In this work, we contribute to video saliency research in two ways. First, we introduce a new benchmark for predicting human eye movements during dynamic scene freeviewing, which is long-time urged in this field. Our dataset, named DHF1K (Dynamic Human Fixation), consists of 1K high-quality, elaborately selected video sequences spanning a large range of scenes, motions, object types and background complexity. Existing video saliency datasets lack variety and generality of common dynamic scenes and fall short in covering challenging situations in unconstrained environments. In contrast, DHF1K makes a significant leap in terms of scalability, diversity and difficulty, and is expected to boost video saliency modeling. Second, we propose a novel video saliency model that augments the CNN-LSTM network architecture with an attention mechanism to enable fast, end-to-end saliency learning. The attention mechanism explicitly encodes static saliency information, thus allowing LSTM to focus on learning more flexible temporal saliency representation across successive frames. Such a design fully leverages existing large-scale static fixation datasets, avoids overfitting, and significantly improves training efficiency and testing performance. We thoroughly examine the performance of our model, with respect to state-of-the-art saliency models, on three largescale datasets (i.e., DHF1K, Hollywood2, UCF sports). Experimental results over more than 1.2K testing videos containing 400K frames demonstrate that our model outperforms other competitors.

The molecular mechanism to regulate energy balance is not completely understood. Here we observed that Egr-1 expression in white adipose tissue (WAT) was highly correlated with dietary-induced obesity and insulin resistance both in mice and humans. Egr-1 null mice were protected from diet-induced obesity and obesity-associated pathologies such as fatty liver, insulin resistance, hyperlipidemia and hyperinsulinemia. This phenotype can be largely explained by the increase of energy expenditure in Egr-1 null mice. Characterization of these mice revealed that the expression of FOXC2 and its target genes were significantly elevated in white adipose tissues, leading to WAT energy expenditure instead of energy storage. Altogether, these studies suggest an important role for Egr-1, which, by repressing FOXC2 expression, promotes energy storage in WAT and favored the development of obesity under high energy intake.

Heterogeneous information networks (HINs) are ubiquitous in real-world applications. In the meantime, network embedding has emerged as a convenient tool to mine and learn from networked data. As a result, it is of interest to develop HIN embedding methods. However, the heterogeneity in HINs introduces not only rich information but also potentially incompatible semantics, which poses special challenges to embedding learning in HINs. With the intention to preserve the rich yet potentially incompatible information in HIN embedding, we propose to study the problem of comprehensive transcription of heterogeneous information networks. e comprehensive transcription of HINs also provides an easy-to-use approach to unleash the power of HINs, since it requires no additional supervision, expertise, or feature engineering. To cope with the challenges in the comprehensive transcription of HINs, we propose the HEER algorithm, which embeds HINs via edge representations that are further coupled with properly-learned heterogeneous metrics. To corroborate the e cacy of HEER, we conducted experiments on two large-scale real-words datasets with an edge reconstruction task and multiple case studies. Experiment results demonstrate the e ectiveness of the proposed HEER model and the utility of edge representations and heterogeneous metrics. e code and data are available at h ps://github.com/GentleZhu/HEER. Homogeneous network embedding. Meanwhile, network embedding has emerged as an e cient and e ective representation learning approach for networked data [4,7,9,16,18,19,19,29,32,37], which signi cantly spares the labor and sources in transforming networks into features that are more machine-actionable. Early network embedding algorithms start from handling the simple, homogeneous networks, and many of them trace to the skip-gram model [13] that aims to learn word representations where words with similar context have similar representation [7,18,19,29].

Sucrose synthase (SUS) plays an important role in carbohydrate metabolism in plants. The SUS genes in licorice remain unknown. To reveal the sucrose metabolic pathway in licorice, all the 12 putative SUS genes of Glycyrrhiza uralensis were systematically identified by genome mining, and two novel SUSs (GuSUS1 and GuSUS2) were isolated and characterized for the first time. Furthermore, we found that the flexible N-terminus was responsible for the low stability of plant SUSs, and deletion of redundant N-terminus improved the stability of GuSUS1 and GuSUS2. The half-life of both GuSUS1 and GuSUS2 mutants was increased by 2-fold. Finally, the GuSUS1 mutant was coupled with UGT73C11 for the glycosylation of glycyrrhetinic acid (GA) with uridine 5′-diphosphate disodium salt hydrate (UDP) in situ recycling, and GA conversion was increased by 7-fold. Our study not only identified the SUS genes in licorice but also provided a stable SUS mutant for the construction of an efficient UDP-recycling system for GA glycosylation.

Pentacyclic triterpenoids have wide applications in the pharmaceutical industry. The precise glucosylation at C-3 OH of pentacyclic triterpenoids mediated by uridine 5'-diphospho-glucosyltransferase (UDP-glucosyltransferase [UGT]) is an important way to produce valuable derivatives with various improved functions. However, most reported UGTs suffer from low regiospecificity toward the OH and COOH groups of pentacyclic triterpenoids, which significantly decreases the

Long non-coding RNAs (lncRNAs) are considered to be important regulators in breast cancer. In the present study, the potential mechanisms and functional roles of lncRNA PSMG3-antisense (AS)1 were investigated in vivo and in vitro. The relative expression levels of lncRNA PSMG3-AS1 and microRNA (miR)-143-3p were determined using reverse-transcription quantitative PCR. The protein expression levels of collagen type 1 alpha 1 (COL1A1) and proliferating cell nuclear antigen (PCNA) were obtained using western blot analysis. Bioinformatics analysis was used to identify the relationship between PSMG3-AS1, miR-143-3p and COL1A1. Colony forming and Cell Counting Kit-8 assays were used to detect cell proliferation. Transwell and wound-healing assays were used to determine cell migration. The results of the present study demonstrated that PSMG3-AS1 expression was increased in breast cancer tumor tissues and cell lines, and that of miR-143-3p was decreased. Knockdown of PSMG3-AS1 increased the level of miR-143-3p expression, which led to the mitigation of proliferation and migration capacity in breast carcinoma cells. Additionally, PSMG3-AS1 knockdown was demonstrated to reduce the mRNA and protein expression levels of COL1A1. miR-143-3p mimic transfection reduced proliferation and migration in MDA-MB-231 and MCF-7 cell lines. Furthermore, miR-143-3p inhibition significantly increased the proliferation and migration of breast cancer cells compared with the negative control group. The mRNA and protein expression levels of PCNA were reduced in the MCF-7 cell line when transfected with miR-143-3p mimics and si-PSMG3-AS1. However, PCNA expression was increased in cells transfected with a miR-143-3p inhibitor. In conclusion, the results of the present study identified a novel lncRNA PSMG3-AS1, which serves as a sponge for miR-143-3p in the pathogenesis of breast cancer. PSMG3-AS1 may be used as a potential therapeutic target gene in breast cancer treatment.

Background Existing studies suggest that dietary vitamins and carotenoids might be associated with a reduced risk of age-related cataract (ARC), although a quantitative summary of these associations is lacking. Objectives The aim of this study was to conduct a meta-analysis of randomized controlled trials (RCTs) and cohort studies of dietary vitamin and carotenoid intake and ARC risk. Methods The MEDLINE, EMBASE, ISI Web of Science, and Cochrane Library databases were searched from inception to June 2018. The adjusted RRs and corresponding 95% CIs for the associations of interest in each study were extracted to calculate pooled estimates. Dose-response relations were assessed with the use of generalized least-squares trend estimation. Results We included 8 RCTs and 12 cohort studies in the meta-analysis. Most vitamins and carotenoids were significantly associated with reduced risk of ARC in the cohort studies, including vitamin A (RR: 0.81; 95% CI: 0.71, 0.92; P = 0.001), vitamin C (RR: 0.80; 95% CI: 0.72, 0.88; P < 0.001), vitamin E (RR: 0.90; 95% CI: 0.80, 1.00; P = 0.049), β-carotene (RR: 0.90; 95% CI: 0.83, 0.99; P = 0.023), and lutein or zeaxanthin (RR: 0.81; 95% CI: 0.75, 0.89; P < 0.001). In RCTs, vitamin E (RR: 0.97; 95% CI: 0.91, 1.03; P = 0.262) or β-carotene (RR: 0.99; 95% CI: 0.92, 1.07; P = 0.820) intervention did not reduce the risk of ARC significantly compared with the placebo group. Further dose-response analysis indicated that in cohort studies the risk of ARC significantly decreased by 26% for every 10-mg/d increase in lutein or zeaxanthin intake (RR: 0.74; 95% CI: 0.67, 0.80; P < 0.001), by 18% for each 500-mg/d increase in vitamin C intake (RR: 0.82; 95% CI: 0.74, 0.91; P < 0.001), by 8% for each 5-mg/d increase in β-carotene intake (RR: 0.92; 95% CI: 0.88, 0.96; P < 0.001), and by 6% for every 5 mg/d increase in vitamin A intake (RR: 0.94; 95% CI: 0.90, 0.98; P < 0.001). Conclusions Higher consumption of certain vitamins and carotenoids was associated with a significant decreased risk of ARC in cohort studies, but evidence from RCTs is less clear.

Polymeric nanoparticles gain enormous interests in cancer therapy. Polyethylenimine (PEI) 25 kD is well known for its high transfection efficiency and cytotoxicity. PEI-CyD (PC) was previously synthesized by conjugating low molecular PEI (M 600) with β-cyclodextrin (β-CyD), which is shown to induce lower cytotoxicity than PEI 25 kD. In the current study, the in vivo immune response of branched PEI 25 kD and PC is investigated. Compared to PC/pDNA, exposure of PEI 25kD/pDNA induces higher level of immune-stimulation evidenced by the increased spleen weight, phagocytic capacity of peritoneal macrophage, and proinflammatory cytokines in serum and liver. Importantly, administration of PEI 25 kD can greatly promote breast cancer metastasis in liver and lung tissues, which correlates with its ability to induce high oxidative stress and NLRP3-inflammasome activation. These results suggest that polymeric nanocarriers have the potential to induce immune-stimulation and cancer metastasis, which may affect their efficiency for cancer therapy.