bluuebunny/crossref_metadata_2025_split huggingface dataset:
A catalog of cis-regulatory mutations in 12 major cancer types
Authors: Cheng Zhongshan , Vermeulen Michael , Rollins-Green Micheal , DeVeale Brian , Babak Tomas 
Published: July 2019

AbstractDespite the recent availability of complete genome sequences of tumors from thousands of patients, isolating disease-causing (driver) non-coding mutations from the plethora of somatic variants is notoriously challenging, and only a handful of validated examples exist. By integrating whole-genome sequencing, gene expression, chromatin accessibility, and genetic data from TCGA, we identified 301 non-coding somatic mutations that affect gene expression in cis. These mutations cluster into 36 hotspot regions with diverse molecular mechanisms of gene expression regulation. We further show that these mutations have hallmark features of noncoding drivers; namely, that they confer a positive selection on growth, functionally disrupt transcription factor binding sites, and contribute to disease progression reflected in decreased overall patient survival.
Molecular Insights on exquisitely Selective SrtA inhibitors towards active site loop forming open/close lid conformations in SrtA from Bacillus anthracis
Authors: Selvaraj Chandrabose , Selvaraj Gurudeeban , Kaliamurthi Satyavani , Wei Dong-Qing , Singh Sanjeev Kumar 
Published: July 2019

AbstractThe present study clearly explains the dependency of inhibitory activities in SrtA inhibitors is closely related to protein conformational changes of SrtA from Bacillus anthracis B. anthracisSortase A (SrtA) protein anchors proteins by recognizing a cell wall sorting signal containing the amino acid sequence LPXTG In order to analyze conformational changes and the role of SrtA enzyme, especially the loop motions which situated proximal to the active site molecular dynamic simulation was carried out for 100ns. Particular loop is examined for its various conformations from the MD trajectories and the open/close lid conformations are considered for the enzyme activity validations. Experimentally verified SrtA inhibitors activity was analyzed through 3D-QSAR and Molecular docking approaches. Results indicate that, biological activity of SrtA inhibitors is closely related to the closed lid conformation of SrtA from Bacillus anthracis. This work may lead to a better understanding of the mechanism of action and aid to design a novel and more potent SrtA inhibitors.
Molecular correlates of topiramate andGRIK1rs2832407 genotype in pluripotent stem cell-derived neural cultures
Authors: Lieberman Richard , Jensen Kevin P. , Clinton Kaitlin , Levine Eric S. , Kranzler Henry R. , Covault Jonathan 
Published: July 2019

AbstractThere is growing evidence that the anticonvulsant topiramate is efficacious in reducing alcohol consumption. Further, an intronic single nucleotide polymorphism (rs2832407, C ➔ A) in theGRIK1gene, which encodes the GluK1 subunit of the excitatory kainate receptor, predicted topiramate’s effectiveness in reducing heavy drinking in a clinical trial. In the current study, we differentiated a total of 22 induced pluripotent stem cell (iPSCs) lines characterized byGRIK1rs2832407 genotype (10 A/A and 12 C/C) into forebrain-lineage neural cultures to explore molecular correlates ofGRIK1genotype that may relate to topiramate’s ability to reduce drinking. Our differentiation protocol yielded mixed neural cultures enriched for glutamatergic neurons. Characterization of theGRIK1locus revealed no effect of rs2832407 genotype onGRIK1isoform mRNA expression, however a significant difference was observed onGRIK1antisense-2, with higher expression in C/C neural cultures. Differential effects of acute exposure to 5 μM topiramate were observed on the frequency of spontaneous synaptic activity in A/A vs. C/C neurons, with a smaller reduction in excitatory event frequency and a greater reduction in inhibitory event frequency observed in C/C donor neurons. This work highlights the use of iPSC technologies to study pharmacogenetic treatment effects in psychiatric disorders and furthers our understanding of the molecular effects of topiramate exposure in human neural cells.
An in silico exploration of combining Interleukin-12 with Oxaliplatin to treat liver-metastatic colorectal cancer
Authors: Wang Qing , Wang Zhijun , Wu Yan , Klinke David J 
Published: July 2019

AbstractBackgroundCombining anti-cancer therapies with orthogonal modes of action, such as direct cytotoxicity and immunostimulatory, hold promise for expanding clinical benefit to patients with metastatic disease. For instance, a chemotherapy agent Oxaliplatin (OXP) in combination with Interleukin-12 (IL-12) can eliminate pre-existing liver metastatic colorectal cancer and protect from relapse in a murine model. However, the underlying dynamics associated with the targeted biology and the combinatorial space consisting of possible dosage and timing of each therapy present challenges for optimizing treatment regimens. To address some of these challenges, we developed a predictive simulation platform for optimizing dose and timing of the combination therapy involving Mifepristone-induced IL-12 and chemotherapy agent OXP.MethodsA multi-scale mathematical model comprised of impulsive ordinary differential equations was developed to describe the interaction between the immune system and tumor cells in response to the combined IL-12 and OXP therapy. An ensemble of model parameters were calibrated to published experimental data using a genetic algorithm and used represent three different phenotypes: responders, partial-responders, and non-responders.ResultsThe multi-scale model captures tumor growth patterns of the three phenotypic responses observed in mice in response to the combination therapy against a tumor re-challenge and was used to explore changing the dose and timing of the mixed immune-chemotherapy on tumor growth subjected to a tumor re-challenge in mice. An increased ratio of CD8+ T effectors to regulatory T cells during and after treatment was key to improve tumor control in the responder cohort. Sensitivity analysis indicates that combined OXP and IL-12 therapy worked more efficiently in responders by increased priming of T cells, enhanced CD8+ T cell-mediated killing, and functional inhibition of regulatory T cells. In a virtual cohort that mimics non-responders and partial-responders, simulations show that an increased dose of OXP alone would improve the response. In addition, enhanced IL-12 expression alone or an increased number of treatment cycles of the mixed immune-chemotherapy can barely improve tumor control for non-responders and partial responders.ConclusionsOverall, this study illustrates how mechanistic models can be used for in silico screening of the optimal therapeutic dose and timing in combined cancer treatment strategies.
Emergent neutrality in consumer-resource dynamics
Authors: D’Andrea Rafael , Gibbs Theo , O’Dwyer James P. 
Published: July 2019

AbstractNeutral theory assumes all species and individuals in a community are ecologically equivalent. This controversial hypothesis has been tested across many taxonomic groups and environmental contexts, and successfully predicts species abundance distributions across multiple high-diversity communities. However, it has been critiqued for its failure to predict a broader range of community properties, particularly regarding community dynamics from generational to geological timescales. Moreover, it is unclear whether neutrality can ever be a true description of a community given the ubiquity of interspecific differences, which presumably lead to ecological inequivalences. Here we derive analytical predictions for when and why non-neutral communities of consumers and resources may present neutral-like outcomes, which we verify using numerical simulations. Our results, which span both static and dynamical community properties, demonstrate the limitations of summarizing distributions to detect non-neutrality, and provide a potential explanation for the successes of neutral theory as a description of macroecological pattern.Author SummaryThe neutral theory of biodiversity assumes that species are ecologically equivalent. Given the natural history observation of ubiquitous phenotypic differences between species, it is surprising that neutral theory has successfully predicted a broad range of biodiversity patterns, and simultaneously unsurprising that these results have not convinced ecologists that the natural world is neutral. However, we have lacked a description of how neutrality can emerge in a natural way from ecological mechanisms and species differences. Our study sheds light on this question, providing a theoretical backdrop for the success of neutral theory as a description of macroecological pattern. We derive a prediction for the degree to which consumers must differ in preferences for different resources before the resulting biodiversity patterns become distinguishable from neutrality. These predictions, which we confirm using simulations, show that neutral-like outcomes are possible even when resource requirements across consumers are very far from neutral. Our results can be tested in experimental microbial communities, where, equipped with an inferred consumption network, our analysis can yield predictions for biodiversity patterns and community turnover at different taxonomic levels.
Terminitor: Cleavage Site Prediction Using Deep Learning Models
Authors: Yang Chen , Li Chenkai , Nip Ka Ming , Warren René L , Birol Inanc 
Published: July 2019

AbstractAs a widespread RNA processing machinery, alternative polyadenylation plays a crucial role in gene regulation. To help decipher its underlying mechanism and understand its impact, it is desirable to comprehensively profile 3’-untranslated region cleavage and associated polyadenylation sites. State-of-the-art polyadenylation site detection tools are known to be influenced by library preparation artefacts or manually selected features. Moreover, recently published machine learning methods have only been tested on pre-constructed datasets, thus lacking validation on experimental data. Here we present Terminitor, the first deep neural network-based profiling pipeline to make predictions from RNA-seq data. We show how Terminitor outperforms competing tools in sensitivity and precision on experimental transcriptome sequencing data, and demonstrate its use with data from short- and long-read sequencing technologies. For species without a good reference transcriptome annotation, Terminitor is still able to pass on the information learnt from a related species and make reasonable predictions. We used Terminitor to showcase how single nucleotide variations can create or destroy polyadenylated cleavage sites in human RNA-seq samples.Author Summary3’ cleavage and polyadenylation of pre-mRNA is part of RNA maturation process. One gene can be cleaved at different positions at its 3’ end, namely alternatively polyadenylation, thus identifying the correct polyadenylated cleavage site (poly(A) CS) is essential to unveil its role in gene regulation under different physiological and pathological conditions. The current poly(A) CS prediction tools are either heavily influenced by RNA-Seq library preparation artefacts or have only been designed and tested on ad hoc datasets, lacking association with real world applications. In this study, we present a deep learning model, Terminitor, that predicts the probability of a nucleotide sequence containing a poly(A) CS, and validated its performance on human and mouse data. Along with the model, we propose a poly(A) CS profiling pipeline for RNA-seq data. We benchmarked our pipeline against competing tools and achieved higher sensitivity and precision in experimental data. The usage of Terminitor is not limited to genome and transcriptome annotation and we expect it to facilitate the identification of novel isoforms, improve the accuracy of transcript quantification and differential expression analysis, and contribute to the repertoire of reference transcriptome annotation.
Genome analysis of the steroid-degrading denitrifying Denitratisoma oestradiolicum DSM 16959 and Denitratisoma sp. strain DHT3
Authors: Chen Yi-Lung , Wei Sean Ting-Shyang , Chiang Yin-Ru 
Published: July 2019

AbstractSteroid hormones (androgens and estrogens) are crucial for development, reproduction, and communication of multicellular eukaryotes. The ubiquitous distribution and persistence of steroid hormones in our ecosystems have become an environmental issue due to the adverse effects on wildlife and humans upon long-term exposure. Microbial degradation is critical for the removal of steroid hormones from ecosystems. The aerobic degradation pathways for androgens and estrogens and the anaerobic degradation pathway for androgen have been studied into some details; however, the mechanism for anaerobic estrogen degradation remains completely unknown. Here, we presented the circular genomes of D. oestradiolicum DSM 16959 and Denitratisoma sp. strain DHT3, two betaproteobacteria capable of anaerobic estrogen degradation. We identified the genes involved in steroid transformation and in the anaerobic 2,3-seco pathway in both genomes. Additionally, the comparative genomic analysis revealed that genes exclusively represented in estrogen-degrading anaerobes might play a role in anaerobic estrogen catabolism.
The plant mobile domain proteins MAIN and MAIL1 interact with the phosphatase PP7L to regulate gene expression and silence transposable elements in Arabidopsis thaliana
Authors: Nicolau Melody , Picault Nathalie , Descombin Julie , Jami-Alahmadi Yasaman , Feng Suhua , Bucher Etienne , Jacobsen Steven E. , Deragon Jean-Marc , Wohlschlegel James , Moissiard Guillaume 
Published: July 2019

ABSTRACTTransposable elements (TEs) are DNA repeats that must remain silenced to ensure cell integrity. Several epigenetic pathways including DNA methylation and histone modifications are involved in the silencing of TEs, and in the regulation of gene expression. In Arabidopsis thaliana, the TE-derived plant mobile domain (PMD) proteins have been involved in TE silencing, genome stability, and control of developmental processes. Using a forward genetic screen, we found that the PMD protein MAINTENANCE OF MERISTEMS (MAIN) acts synergistically and redundantly with DNA methylation to silence TEs. We found that MAIN and its close homolog MAIN-LIKE 1 (MAIL1) interact together, as well as with the phosphoprotein phosphatase (PPP) PP7-like (PP7L). Remarkably, main, mail1, pp7l single and mail1 pp7l double mutants display similar developmental phenotypes, and share common subsets of upregulated TEs and misregulated genes. Finally, phylogenetic analyses of PMD and PP7-type PPP domains among the Eudicot lineage suggest neo-association processes between the two protein domains to potentially generate new protein function. We propose that, through this interaction, the PMD and PPP domains may constitute a functional protein module required for the proper expression of a common set of genes, and for silencing of TEs.AUTHOR SUMMARYThe plant mobile domain (PMD) is a protein domain of unknown function that is widely spread in the angiosperm plants. Although most PMDs are associated with repeated DNA sequences called transposable elements (TEs), plants have domesticated the PMD to produce genic versions that play important roles within the cell. In Arabidopsis thaliana, MAINTENANCE OF MERISTEMS (MAIN) and MAIN-LIKE 1 (MAIL1) are genic PMDs that are involved in genome stability, developmental processes, and silencing of TEs. The mechanisms involving MAIN and MAIL1 in these cellular processes remain elusive. Here, we show that MAIN, MAIL1 and the phosphoprotein phosphatase (PPP) named PP7-like (PP7L) interact to form a protein complex that is required for the proper expression of genes, and the silencing of TEs. Phylogenetic analyses revealed that PMD and PP7-type PPP domains are evolutionary connected, and several plant species express proteins carrying both PMD and PPP domains. We propose that interaction of PMD and PPP domains would create a functional protein module involved in mechanisms regulating gene expression and repressing TEs.
Low-glutathione mutants are impaired in growth but do not show an increased sensitivity to moderate water deficit
Authors: Bangash Sajid A.K. , Solbach David , Jansen Marcus , Fiorani Fabio , Schwarzländer Markus , Kopriva Stanislav , Meyer Andreas J. 
Published: July 2019

AbstractGlutathione is considered a key metabolite for stress defense and elevated levels have frequently been proposed to positively influence stress tolerance. To investigate whether glutathione affects plant performance and the drought tolerance of plants, wild-type Arabidopsis plants and an allelic series of five mutants (rax1, pad2, cad2, nrc1, andzir1) with reduced glutathione contents between 21 and 63 % compared to wild-type glutathione content were phenotypically characterized for their shoot growth under control and water-limiting conditions using a shoot phenotyping platform. Under non-stress conditions thezir1mutant with only 21 % glutathione showed a pronounced dwarf phenotype. All other mutants with intermediate glutathione contents up to 62 % in contrast showed consistently slightly smaller shoots than the wild-type. Moderate drought stress imposed through water withdrawal until shoot growth ceased showed that wild-type plants and all mutants responded similarly in terms of chlorophyll fluorescence and growth retardation. These results lead to the conclusion that glutathione is important for general plant performance but that the glutathione content does not affect tolerance to moderate drought conditions typically experienced by crops in the field.
PPM1H phosphatase counteracts LRRK2 signaling by selectively dephosphorylating Rab proteins
Authors: Berndsen Kerryn , Lis Pawel , Yeshaw Wondwossen , Wawro Paulina S. , Nirujogi Raja S. , Wightman Melanie , Macartney Thomas , Dorward Mark , Knebel Axel , Tonelli Francesca , Pfeffer Suzanne R. , Alessi Dario R. 
Published: July 2019

AbstractMutations that activate LRRK2 protein kinase cause Parkinson’s disease. LRRK2 phosphorylates a subset of Rab GTPases within their Switch-II motif controlling interaction with effectors. An siRNA screen of all protein phosphatases revealed that a poorly studied protein phosphatase, PPM1H, counteracts LRRK2 signaling by specifically dephosphorylating Rab proteins. PPM1H knock out increased endogenous Rab phosphorylation and inhibited Rab dephosphorylation. Overexpression of PPM1H suppressed LRRK2-mediated Rab phosphorylation. PPM1H also efficiently and directly dephosphorylated Rab8A in biochemical studies. A “substrate-trapping” PPM1H mutant (Asp288Ala) binds with high affinity to endogenous, LRRK2-phosphorylated Rab proteins, thereby blocking dephosphorylation seen upon addition of LRRK2 inhibitors. PPM1H is localized to the Golgi and its knockdown suppresses primary cilia formation, similar to pathogenic LRRK2. Thus, PPM1H acts as a key modulator of LRRK2 signaling by controlling dephosphorylation of Rab proteins. PPM1H activity enhancers could offer a new therapeutic approach to prevent or treat Parkinson’s disease.
Mathematical analysis of thermally radiative time-dependent Sisko nanofluid flow for curved surface
Authors: Khan Waqar Azeem , Waqas Muhammad , Ali Mehboob , Sultan F. , Shahzad M. , Irfan M. 
Published: July 2019

Purpose
This paper aims to develop a mathematical model featuring Brownian motion and thermophoresis. The idea of curved stretching subjected to time-dependent non-Newtonian (Sisko) fluid flow is introduced.

Design/methodology/approach
Shooting scheme is implemented to compute nonlinear systems.

Findings
Velocity profile of Sisko magnetonanofluid enhances for augmented values of curvature parameter.

Originality/value
To the best of the authors’ knowledge, no such analysis has yet been reported.
Does the hospitality industry need or deserve talent?
Authors: Baum Tom 
Published: July 2019

PurposeThis paper aims to confront the most challenging issues that the hospitality industry faces. This relates to the recruitment and retention of talented future leaders. This is a long-standing issue but one that is increasing in importance as industry changes, combined with external pressures within the labour market (demographic and competitive), act to restructure the recruitment landscape in many countries.Design/methodology/approachThis paper provides a literature-based analysis that addresses two key questions relating to the hospitality industry and talent – does the sector need talent and, controversially, does it deserve talent? The literature has been addressed on the basis of the author’s in-depth knowledge and the use of a wide range of pertinent search terms relating to the core themes of hospitality and talent management.FindingsThe paper assesses evidence with respect to both questions, framed as propositions, and concludes that the current talent pipelines, upon which hospitality substantially depends, may not be fit for purpose, and that the wider workplace culture within hospitality is not compatible with the attraction of the best into the industry.Research limitations/implicationsThe paper challenges the established practice, both within the hospitality industry, in terms of its workplace environment, and in the way its educational partners (hospitality management schools) prepare young people for the industry. The outcomes of the analysis do not provide much by way of succour to either.Practical implicationsImplicit in this paper is a call to key stakeholders (industry and education) in the search for future leaders of the hospitality industry to address and review both the industry workplace, to make it more attractive and rewarding for young graduates, and the educational model that still dominates hospitality management programmes in preparing them for careers.Social implicationsCareers in hospitality will remain “Cinderella” options for young graduates until action is taken by stakeholders to reposition the nature of the careers on offer and the focus of the programmes available in preparation for them.Originality/valueThe approach taken is the presentation of widely recognised themes in an original format.
Assessing batteries supply chain networks for low impact vehicles
Authors: Rafele Carlo , Mangano Giulio , Cagliano Anna Corinna , Carlin Antonio 
Published: July 2019

Purpose
This paper aims to evaluate different logistics configuration to deliver batteries from the supplier to the production lines of a European carmaker who is implementing new propulsions for its models.

Design/methodology/approach
Several scenarios about the supply chain for traction batteries have been identified based on the company’s requirements and constraints. Then, the variables used for the assessment of each scenario have been selected to calculate the unit battery supply chain cost.

Findings
The results underline that a direct transport without intermediate nodes is the cheapest one. On the contrary, an additional warehouse makes the organization of the network more complex. However, with this configuration, it is possible to cover the risk of supply since that a certain level of inventory is always guaranteed.

Research limitations/implications
This study is limited to the analysis of only one model car, and just manual operations have been taken into account for computing the human resource time and cost. The present study is one of the first works exploring the organization of the supply chain for the batteries integrated in electric and hybrid vehicles together with the choice of the location of the related warehouses.

Originality/value
This paper is one of the first work on the assessment of batteries’ supply chain that are going to be integrated in low impact vehicles, focusing on location of the associated warehouse. The evaluation is carried out by taking into account all the sources of cost.