bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of a small molecule that stimulates human β-cell proliferation and insulin secretion, and protects against cytotoxic stress in rat insulinoma cells
Authors: Hohmeier Hans E. , Zhang Lu , Taylor Brandon , Stephens Samuel , McNamara Peter , Laffitte Bryan , Newgard Christopher B. 
Published: October 2019

AbstractA key event in the development of both major forms of diabetes is the loss of functional pancreatic islet β-cell mass. Strategies aimed at enhancing β-cell regeneration have long been pursued, but methods for reliably inducing human β-cell proliferation with full retention of key functions such as glucose-stimulated insulin secretion (GSIS) are still very limited. We have previously reported that overexpression of the homeobox transcription factor Nkx6.1 stimulates β-cell proliferation, while also enhancing GSIS and providing protection against β-cell cytotoxicity through induction of the VGF prohormone. We developed an Nkx6.1 pathway screen by stably transfecting 832/13 rat insulinoma cells with a VGF promoter-luciferase reporter construct, using the resultant cell line to screen a 630,000 compound chemical library. We isolated three compounds with consistent effects to stimulate human islet cell proliferation. Further studies of the most potent of these compounds, GNF-9228, revealed that it selectively activates human β-cell relative to α-cell proliferation and has no effect on δ-cell replication. In addition, pre-treatment, but not short term exposure of human islets to GNF-9228 enhances GSIS. GNF-9228 also protects 832/13 insulinoma cells against ER stress- and inflammatory cytokine-induced cytotoxicity. In contrast to recently emergent Dyrk1a inhibitors that stimulate human islet cell proliferation, GNF-9228 does not activate NFAT translocation. These studies have led to identification of a small molecule with pleiotropic positive effects on islet biology, including stimulation of human β-cell proliferation and insulin secretion, and protection against multiple agents of cytotoxic stress.
Bees support farming. Does farming support bees?
Authors: Virkar Preeti S. , Siddhu Ekta , Uniyal V. P. 
Published: October 2019

AbstractTropical regions are subjected to rapid land use changes altering species composition and diversity in communities. The non-Apisbees are vital invertebrates continued to be highly neglected in the tropics. We compared their diversity status, richness and composition across natural areas and agroecosystems in Doon valley, a subtropical-temperate landscape situated at the foothills of outer Himalayas in India. We investigated how two major habitats relate to non-Apisbee diversity, specifically seeking answers to (1) Whether natural habitat is a refuge to richer and rarer bee communities than agroecosystems? (2) Are natural habitats important for supporting wild bee populations in agroecosystems? (3) Do polyculture farms behave similar to natural habitats and therefore support richer bee communities than monoculture? Observation and pantrap sampling were used to collect data. We recorded 43 species belonging to bees of five families. The findings of our investigation demonstrate the importance of natural habitats as a potential refuge for non-Apisbees. The findings highlighted that Doon valley harboured twenty-five rare species of non-Apisbees, and natural habitats are a refuge to 11 rare specialist species (clamtest; Specialization threshold K = 2/3, Alpha level = 0.005). Natural habitat diversity in Doon valley supports bee communities in nearby agroecosystems (R2 = 0.782, SE = 0.148, P = 0.004). Polyculture practices in agroecosystems (<100m from forest H’ = 2.15; >100m from forest = 2.08) in the valley mimic natural habitats (H’ = 2.37) and support diverse non-Apisbee communities (2.08) in comparison to monocultures (<100m from forest H’ = 2.13; >100m from forest =1.56). Bees evolved with flowering plants over 120 million years and they suffice an ever-growing anthropogenic nutrition needs with their services through enhanced agricultural production in pursuit of forage. We finally recommend similar assessments of bee diversity and plants they support in different habitats and vice versa.
A computational approach for mapping heme biology in the context of hemolytic disorders
Authors: Humayun Farah , Domingo-Fernández Daniel , George Ajay Abisheck Paul , Hopp Marie-Thérèse , Syllwasschy Benjamin F. , Detzel Milena S. , Hoyt Charles Tapley , Hofmann-Apitius Martin , Imhof Diana 
Published: October 2019

AbstractHeme is an iron ion-containing molecule found within hemoproteins such as hemoglobin and cytochromes that participates in diverse biological processes. While its unlimited supply has been implicated in deleterious processes in several diseases including malaria, sepsis, ischemia-reperfusion, and disseminated intravascular coagulation, little is known about its regulatory and signaling functions. A majority of the computational research to elucidate these functions has been purely data-driven due to the absence of curated pathway resources, which have proven useful in the computational study in other indications. Here, we present two resources aimed to exploit this unexplored information to model heme biology. The first resource is an ontology covering heme-specific terms not yet included in standard controlled vocabularies. Using this ontology, we curated and modeled a corpus of 46 scientific articles to generate a mechanistic knowledge graph representing the heme’s interactome for that particular literature. Finally, we demonstrated the utility of these resources by investigating the role of heme in the Toll-like receptor signaling pathway. Our analysis proposed a series of crosstalk events that could explain the role of heme in activating the TLR4 signaling pathway. In summary, the presented work opens the door for the scientific community to explore in more detail the published knowledge on heme biology.
Predicting agronomic traits and associated genomic regions in diverse rice landraces using marker stability
Authors: Orhobor Oghenejokpeme I. , Alexandrov Nickolai N. , Chebotarov Dmytro , Kretzschmar Tobias , McNally Kenneth L. , Sanciangco Millicent D. , King Ross D. 
Published: October 2019

AbstractTo secure the world’s food supply it is essential that we improve our knowledge of the genetic underpinnings of complex agronomic traits. In this paper, we report our findings from performing trait prediction and association mapping using marker stability in diverse rice landraces. We used the least absolute shrinkage and selection operator as our marker selection algorithm, and considered twelve real agronomic traits and a hundred simulated traits using a population with approximately a hundred thousand markers. For trait prediction, we considered several statistical/machine learning methods. We found that some of the methods considered performed best when preselected markers using marker stability were used. However, our results also show that one might need to make a trade-off between model size and performance for some learning methods. For association mapping, we compared marker stability to the genome-wide efficient mixed-model analysis (GEMMA), and for the simulated traits, we found that marker stability significantly outperforms GEMMA. For the real traits, marker stability successfully identifies multiple associated markers, which often entail those selected by GEMMA. Further analysis of the markers selected for the real traits using marker stability showed that they are located in known quantitative trait loci (QTL) using the QTL Annotation Rice Online database. Furthermore, co-functional network prediction of the selected markers using RiceNet v2 also showed association to known controlling genes. We argue that a wide adoption of the marker stability approach for the prediction of agronomic traits and association mapping could improve global rice breeding efforts.
CrispRdesignR: A Versatile Guide RNA Design Package in R for CRISPR/Cas9 Applications
Authors: Beeber Dylan , Chain Frédéric JJ 
Published: October 2019

AbstractThe success of CRISPR/Cas9 gene editing applications relies on the efficiency of the single guide RNA (sgRNA) used in conjunction with the Cas9 protein. Current sgRNA design software vary in the details they provide on sgRNA sequence efficiency and are almost exclusively restricted to model organisms. The crispRdesignR package aims to address these limitations by providing comprehensive sequence features of the generated sgRNAs in a single program, which allows users to predict sgRNA efficiency and design sgRNA sequences for systems that currently do not have optimized efficiency scoring methods. crispRdesignR reports extensive information on all designed sgRNA sequences with robust off-target calling and annotation and can be run in a user-friendly graphical interface. The crispRdesignR package is implemented in R and has fully editable code for specialized purposes including sgRNA design in user-provided genomes. The package is platform independent and extendable, with its source code and documentation freely available at https://github.com/dylanbeeber/crispRdesignR.
Variant calling using NGS and sequence capture data for population and evolutionary genomic inferences in Norway Spruce (Picea abies)
Authors: Bernhardsson Carolina , Wang Xi , Eklöf Helena , Ingvarsson Pär K. 
Published: October 2019

AbstractAdvances in next-generation sequencing methods and the development of new statistical and computational methods have opened up possibilities made for large-scale, high quality genotyping in most organisms. Conifer genomes are large and are known to contain a high fraction of repetitive elements and this complex genome structure has bearings for approaches that aim to use next-generation sequencing methods for genotyping. In this chapter we provide a detailed description of a workflow for variant calling using next-generation sequencing in Norway spruce (Picea abies). The workflow that starts with raw sequencing reads and proceeds through read mapping to variant calling and variant filtering. We illustrate the pipeline using data derived from both whole-genome resequencing data and reduced-representation sequencing. We highlight possible problems and pitfalls of using next-generation sequencing data for genotyping stemming from the complex genome structure of conifers and how those issues can be mitigated or eliminated.
The phase separation-dependent FUS interactome reveals nuclear and cytoplasmic function of liquid-liquid phase separation
Authors: Reber Stefan , Lindsay Helen , Devoy Anny , Jutzi Daniel , Mechtersheimer Jonas , Domanski Michal , Mühlemann Oliver , Barabino Silvia M.L. , Ruepp Marc-David 
Published: October 2019

AbstractLiquid-liquid phase separation (LLPS) of proteins and RNAs has emerged as the driving force underlying the formation of membrane-less organelles. Such biomolecular condensates have various biological functions and have been linked to disease. One of the best studied proteins undergoing LLPS is Fused in Sarcoma (FUS), a predominantly nuclear RNA-binding protein. Mutations in FUS have been causally linked to Amyotrophic Lateral Sclerosis (ALS), an adult-onset motor neuron disease, and LLPS followed by aggregation of cytoplasmic FUS has been proposed to be a crucial disease mechanism. In spite of this, it is currently unclear how LLPS impacts the behaviour of FUS in cells, e.g. its interactome. In order to study the consequences of LLPS on FUS and its interaction partners, we developed a method that allows for the purification of phase separated FUS-containing droplets from cell lysates. We observe substantial alterations in the interactome of FUS, depending on its biophysical state. While non-phase separated FUS interacts mainly with its well-known interaction partners involved in pre-mRNA processing, phase-separated FUS predominantly binds to proteins involved in chromatin remodelling and DNA damage repair. Interestingly, factors with function in mitochondria are strongly enriched with phase-separated FUS, providing a potential explanation for early changes in mitochondrial gene expression observed in mouse models of ALS-FUS. In summary, we present a methodology that allows to investigate the interactome of phase-separating proteins and provide evidence that LLPS strongly shapes the FUS interactome with important implications for function and disease.
Is the edulcorate power of two intense sweeteners sucralose and stevia same in ice cream and frozen desserts?
Authors: Bragion Daniela Mariana de Lima , Bolini Helena Maria André 
Published: October 2019

Purpose
Carob has been proposed as a healthy, stimulant-free alternative to chocolate in frozen desserts. In order to make carob a viable and attractive alternative, food producers need to know how it interacts with sweeteners and frozen dessert dispersion matrices. The purpose of this paper is to find the optimal sweetener concentration in three plant-based frozen desserts and carob-flavoured milk dispersion matrix ice cream.

Design/methodology/approach
The ideal sucrose concentrations (per cent) were determined through an affective test using the “just-about-right” scale for carob-flavoured frozen desserts made with cashew nut, coconut and soy beverage, as well as milk dispersion matrix. The sweetness equivalence of artificial sweeteners relative to sucrose was determined by the magnitude estimation test.

Findings
The authors identified the concentrations of sucrose, stevia and sucralose that produced ideal sweetness in carob-flavoured frozen desserts. Concentrations for soy-based frozen desserts differed from the other dispersion mediums tested. Plant-based frozen desserts exhibited a higher ratio of sweetening power of stevia and sucralose to sucrose compared to milk-based ice cream by a factor of 1.18 and 1.14, respectively.

Originality/value
This study undertook a comprehensive survey of a dairy-free and chocolate-free alternative to chocolate ice cream and found new sweetener interactions with dispersion matrices in carob-flavoured frozen desserts. The findings in this study can be applied in the development of carob-flavoured soybean-, coconut-, cashew nut- and milk-based frozen desserts.
Factors influencing travelers’ behavioral intentions to use P2P accommodation based on trading activity: Airbnb vs Couchsurfing
Authors: Aruan Daniel Tumpal H. , Felicia Felicia 
Published: October 2019

Purpose
The growth of information and communication technology and the appearance of the sharing economy have affected the market. This trend will potentially create a competitive transformation, especially in the accommodation sector. While Airbnb has become the leader in the sharing economy, more competitors are coming into the market, some with different business propositions and positioning strategies, thereby offering different points of differences (PODs). The purpose of this study is to identify and compare the factors that influence the usage of peer-to-peer (P2P) accommodation services for trading activity (renting vs lending), particularly between Airbnb and Couchsurfing. More specifically, this study examines the causal relationships among some major factors that influence customers’ purchase intentions, such as perceived risk, perceived value, price sensitivity and word of mouth.

Design/methodology/approach
A total of 400 millennial respondents – 200 for each service – who have used the respective mobile applications participated in the online survey. Using structural equation modeling, the analysis revealed that the model acts differently across the groups.

Findings
The results revealed that Airbnb respondents paid more attention to perceived risks when booking the accommodation, thus indicating that they are more risk-averse, whereas Couchsurfing’s users sought the perceived value that they would receive at the destination.

Practical implications
The findings of this study are beneficial for Airbnb and Couchsurfing in particular and players in the industry in general.

Originality/value
This study reveals that factors that influence the intention to use the sharing economy platform work differently based on the form of trading activities.
Design and evaluation of mobile sensing technologies for identifying medicines by people with visual disabilities
Authors: Façanha Agebson Rocha , Carneiro Araújo Maria Conceição , Viana Windson , Sánchez Jaime 
Published: October 2019

PurposePeople with visual impairments may have difficulty in identifying information, either on a bottle or package of medicine. As a result, many of them need the help of a third party to discern which medication they should take. In this perspective, this study aims to assist people with visual impairments to identify their medicine by using mobile sensing technologies.Design/methodology/approachThe authors have developed three versions of a mobile application. They use three technologies, namely, near field communication, QR code and magnetic field, for drug identification. The entire development process was based on user-centered design. And, the authors also performed an initial usability assessment of these applications with ten users who were blind.FindingsPreliminary results show user preference for the near field communication approach and reinforce some known drawbacks concerning the use of QR code by people with visual impairments.Research limitations/implicationsAlthough the authors have evaluated these technologies with few mobile devices, they perceived that the acquired values of the magnetic field suffered distortions culminating, in some cases, in a non-identification of the medicine, or even in incorrect identification.Practical implicationsCurrent mobile device magnet sensors are not yet robust to be used for medicine identification.Social implicationsMobile apps combined with medicine identification can contribute to the autonomy of people who are blind.Originality/valueThe main contribution of this paper is to integrate and analyze distinct mobile-based sensing technologies for identifying medicines by people with visual impairments.
Dynamic impact of social network on knowledge contribution loafing in mobile collaboration: a hidden Markov model
Authors: Jiang Shan , Zhang Xi , Cheng Yihang , Xu Dongming , Ordoñez De Pablos Patricia , Wang Xuyan 
Published: October 2019

PurposeSocial loafing in knowledge contribution (namely, knowledge contribution loafing [KCL]) usually happens in group context, especially in the mobile collaboration tasks. KCL shows dynamic features over time. However, most previous studies are based on static assumption, that is, KCL will not change over time. This paper aims to reveal the dynamics of KCL in mobile collaboration and analyze how network centrality influences KCL states considering the current loafing state.Design/methodology/approachThis study is based on empirical study design. Real mobile collaboration behavioral data related to knowledge contribution were collected to investigate the dynamic relationship between network centrality and KCL. In total, 4,127 chat contents were collected through Slack (a mobile collaboration APP). The text data were first analyzed using the text analysis method and then analyzed by a machine learning method called hidden Markov model.FindingsFirst, the results reveal the inner structure of KCL, showing that it has three states (low, medium and high). Second, it is found that network centrality positively influences individuals involved in medium and high loafing state, while it has a negative influence on individuals with low loafing state.Research limitations/implicationsThe limitations are related to the single machine learning method and no subdivision of social network. First, this paper only uses one kind of text classification model (TF-IDF) to divide chat contents, which may not be superior to other classification models. This paper considers the eigenvector centrality, and not further divides the social network into advice network and expressive network.Practical implicationsThis study helps companies infer tendency of different KCL and dynamically re-organize a mobile collaborative team for better knowledge contribution.Originality/valueFirst, previous studies based on static assumptions regarding KCL as static and the relationship between loafing reducing mechanisms and team members KCL does not change over time. This study relaxes static assumptions and allows KCL to change during the process of collaboration. Second, this study allows the impact of network centrality to be different when members are in different KCL states.
Strategic cost modelling and optimisation for highway asset maintenance
Authors: Tee Kong Fah , Ekpiwhre Ejiroghene 
Published: October 2019

Purpose
The purpose of this paper is to propose and confer a strategic cost model as a concept for good decision making for highway asset treatment in the transport industry.

Design/methodology/approach
The paper is based on asset performance condition and treatment renewals using a five-point performance for developing prospective treatment strategies. The strategic cost model is presented in the similitude of picturesque and its outcomes via an exploratory data analysis.

Findings
The results articulate the best maintenance plan for the forthcoming and future years. The strategic cost model uses the combination of the current condition band, the sample area and likely treatment cost for proposing the optimal treatment solution based on consideration of desired treatment level.

Practical implications
The strategic cost model is suitable for outlining the asset performance condition, treatment renewals and analytical cost optimisation. The formulated analytical cost model and developed prospective strategies enable good decision making, long-term contract negotiations and whole life cost maintenance and management.

Originality/value
Embracing eminent performance condition from the research area of lifecycle planning and deterioration models of a physical asset, a prospective cost strategy for asset maintenance is proposed in the study. The resultant treatment strategies using the analytical approach portray the ability that enables the adaptation of expected outcomes.
What s-commerce implies? Repurchase intention and its antecedents
Authors: Lim Xin-Jean , Cheah Jun-Hwa , Waller David S. , Ting Hiram , Ng Siew Imm 
Published: October 2019

PurposeThe purpose of this paper is to examine the impact of social commerce (s-commerce) cues (i.e. trust, compatibility, reliability and responsiveness) on repurchase intention in apparel s-commerce along with the mediating effect of customer engagement and the moderating effect of s-commerce navigation.Design/methodology/approachUsing the purposive sampling technique, face-to-face survey was administered to Gen-Y social media users in Malaysia. Subsequently, 384 respondents were sampled. Partial least squares-structural equation modeling was used to perform the analyses.FindingsS-commerce cues have a positive effect on customer engagement, which in turn leads to repurchase intention of apparel among Gen-Y. Particularly, customer engagement also mediates the relationship between s-commerce cues and repurchase intention. S-commerce navigation is found to moderate the effect of engagement on repurchase intention.Research limitations/implicationsThe findings are derived from the perception of Gen-Y in Malaysia and do not represent the entire population. Future research could investigate the same phenomena across generations and consider heterogeneity issues to provide more insights.Practical implicationsApparel s-commerce retailers are suggested to engage with customers more in the e-retail environment to build a lasting relationship. Contextual factors such as ease of navigation should be observed to enhance the desired response of diverse customers today.Originality/valueThis study adds to the growing body of knowledge on relationship marketing by assessing the impact of customer engagement and navigation on the relationships between s-commerce cues and repurchase intention in the contemporary setting.