Search

Abstract Transformer tracking always takes paired template and search images as encoder input and conduct feature extraction and target‐search feature correlation by self and/or cross attention operations, thus the model complexity will grow quadratically with the number of input images. To alleviate the burden of this tracking paradigm and facilitate practical deployment of Transformer‐based trackers, we propose a dual pooling transformer tracking framework, dubbed as DPT, which consists of three components: a simple yet efficient spatiotemporal attention model (SAM), a mutual correlation pooling Transformer (MCPT) and a multiscale aggregation pooling Transformer (MAPT). SAM is designed to gracefully aggregates temporal dynamics and spatial appearance information of multi‐frame templates along space‐time dimensions. MCPT aims to capture multi‐scale pooled and correlated contextual features, which is followed by MAPT that aggregates multi‐scale features into a unified feature representation for tracking prediction. DPT tracker achieves AUC score of 69.5 on LaSOT and precision score of 82.8 on TrackingNet while maintaining a shorter sequence length of attention tokens, fewer parameters and FLOPs compared to existing state‐of‐the‐art (SOTA) Transformer tracking methods. Extensive experiments demonstrate that DPT tracker yields a strong real‐time tracking baseline with a good trade‐off between tracking performance and inference efficiency.

For decades in China, carbon neutrality policies have spurred the establishment of northern margin mangroves as artificial blue carbon ecosystems. However, there has been limited research on the impact of plantation and invasion on the stocks and sources of soil carbon and nitrogen in rehabilitated coastal wetlands. Non-native Kandelia obovata afforestation began on Ximen Island, Zhejiang, China, where Spartina alterniflora invasion had also occurred decades ago. Soil cores were collected from both mangrove and salt marsh habitats with depths from 0 to 50 cm and were analyzed for total carbon (TC), soil organic carbon (SOC), total nitrogen (TN), and the isotope of carbon and nitrogen in sediments. The results indicated that there were no significant differences in the TC, SOC, and C/N ratio between the K. obovata and the S. alterniflora, but there were significant differences in TN, isotope δ13C, and δ15N. The SOC content of both ecosystems in the 0–20 cm layer was significantly higher than that in the 30–50 cm layer. Our study has shown that the main sources of carbon and nitrogen for mangroves and salt marshes are different, especially under the impact of external factors, such as tidal waves and aquaculture. These findings provide insight into the ecological functioning of subtropical coastal wetlands and an understanding of the biogeochemical cycles of northern margin mangrove ecosystems.

Abstract Scene perception and trajectory forecasting are two fundamental challenges that are crucial to a safe and reliable autonomous driving (AD) system. However, most proposed methods aim at addressing one of the two challenges mentioned above with a single model. To tackle this dilemma, this paper proposes spatio‐temporal semantics and interaction graph aggregation for multi‐agent perception and trajectory forecasting (ST‐SIGMA), an efficient end‐to‐end method to jointly and accurately perceive the AD environment and forecast the trajectories of the surrounding traffic agents within a unified framework. ST‐SIGMA adopts a trident encoder–decoder architecture to learn scene semantics and agent interaction information on bird’s‐eye view (BEV) maps simultaneously. Specifically, an iterative aggregation network is first employed as the scene semantic encoder (SSE) to learn diverse scene information. To preserve dynamic interactions of traffic agents, ST‐SIGMA further exploits a spatio‐temporal graph network as the graph interaction encoder. Meanwhile, a simple yet efficient feature fusion method to fuse semantic and interaction features into a unified feature space as the input to a novel hierarchical aggregation decoder for downstream prediction tasks is designed. Extensive experiments on the nuScenes data set have demonstrated that the proposed ST‐SIGMA achieves significant improvements compared to the state‐of‐the‐art (SOTA) methods in terms of scene perception and trajectory forecasting, respectively. Therefore, the proposed approach outperforms SOTA in terms of model generalisation and robustness and is therefore more feasible for deployment in real‐world AD scenarios.

Background: To reveal candidate genes and the molecular genetic mechanism underlying primary feather color trait in ducks, a genome-wide association study (GWAS) for the primary feather color trait was performed based on the genotyping-by-sequencing (GBS) technology for a native Chinese female duck, Longyan Shan-ma ducks.Methods: Blood genomic DNA from 314 female Longyan Shan-ma duck were genotyped using GBS technology. A GWAS for the primary feather color trait with genome variations was performed using an univariate linear mixed model based on all SNPs in autosomes.Results: Seven genome-wide significant single nucleotide polymorphisms (SNPs, Bonferroni-adjusted p-value

Sediment is an important part of the lake and reservoir ecosystem, and also an important "source" and "sink" of pollutants. In this paper, sediment A (Xinlicheng Reservoir Sediments), sediment B (eutrophic lake reservoir sediments) and soil C (topsoil at the inflow of Yitong River near Xinlicheng Reservoir) are used as research objects, and batch experiments are used to study the adsorption capacity and release risk of phosphorus (P). The results showed that the maximum adsorption capacity of the adsorbent for phosphorus accounted for 91.51-99.63% of the total adsorption capacity within 0-120 min; when the background liquid phosphorus concentration is lower, soil and sediment all have different degrees of phosphorus release. By this time soil and sediment is the "source" of pollutants; when the phosphorus concentration is 10 mg/L, the maximum adsorption capacity is 116.19-428.91 mg/kg, and the adsorption capacity of sediment A is 2.41 times and that of soil C and sediment B, respectively. 3.69 times, indicating that if phosphorus enters the water body from the soil due to surface runoff and other factors, the sediment has a strong adsorption capacity for phosphorus, that is, soil and sediment is an effective "sink" of phosphorus; the Henry equation is used to fit the P adsorption isotherm effect. Preferably, and r is greater than 0.968. The amount of phosphorus absorbed by sediment A and sediment B is affected by pH higher than that of soil C. When the value of pH is 7, the adsorption amount is the largest; the P induced lake eutrophication risk index (ERI) of sediment A, sediment B and soil C is sediment B > soil C > sediment A. As the temperature of sediment and soil rises, the ERI index of phosphorus gradually decreases.

Abstract Huntington’s disease (HD) is a neurodegenerative disease. MicroRNAs (miRNAs) are small non-coding RNAs that mediate post-transcriptional regulation of target genes. Although miRNAs are extensively edited in human brains, the editome of miRNAs in brains of HD patients is largely unknown. By analyzing the small RNA sequencing profiles of brain tissues of 28 HD patients and 83 normal controls, 1182 miRNA editing sites with significant editing levels were identified. In addition to 27 A-to-I editing sites, we identified 3 conserved C-to-U editing sites in miRNAs of HD patients. 30 SNPs in the miRNAs of HD patients were also identified. Furthermore, 129 miRNA editing events demonstrated significantly different editing levels in prefrontal cortex samples of HD patients (HD-PC) when compared to those of healthy controls. We found that hsa-mir-10b-5p was edited to have an additional cytosine at 5’-end in HD-PC, and the edited hsa-mir-10b repressed GTPBP10 that was often downregulated in HD. The down-regulation of GTPBP10 might contribute to the progression of HD by causing gradual loss of function of mitochondrial. These results provide the first endeavor to characterize the miRNA editing events in HD and their potential functions.

Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most destructive wheat diseases worldwide. Understanding the effects of cultivar mixture on disease control and population genetic structure of Pst could promote the effective application of cultivar mixtures. This study designed nine cultivar mixtures composed of different component cultivars with field experiments in Zitong County, Sichuan Province in two seasons from 2016 to 2018. Diseased leaves were collected in each plot of treatment in the spring and, in total, 835 and 568 isolates were obtained and genotyped with 10 pairs of simple sequence repeat markers in the 2 years, respectively. The observed and theoretical values of the area under the disease progress curve (AUDPC), wheat yield, Pst genotypic diversity, and the frequency of Pst dominant genetic groups were compared among cultivar mixtures. With the 2 years’ experiments, there were three and two cultivar mixtures, respectively, showing significant effect on the relative reduction of AUDPC; there were no significant effects on the relative yield increase in all mixtures in the 2 years. There were four and five cultivar mixtures showing positive effects on the relative increase of Pst genotypic diversity in the 2 years, respectively. Moreover, all cultivar mixtures could decrease the frequencies of Pst dominant genetic groups on highly susceptible component cultivar compared with their theoretical frequencies.[Figure: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

ABSTRACT Harnessing indigenous soil microbial suppression is an emerging strategy for managing soilborne plant diseases. Soil moisture is a vital factor in soil microbiomes, but its role in the regulation of microbial suppression is poorly understood. Here, we investigated the correlation of root rot disease of Panax notoginseng with rhizosphere microbial communities mediated by soil moisture gradients from 55% to 100% field capacity (FC); then, we captured the disease-suppressive and disease-inductive microbiomes and validated their functions by a culture experiment with synthetic microbiotas containing keystone species. We found that proper soil moisture at 75% to 95% FC could maintain a disease-suppressive microbiome to alleviate root rot disease. However, extremely low or high soil moistures (>95% FC or

ABSTRACT Wheat stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a crucial disease for wheat worldwide and constantly threatens wheat production in southwestern and northwestern China, where the environment is a good fit for Pst oversummering and overwintering. However, the underlying genetic dynamics of spring epidemic Pst populations across large areas of continuous planting in the southwestern and northwestern regions are poorly understood. A total of 2,103 Pst isolates were sampled in the spring of 2019 from the two agroecosystems and grouped into three horizontal spatial scales (countywide, provincial, and regional subpopulations) and two vertical spatial scales that consisted of elevational and geomorphic subpopulations. A total of 776 multilocus genotypes were identified, with the highest genetic diversity found in the northern and Sichuan populations, particularly in the Ningxia and Sichuan Basins, while the lowest genetic diversity was found in the Yunnan and Guizhou populations. Multivariate discriminant analysis of principal components (DAPC) and STRUCTURE (STRUCTURE 2.3.4) analyses revealed variation in the genotypic compositions of the molecular groups on horizontal and vertical dimensions from north to south or vice versa and from low to high or vice versa, respectively. The regional neighbor-joining tree revealed three large spatial structures consisting of the southwestern, the northwestern, and the Xinjiang regions, while the Tibetan population connected the southwestern and northwestern regions. The isolates of the Sichuan Basin were scattered over the four quartiles by principal coordinate analysis, which indicated frequent genotype interchange with others. Greater genetic differentiation was observed between the southwestern and northwestern regions. Linkage equilibrium (P ≥ 0.05) was detected on different spatial scales, suggesting that Pst populations are using sexual reproduction or mixed reproduction (sexual and clonal reproduction) in southwestern and northwestern China. IMPORTANCE Understanding the epidemiology and population genetics of plant pathogens is crucial to formulate efficient predictions of disease outbreaks and achieve sustainable integrated disease management, especially for pathogens with migratory capability. Here, this study covers the genetic homogeneity and heterogeneity of different geographical Pst populations on broad to fine spatial scales from the key epidemic regions of the two agroecosystems in China, where wheat stripe rust occurs annually. We provide knowledge of the population genetics of Pst and reveal that, for instance, there is greater genetic diversity in northwestern China, there are close genetic relationships between Yunnan and Guizhou and between Gansu-Ningxia and Qinghai, and there are effects of altitude on genetic compositions, etc. All of these findings clarify the genetic relationships and expand the insights into the population dynamics and evolutionary mechanisms of Pst in southwestern and northwestern China, providing a theoretical basis for achieving sustainable control of wheat stripe rust in key epidemic regions.

Abstract Background MicroRNAs (miRNAs) are small non-coding RNAs that play important roles by regulating other genes. Rosa rugosa Thunb. is an important ornamental and edible plant, yet there are only a few studies on the miRNAs and their functions in R. rugosa. Results We sequenced 10 samll RNA profiles from the roots, petals, pollens, stamens, and leaves and 4 RNA-seq profiles in leaves and petals to analysis miRNA, phasiRNAs and mRNAs in R. rugosa. In addition, we acquired a degradome sequencing profile from leaf of R. rugosa to identify miRNA and phasiRNA targets using the SeqTar algorithm. We have identified 321 conserved miRNA homologs including primary transcripts for 25 conserved miRNAs, and 22 novel miRNAs. We identified 592 putative targets of the conserved miRNAs or tasiRNAs that showed significant accumulations of degradome reads. We found differential expression patterns of conserved miRNAs in five different tissues of R. rugosa. We identified three hundred and thirty nine 21 nucleotide (nt) PHAS loci, and forty nine 24 nt PHAS loci, respectively. Our results suggest that miR482 triggers generations of phasiRNAs by targeting nucleotide-binding, leucine-rich repeat (NB-LRR) disease resistance genes in R. rugosa. Our results also suggest that the deregulated genes in leaves and petals are significantly enriched in GO terms and KEGG pathways related to metabolic processes and photosynthesis. Conclusions These results significantly enhanced our knowledge of the miRNAs and phasiRNAs, as well as their potential functions, in R. rugosa.

PRML, a novel candlestick pattern recognition model using machine learning methods, is proposed to improve stock trading decisions. Four popular machine learning methods and 11 different features types are applied to all possible combinations of daily patterns to start the pattern recognition schedule. Different time windows from one to ten days are used to detect the prediction effect at different periods. An investment strategy is constructed according to the identified candlestick patterns and suitable time window. We deploy PRML for the forecast of all Chinese market stocks from Jan 1, 2000 until Oct 30, 2020. Among them, the data from Jan 1, 2000 to Dec 31, 2014 is used as the training data set, and the data set from Jan 1, 2015 to Oct 30, 2020 is used to verify the forecasting effect. Empirical results show that the two-day candlestick patterns after filtering have the best prediction effect when forecasting one day ahead; these patterns obtain an average annual return, an annual Sharpe ratio, and an information ratio as high as 36.73%, 0.81, and 2.37, respectively. After screening, three-day candlestick patterns also present a beneficial effect when forecasting one day ahead in that these patterns show stable characteristics. Two other popular machine learning methods, multilayer perceptron network and long short-term memory neural networks, are applied to the pattern recognition framework to evaluate the dependency of the prediction model. A transaction cost of 0.2% is considered on the two-day patterns predicting one day ahead, thus confirming the profitability. Empirical results show that applying different machine learning methods to two-day and three-day patterns for one-day-ahead forecasts can be profitable.

The western basin of Lake Erie, the shallowest of the Laurentian Great Lakes in North America, is now plagued by harmful algal blooms annually due to nutrient discharges primarily from its basin. Water quality was impacted so significantly by toxic cyanobacteria in 2014 that the city of Toledo’s water supply was shut off, affecting hundreds of thousands of residents. A new agricultural land management approach, ‘wetlaculture (=wetland + agriculture)’, has a goal of reducing the need for fertilizer applications while preventing fluxes of nutrients to downstream aquatic ecosystems. A wetlaculture mesocosm experiment was set up on agricultural land near Defiance, Ohio, on the northwestern edge of the former ‘Great Black Swamp’. The mesocosms were randomly assigned to four hydrologic treatments involving two water depths (no standing water and ~10-cm of standing water) and two hydraulic loading rates (10 and 30 cm week−1). Nearby agricultural ditch water was pumped to provide weekly hydraulic loading rates to the mesocosms. During the two-year period, the net mass retention of phosphorus from the water was estimated to have averaged 1.0 g P m−2 in the wetland mesocosms with a higher hydraulic loading rate, while the highest estimated net nitrogen mass retention (average 22 g N m−2) was shown in the wetland mesocosms with 10 cm of standing water and higher hydraulic loading rate. Our finding suggests that hydrologic conditions, especially water level, contribute directly and indirectly to nutrient retention, partially through the quick response of the wetland vegetation community. This study provides valuable information for scaling up to restore significant areas of wetlaculture/wetlands in the former Great Black Swamp, strategically focused on reducing the nutrient loading to western Lake Erie from the Maumee River Basin.

A disc filter (DF) is an important component in a micro irrigation system. However, it has a high head loss and low filtration efficiency, which can lead to the inoperability of micro irrigation systems. To improve the filtration ability and to decrease the pressure loss of the irrigation system, it is necessary to internalize the hydraulic characteristics of DFs. In this study, the filter bed of a DF was divided into three parts, i.e., upper, middle, and lower, which were wrapped with a transparent film. The wrapped part was completely blocked. The purpose was to analyze the hydraulic characteristics of different clogged conditions in three types of filters under four types of flows. In addition, we attempted to simulate the filter operation process with computational fluid dynamics, based on two aspects—a macroscopic model and a simplified model. The results showed that the patterns of head loss among all of the DFs was consistent, and the macroscopic model that treated filter bed as a porous medium could express the measured results. The macroscopic models observed that there was a circular flow in the DF, and the flow velocity presented a symmetrical distribution in a horizontal direction. The middle of the filter element appeared in a high-pressure area and demonstrated the highest head loss, which may be the main flow area of the DF, and the inner flow characteristics of the DF were consistent under different conditions. The simplified models showed that the main flow area is near the filter bed in the inner DF, and the flow is tangent to the filter bed between 45 and 90 degrees in a horizontal direction. The uneven distribution of velocity and pressure on the filter bed might be necessary factors to impact filter efficiency.

MicroRNAs (miRNAs) are small non-coding RNAs that are critical in post-transcriptional regulation. Macaca mulatta is an important nonhuman primate that is often used in basic and translational researches. However, the annotation of miRNAs in Macaca mulatta is far from complete, and there are no reports of miRNA editing events in Macaca mulatta, although editing may affect the biogenesis or functions of the miRNAs. To improve miRNA annotation and to reveal editing events of miRNAs in Macaca mulatta, we generated 12 small RNA profiles from eight tissues and performed comprehensive analysis of these profiles. We identified 479 conserved pre-miRNAs that have not been reported in Macaca mulatta and 17 species specific miRNAs. Furthermore, we identified 3386 editing sites with significant editing levels from 471 pre-miRNAs after analyzing the 12 self-generated and 58 additional published sRNA-seq profiles from 17 different types of organs or tissues. In addition to 16 conserved A-to-I editing sites, we identified five conserved C-to-U editing sites in miRNAs of Macaca mulatta and Homo sapiens. We also identified 11 SNPs in the miRNAs of Macaca mulatta. The analysis of the potential targets of 69 miRNAs with editing or mutation events in their seed regions suggest that these editing or mutation events severely changed their targets and their potential functions. These results significantly increase our understanding of miRNAs and their mutation/editing events in Macaca mulatta.

Bingbing Jiang1, John B Barnett2,3, Bingyun Li1,4,5#1Biomaterials, Bioengineering and Nanotechnology Laboratory, Department of Orthopaedics, School of Medicine, 2Department of Microbiology, Immunology, and Cell Biology, 3Center for Immunopathology and Microbial Pathogenesis, School of Medicine, 5Department of Chemical Engineering, College of Engineering and Mineral Resources, West Virginia University, Morgantown, WV, USA; 4WVNano Initiative, Morgantown, WV, USA; #Aided by a grant from Osteosynthesis and Trauma Care (OTC) FoundationAbstract: There has been considerable interest in polyelectrolyte multilayer nanofilms, which have a variety of applications ranging from optical and electrochemical materials to biomedical devices. Polyelectrolyte multilayer nanofilms are constructed from aqueous solutions using electrostatic layer-by-layer self-assembly of oppositely-charged polyelectrolytes on a solid substrate. Multifunctional polyelectrolyte multilayer nanofilms have been studied using charged dyes, metal and inorganic nanoparticles, DNA, proteins, and viruses. In the past few years, there has been increasing attention to developing polyelectrolyte multilayer nanofilms as drug delivery vehicles. In this mini-review, we present recent developments in polyelectrolyte multilayer nanofilms with tunable drug delivery properties, with particular emphasis on the strategies in tuning the loading and release of drugs in polyelectrolyte multilayer nanofilms as well as their applications.Keywords: nanofilm, polyelectrolyte multilayer, drug delivery, electrostatic layer-by-layer self-assembly, biomedical device, surface modification

Bingbing Jiang1, Bingyun Li1,2,31Biomaterials, Bioengineering and Nanotechnology Laboratory, Department of Orthopaedics, School of Medicine, West Virginia University, Morgantown, WV, USA; 2WVNano Initiative, WV, USA; 3Department of Chemical Engineering, College of Engineering and Mineral Resources, West Virginia University, Morgantown, WV, USA Abstract: Polypeptide multilayer nanofilms were prepared using electrostatic layer-by-layer self-assembly nanotechnology. Small charged drug molecules (eg, cefazolin, gentamicin, and methylene blue) were loaded in polypeptide multilayer nanofilms. Their loading and release were found to be pH-dependent and could also be controlled by changing the number of film layers and drug incubation time, and applying heat-treatment after film formation. Antibiotic-loaded polypeptide multilayer nanofilms showed controllable antibacterial properties against Staphylococcus aureus. The developed biodegradable polypeptide multilayer nanofilms are capable of loading both positively- and negatively-charged drug molecules and promise to serve as drug delivery systems on biomedical devices for preventing biomedical device-associated infection, which is a significant clinical complication for both civilian and military patients.Keywords: polypeptide, self-assembly, polyelectrolyte multilayer, nanofilm, charged molecule, tunable release

BACKGROUND AND AIMS:Sanqi ginseng (Panax notoginseng) growth is often hampered by replant failure. In this study, we aimed to examine the role of autotoxicity in Sanqi replant failures and assess the role of ginsenosides in autotoxicity. METHODS:The autotoxicities were measured using seedling emergence bioassays and root cell vigor staining. The ginsenosides in the roots, soils, and root exudates were identified with HPLC-MS. RESULTS:The seedling emergence and survival rate decreased significantly with the continuous number of planting years from one to three years. The root exudates, root extracts, and extracts from consecutively cultivated soils also showed significant autotoxicity against seedling emergence and growth. Ginsenosides, including R1, Rg1, Re, Rb1, Rb3, Rg2, and Rd, were identified in the roots and consecutively cultivated soil. The ginsenosides, Rg1, Re, Rg2, and Rd, were identified in the root exudates. Furthermore, the ginsenosides, R1, Rg1, Re, Rg2, and Rd, caused autotoxicity against seedling emergence and growth and root cell vigor at a concentration of 1.0 µg/mL. CONCLUSION:Our results demonstrated that autotoxicity results in replant failure of Sanqi ginseng. While Sanqi ginseng consecutively cultivated, some ginsenosides can accumulate in rhizosphere soils through root exudates or root decomposition, which impedes seedling emergence and growth.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease characterized by loss of motor neurons. The mechanisms leading to motor neuron degeneration in ALS are unclear. However, there is evidence for involvement of endoplasmic reticulum (ER) stress and the unfolded protein response (UPR) in ALS, notably in mutant SOD1 mediated models of ALS. Stress induced phosphorylation of the eIF2 alpha subunit by eukaryotic translation initiation factor 2-alpha kinase 3 Perk activates the UPR. Guanabenz is a centrally acting alpha2 adrenergic receptor agonist shown to interact with a regulatory subunit of the protein phosphatase, Pp1/Gadd34, and selectively disrupt the dephosphorylation of the alpha subunit of eukaryotic initiation factor 2 (eif2alpha). Here we demonstrate that guanabenz is protective in fibroblasts expressing G93A mutant SOD1 when they are exposed to tunicamycin mediated ER stress. However, in contrast to other reports, guanabenz treatment accelerated ALS-like disease progression in a strain of mutant SOD1 transgenic ALS mice. This study highlights challenges of pharmacological interventions of cellular stress responses in whole animal models of ALS.

Inflammatory cytokines play an important role in the pathogenesis of heart failure. We have recently found the cytokine TWEAK (tumor necrosis factor (TNF)-like weak inducer of apoptosis), a member of the TNF superfamily, to be increased in patients with cardiomyopathy and result in the development of heart failure when overexpressed in mice. The molecular mechanisms underlying TWEAK-induced cardiac pathology, however, remain unknown.Using mouse models of elevated circulating TWEAK levels, established through intravenous injection of adenovirus expressing TWEAK or recombinant TWEAK protein, we find that TWEAK induces a progressive dilated cardiomyopathy with impaired contractile function in mice. Moreover, TWEAK treatment is associated with decreased expression of peroxisome proliferator-activated receptor gamma coactivator-1α (PGC1α) and genes required for mitochondrial oxidative phosphorylation, which precede the onset of cardiac dysfunction. TWEAK-induced downregulation of PGC1α requires expression of its cell surface receptor, fibroblast growth factor-inducible 14 (Fn14). We further find that TWEAK downregulates PGC1α gene expression via the TNF receptor-associated factor 2 (TRAF2) and NFκB signaling pathways. Maintaining PGC1α levels through adenoviral-mediated gene expression is sufficient to protect against TWEAK-induced cardiomyocyte dysfunction.Collectively, our data suggest that TWEAK induces cardiac dysfunction via downregulation of PGC1α, through FN14-TRAF2-NFκB-dependent signaling. Selective targeting of the FN14-TRAF2-NFκB-dependent signaling pathway or augmenting PGC1α levels may serve as novel therapeutic strategies for cardiomyopathy and heart failure.

Aberrantly elevated sterol regulatory element binding protein (SREBP), the lipogenic transcription factor, contributes to the development of fatty liver and insulin resistance in animals. Our recent studies have discovered that AMP-activated protein kinase (AMPK) phosphorylates SREBP at Ser-327 and inhibits its activity, represses SREBP-dependent lipogenesis, and thereby ameliorates hepatic steatosis and atherosclerosis in insulin-resistant LDLR(-/-) mice. Chronic inflammation and activation of NLRP3 inflammasome have been implicated in atherosclerosis and fatty liver disease. However, whether SREBP is involved in vascular lipid accumulation and inflammation in atherosclerosis remains largely unknown.The preclinical study with aortic pouch biopsy specimens from humans with atherosclerosis and diabetes shows intense immunostaining for SREBP-1 and the inflammatory marker VCAM-1 in atherosclerotic plaques. The cleavage processing of SREBP-1 and -2 and expression of their target genes are increased in the well-established porcine model of diabetes and atherosclerosis, which develops human-like, complex atherosclerotic plaques. Immunostaining analysis indicates an elevation in SREBP-1 that is primarily localized in endothelial cells and in infiltrated macrophages within fatty streaks, fibrous caps with necrotic cores, and cholesterol crystals in advanced lesions. Moreover, concomitant suppression of NAD-dependent deacetylase SIRT1 and AMPK is observed in atherosclerotic pigs, which leads to the proteolytic activation of SREBP-1 by diminishing the deacetylation and Ser-372 phosphorylation of SREBP-1. Aberrantly elevated NLRP3 inflammasome markers are evidenced by increased expression of inflammasome components including NLPR3, ASC, and IL-1β. The increase in SREBP-1 activity and IL-1β production in lesions is associated with vascular inflammation and endothelial dysfunction in atherosclerotic pig aorta, as demonstrated by the induction of NF-κB, VCAM-1, iNOS, and COX-2, as well as by the repression of eNOS.These translational studies provide in vivo evidence that the dysregulation of SIRT1-AMPK-SREBP and stimulation of NLRP3 inflammasome may contribute to vascular lipid deposition and inflammation in atherosclerosis.