The properties of wool-based activated carbon tubes prepared by potassii with no gas and its mechanism study

In this study, the wool-based activated carbon tubes (ACTs) were successfully prepared by potassii as additive. The ACTs had formed a tubular morphology with numerous pores located in both two sides. The mechanism of the tube formation were mainly investigated by removing overlapping scales on the surface of fibers and comparing the effects of experimental parameters. The removal method were carried out by formic acid and ultrasonic wave oscillation. The influence between scales and tubes was characterized by scanning electron microscopy (SEM), thermogravimetric analysis (TGA), methylene blue (MB) through discussing the morphology study, thermal property and adsorption capacity of ACTs. The surface morphology of the ACTs were affected by carbonization temperature, while the scale layers has no relations with the formation of a tubular morphology. Scale layers had almost no effects on thermal decomposition because close weight loss between ACKC2 and ACKC5. The adsorption capacity of ACTs from raw wool using two-step method is in the range of 18.50-26.75 mg/g, which was obviously higher than using one-step method with 14.40-84.00 mg/g. The adsorption capacity of ACTs decreased because of the removal of scale layers using one-step, which is contrary to ones using two-step

PepMapper: a collaborative web tool for mapping epitopes from affinity-selected peptides

Epitope mapping from affinity-selected peptides has become popular in epitope prediction, and correspondingly many Web-based tools have been developed in recent years. However, the performance of these tools varies in different circumstances. To address this problem, we employed an ensemble approach to incorporate two popular Web tools, MimoPro and Pep-3D-Search, together for taking advantages offered by both methods so as to give users more choices, support and convenience for their specific purposes of epitope-peptide mapping. The combined operation of Union finds as many associated peptides as possible from both methods, which increases sensitivity in finding potential epitopic regions on a given antigen surface. The combined operation of Intersection achieves to some extent the mutual verification by the two methods and hence increases the likelihood of locating the genuine epitopic region on a given antigen in relation to the interacting peptides. The Consistency between Intersection and Union is an indirect sufficient condition to assess the likelihood of successful peptide-epitope mapping. On average from 27 tests, the combined operations of PepMapper outperformed either MimoPro or Pep-3D-Search alone. Therefore, PepMapper is another multipurpose mapping tool for epitope prediction from affinity-selected peptides. The Web server can be freely accessed at: http://informatics.nenu.edu.cn/PepMapper

The Characteristics and Regulatory Mechanisms of Superoxide Generation from eNOS Reductase Domain.

In addition to superoxide (O2 .-) generation from nitric oxide synthase (NOS) oxygenase domain, a new O2 .- generation site has been identified in the reductase domain of inducible NOS (iNOS) and neuronal NOS (nNOS). Cysteine S-glutathionylation in eNOS reductase domain also induces O2 .- generation from eNOS reductase domain. However, the characteristics and regulatory mechanism of the O2 .- generation from NOS reductase domain remain unclear. We cloned and purified the wild type bovine eNOS (WT eNOS), a mutant of Serine 1179 replaced with aspartic acid eNOS (S1179D eNOS), which mimics the negative charge caused by phosphorylationand truncated eNOS reductase domain (eNOS RD). Both WT eNOS and S1179D eNOS generated significant amount of O2 .- in the absence of BH4 and L-arginine. The capacity of O2 .- generation from S1179D eNOS was significantly higher than that of WT eNOS (1.74:1). O2 .- generation from both WT eNOS and S1179D eNOS were not completely inhibited by 100nM tetrahydrobiopterin(BH4). This BH4 uninhibited O2 .- generation from eNOS was blocked by 10mM flavoprotein inhibitor, diphenyleneiodonium (DPI). Purified eNOS reductase domain protein confirmed that this BH4 uninhibited O2 .- generation originates at the FMN or FAD/NADPH binding site of eNOS reductase domain. DEPMPO-OOH adduct EPR signals and NADPH consumptions analyses showed that O2 .- generation from eNOS reductase domain was regulated by Serine 1179 phosphorylation and DPI, but not by L-arginine, BH4 or calmodulin (CaM). In addition to the heme center of eNOS oxygenase domain, we confirmed another O2 .- generation site in the eNOS reductase domain and characterized its regulatory properties

MMM: Multi-source multi-net micro-video recommendation with clustered hidden item representation learning

Unlike traditional video recommendations, micro-video inherits the characteristics of social platforms, such as social relation. A large amount of micro-videos showing explosive growth is badly affecting the user’s choice. In this paper, we propose a multi-source multi-net micro-video recommendation model that recommends micro-videos fitting users’ best interests. Different from existing works, as micro-video inherits the characteristics of social platforms, we simultaneously incorporate multi-source content data of items and multi-networks of users to learn user and item representations for recommendation. This information can be complementary to each other in a way that multi-modality data can bridge the semantic gap among items, while multi-type user networks, such as following and reposting, are able to propagate the preferences among users. Furthermore, to discover the hidden categories of micro-videos that properly match users’ interests, we interactively learn the user–item representations and perform the hidden item category clustering. The resulted categorical representations are interacted with user representations to model user preferences at different levels of hierarchies. Finally, multi-source content item data, multi-type user networks and hidden item categories are jointly modelled in a unified recommender, and the parameters of the model are collaboratively learned to boost the recommendation performance. Experiments on a real dataset demonstrate the effectiveness of the proposed model and its advantage over the state-of-the-art baselines. © 2019, The Author(s)

Integrating human rights approaches into public health practices and policies to address health needs amongst Rohingya refugees in Bangladesh: A systematic review and meta-ethnographic analysis

The Rohingya people of Myanmar are one of the most persecuted communities in the world and are forced to flee their home to escape conflict and persecution. Bangladesh receives the majority of the Rohingya refugees. On arrival they experience a number of human rights issues and the extent to which human rights approaches are used to inform public health programs is not well documented. The aim of this systematic review was to document human rights- human rights-related health issues and to develop a conceptual human rights framework to inform current policy practice and programming in relation to the needs of Rohingya refugees in Bangladesh

RecKGC: Integrating recommendation with knowledge graph completion

Both recommender systems and knowledge graphs can provide overall and detailed views on datasets, and each of them has been a hot research domain by itself. However, recommending items with a pre-constructed knowledge graph or without one often limits the recommendation performance. Similarly, constructing and completing a knowledge graph without a target is insufficient for applications, such as recommendation. In this paper, we address the problems of recommendation together with knowledge graph completion by a novel model named RecKGC that generates a completed knowledge graph and recommends items for users simultaneously. Comprehensive representations of users, items and interactions/relations are learned in each respective domain, such as our attentive embeddings that integrate tuples in a knowledge graph for recommendation and our high-level interaction representations of entities and relations for knowledge graph completion. We join the tasks of recommendation and knowledge graph completion by sharing the comprehensive representations. As a result, the performance of recommendation and knowledge graph completion are mutually enhanced, which means that the recommendation is getting more effective while the knowledge graph is getting more informative. Experiments validate the effectiveness of the proposed model on both tasks. © 2019, Springer Nature Switzerland AG

MimoPro : a more efficient Web-based tool for epitope prediction using phage display libraries

Background: A B-cell epitope is a group of residues on the surface of an antigen which stimulates humoral responses. Locating these epitopes on antigens is important for the purpose of effective vaccine design. In recent years, mapping affinity-selected peptides screened from a random phage display library to the native epitope has become popular in epitope prediction. These peptides, also known as mimotopes, share the similar structure and function with the corresponding native epitopes. Great effort has been made in using this similarity between such mimotopes and native epitopes in prediction, which has resulted in better outcomes than statistics-based methods can. However, it cannot maintain a high degree of satisfaction in various circumstances. Results: In this study, we propose a new method that maps a group of mimotopes back to a source antigen so as to locate the interacting epitope on the antigen. The core of this method is a searching algorithm that is incorporated with both dynamic programming (DP) and branch and bound (BB) optimization and operated on a series of overlapping patches on the surface of a protein. These patches are then transformed to a number of graphs using an adaptable distance threshold (ADT) regulated by an appropriate compactness factor (CF), a novel parameter proposed in this study. Compared with both Pep-3D-Search and PepSurf, two leading graph-based search tools, on average from the results of 18 test cases, MimoPro, the Web-based implementation of our proposed method, performed better in sensitivity, precision, and Matthews correlation coefficient (MCC) than both did in epitope prediction. In addition, MimoPro is significantly faster than both Pep-3D-Search and PepSurf inprocessing. Conclusions: Our search algorithm designed for processing well constructed graphs using an ADT regulated by CF is more sensitive and significantly faster than other graph-based approaches in epitope prediction. MimoPro is a viable alternative to both PepSurf and Pep-3D-Search for epitope prediction in the same kind, and freely accessible through the MimoPro server located at http://informatics.nenu.edu.cn/MimoPr

Benefits of clearing forest plantations to restore nature? Evidence from a discrete choice experiment in Flanders, Belgium

To ensure the long-term survival of its most valuable and threatened habitats, the European Union (EU) is committing its Member States to develop a network of protected areas. Flanders (northern Belgium) is a highly urbanised region, where natural environments are scarce. Policy-makers are converting existing forest plantations (mostly former coniferous plantations) into natural areas to comply with the EU requirements about nature restoration and satisfy the growing demand for recreation and amenity spaces. The conversion of forest plantations into higher value nature, however, sometimes meets public opposition because it often involves clearcuts and landscape modification. Regional planning authorities are looking for case studies demonstrating which type of nature restoration is valued and thus supported by citizens. Past valuation studies show that personal, site-specific and spatial characteristics influence preferences. However, little is known about the relative importance of such factors. We conduct a discrete choice experiment to investigate preferences for nature restoration scenarios that involve forest conversion. A mixed logit and a latent class model are estimated and the influence of socio-demographic characteristics is explored. Willingness-to-pay (WTP) estimates are elicited. Though people generally prefer the forest habitat type, our results suggest that public support exists for converting forest plantations if this contributes to increasing landscape diversity and species richness. Based on our findings, we recommend small scale cuts. This in order to gently open the landscape, assist the natural regeneration process and help current species adapt to that landscape modification. © 2014 Elsevier B.V

Characterization of N-Glycan Structures on the Surface of Mature Dengue 2 Virus Derived from Insect Cells

<div><p>DENV envelope glycoprotein (E) is responsible for interacting with host cell receptors and is the main target for the development of a dengue vaccine based on an induction of neutralizing antibodies. It is well known that DENV E glycoprotein has two potential N-linked glycosylation sites at Asn67 and Asn153. The N-glycans of E glycoprotein have been shown to influence the proper folding of the protein, its cellular localization, its interactions with receptors and its immunogenicity. However, the precise structures of the N-glycans that are attached to E glycoprotein remain elusive, although the crystal structure of DENV E has been determined. This study characterized the structures of envelope protein N-linked glycans on mature DENV-2 particles derived from insect cells via an integrated method that used both lectin microarray and MALDI-TOF-MS. By combining these methods, a high heterogeneity of DENV N-glycans was found. Five types of N-glycan were identified on DENV-2, including mannose, GalNAc, GlcNAc, fucose and sialic acid; high mannose-type N-linked oligosaccharides and the galactosylation of N-glycans were the major structures that were found. Furthermore, a complex between a glycan on DENV and the carbohydrate recognition domain (CRD) of DC-SIGN was mimicked with computational docking experiments. For the first time, this study provides a comprehensive understanding of the N-linked glycan profile of whole DENV-2 particles derived from insect cells.</p></div

Relative expression levels of DENV-2 glycan binders by lectin microarray.

<p>The glycans binders were categorized into five types. (A) The GlcNAc binder DSA showed a stronger binding signal than the others. (B) (GlcNAc)n binders. (C) Bisecting and biantennary GlcNAc binders. (D) Mannose binders. (E) Gal binders. (F) Fucose binders. (G) Sialic acid binders.</p