No abstract

No abstract

Twenty-nine marine bacterial strains were isolated from the sponge Hymeniacidon perleve at Nanji island, and antimicrobial screening showed that eight strains inhibited the growth of terrestrial microorganisms. The strain NJ6-3-1 with wide antimicrobial spectrum was identified as Pseudoalteromonas piscicida based on its 16S rRNA sequence analysis. The major antimicrobial metabolite, isolated through bioassay-guide fractionation of TLC bioautography overlay assay, was identified as norharman (a beta-carboline alkaloid) by EI-MS and NMR.

No abstract

Despite the mounting studies exploring the role of estrogen receptor alpha (ERα), estrogen receptor beta (ERβ) and androgen receptor (AR) in gastric cancer (GC), there remain controversies in those findings. The present study investigated the expression of ERα, ERβ and AR in Chinese gastric cancer by immunohistochemistry, analyzed their clinical relevance in gastric cancer, and examined the potential mechanisms by which ERα and AR modulated GC progression. The positive rate of ERα, ERβ and AR in GC tissues was 6% (9/150), 93.5% (143/153), and 42.4% (59/139), respectively. The expression of ERα was an independent unfavorable risk factor for overall survival (OS) (hazard ratio [HR] = 3.639, 95% confidence interval [CI] = 1.432-9.246, p = 0.007) for GC patients. Moreover, AR was borderline significantly associated with poor progress free survival (PFS) after adjustment with other variables (HR = 1.573, 95% CI = 0.955-2.592, p = 0.075). Knockdown of ERα inhibited the proliferation, migration and invasion of GC cells possibly via modulating the expression of p53, p21, p27, cyclin D1 and E-cadherin. Downregulation of AR suppressed the migration and invasion of GC cells and inhibited the epithelial-mesenchymal transition (EMT) associated pathways.ConclusionThe present study showed that positive ERα was associated with poor prognosis of Chinese GC patients. ERα might modulate the proliferation, migration and invasion via regulating the expression of p53, p21, p27, cyclin D1 and E-cadherin. ERα could be a valuable prognostic biomarker and promising therapeutic target for Chinese GC patients.

Latent factor models have been widely used for recommendation. Most existing latent factor models mainly utilize the rating information between users and items, although some recently extended models add some auxiliary information to learn a unified latent factor between users and items.  The unified latent factor only represents the latent features of users and items from the aspect of purchase history. However, the latent features of users and items may stem from different aspects, e.g., the brand-aspect and category-aspect of items. In this paper, we propose a Neural network based Aspect-level Collaborative Filtering model (NeuACF) to exploit different aspect latent factors. Through modelling rich objects and relations in recommender system as a heterogeneous information network, NeuACF first extracts different aspect-level similarity matrices of users and items through different meta-paths and then feeds an elaborately designed deep neural network with these matrices to learn aspect-level latent factors. Finally, the aspect-level latent factors are effectively fused with an attention mechanism for the top-N recommendation. Extensive experiments on three real datasets show that NeuACF significantly outperforms both existing latent factor models and recent neural network models.

Real-time detection of phosphate has significant meaning in marine environmental monitoring and forecasting the occurrence of harmful algal blooms. Conventional monitoring instruments are dependent on artificial sampling and laboratory analysis. They have various shortcomings for real-time applications because of the large equipment size and high production cost, with low target selectivity and the requirement of time-consuming procedures to obtain the detection results. We propose an optofluidic miniaturized analysis chip combined with micro-resonators to achieve real-time phosphate detection. The quantitative water-soluble components are controlled by the flow rate of the phosphate solution, chromogenic agent A (ascorbic acid solution) and chromogenic agent B (12% ammonium molybdate solution, 80% concentrated sulfuric acid and 8% antimony potassium tartrate solution with a volume ratio of 80 : 18 : 2). Subsequently, an on-chip Fabry-Pérot microcavity is formed with a pair of aligned coated fiber facets. With the help of optical feedback, the absorption of phosphate can be enhanced, which can avoid the disadvantages of the macroscale absorption cells in traditional instruments. It can also overcome the difficulties of traditional instruments in terms of size, parallel processing of numerous samples and real-time monitoring, etc. The absorption cell length is shortened to 300 μm with a detection limit of 0.1 μmol L. The time required for detection is shortened from 20 min to 6 seconds. Predictably, microsensors based on optofluidic technology will have potential in the field of marine environmental monitoring.

No abstract