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Circular RNAs (circRNAs) are a class of endogenous non-coding RNAs with covalently closed circular structures, which play an important role in transcriptional and post-transcriptional regulation. Tiller is an important agronomic trait that determines plant morphological architecture and affects spike number in wheat. However, no studies on the characteristics and functions of circRNAs involved in the regulation of wheat tiller. Here, we performed a genome-wide identification of circRNAs using ribosomal-depleted RNA-seq from wheat tiller of two pairs near-isogenic lines. A total of 686 circRNAs were identified and distributed on 21 chromosomes of wheat, of which 537 novel circRNAs. Unlike other plants, the majority of these circRNAs (61.8%) were derived from intergenic regions. One circRNA-mediated network associated with tillering was constructed through weighted gene co-expression network analysis, including 323 circRNAs, 117 miRNAs and 968 mRNAs. GO and pathway enrichment analysis of mRNAs suggested that these circRNAs are involved in cell cycle, ncRNA export from nucleus, developmental process, Plant hormone signal transduction, MAPK signaling pathway, RNA degradation. Of these circRNAs, 10 circRNAs are associated with known tillering/branching genes in rice or Arabidopsis thaliana, including OsCesA7, EBR1, DTE1, CRD1, LPA1, PAY1, LRK1, OsNR2, OsCCA1, OsBZR1. In summary, we present the first study of the identification and characterization of circRNAs in wheat tiller, and the results suggest these circRNAs associated with tillering could play an important role in wheat tiller formation and development.

Objective The reprogramming of metabolism is an important factor in the metastatic process of cancer. In our study, we intended to investigate the predictive value of metabolism-related genes (MRGs) in recurrent gastric cancer (GC) patients with peritoneal metastasis. Methods The sequencing data of mRNA of GC patients were obtained from Asian Cancer Research Group (ACRG) and the GEO databases (GSE53276). The differentially expressed MRGs (DE-MRGs) between a cell line without peritoneal metastasis (HSC60) and one with peritoneal metastasis (60As6) were analyzed with the Limma package. According to the LASSO regression, eight MRGs were identified as crucially related to peritoneal seeding recurrence in patients. Then, disease free survival related genes were screened using Cox regression, and a promising prognostic model was constructed based on 8 MRGs. We trained and verified it in two independent cohort. Results We confirmed 713 DE-MRGs and the enriched pathways. Pathway analysis found that the MRG-related pathways were related to tumor metabolism development. With the help of Kaplan–Meier analysis, we found that the group with higher risk scores had worse rates of peritoneal seeding recurrence than the group with lower scores in the cohorts. Conclusions This study developed an eight-gene signature correlated with metabolism that could predict peritoneal seeding recurrence for GC patients. This signature could be a promising prognostic model, providing better strategy in treatment.

As the most promising primary explosive in micro-initiator, copper azide is eye-catching due to its outstanding detonation power, but it is limited due to its high electrostatic sensitivity and difficulty in terms of molding. In this work, we have developed a novel, green and simple strategy, based on graphene oxide modified copper-containing metal–organic framework materials, using water-soluble polyvinyl alcohol as binder to synthesize spherical copper azide/Carbon/reduced graphene oxide (CA/C/rGO) composite, in which CA nanoparticles are uniformly distributed on the porous carbon framework. Detailed characterization shows that the coordination effect of carbon framework material and graphene makes the obtained spherical CA/C/rGO have remarkable electrostatic stability and ignition ability. The obtained CA/C/rGO material has an electrostatic sensitivity of 2.0 mJ and a flame sensitivity of 45 cm, which greatly enhances its electrostatic safety and maintains good ignition performance. The CA/C/rGO is further assembled in a micro-initiator, which successfully detonates the secondary explosive hexanitrohexaazaisowurtzitane (CL-20). The manufacturing process of CA/C/rGO materials is environmentally friendly, easy to volume-produce, and can be well matched with the charging method of the micro-initiator system.

In poultry, organic zinc compounds have higher bioavailability than inorganic zinc sources. However, as an organic zinc source, the application of zinc lactate (ZL) on Chinese yellow-feathered broilers has been rarely reported. Hence, the present study aimed to investigate the effects of ZL supplementation on growth performance, small intestinal morphology, serum biochemical parameters, immune organ index, as well as hepatic metallothionein of Chinese yellow-feathered broilers. A total of 2100 broilers (19 days old) were randomly assigned to 5 treatment groups, including the control (fed basal diet), ZL40 (basal diet plus 40 mg/kg ZL), ZL60 (basal diet plus 60 mg/kg ZL), ZL80 (basal diet plus 80 mg/kg ZL), and ZS80 (basal diet plus 80 mg/kg ZS. Each treatment group had 6 replicates with 70 chickens per replicate. Compared to the control group, the ZL40 and the ZS80 groups had a lower feed to gain ratio (P P P P P P

Meiosis, a highly conserved process in organisms from fungi to mammals, is subjected to protein phosphorylation regulation. Due to the low abundance of phosphorylation, there is a lack of systemic characterization of phosphorylation regulation of meiosis in mammals. Using the phosphoproteomic approach, we profiled large-scale phosphoproteome of purified primary spermatocytes undergoing meiosis I, and identified 14,660 phosphorylation sites in 4419 phosphoproteins. Kinase-substrate phosphorylation network analysis followed by in vitro meiosis study showed that CDK9 was essential for meiosis progression to metaphase I and had enriched substrate phosphorylation sites in proteins involved in meiotic cell cycle. In addition, histones and epigenetic factors were found to be widely phosphorylated. Among those, HASPIN was found to be essential for male fertility. Haspin knockout led to misalignment of chromosomes, apoptosis of metaphase spermatocytes and a decreased number of sperm by deregulation of H3T3ph, chromosomal passenger complex (CPC) and spindle assembly checkpoint (SAC). The complicated protein phosphorylation and its important regulatory functions in meiosis indicated that in-depth studies of phosphorylation-mediated signaling could help us elucidate the mechanisms of meiosis.

A sustainable natural polymer, cellulose, has been used as precursor for producing carbonaceous materials. Ionothermal carbonization (ITC) in ionic liquid (IL) could transform biomass into functional carbon materials at a relatively low temperature. In order to improve the ITC carbon yields and structures, the first raw transition metal chlorides were added into IL, 1-Butyl-3-methyl-imidazole chloride (BmimCl), and their catalyzing effects were compared. It is found that the catalyzing effects of transition metal chlorides are mainly correlated to their cation size. With the addition of 0.5wt% NiCl2 (based on IL), a high carbon yield of 94wt% is obtained. Additionally, the bio-based carbonaceous materials exhibit a higher graphitization degree with the addition of metal chloride. Furthermore, the IL shows good cyclability, and the carbon yield remains to be higher than 80 wt% after 5 cycles.

Excessive fluoride (F) exposure can lead to liver damage; moreover, recent studies found that the addition of appropriate calcium (Ca) can alleviate the symptom of skeletal fluorosis. However, whether Ca can relieve F-induced liver damage through the mitochondrial apoptosis pathway has not been reported yet. Therefore, we assessed the liver morphology, serum transaminase content, liver oxidative stress-related enzymes, and apoptosis-related gene and protein expression in Sprague Dawley (SD) rats treated with 150 mg/L sodium fluoride (NaF) and different concentrations of calcium carbonate (CaCO3) for 120 days. Our results showed that NaF brought out pathological changes in liver morphology, serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels increased, total antioxidant capacity (T-AOC), superoxide dismutase (SOD), glutathione peroxidase (GSH-Px) content decreased, and malondialdehyde (MDA) content increased, suggesting that NaF caused hepatotoxicity and oxidative stress. In addition, the results of quantitative real-time PCR (qRT-PCR) and immunohistochemistry showed that NaF exposure upregulated the expression of Bcl-2-associated x protein (Bax), rho-related coiled-coil kinase 1 (ROCK1), cytochrome C (Cyto-C) mRNA and protein (P < 0.01), and downregulated B cell lymphoma 2 (Bcl-2) protein and mRNA (P < 0.01), indicating that excessive F exposure activated mitochondrial-mediated apoptosis in the liver. However, the addition of 1% CaCO3 to the diet significantly increased the expression of anti-apoptotic gene Bcl-2 (P < 0.01), inhibited the activation of the mitochondrial apoptosis pathway, and reduced mitochondrial damage. In summary, supplementing 1% CaCO3 in the diet can alleviate the NaF-induced liver cell damage through the mitochondrial apoptosis pathway.

Purpose Positive margins after gastrectomy have been associated with poor patient prognosis. This study aimed to identify risk factors associated with margin-positive resections. Methods The National Cancer Database was queried from 2004 to 2014 for all patients with gastric adenocarcinoma who underwent resection with curative intent and had known margin status. Univariable and multivariable logistic regression analysis was performed to identify variables associated with positive margins. Results A total of 32,193 patients were identified who met study inclusion criteria, of which 11.8% (3786 patients) had a margin-positive resection. Tumor size > 6 cm, T3 or T4 tumors, tumor location in the body of stomach or in multiple regions, signet ring cell histology, presence of lymphovascular invasion, positive lymph node involvement, and lack of neoadjuvant therapy were independently associated with an increased risk of positive margins. Conclusions Advanced disease characteristics, aggressive tumor pathology, and absence of neoadjuvant therapy were associated with margin-positive resections.

Phosphate, a key plant nutrient, is perceived through inositol polyphosphates (InsPs) by SPX domain-containing proteins. SPX1 an inhibit the PHR2 transcription factor to maintain Pi homeostasis. How SPX1 recognizes an InsP molecule and represses transcription activation by PHR2 remains unclear. Here we show that, upon binding InsP6, SPX1 can disrupt PHR2 dimers and form a 1:1 SPX1-PHR2 complex. The complex structure reveals that SPX1 helix α1 can impose a steric hindrance when interacting with the PHR2 dimer. By stabilizing helix α1, InsP6 allosterically decouples the PHR2 dimer and stabilizes the SPX1-PHR2 interaction. In doing so, InsP6 further allows SPX1 to engage with the PHR2 MYB domain and sterically block its interaction with DNA. Taken together, our results suggest that, upon sensing the surrogate signals of phosphate, SPX1 inhibits PHR2 via a dual mechanism that attenuates dimerization and DNA binding activities of PHR2., SPX proteins sense phosphate levels in plant cells by binding to inositol polyphosphates (InsP) and suppressing the activity of PHR transcription factors. Here the authors show that when bound to InsP6, the rice SPX1 protein inhibits the activity of PHR2 by attenuating both its dimerization and DNA binding activity.

Intelligent service robot is a challenging area of research that is rapidly expanding in our daily life. To meet robot’s object detection requirements in a messy surrounding, this paper provides a visual object detection method based on color and shape features. Firstly, a color hierarchical model and a multi-size filter are built to obtain initial object regions from scene image. Then a straight line-corner-arc strategy is presented to detect shape features. After comparing color and shape features with known-objects’ features stored in database, the detection scope is narrowed. So speeded up robust features algorithm is used to quickly match object features. The proposed method is tested by mobile robot in a semi-structured indoor environment. Finally, combined with the above steps, the total detection accuracy achieves 88.5% that confirms the feasibility of the proposed method.

Extracorporeal shock wave therapy (ESWT) has been reported as a new therapy for carpal tunnel syndrome (CTS). However, few studies have compared ESWT with the local corticosteroid injection (LCI). In this study, a randomized controlled trial comparing 30 patients with ESWT and 25 patients treated with LCI was conducted. The clinical outcomes were obtained with tests including the visual analog scale (VAS) for pain and paresthesia, the Boston Carpal Tunnel Questionnaire (BQ), and a nerve conduction study, before the study started and at three, nine, and 12 weeks after the start of the treatment. Significantly greater improvement in the VAS and BQ scores was noted for the ESWT group than for the LCI group (P < 0.05). For the nerve conduction study, there was a significant improvement in the median nerve sensory nerve action potential distal latency at the nine and 12-week follow-ups for the ESWT group. ESWT is a useful noninvasive short-term treatment for mild to moderate carpal tunnel syndrome and elicits a better recovery than LCI does, but more research is needed to test the clinical outcomes of ESWT.

Blind image deblurring is a long-standing ill-posed inverse problem which aims to recover a latent sharp image given only a blurry observation. So far, existing studies have designed many effective priors w.r.t. the latent image within the maximum a posteriori (MAP) framework in order to narrow down the solution space. These non-convex priors are always integrated into the final deblurring model, which makes the optimization challenging. However, due to unknown image distribution, complex kernel structure and non-uniform noises in real-world scenarios, it is indeed challenging to explicitly design a fixed prior for all cases. Thus we adopt the idea of adaptive optimization and propose the sparse structure control (SSC) for the latent image during the optimization process. In this paper, we only formulate the necessary optimization constraints in a lightweight MAP model with no priors. Then we develop an inexact projected gradient scheme to incorporate flexible SSC in MAP inference. Besides lp-norm based SSC in our previous work, we also train a group of denoising convolutional neural networks (CNNs) to learn the sparse image structure automatically from the training data under different noise levels, and we show that CNNs-based SSC can achieve similar results compared with lp-norm but are more robust to noise. Extensive experiments demonstrate that the proposed adaptive optimization scheme with two types of SSC achieves the state-of-the-art results on both synthetic data and real-world images.

Using 2008 China Time Use Survey data, this paper provides empirical evidence on whether and how Chinese couples synchronize their time use. The main findings are: (1) Chinese couples do deliberately coordinate their time use to gain more synchronous time in household work and leisure. (2) Non-couples also synchronize their activities if they live in the same household, but their time synchronization is much weaker than that of couples. (3) Couples’ synchronous time is significantly correlated to the husband’s and the wife’s labor supply and job characteristics, including wage rates, employment status, and occupation, as well as other personal characteristics and household demographics. This correlation differs between urban and rural couples. Generally speaking, urban couples are more similar to their Western counterparts. This paper is the first to provide a profile of couples’ coordination of time allocation in the socioeconomic context of a developing country, and it deepens the understanding of couples’ joint time allocation.

Recent years have witnessed the emerging and booming of social platforms (e.g., Facebook, Instagram, YouTube, and Flickr etc.), where people record, share/broadcast, and comment on media content, i.e., images and videos, leading to an accelerated proliferation of social media on the Internet. The rapid increase of social media has raised numerous new research challenges to multimedia content analysis. On the other hand, the availability of massive social media has also presented many exciting opportunities and challenges to attack in particular within the field of multimedia content analysis. This special issue aims to report recent research on large-scale social multimedia analysis and presents papers dealing with the various topics in this field. After rigorous reviewing, 11 papers were accepted for publication in MTAP. These papers cover most aspects for social media analysis. In particular, the papers of this issue concern (i) feature description and indexing for social media content, (ii) semantic understanding of social media, (iii) efficiency strategy for large scale practical social media analysis systems, (iv) social multimedia enabled applications, (v) social image processing and finally (vi) evaluations for social video content analysis. They are briefly discussed as follows. Multimed Tools Appl (2016) 75:1365–1369 DOI 10.1007/s11042-016-3255-z

As a new information sharing platform, microblog has got explosive growth in recent years and has become an important source for public opinion mining. A variety of information like the reviews of brands/products or the trends of events can be socially sensed from such kind of data. However, it is still a challenging task to search relevant microblogs as the user generated content tends to be mixed with noise. Besides short text, image is getting popular in microblogs due to its power in visual information conveying. In this paper, we leverage textual and visual cues integratedly and propose a general re-ranking approach for microblog retrieval via multi-graph semi-supervised learning. We argue that the different types of information in microblogs correspond to different relationships among microblogs and each type of the relationship can be represented as a similarity graph. We then integrate different graphs into a unified framework and solve them simultaneously for microblog re-ranking. Extensive experiments on a recently published Brand-Social-Net dataset showed the effectiveness of the proposed method and marginal improvements have been achieved in accuracy as compared to the single graph model based method.

Carbon-coated ZnFe2O4 spheres with sizes of ~110–180 nm anchored on graphene nanosheets (ZF@C/G) are successfully prepared and applied as anode materials for lithium ion batteries (LIBs). The obtained ZF@C/G presents an initial discharge capacity of 1235 mAh g−1 and maintains a reversible capacity of 775 mAh g−1 after 150 cycles at a current density of 500 mA g−1. After being tested at 2 A g−1 for 700 cycles, the capacity still retains 617 mAh g−1. The enhanced electrochemical performances can be attributed to the synergetic role of graphene and uniform carbon coating (~3–6 nm), which can inhibit the volume expansion, prevent the pulverization/aggregation upon prolonged cycling, and facilitate the electron transfer between carbon-coated ZnFe2O4 spheres. The electrochemical results suggest that the synthesized ZF@C/G nanostructures are promising electrode materials for high-performance lithium ion batteries.

Online social video websites such as YouTube allow users to manually annotate their video documents with textual labels. These labels can be used as indexing keywords to facilitate search and organization of video data. However, manual video annotation is usually a labor-intensive and time-consuming process. In this work, we propose a novel social video annotation approach that combines multiple feature sets based on a tri-adaptation approach. For the shots in each video, they are annotated by aggregating models that are learned from three complementary feature sets. Meanwhile, the models are collaboratively adapted by exploring unlabeled shots. In this sense, the method can be viewed as a novel semi-supervised algorithm that explores three complementary views. Our approach also exploits the temporal smoothness of video labels by applying a label correction strategy. Experiments on a web video dataset demonstrate the effectiveness of the proposed approach.

Nowadays, numerous social videos have pervaded on the web. Social web videos are characterized with the accompanying rich contextual information which describe the content of videos and thus greatly facilitate video search and browsing. Generally, those contextual data such as tags are provided at the whole video level, without temporal indication of when they actually appear in the video, let alone the spatial annotation of object related tags in the video frames. However, many tags only describe parts of the video content. Therefore, tag localization, the process of assigning tags to the underlying relevant video segments or frames even regions in frames is gaining increasing research interests and a benchmark dataset for the fair evaluation of tag localization algorithms is highly desirable. In this paper, we describe and release a dataset called DUT-WEBV, which contains about 4,000 videos collected from YouTube portal by issuing 50 concepts as queries. These concepts cover a wide range of semantic aspects including scenes like "mountain", events like "flood", objects like "cows", sites like "gas station", and activities like "handshaking", offering great challenges to the tag (i.e., concept) localization task. For each video of a tag, we carefully annotate the time durations when the tag appears in the video and also label the spatial location of object with mask in frames for object related tag. Besides the video itself, the contextual information, such as thumbnail images, titles, and YouTube categories, is also provided. Together with this benchmark dataset, we present a baseline for tag localization using multiple instance learning approach. Finally, we discuss some open research issues for tag localization in web videos.

Along with the high-speed cameras are more and more widely applied, how to automatically segment the region of interest in the slow-motion video is a new issue. In this paper, a color slow-motion video segmentation method is proposed. The main strategy is based on region growing and pixel color difference. A rapid color similarity computing method is improved and applied for classifying different pixels. An algorithm based on four directions corrosion is proposed to automatically extract the seed points for the serialized video frames. Utilizing this method, the color frames of the slow-motion videos can be segmented in series automatically. Also, the multithreading mode of parallel computing is introduced in the entire segmentation process. This method is not complicated but automatic. The regions of interest in the slow-motion video frames can be segmented clearly. This novel method can provide support to the video related applications.

Numerous web videos associated with rich metadata are available on the Internet today. While such metadata like video tags bring us facilitation and opportunities for video search and multimedia content understanding, some challenges also arise due to the fact that those video tags are usually annotated at the video level, while many tags actually only describe parts of the video content. How to localize the relevant parts or frames of web video for given tags is the key to many applications and research tasks. In this paper we propose combining topic model and relevance filtering to localize relevant frames. Our method is designed in three steps. First, we apply relevance filtering to assign relevance scores to video frames and a raw relevant frame set is obtained by selecting the top ranked frames. Then, we separate the frames into topics by mining the underlying semantics using latent Dirichlet allocation and use the raw relevance set as validation set to select relevant topics. Finally, the topical relevances are used to refine the raw relevant frame set and the final results are obtained. Experiment results on two real web video databases validate the effectiveness of the proposed approach.

The matching quality between the femoral head prosthesis and the acetabulum plays an important role in the operative treatment of the artificial femoral head replacement. In order to obtain a more accurate model of the femoral head prosthesis for the target sufferer, an improved individualized modeling system was presented in this paper. It was different from our previous system based on the sphere fitting method. This new system could reconstruct a more accurate ellipsoid model of the femoral head for the target sufferer. It could recover the necrotic femoral heads into the satisfactory models. These models could well match with the acetabulums. This improved system afforded a theoretical model for the accurate surgical position fixing in the orthopaedic clinic. And this system also provided an innovative practical means for the individualized modeling and manufacture of the artificial femoral head prosthesis.

With the fast-growing of online shopping services, there are millions even billions of commercial item images available on the Internet. How to effectively leverage visual search method to find the items of users' interests is an important yet challenging task. Besides global appearances (e.g., color, shape or pattern), users may often pay more attention to the local styles of certain products, thus an ideal visual item search engine should support detailed and precise search of similar images, which is beyond the capabilities of current search systems. In this paper, we propose a novel system named iSearch and global/local matching of local features are combined to do precise retrieval of item images in an interactive manner. We extract multiple local features including scale-invariant feature transform (SIFT), regional color moments and object contour fragments to sufficiently represent the visual appearances of items; while global and local matching of large-scale image dataset are allowed. To do this, an effective contour fragments encoding and indexing method is developed. Meanwhile, to improve the matching robustness of local features, we encode the spatial context with grid representations and a simple but effective verification approach using triangle relations constraints is proposed for spatial consistency filtering. The experimental evaluations show the promising results of our approach and system.

Prostate-specific antigen (PSA) is a protease produced in the prostate that cleaves insulin-like growth factor binding protein-3 and other proteins. Production is mediated by the androgen receptor (AR) binding to the androgen response elements (ARE) in the promoter region of the PSA gene. Studies of a single nucleotide polymorphism (PSA -158 G/A, rs266882) in ARE1 of the PSA gene have been conflicting for risk of prostate cancer and effect on plasma PSA levels. In this nested case-control analysis of 500 white cases and 676 age- and smoking-matched white controls in the Physicians' Health Study we evaluated the association of rs266882 with risk and survival of prostate cancer and prediagnostic total and free PSA plasma levels, alone or in combination with AR CAG repeats. We used conditional logistic regression, linear regression and Cox regression, and found no significant associations between rs266882 (GG allele vs AA allele) and overall prostate cancer risk (RR=1.21, 95% confidence intervals (CI): 0.88-1.67) or prostate cancer-specific survival (RR=0.94, 95%CI: 0.56-1.58). Similarly, no associations were found among high grade or advanced stage tumours, or by calendar year of diagnosis. There was no significant association between rs266882 and baseline total or free PSA levels or the AR CAG repeats, nor any interaction associated with prostate cancer risk. Meta-analysis of 12 studies of rs266882 and overall prostate cancer risk was null.

Background Venous thromboembolic co-morbidities can have a significant impact on treatment response, treatment options, quality of life, and ultimately, survival from cancer. The extent of venous thromboembolic co-morbidity among older renal cell cancer patients is poorly described in the literature. It is important to understand the scope of venous thromboembolic events, before and after diagnosis, in order to offer renal cell cancer patients optimal care and improved quality of life. Methods The main goal of this study was to estimate and describe the incidence of venous thromboembolic events before and after renal cell cancer diagnosis. SEER-Medicare linked data (1991–2003) was utilized for this retrospective cohort analysis (n = 11,950) of older renal cell cancer patients (≥ 65 years). Incidence rates and proportions in addition to multivariable Cox proportional hazard and logistic regression models were utilized to describe the incidence and relative risk of venous thromboembolic events. Results We observed that in the 12 months after diagnosis, 8.3% of renal cell cancer patients experienced a deep venous thrombosis, 2.4% experienced a pulmonary embolism, and 3.9% experienced other thromboembolic events. Nearly 70% of venous thromboembolic events occurred in the first 90 days after renal cell cancer diagnosis. Renal cell cancer patients were 2–4 times more likely to have a venous thromboembolic event in the 12 months after cancer diagnosis than non-cancer patients followed during the same time frame. Recent history of a venous event substantially increased the risk of that same event in the 12 months after diagnosis (HR = 5.2-18.8). Conclusion Venous thromboembolic events are common and serious co-morbidities that should be closely monitored in older renal cell cancer patients, particularly during the first 3 months following diagnosis and among those with a recent history of a venous thromboembolic event.