BL-MNE: Emerging Heterogeneous Social Network Embedding through Broad Learning with Aligned Autoencoder

Network embedding aims at projecting the network data into a low-dimensional feature space, where the nodes are represented as a unique feature vector and network structure can be effectively preserved. In recent years, more and more online application service sites can be represented as massive and complex networks, which are extremely challenging for traditional machine learning algorithms to deal with. Effective embedding of the complex network data into low-dimension feature representation can both save data storage space and enable traditional machine learning algorithms applicable to handle the network data. Network embedding performance will degrade greatly if the networks are of a sparse structure, like the emerging networks with few connections. In this paper, we propose to learn the embedding representation for a target emerging network based on the broad learning setting, where the emerging network is aligned with other external mature networks at the same time. To solve the problem, a new embedding framework, namely "Deep alIgned autoencoder based eMbEdding" (DIME), is introduced in this paper. DIME handles the diverse link and attribute in a unified analytic based on broad learning, and introduces the multiple aligned attributed heterogeneous social network concept to model the network structure. A set of meta paths are introduced in the paper, which define various kinds of connections among users via the heterogeneous link and attribute information. The closeness among users in the networks are defined as the meta proximity scores, which will be fed into DIME to learn the embedding vectors of users in the emerging network. Extensive experiments have been done on real-world aligned social networks, which have demonstrated the effectiveness of DIME in learning the emerging network embedding vectors.Comment: 10 pages, 9 figures, 4 tables. Full paper is accepted by ICDM 2017, In: Proceedings of the 2017 IEEE International Conference on Data Mining

Gut bacterial species in late trimester of pregnant sows influence the occurrence of stillborn piglet through pro-inflammation response

Maternal gut microbiota is an important regulator for the metabolism and immunity of the fetus during pregnancy. Recent studies have indicated that maternal intestinal microbiota is closely linked to the development of fetus and infant health. Some bacterial metabolites are considered to be directly involved in immunoregulation of fetus during pregnancy. However, the detailed mechanisms are largely unknown. In this study, we exploited the potential correlation between the gut microbiota of pregnant sows and the occurrence of stillborn piglets by combining the 16S rRNA gene and metagenomic sequencing data, and fecal metabolome in different cohorts. The results showed that several bacterial species from Bacteroides, potential pathogens, and LPS-producing bacteria exhibited significantly higher abundances in the gut of sows giving birth to stillborn piglets. Especially, Bacteroides fragilis stood out as the key driver in both tested cohorts and showed the most significant association with the occurrence of stillborn piglets in the DN1 cohort. However, several species producing short-chain fatty acids (SCFAs), such as Prevotella copri, Clostridium butyricum and Faecalibacterium prausnitzii were enriched in the gut of normal sows. Functional capacity analysis of gut microbiome revealed that the pathways associated with infectious diseases and immune diseases were enriched in sows giving birth to stillborn piglets. However, energy metabolism had higher abundance in normal sows. Fecal metabolome profiling analysis found that Lysophosphatidylethanolamine and phosphatidylethanolamine which are the main components of cell membrane of Gram-negative bacteria showed significantly higher concentration in stillbirth sows, while SCFAs had higher concentration in normal sows. These metabolites were significantly associated with the stillborn-associated bacterial species including Bacteroides fragilis. Lipopolysaccharide (LPS), IL-1β, IL-6, FABP2, and zonulin had higher concentration in the serum of stillbirth sows, indicating increased intestinal permeability and pro-inflammatory response. The results from this study suggested that certain sow gut bacterial species in late trimester of pregnancy, e.g., an excess abundance of Bacteroides fragilis, produced high concentration of LPS which induced sow pro-inflammatory response and might cause the death of the relatively weak piglets in a farrow. This study provided novel evidences about the effect of maternal gut microbiota on the fetus development and health

ABO genotype alters the gut microbiota by regulating GalNAc levels in pigs.

peer reviewedThe composition of the intestinal microbiome varies considerably between individuals and is correlated with health1. Understanding to what extend and how host genetics contributes to this variation is paramount yet has proven difficult as few associations have been replicated, particularly in humans2. We herein study the effect of host genotype on the composition of the intestinal microbiota in a large mosaic pig population. We show that, under conditions of exacerbated genetic diversity and environmental uniformity, microbiota composition and abundance of specific taxa are heritable. We map a quantitative trait locus affecting the abundance of Erysipelotrichaceae species and show that it is caused by a 2.3-Kb deletion in the N-acetyl-galactosaminyl-transferase gene underpinning the ABO blood group in humans. We show that this deletion is a ≥3.5 million years old trans-species polymorphism under balancing selection. We demonstrate that it decreases the concentrations of N-acetyl-galactosamine in the gut thereby reducing the abundance of Erysipelotrichaceae that can import and catabolize N-acetyl-galactosamine. Our results provide very strong evidence for an effect of host genotype on the abundance of specific bacteria in the intestine combined with insights in the molecular mechanisms that underpin this association. They pave the way towards identifying the same effect in human rural populations

Isolation and detection of A549 lung cancer cells based on magnetic separation and indirect immunofluorescence technologies

This article reports the development of a combining immunomagnetic separation technology with indirect immunofluorescence technology for separating and determining of the carcinoma A549 cells.Magnetic beads weresynthesized by chemical precipitation.Immunomagneticbeads were constructed by grafted EGFR to the surface of Fe3O4 nanoparticles coated by lipid.The carcinoma A549 cells could specifically bind with the EGFR antibody on the immunomagnetic's surface.The carcinoma A549 cells could be isolatedand enriched from the mixed cellsunder the action of in the magnetic field.The separated cells could connect with the specific antibody contained PE fluorophore and the location of cellnucleus can be confirmed by DAPI to stain the cell nucleus.The carcinoma A549 cells could be quantitatively detectedbyobserving inversion fluorescence microscope.All those results indicate that the method of combining Immunomagnetic separation technology and indirect immunofluorescence technology have a good specificity and high sensitivity for isolationand detection of the carcinoma A549 cells.thedetection limit is three cells per milliliter

The complete chloroplast genome of Epimedium jinchengshanense Y. J. Zhang & J. Q. Li (Berberidaceae), an ornamental and medicinal species

Epimedium jinchengshanense Y. J. Zhang & J. Q. Li 2014 is an important ornamental and medicinal herb, but of unclear taxonomy. In this study, the complete chloroplast genome of E. jinchengshanense was sequenced. The genome was 157,169 bp in length, with a large single-copy region of 88, 520 bp, a small single-copy region of 17,075 bp and 2 inverted repeat regions of 25, 787 bp. The genome consisted of 113 unique genes, including 79 protein-coding genes, 30 tRNA genes and 4 rRNA genes. The GC contents were 38.78%. Phylogenetic analysis showed a close relationship between E. jinchengshanense and E. ilicifolium, which was explained by the morphological similarity of flowers and leaves of the two species

Highly Sensitive Naphthalimide-Based Fluorescence Polarization Probe for Detecting Cancer Cells

Fluorescence polarization (FP)-based signal is a self-referencing fluorescence signal, and it is less dependent on dye concentration and environmental interferences, which makes FP measurement an attractive alternative sensing technology to fluorescence intensity-based detection. However, most of the fluorescence polarization probes were constructed by introducing fluorescein, rhodamine, and cyanine dyes, which have relatively shorter excited-state lifetimes compared with BODIPY and naphthalimide dyes. Herein, a first naphthalimide based fluorescence polarization probe (<b>BIO</b>) was designed and synthesized for selective and direct detection of cancer cells. The relatively longer excited-state lifetimes and high photostability of naphthalimide makes <b>BIO</b> more sensitive and accuracy in quantitative determination of HeLa cells in homogeneous solution without cell lysis and further separation steps. The detection limit of <b>BIO</b> for HeLa cells was about 85 cells mL^–1, the linear range was from 2.5 × 10² cells mL^–1 to 1 × 10⁶ cells mL^–1 and the response time is no more than 25 min. Moreover, due to the relatively high photostability of naphthalimide, <b>BIO</b> was particularly suitable for live cell imaging under continuous irradiation with confocal microscopy, and the specific interaction of <b>BIO</b> with CD44-overexpressing cell lines was clearly visualized. Importantly, this <b>BIO</b> based sensing platform offers a direct and real-time tool for cancer cell diagnosis when complemented with the use of naphthalimide-based fluorescence polarization probe

Experimental data of "Direct space-time manipulation mechanism for spatio-temporal coupling of ultrafast light field"

The compressed package contains the experimental data from "Direct space-time manipulation mechanism for spatio-temporal coupling of ultrafast light field".</p

Extensive identification of serum metabolites related to microbes in different gut locations and evaluating their associations with porcine fatness

Abstract Gut microbiota plays important roles in host metabolism. Whether and how much the gut microbiota in different gut locations contributes to the variations of host serum metabolites are largely unknown, because it is difficult to obtain microbial samples from different gut locations on a large population scale. Here, we quantified the gut microbial compositions using 16S rRNA gene sequencing for 1070 samples collected from the ileum, cecum and faeces of 544 F6 pigs from a mosaic pig population. Untargeted metabolome measurements determined serum metabolome profiles. We found 1671, 12,985 and 103,250 significant correlations between circulating serum metabolites and bacterial ASVs in the ileum, cecum, and faeces samples. We detected nine serum metabolites showing significant correlations with gut bacteria in more than one gut location. However, most metabolite‐microbiota pairwise associations were gut location‐specific. Targeted metabolome analysis revealed that CDCA, taurine, L‐leucine and N‐acetyl‐L‐alanine can be used as biomarkers to predict porcine fatness. Enriched taxa in fat pigs, for example Prevotella and Lawsonia intracellularis were positively associated with L‐leucine, while enriched taxa in lean pigs, such as Clostridium butyricum, were negatively associated with L‐leucine and CDCA, but positively associated with taurine and N‐acetyl‐L‐alanine. These results suggested that the contributions of gut microbiota in each gut location to the variations of serum metabolites showed spatial heterogeneity