids that has been implicated to contribute to the development of cardiovascular disease. The purpose of this study was to investigate whether UII affects the development of atherosclerosis in cholesterol-fed rabbits. UII was infused for 16 weeks through an osmotic mini-pump into male Japanese White rabbits fed on a high-cholesterol diet. Plasma lipids and body weight were measured every 4 weeks. Aortic atherosclerotic lesions along with cellular components, collagen fibers, matrix metalloproteinase-1 and -9 were examined. Moreover, vulnerability index of atherosclerotic plaques was evaluated. UII infusion significantly increased atherosclerotic lesions within the entire aorta by 21% over the control (P = 0.013). Atherosclerotic lesions were increased by 24% in the aortic arch (P = 0.005), 11% in the thoracic aorta (P = 0.054) and 18% in the abdominal aorta (P = 0.035). These increases occurred without changes in plasma levels of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides or body weight. Immunohistochemical staining revealed that macrophages and matrix metalloproteinase-9 were significantly enhanced by 2.2-fold and 1.6-fold in UII group. In vitro studies demonstrated that UII up-regulated the expression of vascular cell adhesion protein-1 and intercellular adhesion molecule-1 in human umbilical vein endothelial cells, which was inhibited by the UII receptor antagonist urantide. In conclusion, our results showed that UII promotes the development of atherosclerotic lesions and destabilizes atherosclerotic plaques in cholesterol-fed rabbits. [ABSTRACT FROM AUTHOR]

Abstract: Introduction: Probucol (PB) and cilostazol (CZ) both exhibit anti-atherogenic effects. However, their combinatorial effects are unclear. This study was designed to investigate their combinatorial anti-atherogenic effect in cholesterol-fed rabbits. Materials and Methods: Rabbits were fed a cholesterol diet with PB or CZ alone or both PB and CZ for 16weeks. The plasma levels of total cholesterol, LDL-cholesterol, HDL-cholesterol, C-reactive protein, superoxide dismutase, malondialdehyde, and nitric oxide (NO) were measured. The aortic atherosclerotic lesions were grossly and microscopically evaluated. Additionally, in vitro experiments were conducted using human umbilical vein endothelial cells. Results and Conclusion: We found that the PB group and the PB+CZ group exhibited a reduction in the lesion areas (70% in the PB+CZ group, 56% in the PB group) compared with the vehicle group. However, although PB alone and PB+CZ led to a reduction in the lesion size, the histological analysis revealed that only PB+CZ significantly decreased the macrophage accumulation and smooth muscle cell proliferation in the lesions compared with the vehicle group. The plasma levels of total cholesterol in the PB+CZ group were decreased compared with the vehicle group, Moreover, PB+CZ exerted obvious anti-oxidant and anti-inflammatory effects. Interestingly, the PB+CZ treatment led to a marked increase in the levels of plasma NO. The in vitro experiments showed that the combinatorial treatment up-regulated the levels of NO and protein S-nitrosylation in endothelial cells treated with oxidized LDL. In summary, these results suggest that PB and CZ exert combinatorial anti-atherogenic effects. [Copyright &y& Elsevier]

SmCo is an emerging perpendicular magnetic material for super-high density magnetic recording, due to its large magnetic anisotropy energy. In this paper, the magnetic moments of SmCoCu have been studied using first principles calculation based on density-functional theory (DFT). Calculations are performed using the pseudopotential plane wave DFT code Vienna ab initio simulation package (VASP) with the projector augmented wave (PAW) method. The local density approximation LDA+ U method is used for the calculation of the exchange correlation energy of Sm. The calculation results show that the average Co magnetic moment of SmCoCu decreases with the increase of Cu doping concentrations, and the influence of the Cu doping on the spin state of Co is greater than that of Sm. The magnetic anisotropy energy of SmCo is analyzed. The electronic density of states and the differential in spin densities of atoms show that the spatial distribution of 4 f electron and the 4 f-3 d coupling are the controlling factors of the magnetic anisotropy energy of SmCo. [ABSTRACT FROM AUTHOR]

Abstract: It is rather challenging for current variable selectors to handle situations where the number of covariates under consideration is ultra-high. Consider a motivating clinical trial of the drug bortezomib for the treatment of multiple myeloma, where overall survival and expression levels of 44760 probesets were measured for each of 80 patients with the goal of identifying genes that predict survival after treatment. This dataset defies analysis even with regularized regression. Some remedies have been proposed for the linear model and for generalized linear models, but there are few solutions in the survival setting and, to our knowledge, no theoretical support. Furthermore, existing strategies often involve tuning parameters that are difficult to interpret. In this paper, we propose and theoretically justify a principled method for reducing dimensionality in the analysis of censored data by selecting only the important covariates. Our procedure involves a tuning parameter that has a simple interpretation as the desired false positive rate of this selection. We present simulation results and apply the proposed procedure to analyze the aforementioned myeloma study. [Copyright &y& Elsevier]

Abstract: Background/aims: Traditional Chinese herbal therapies are widely used for the treatment of chronic hepatitis C (CHC) in Asia. The aim of this study was to perform a meta-analysis of randomised controlled trials (RCTs) comparing interferon therapies with Chinese herbal therapies and/or interferon plus Chinese herb therapies for the treatment of CHC. Methods: The Cochrane Central Register of Controlled Trials, Medline, Science Citation Index, EMBASE, China National Knowledge Infrastructure, Wanfang Database and China Biomedical Database were searched to identify RCTs that evaluated the virological response to interferon therapies, Chinese herbal therapies and interferon plus Chinese herb therapies in CHC patients. We statistically combined data using a random-effect meta-analysis according to the intention-to-treat principle. Results: The literature search yielded 770 studies, and 26 RCTs comprising 1905 patients matched the selection criteria. Overall, the sustained virological response (SVR) was significantly higher in patients treated with interferon plus Chinese herbs than in patients treated with interferon alone (49% vs 33%, relative risk, 1.52; 95% confidence interval: 1.23–1.89; p <0.05). Combined therapies of interferon plus Chinese herb therapies were also superior to interferon therapies alone in achieving the end-of-treatment viral response (ETVR), and resulted in fewer relapses, fewer adverse events and more rapid alanine transaminase normalisation. Interferon therapies achieved higher ETVR than Chinese herbal therapies, but they yielded a similar SVR. Conclusions: The current evidence suggests that combined therapies of interferon plus Chinese herbs yielded a higher SVR, and resulted in fewer relapses and fewer adverse events than interferon therapies. [ABSTRACT FROM AUTHOR]

Background: The standard treatments for chronic infection with the hepatitis C virus (HCV) are peginterferon α-2a or α-2b plus ribavirin, but it remains unclear if one has a better efficacy and safety profile. Objective: The aim of this study was to perform a meta-analysis of randomized controlled trials (RCTs) comparing peginterferon α-2a and α-2b (in combination with ribavirin) treatments for chronic HCV. Methods: The Cochrane Central Register of Controlled Trials, MEDLINE, Science Citation Index, and EMBASE were searched (1966–April 2010) to identify RCTs that evaluated the sustained virologic response (SVR) to peginterferon α-2a and peginterferon α-2b in patients with chronic HCV. The inclusion criteria were: RCT studies designed to compare the therapeutic effects of peginterferon α-2a (180 μg/wk) and peginterferon α-2b (1.5 μg/kg/wk) for treatment-naive patients with chronic HCV; patients treated for ≥24 weeks if infected with HCV genotypes 2 or 3 and for ≥48 weeks if infected with genotypes 1 or 4, with 24-week follow-ups; and publications written in any language. Reports of duplicated studies were excluded by examining the author list, parent institution, sample size, and results. The primary outcome was the SVR, and the other measures included the liver-related morbidity, all-cause mortality, and adverse events leading to treatment discontinuation. Results: The literature search yielded 5580 studies, and 7 RCTs comprising 3212 patients matched the inclusion/exclusion criteria. Overall, the SVR rate was significantly higher in patients treated with peginterferon α-2a than in patients treated with peginterferon α-2b (50% vs 46%, respectively; relative risk [RR] = 1.11; 95% CI, 1.02–1.20; P < 0.05) and varying levels of ribavirin treatment. The subgroup analysis found that, in patients with genotypes 1 or 4, the difference between SVR rate in patients treated with peginterferon α-2a and patients treated with peginterferon α-2b was not statistically significant (43% vs 39%; RR = 1.25; 95% CI, 0.99–1.57). A significantly higher SVR rate was achieved in the HCV patients with genotypes 2 or 3 treated with peginterferon α-2a compared with the patients treated with peginterferon α-2b (86% vs 77%; RR = 1.11; 95% CI, 1.02–1.22; P = 0.02). The meta-analysis of adverse events leading to treatment discontinuation revealed no significant differences between the 2 treatments. Conclusions: The evidence reviewed in this meta-analysis suggests that peginterferon α-2a treatment was associated with a higher SVR rate than peginterferon α-2b treatment in patients with chronic HCV also treated with ribavirin. However, the available evidence on adverse events was insufficient to make recommendations. [Copyright &y& Elsevier]

Abstract: Introduction: Thiazolidinedione (TZD) is widely used a drug for the treatment of type 2 diabetes and protects against cardiovascular events in human. However, it is not clear whether TZD can directly inhibit the progression of atherosclerosis. To test the hypothesis whether administration of TZD could reduce the development of atherosclerosis, we studied the effects of rosiglitazone on aortic atherosclerosis of rabbits fed a cholesterol diet. Materials and methods: Male Japanese White rabbits were fed a diet containing either 0.3% cholesterol diet (control group, n=10) or 0.3% cholesterol with rosiglitazone (TZD-treated group, n=12) for 16 weeks. We compared the plasma lipids and the extent of aortic atherosclerosis between two groups. Results and conclusions: TZD treatment significantly resulted in the reduction of aortic atherosclerosis by 21% in the aortic arch (p<0.01), 20% in the thoracic aorta (p=0.14), and 28% in the abdominal aorta (p=0.25), without affecting the plasma levels of triglycerides, total cholesterol, high-density lipoprotein cholesterol, glucose and insulin. Immunohistochemical staining showed that the cellular components (macrophages and smooth muscle cells) of the lesions of TZD-treated rabbits were unchanged compared to those of control rabbits. In addition, TZD treatment also led to dramatic improvement of fatty liver in cholesterol-fed rabbits. Our results suggest that the activation of PPARγ can be beneficial for the treatment of atherosclerosis and fatty liver independent upon the improvement of plasma lipids and glucose metabolism. [Copyright &y& Elsevier]

Recovering aged bitumen from reclaimed asphalt pavement (RAP) is crucial for the evolution of pavement recycling. This study delves deeply into the effects of rejuvenator components on the rheological properties of rejuvenated bitumen across a wide temperature range. The investigation utilized the rolling thin film oven test (RTFOT) and the pressure aging vessel (PAV) test to simulate the short-term and long-term aging of the bitumen binder, respectively. Four distinct rejuvenators were then applied to recover the bitumen at varied aging levels. Detailed chemical analyses, encompassing the four-fraction (SARA) method and Fourier transform infrared spectroscopy (FTIR), were employed to identify the chemical compositions and key functional groups of both the rejuvenators and the rejuvenated bitumen. The rheological behavior of rejuvenated bitumen was assessed through a comprehensive series of tests, including conventional, temperature sweep, frequency sweep, multiple stress creep recovery (MSCR), linear amplitude sweep (LAS), and bending beam rheometer (BBR) tests. A Pearson correlation analysis highlighted a significant positive association between specific rejuvenator components, notably asphaltene (As), saturate (S), and aromatic (Ar), and the high-temperature performance of the rejuvenated bitumen. The findings of this research offer insights into the formulation of rejuvenators, potentially enhancing the performance of rejuvenated asphalt pavements and facilitating sustainable infrastructure advancements. • A significant correlation between high-temperature property and component was found. • The deterioration no only relied on the chemical components at low temperature. • MSCR, G-R parameter, and m-valve are more representative to evaluate properties. • The findings of this research offer insights into the formulation of rejuvenators. [ABSTRACT FROM AUTHOR]

Mediation analysis is difficult when the number of potential mediators is larger than the sample size. In this paper we propose new inference procedures for the indirect effect in the presence of high-dimensional mediators for linear mediation models. We develop methods for both incomplete mediation, where a direct effect may exist, and complete mediation, where the direct effect is known to be absent. We prove consistency and asymptotic normality of our indirect effect estimators. Under complete mediation, where the indirect effect is equivalent to the total effect, we further prove that our approach gives a more powerful test compared to directly testing for the total effect. We confirm our theoretical results in simulations, as well as in an integrative analysis of gene expression and genotype data from a pharmacogenomic study of drug response. We present a novel analysis of gene sets to understand the molecular mechanisms of drug response, and also identify a genome-wide significant noncoding genetic variant that cannot be detected using standard analysis methods. [ABSTRACT FROM AUTHOR]

This paper proposes a temporary support system for improving the efficiency and safety of underground roadway excavation in coal mines. Firstly, this study establishes a calculation model for the initial supporting force of the excavation of roadway temporary support and a gray system-based automatic prediction model for the initial supporting force level, based on the mechanism of temporary support controlling the roof. These models enable the prediction of the required initial supporting force at different locations along the roadway's temporary support area, thereby providing a basis for controlling the initial supporting force of the temporary support system. To achieve efficient and adaptive control of the initial supporting force of temporary supports at different locations, this study designs a support force controller based on Simulated Annealing Particle Swarm Optimization Proportional-Integral-Derivative (SAPSO-PID). This study establishes a mathematical model for the hydraulic cylinder pressure system controlled by the temporary support overflow valve and conducts a stability analysis and model verification. The study constructs a simulation control system for the initial supporting force based on SAPSO-PID using the combined simulation platform of AMESim and Matlab. The simulation results demonstrate that the proposed support force control system efficiently achieves adaptive control of the initial supporting force of temporary supports. An experimental system in the underground roadway of a coal mine is constructed to validate the results of the simulation analysis. [ABSTRACT FROM AUTHOR]

Background: Rabbits are well-domesticated animals. As a crucial economic animal, rabbit has been successfully bred into wool-use, meat-use and fur-use breeds. Hair length is one of the most economically important traits affecting profitability in wool rabbits. In this study, to identify selection signatures with the long-hair trait, whole-genomic resequencing of long-haired rabbits (Angora rabbits) and short-haired rabbits (Rex and New Zealand rabbits) was performed. Results: By genome-wide selective sweeping analysis based on population comparison, we identified a total of 5.85 Mb regions (containing 174 candidate genes) with strong selection signals. Six of these genes (Dusp1, Ihh, Fam134a, Map3k1, Spata16, and Fgf5) were enriched in the MAPK signalling and Hedgehog signalling pathways, both of which are closely associated with hair growth regulation. Among these genes, Fgf5 encodes the FGF5 protein, which is a well-established regulator of hair growth. There was a nonsynonymous nucleotide substitution (T19234C) in the Fgf5 gene. At this locus, the C allele was present in all of the tested Angora rabbits, while the T allele was dominant in New Zealand and Rex rabbits. We further confirmed that the C allele was conserved in Angora rabbits by screening an additional 135 rabbits. Moreover, the results of functional predictions and co-immunoprecipitation revealed that the T19234C mutation impaired the binding capacity of FGF5 to its receptor FGFR1. Conclusions: We discovered that the homozygous missense mutation T19234C within Fgf5 might contribute to the long-hair trait of Angora rabbits by reducing its receptor binding capacity. This finding will provide new insights into the genetic basis underlying the genetic improvement of Angora rabbits and benefit the improvement of rabbit breeding in the future. [ABSTRACT FROM AUTHOR]

Accumulated evidence shows that elevated urotensin II (UII) levels are associated with cardiovascular diseases. However, the role of UII in the initiation, progression, and regression of atherosclerosis remains to be verified. Different stages of atherosclerosis were induced in rabbits by a 0.3% high cholesterol diet (HCD) feeding, and either UII (5.4 μg/kg/h) or saline was chronically infused via osmotic mini-pumps. UII promoted atherosclerotic fatty streak formation in ovariectomized female rabbits (34% increase in gross lesion and 93% increase in microscopic lesion), and in male rabbits (39% increase in gross lesion). UII infusion significantly increased the plaque size of the carotid and subclavian arteries (69% increase over the control). In addition, UII infusion significantly enhanced the development of coronary lesions by increasing plaque size and lumen stenosis. Histopathological analysis revealed that aortic lesions in the UII group were characterized by increasing lesional macrophages, lipid deposition, and intra-plaque neovessel formation. UII infusion also significantly delayed the regression of atherosclerosis in rabbits by increasing the intra-plaque macrophage ratio. Furthermore, UII treatment led to a significant increase in NOX2 and HIF-1α/VEGF-A expression accompanied by increased reactive oxygen species levels in cultured macrophages. Tubule formation assays showed that UII exerted a pro-angiogenic effect in cultured endothelial cell lines and this effect was partly inhibited by urantide, a UII receptor antagonist. These findings suggest that UII can accelerate aortic and coronary plaque formation and enhance aortic plaque vulnerability, but delay the regression of atherosclerosis. The role of UII on angiogenesis in the lesion may be involved in complex plaque development. [ABSTRACT FROM AUTHOR]

Objective: Type I interferon receptor signaling contributes to several autoimmune and vascular diseases such as lupus, atherosclerosis and stroke. The purpose of this study was to assess the influence of type I interferon receptor deficiency on the formation and progression of experimental abdominal aortic aneurysms (AAAs). Methods: AAAs were induced in type I interferon receptor subunit 1 (IFNAR1)-deficient and wild type control male mice via intra-infrarenal aortic infusion of porcine pancreatic elastase. Immunostaining for IFNAR1 was evaluated in experimental and clinical aneurysmal abdominal aortae. The initiation and progression of experimental AAAs were assessed via ultrasound imaging prior to (day 0) and days 3, 7 and 14 following elastase infusion. Aneurysmal histopathology was analyzed at sacrifice. Results: Increased aortic medial and adventitial IFNAR1 expression was present in both clinical AAAs harvested at surgery and experimental AAAs. Following AAA induction, wild type mice experienced progressive, time-dependent infrarenal aortic enlargement. This progression was substantially attenuated in IFNAR1-deficient mice. On histological analyses, medial elastin degradation, smooth muscle cell depletion, leukocyte accumulation and neoangiogenesis were markedly diminished in IFNAR1-deficient mice in comparison to wild type mice. Conclusion: IFNAR1 deficiency limited experimental AAA progression in response to intra-aortic elastase infusion. Combined with clinical observations, these results suggest an important role for IFNAR1 activity in AAA pathogenesis. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ2 meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases. [ABSTRACT FROM AUTHOR]

Intimal hyperplasia (IH) is a common pathological feature of vascular proliferative diseases, such as atherosclerosis and restenosis after angioplasty. Urotensin II (UII) and its receptor (UTR) are widely expressed in cardiovascular tissues. However, it remains unclear whether the UII/UTR system is involved in IH. Right unilateral common carotid artery ligation was performed and maintained for 21 days to induce IH in UTR knockout (UTR−/−) and wild-type (WT) mice. Histological analysis revealed that compared with WT mice, UTR-deficient mice exhibited a decreased neointimal area, angiostenosis and intima–media ratio. Immunostaining revealed fewer smooth muscle cells (SMCs), endothelial cells and macrophages in the lesions of UTR−/− mice than in those of WT mice. Protein interaction analysis suggested that the UTR may affect cell proliferation by regulating YAP and its downstream target genes. In vitro experiments revealed that UII can promote the proliferation and migration of SMCs, and western blotting also revealed that UII increased the protein expression of RhoA, CTGF, Cyclin D1 and PCNA and downregulated p-YAP protein expression, while these effects could be partly reversed by urantide. To evaluate the translational value of UTRs in IH management, WT mice were also treated with two doses of urantide, a UTR antagonist, to confirm the benefit of UTR blockade in IH progression. A high dose of urantide (600 μg/kg/day), rather than a low dose (60 μg/kg/day), successfully improved ligation-induced IH compared with that in mice receiving vehicle. The results of the present study suggested that the UII/UTR system may regulate IH partly through the RhoA-YAP signaling pathway. [Display omitted] • We found that urotensin II receptor (UTR) deficiency ameliorates ligation-induced carotid intimal hyperplasia (IH) in mice. • Cultured SMCs experiment suggested that the UII/UTR system may regulate IH partly through the RhoA-YAP signaling pathway. • Urantide, a UTR antagonist, was found that can improve IH in mice. [ABSTRACT FROM AUTHOR]

Summary: Objectives: There are limited chemotherapeutic options for advanced recurrent or metastatic SCCHN. The efficacy and toxicity of docetaxel with or without vandetanib was investigated in these patients. Materials and Methods: Patients with pathologically confirmed, recurrent or metastatic SCCHN who had progressed on platinum based therapy given as definitive or palliative treatment, were randomized in this open label, multicenter phase II study of docetaxel (75mg/m2 IV Q3weeks) with or without vandetanib (100mg PO daily). The primary objective was response rate (RR) and secondary objectives were progression free survival (PFS), overall survival (OS), disease control rate (DCR) and duration of response (DOR). Results: 29 analyzable patients were enrolled, 14 in docetaxel arm and 15 in combined arm. PR was achieved in 1 patient in the docetaxel arm and 2 patients in the combined arm. The objective RR was 7% (1/14) (95% CI 0.2–33.8%) in the single and 13% (2/15) (95% CI 1.6–40.4%) combined arm. The median PFS was 3.21 (95% CI 3.0–22.0) and 9 (95% CI (5.86–18.1) weeks; median OS was 26.8(95% CI 17.7–100.7+) and 24.1 (95% CI, 16.4–171.1+) weeks. Most common adverse events were fatigue, dysphagia, diarrhea or constipation, cytopenias and alopecia. Conclusions: Although an initial benefit in response was noted and statistical criteria met there was only a minor trend towards improved PFS for the combined arm. The study was designed with low threshold for activity in each arm and results were deemed not to be of enough clinical significance in this group of patients to continue accrual. [Copyright &y& Elsevier]

Background: Cardiovascular diseases remain the leading cause of morbidity and mortality worldwide, most of which are caused by atherosclerosis. Discerning processes that participate in macrophage-to-foam cell formation are critical for understanding the basic mechanisms underlying atherosclerosis. To explore the molecular mechanisms of foam cell formation, differentially expressed proteins were identified. Methods: Human peripheral blood mononuclear cells were stimulated with macrophage colony-stimulating factor, and obtained macrophages were transformed into foam cells by oxidized low-density lipoprotein. Tandem mass tag (TMT) labeling combined with mass spectrometry was performed to find associations between foam cell transformation and proteome profiles. Results: Totally, 5146 quantifiable proteins were identified, among which 1515 and 182 differentially expressed proteins (DEPs) were found in macrophage/monocyte and foam cell/macrophage, respectively. Subcellular localization analysis revealed that downregulated DEPs of macrophages/monocytes were mostly located in the nucleus, whereas upregulated DEPs of foam cells/macrophages were mostly extracellular or located in the plasma membrane. Functional analysis of DEPs demonstrated that cholesterol metabolism-related proteins were upregulated in foam cells, whereas immune response-related proteins were downregulated in foam cells. The protein interaction network showed that the DEPs with the highest interaction scores between macrophages and foam cells were mainly concentrated in lysosomes and the endoplasmic reticulum. Conclusions: Proteomics analysis suggested that cholesterol metabolism was upregulated, while the immune response was suppressed in foam cells. KEGG enrichment analysis and protein-protein interaction analysis indicated that DEPs located in the endoplasmic reticulum and lysosomes might be key drivers of foam cell formation. These data provide a basis for identifying the potential proteins associated with the molecular mechanism underlying macrophage transformation to foam cells. [ABSTRACT FROM AUTHOR]

Objective: Elastase-induced abdominal aortic aneurysm (AAA) model is widely used for aneurysmal pathogenesis and translational research. However, temporal alternations in aneurysmal histologies remain unknown. This study is aimed at analyzing temporal immunopathologies of aneurysmal aorta following experimental AAA induction.Methods: Male C57BL/6J mice at the age of 10-14 weeks received intra-aortic infusion of elastase to induce AAAs. Aortic diameters at the baseline and indicated days after AAA induction were measured, and aortae were collected for histopathological analysis.Results: Aorta diameters increased from 0.52 mm at the baseline levels to 0.99 mm, 1.34 mm, and 1.41 mm at days 7, 14, and 28, respectively, corresponding 90%, 158%, and 171% increases over the baseline level. Average aortic diameters did not differ between days 14 and 28. Severe elastin degradation and smooth muscle cell depletion were found at days 14 and 28 as compared to the baseline and day 7. No difference in the scores of medial elastin and SMC destruction was noted between days 14 and 28. Consistent results were found for leukocyte accumulation, neoangiogenesis, and matrix metalloproteinase expression. Twenty-eight days after AAA induction, all aneurysmal pathologies showed an attenuated trend, although most histopathological parameters did no differ between days 14 and 28.Conclusion: Our data suggest that almost aneurysmal immunohistopathologies reach maximal 14 days following AAA induction. Analysis of day 14 histologies is sufficient for AAA pathogenesis and translational studies in elastase-induced mouse experimental AAAs. [ABSTRACT FROM AUTHOR]

Abstract: Resveratrol is an active polyphenol found in red wine that has anti-cancer effects, but the molecular mechanisms of resveratrol on tumor invasion inhibition have not been well documented. The aim of this study was to elucidate the effects of resveratrol on invasion ability of human hepatocellular carcinoma cells and TNF-α-mediated MMP-9 expression. The expression activity of MMP-9 was measured by zymography, RT-PCR and western blot analysis. The expression of NF-kappa B was measured by EMSA and western blot analysis. TNF-α induced the MMP-9 expression in HepG2 cells. Resveratrol significantly inhibited TNF-α-mediated MMP-9 expression in HepG2 cells. NF-kappa B inhibitor induced a marked reduction in MMP-9 expression, and it suggested that NF-kappa B could play an important role in TNF-α-mediated MMP-9 expression. Furthermore, resveratrol significantly suppressed TNF-α-mediated NF-kappa B expression and invasion of HepG2 cells. Our results showed that resveratrol inhibited TNF-α-mediated MMP-9 expression and invasion of human hepatocellular carcinoma cells. The inhibitory effects are partly associated with the downregulation of the NF-kappa B signaling pathway. [Copyright &y& Elsevier]

Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administration of broad‐spectrum antibiotics is associated with improved outcomes, but early recognition of sepsis remains a major challenge. In a two‐center cohort study with prospective sample collection from 1400 adult patients in emergency departments suspected of sepsis, we sought to determine the diagnostic and prognostic capabilities of a machine‐learning algorithm based on clinical data and a set of uncommonly measured biomarkers. Specifically, we demonstrate that a machine‐learning model developed using this dataset outputs a score with not only diagnostic capability but also prognostic power with respect to hospital length of stay (LOS), 30‐day mortality, and 3‐day inpatient re‐admission both in our entire testing cohort and various subpopulations. The area under the receiver operating curve (AUROC) for diagnosis of sepsis was 0.83. Predicted risk scores for patients with septic shock were higher compared with patients with sepsis but without shock (p < 0.0001). Scores for patients with infection and organ dysfunction were higher compared with those without either condition (p < 0.0001). Stratification based on predicted scores of the patients into low, medium, and high‐risk groups showed significant differences in LOS (p < 0.0001), 30‐day mortality (p < 0.0001), and 30‐day inpatient readmission (p < 0.0001). In conclusion, a machine‐learning algorithm based on electronic medical record (EMR) data and three nonroutinely measured biomarkers demonstrated good diagnostic and prognostic capability at the time of initial blood culture. [ABSTRACT FROM AUTHOR]

Plasma lipid and glucose levels are important parameters for evaluating the onset and development of metabolic and cardiovascular diseases. In clinical and experimental studies of humans or mice, fasting is often required before testing plasma lipid and glucose levels. The rabbit is a valuable animal model for cardiovascular disease research. However, whether fasting is necessary for measuring plasma lipid and glucose levels in rabbits remains unclear. In the current study, 12 healthy Japanese white rabbits (males weighing 2.5–3.0 kg) were randomly divided into a chow diet group (n = 6) and a high cholesterol diet group (n = 6). They were fed either a standard chow diet or a chow diet supplemented with 0.5% cholesterol and 3% corn oil for 12 weeks. After 12 weeks, the plasma levels of total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol and glucose were measured before and after various fasting durations (8, 12, 16, 20 and 24 h). The results showed that there were no significant differences in lipid levels between the fasting and non-fasting samples, whereas glucose levels were lower after 8 h of fasting than in the absence of fasting. Moreover, the glucose levels were restored to normal after 8 h of refeeding. These results indicate that fasting does not affect plasma lipid values in rabbits but that fasting is important for determining the glucose level in rabbits. These findings may be helpful for future rabbit experiments and beneficial for animal welfare. [ABSTRACT FROM AUTHOR]

The Himalayan marmot (Marmota himalayana), a natural host and transmitter of plague, is also susceptible to the hepadnavirus infection. To reveal the genetic basis of the hepadnavirus susceptibility and the immune response to plague, we systematically characterized the features of immune genes in Himalayan marmot with those of human and mouse. We found that the entire major histocompatibility complex region and the hepatitis B virus pathway genes of the Himalayan marmot were conserved with those of humans. A Trim (tripartite motif) gene cluster involved in immune response and antiviral activity displays dynamic evolution, which is reflected by the duplication of Trim5 and the absence of Trim22 and Trim34. Three key regions of Ntcp, which is critical for hepatitis B virus entry, had high identity among seven species of Marmota. Moreover, we observed a severe alveolar hemorrhage, inflammatory infiltrate in the infected lungs and livers from Himalayan marmots after infection of EV76, a live attenuated Yersinia pestis strain. Lots of immune genes were remarkably up-regulated, which several hub genes Il2rγ, Tra29, and Nlrp7 are placed at the center of the gene network. These findings suggest that Himalayan marmot is a potential animal model for study on the hepadnavirus and plague infection. [ABSTRACT FROM AUTHOR]

Background: Marmots are large Holarctic rodents with unique biological features, making them potential animal models in various research fields. Due to the rapid accumulation of the genetic data in marmots, a highly integrative database is urgent needed. Description: iMarmot is freely available on the web at http://www.marmotdb.org/ and currently contains the biological information of 14 marmots, genomic sequence of 6 marmots, syntenic relationship and orthologs among 3 marmots, and expression profiles of several hibernators and plague hosts. To assist with the genomic and transcriptomic analysis, we also integrated a set of analysis and visualization tools, such as KEGG or GO enrichment analysis, PCA, Blast, Muscle, GeneWise, Lastz, and JBrowse. Particularly, one DEGs (differentially expressed genes) module has been implemented in this database to visualize the gene expression changes in hibernators and plague hosts. Conclusion: This database will provide comprehensive information and analysis platform for researchers interested in understanding the biological features of marmots. [ABSTRACT FROM AUTHOR]

Phenotypic switching of vascular smooth muscle cells (VSMCs) plays an essential role in the development of atherosclerosis. Protein inhibitor of activated STAT (Pias) regulates VSMCs phenotype via acting as sumo E3 ligase to promote protein sumoylation. Our previous study indicated that Pias3 expression decreased in atherosclerotic lesions. Therefore, this study aimed to explore the role of Pias3 on VSMCs phenotype switching during atherosclerosis. ApoE −/− and ApoE −/− Pias3 −/− double-deficient mice were fed with high-fat/high-cholesterol diet to induce atherosclerosis. Aorta tissues and primary VSMCs were collected to assess plaque formation and VSMCs phenotype. In vitro , Pias3 was overexpressed in A7r5 , a VSMCs cell line, by transfection with Pias3 plasmid. Real-time quantitative PCR, immunoblotting, immunoprecipitation, were used to analyze the effect of Pias3 on VSMCs phenotypic switching. Pias3 deficiency significantly exacerbated atherosclerotic plaque formation and promoted VSMCs phenotypic switching to a synthetic state within lesion. In vitro , overexpressing Pias3 in VSMCs increased the expression of contractile markers (myosin heavy chain 11, calponin 1), while it decreased the level of synthetic marker (vimentin). Additionally, Pias3 overexpression blocked PDGF-BB-induced VSMCs proliferation and migration. Immunoprecipitation and mass spectrometry results showed that Pias3 enhanced sumoylation and ubiquitination of vimentin, and shortened its half-life. Moreover, the ubiquitination level of vimentin was impaired by 2-D08, a sumoylation inhibitor. This suggests that Pias3 might accelerate the ubiquitination-degradation of vimentin by promoting its sumoylation. These results indicate that Pias3 might ameliorate atherosclerosis progression by suppressing VSMCs phenotypic switching and reducing vimentin protein stability. [Display omitted] • Pias3 deficiency aggravates atherosclerotic plaque formation in ApoE −/− mice. • Pias3 impedes VSMCs phenotypic switching from contractile to synthetic state. • Pias3 might accelerate the ubiquitination-degradation of vimentin by promoting its sumoylation. [ABSTRACT FROM AUTHOR]

• A linear weighted model coupling AHP and Entropy (AELW) is proposed to calculate indicator weight. • The eco-geo-environmental vulnerability (EGEV) of Zhungeer City was assessed and mapped via the AELW model and multi-source data integration. • EGEV of towns and open-pit mining aggregation areas are analyzed. • This study provides some practical suggestions for reducing regional EGEV and adaptive management. Assessing the ecological and geological environment vulnerability (EGEV) of cities arid and semi-arid regions is important for urban planning, development, and ecological protection. This study investigated the ecological and geological environmental problems and possible potential risk factors in Zhungeer City and constructed an EGEV assessment index system covering the geological environment, human activities, coal mining, and hydrological conditions. We proposed a linear weighted model to calculate the comprehensive weight of each indicator using the Analytical Hierarchy Process (AHP) and Entropy method based on distance function optimization (AELW), and frequency ratio accuracy is then introduced to compare the remarkable classification performance between AELW and other models. The frequency ratio accuracy results show that AELW model has the highest accuracy for EGEV assessment (62.77 %), followed by Multiplicative Integrated Normalization Model (MINM, 61.46 %), AHP (60.98 %), Ideal Point Model (IPM, 60.30 %) and Entropy (53.55 %). The EGEV of Zhungeer was classified as I-V from lowest into highest, among which the EGEV of I-II-III accounted for 78.15 %, EGEV of IV accounted for 16.42 %, and the EGEV of V risk area accounted for 5.43 %, with a good overall ecological and geological environment quality. These results can provide tangible management suggestions for reducing EGEV in Zhungeer city, and the AELW model provides direction for EGEV assessment in other similar areas. [ABSTRACT FROM AUTHOR]

Porcine reproductive and respiratory syndrome virus (PRRSV) causes inflammatory injuries in infected pigs. PRRSV induces secretion of high mobility group box 1 (HMGB1) that enhances inflammatory response. However, the mechanism of PRRSV-induced HMGB1 secretion is unknown. Here, we discovered PRRSV induced HMGB1 secretion via activating protein kinase C-delta (PKCδ). HMGB1 secretion was positively correlated with PKCδ activation in PRRSV-infected cells in a dose and time-dependent manner. Suppression of PKCδ with inhibitor and siRNA significantly blocked PRRSV-induced HMGB1 translocation and secretion, which indicates PKCδ activation is essential for the PRRSV-mediated HMGB1 secretion. In addition, PKCδ knockdown in PRRSV-infected cells led to downregulation of inflammatory cytokines, including IL-1beta and IL-6. Moreover, PRRSV E and pORF5a proteins were found to activate PKCδ and consequent HMGB1 secretion. These results demonstrate PRRSV activates PKCδ to induce HMGB1 secretion via E and pORF5a. This finding provides insights on the inflammatory response and pathogenesis of PRRSV infection. [ABSTRACT FROM AUTHOR]

High levels of plasma high-density lipoprotein-cholesterol (HDL-C) are inversely associated with the risk of atherosclerosis and other cardiovascular diseases; thus, pharmacological inhibition of cholesteryl ester transfer protein (CETP) is considered to be a therapeutic method of raising HDL-C levels. However, many CETP inhibitors have failed to achieve a clinical benefit despite raising HDL-C. In the study, we generated transgenic (Tg) rabbits that overexpressed the human CETP gene to examine the influence of CETP on the development of atherosclerosis. Both Tg rabbits and their non-Tg littermates were fed a high cholesterol diet for 16 weeks. Plasma lipids and body weight were measured every 4 weeks. Gross lesion areas of the aortic atherosclerosis along with lesional cellular components were quantitatively analyzed. Overexpression of human CETP did not significantly alter the gross atherosclerotic lesion area, but the number of macrophages in lesions was significantly increased. Overexpression of human CETP did not change the plasma levels of total cholesterol or low-density lipoprotein cholesterol but lowered plasma HDL-C and increased triglycerides. These data revealed that human CETP may play an important role in the development of atherosclerosis mainly by decreasing HDL-C levels and increasing the accumulation of macrophage-derived foam cells. [ABSTRACT FROM AUTHOR]

E. O. Wilson proposed in Sociobiology that similarities between human and animal societies reflect common mechanistic and evolutionary roots. When introduced in 1975, this controversial hypothesis was beyond science's ability to test. We used genomic analyses to determine whether superficial behavioral similarities in humans and the highly social honey bee reflect common molecular mechanisms. Here, we report that gene expression signatures for individual bees unresponsive to various salient social stimuli are significantly enriched for autism spectrum disorder-related genes. These signatures occur in the mushroom bodies, a high-level integration center of the insect brain. Furthermore, our finding of enrichment was unique to autism spectrum disorders; brain gene expression signatures from other honey bee behaviors do not show this enrichment, nor do datasets from other human behavioral and health conditions. These results demonstrate deep conservation for genes associated with a human social pathology and individual differences in insect social behavior, thus providing an example of how comparative genomics can be used to test sociobiological theory. [ABSTRACT FROM AUTHOR]

Animals exhibit dramatic immediate behavioral plasticity in response to social interactions, and brief social interactions can shape the future social landscape. However, the molecular mechanisms contributing to behavioral plasticity are unclear. Here, we show that the genome dynamically responds to social interactions with multiple waves of transcription associated with distinct molecular functions in the brain of male threespined sticklebacks, a species famous for its behavioral repertoire and evolution. Some biological functions (e.g., hormone activity) peaked soon after a brief territorial challenge and then declined, while others (e.g., immune response) peaked hours afterwards. We identify transcription factors that are predicted to coordinate waves of transcription associated with different components of behavioral plasticity. Next, using H3K27Ac as a marker of chromatin accessibility, we show that a brief territorial intrusion was sufficient to cause rapid and dramatic changes in the epigenome. Finally, we integrate the time course brain gene expression data with a transcriptional regulatory network, and link gene expression to changes in chromatin accessibility. This study reveals rapid and dramatic epigenomic plasticity in response to a brief, highly consequential social interaction. [ABSTRACT FROM AUTHOR]

Aim: To compare pathological findings in the placenta and cord with the prognosis of full-term infants in cases of neonatal infection and microbial analyses. Methods: The pathological findings in the placenta and cord and microbial analyses of amniotic fluid and neonatal samples based on culture or polymerase chain reaction (PCR) were observed in 1208 full-term mother–infant pairs at our center. We also collected neonatal clinical infection data, such as the occurrence of septicemia and other infectious diseases. Results: Neonatal infection and positive identification of microorganisms were more common in the funisitis and/or chorionic vasculitis group than in the histologic chorioamnionitis group. Conclusion: Funisitis and/or chorionic vasculitis is a valuable pathological marker for assessing the comparison between intrauterine infection and neonatal inflammatory conditions in infants delivered at full-term. [ABSTRACT FROM PUBLISHER]