bluuebunny/crossref_metadata_2025_split huggingface dataset:
CD4+ T cells from chronic Chagas disease patients with different degrees of cardiac compromise exhibit distinct expression patterns of inhibitory receptors TIGIT, Tim-3 and Lag-3
Authors: Alcaraz Paula B. , Girard Magali C. , Beati M. Paula , Chadi Raul , Fernandez Marisa , Hernandez Yolanda , Gómez Karina A. , Acevedo Gonzalo R. 
Published: July 2019

AbstractT cells are central to adaptive immune response against T. cruzi infection. In the chronic stage of Chagas disease, circulating parasite-specific memory T cells show reduced functionality and increased expression of inhibitory receptors, possibly as a result of persistent antigenic stimulation. This exhausted phenotype has been linked to progression of cardiac pathology while, contrariwise, the presence of polyfunctional T cells shows association with therapeutic success and more efficient control of infection. Given this, we hypothesized that inhibitory receptors TIGIT, Tim-3 and Lag-3 may be involved in immune modulation of anti-T. cruzi T cell response, and therefore may play a role in the containment or the unleashing of inflammatory phenomena that ultimately lead to tissue damage and pathology. In this preliminary study, we assess the frequency of CD4+ T cells expressing each of these receptors and their relation to cellular activation. Samples from chronic Chagas disease patients with different degrees of cardiac compromise, and non-infected donors were analyzed under different stimulation conditions. Our results show that the frequency of TIGIT+ CD4+ T cells is increased in Chagas patients, while Tim-3+ cells are more abundant in patients with signs of cardiac alterations. In addition, the frequency of Lag-3+ cells increases in non-activated CD4+ T cells from Chagas patients without demonstrable cardiopathy upon pathogen-specific in vitro antigenic stimulation.
PheGWAS: A new dimension to visualize GWAS across multiple phenotypes
Authors: George Gittu , Gan Sushrima , Huang Yu , Appleby Philip , Nar A.S. , Venkatesan Radha , Mohan Viswanathan , Palmer Colin N.A , Doney Alex S.F 
Published: July 2019

AbstractMotivationPheGWAS was developed to enhance exploration of phenome-wide pleiotropy at the genome-wide level through the efficient generation of a dynamic visualization combining Manhattan plots from GWAS with PheWAS to create a three-dimensional “landscape”. Pleiotropy in sub-surface GWAS significance strata can be explored in a sectional view plotted within user defined levels. Further complexity reduction is achieved by confining to a single chromosomal section. Comprehensive genomic and phenomic coordinates can be displayed.ResultsPheGWAS is demonstrated using summary data from Global Lipids Genetics Consortium (GLGC) GWAS across multiple lipid traits. For single and multiple traits PheGWAS highlighted all eight-eight and sixty-nine loci respectively. Further, the genes and SNPs reported in GLGC were identified using additional functions implemented within PheGWAS. Not only is PheGWAS capable of identifying independent signals but also provide insights to local genetic correlation (verified using HESS) and in identifying the potential regions that share causal variants across phenotypes (verified using colocalization tests).Availability and ImplementationThe PheGWAS software and code are freely available at (https://github.com/georgeg0/PheGWAS).Contacta.doney@dundee.ac.uk, g.z.george@dundee.ac.uk
Decentralized Control of Insect Walking – a simple neural network explains a wide range of behavioral and neurophysiological results
Authors: Schilling Malte , Cruse Holk 
Published: July 2019

AbstractControl of walking with six or more legs in an unpredictable environment is a challenging task, as many degrees of freedom have to be coordinated. Generally, solutions are proposed that rely on (sensory-modulated) CPGs, mainly based on data from neurophysiological studies. Here, we are introducing a sensor based controller operating on artificial neurons, being applied to a (simulated) hexapod robot with a morphology adapted toCarausius morosus. We show that such a decentralized solution leads to adaptive behavior when facing uncertain environments which we demonstrate for a large range of behaviors – slow and fast walking, forward and backward walking, negotiation of curves and walking on a treadmill with various treatment of individual legs. This approach can as well account for these neurophysiological results without relying on explicit CPG-like structures, but can be complemented with these for very fast walking.
Mathematical models of protease-based enzymatic biosensors
Authors: Agrawal Deepak K. , Khare Sagar D. , Sontag Eduardo D 
Published: July 2019

AbstractAn important goal of synthetic biology is to build biosensors and circuits with well-defined input-output relationships that operate at speeds found in natural biological systems. However, for molecular computation, most commonly used genetic circuit elements typically involve several steps from input detection to output signal production: transcription, translation, and post-translational modifications. These multiple steps together require up to several hours to respond to a single stimulus, and this limits the overall speed and complexity of genetic circuits. To address this gap, molecular frame-works that rely exclusively on post-translational steps to realize reaction networks that can process inputs at a timescale of seconds to minutes have been proposed. Here, we build mathematical models of fast biosensors capable of producing Boolean logic functionality. We employ protease-based chemical and light-induced switches, investigate their operation, and provide selection guidelines for their use as on-off switches. We then use these switches as elementary blocks, developing models for biosensors that can perform OR and XOR Boolean logic computation while using reaction conditions as tuning parameters. We use sensitivity analysis to determine the time-dependent sensitivity of the output to proteolytic and protein-protein binding reaction parameters. These fast protease-based biosensors can be used to implement complex molecular circuits with a capability of processing multiple inputs controllably and algorithmically. Our framework for evaluating and optimizing circuit performance can be applied to other molecular logic circuits.
Inoculation with the mycorrhizal fungus Rhizophagus irregularis modulates the relationship between root growth and nutrient content in maize (Zea mays ssp. mays L.)
Authors: Ramírez-Flores M. Rosario , Bello-Bello Elohim , Rellán-Álvarez Rubén , Sawers Ruairidh J. H. , Olalde-Portugal Víctor 
Published: July 2019

ABSTRACTPlant root systems play an essential role in nutrient and water acquisition. In resource-limited soils, modification of root system architecture is an important strategy to optimize plant performance. Most terrestrial plants also form symbiotic associations with arbuscular mycorrhizal fungi to maximize nutrient uptake. In addition to direct delivery of nutrients, arbuscular mycorrhizal fungi benefit the plant host by promoting root growth. Here, we aimed to quantify the impact of arbuscular mycorrhizal symbiosis on root growth and nutrient uptake in maize. Inoculated plants showed an increase in both biomass and the total content of twenty quantified elements. In addition, image analysis showed mycorrhizal plants to have denser, more branched root systems. For most of the quantified elements, the increase in content in mycorrhizal plants was proportional to root and overall plant growth. However, the increase in boron, calcium, magnesium, phosphorus, sulfur and strontium was greater than predicted by root system size alone, indicating fungal delivery to be supplementing root uptake.
Multi-tissue network analysis for drug prioritization in knee osteoarthritis
Authors: Neidlin Michael , Dimitrakopoulou Smaragda , Alexopoulos Leonidas G 
Published: July 2019

ABSTRACTKnee osteoarthritis (OA) is a joint disease that affects several tissues: cartilage, synovium, meniscus and subchondral bone. The pathophysiology of this complex disease is still not completely understood and existing pharmaceutical strategies are limited to pain relief treatments.Therefore, a computational method was developed considering the diverse mechanisms and the multi-tissue nature of OA in order to suggest pharmaceutical compounds. Specifically, weighted gene co-expression network analysis (WGCNA) was utilized to identify gene modules that were preserved across four joint tissues. The driver genes of these modules were selected as an input for a network-based drug discovery approach.WGCNA identified two preserved modules that described functions related to extracellular matrix physiology and immune system responses. Compounds that affected various anti-inflammatory pathways and drugs targeted at coagulation pathways were suggested. 9 out of the top 10 compounds had a proven association with OA and significantly outperformed randomized approaches not including WGCNA. The method presented herein is a viable strategy to identify overlapping molecular mechanisms in multi-tissue diseases such as OA and employ this information for drug discovery and compound prioritization.
Finding missing links in interaction networks
Authors: Terry J. Christopher D. , Lewis Owen T. 
Published: July 2019

AbstractDocumenting which species interact within ecological communities is challenging and labour-intensive. As a result, many interactions remain unrecorded, potentially distorting our understanding of network structure and dynamics. We test the utility of four structural models and a new coverage-deficit model for predicting missing links in both simulated and empirical bipartite networks. We find they can perform well, but that the predictive power of structural models varies with the underlying network structure. Predictions can be improved by ensembling multiple models. Sample-coverage estimators of the number of missed interactions are highly correlated with the number of missed interactions, but strongly biased towards underestimating the true number of missing links. Augmenting observed networks with most-likely missing links improves estimates of qualitative network metrics. Tools to identify likely missing links can be simple to implement, allowing the prioritisation of research effort and more robust assessment of network properties.
Prognostic Role of c-Met Overexpression in High Grade Glioma: a Meta-analysis
Authors: Wu Bo , Ma Yuhan , Zhong Sheng , Ge Junliang , Jiang Shanshan , Zhang Yuan , Xu Haiyang 
Published: July 2019

AbstractObjectivesThis study aims to assess the relationship between the expression of c-Met and the prognosis of high grade glioma patients.MethodThe MET proto-oncogene encoded c-Met protein. The gene expression data of 325 patients were downloaded from CGGA. The Oncomine database analysis and the prognosis analysis were conducted. Besides, meta-analysis was also performed to confirm the conclusion.ResultOncomine database was identified and analyzed and results showed that the MET copy number was obviously higher in glioblastoma than normal tissue consistently (p<0.001). The prognostic analysis of 325 high grade glioma samples showed that high c-Met expression patients had poor overall survival (OS) and progression free survival (PFS) than the low c-Met expression patients dramatically (HR, 2.223; 95% CI: 1.662 to 2.974; P<0.0001 and HR, 2.089; 95% CI: 1.578 to 2.770; P<0.0001). 6 studies involving 503 patients were included in the meta-analysis. The pooled results indicated that the high expression of c-Met was not significantly associated with OS (HR =1.01, 95% CI:0.93-1.09), but strongly connected with shorter PFS (HR =1.92, 95% CI:1.42-2.58, p<0.01).Conclusionc-Met overexpression has correlation with poor prognosis of high grade glioma patients.
The developmental needs of coaches and coachees
Authors: Eastman Christine Angela 
Published: July 2019

Purpose
The purpose of this paper is to highlight the key findings, themes and concepts in coaching from the inception of the International Journal of Mentoring and Coaching in Education in early 2012 to the end of 2018. The review examines how coaching is theorized and practised in an educational context, and how coaching has evolved across educational disciplines.

Design/methodology/approach
The study is based on an analysis of research trends published in the International Journal of Mentoring and Coaching in Education from Volume 1 Issue 1 (2012) to Volume 7 Issue 4 (2018). The criterion according to which the articles were selected for inclusion in the literature review is whether the word “coaching” is used in the title, abstract or keywords.

Findings
Across a wide range of geographical and institutional contexts, the studies surveyed in this literature review point to the different ways in which coaching interventions support success in teaching and leadership. This review identifies three principal themes across the literature on coaching: confidence, trust and identity.

Research limitations/implications
The literature review is confined to studies published in a single publication and is therefore not representative of the entire field of coaching research.

Practical implications
The focus of this review is coaching in education. The review comprises a survey of research concepts, innovation and creativity in the area of coaching and education. It highlights advances in the field of coaching and education and points to areas of development for future research.

Originality/value
By bringing together existing research in a number of areas across the field of coaching, this literature review provides a coherent overview of a rapidly evolving and diverse field.
Environmental reporting by the Malaysian local governments
Authors: Che Ku Kassim Che Ku Hisam , Ahmad Suraya , Mohd Nasir Noor Emilina , Wan Mohd Nori Wan Mohd Nazif , Mod Arifin Nur Nariza 
Published: July 2019

PurposeThe purpose of this paper is to examine the environmental reporting (ER) practices of the local governments (LGs) in Malaysia. Specifically, it examines the driving motives for ER and also the underlying reasons for lack of disclosures in an array of reporting media.Design/methodology/approachA self-administered survey is conducted to all LGs in Peninsular Malaysia. The items in the questionnaire are based on the prior literature on social and environmental disclosures made by the public sector organisations (PSOs).FindingsThe results suggest that maintaining and/or improving the legitimacy status is the main driving motive for LGs to provide environmental disclosures in the absence of any regulatory requirements. On the other hand, a lack of skilled staff to handle ER is the primary reason contributing to the lack of environmental information being supplied to stakeholders.Originality/valueThe paper represents one of the few attempts made in examining the ER practices of the LGs within the perspective of a developing country. Insufficient research on this aspect contributes to a limited understanding on the development of ER practices in different economic stage and environment. The findings may be of interest to the relevant authorities in any policy changes that can further improve the extent and quality of environmental disclosures made by the LGs.
Vascular balloon occlusion and planned caesarean hysterectomy for morbidly adherent placenta: A systematic review
Authors: Makary Michael , Chowdary Prathima , Westgate Jenny Ann 
Published: July 2019

BackgroundMorbidly adherent placenta is potentially life‐threatening, often requiring technically difficult surgery and large blood loss. Use of intravascular balloon occlusion with or without hysterectomy to reduce blood loss is increasing despite associated morbidity and lack of evidence of efficacy.AimsTo evaluate if prophylactic use of vascular balloon occlusion at the time of planned caesarean hysterectomy for antenatally diagnosed morbidly adherent placenta reduces blood loss and transfusion requirements, and determine rate of associated complications.Materials and MethodsA systematic review of PubMed and Medline covering January 1997 to December 2018 was conducted. Key words included placenta accreta, increta, percreta, and morbidly adherent placenta, balloon, interventional radiology, embolization, and caesarean hysterectomy.ResultsNineteen studies were included. Only three studies had appropriate controls: two with balloon placement in the internal iliac arteries and one in the common iliac arteries. One showed no difference in blood loss or transfusion requirements, the second showed a reduction in cases of percreta only and the third reported reduction in blood loss. Only few studies reported objective measures of blood loss. Blood loss and transfusion were still high (2.26 L and 3.79 units, respectively) despite use of vascular balloons. Balloon catheter use was associated with a 7.5% rate of complications; 4.5% were minor and 3.0% major.ConclusionsThere is a large body of poor data evaluating efficacy of prophylactic vascular balloon occlusion in cases of planned caesarean hysterectomy for known morbidly adherent placenta. Limited relevant data provide only scant evidence that these techniques are beneficial in reducing blood loss, despite associated significant complications.
Learning Fuzzy Set Representations of Partial Shapes on Dual Embedding Spaces
Authors: Sung Minhyuk , Dubrovina Anastasia , Kim Vladimir G. , Guibas Leonidas 
Published: July 2019

AbstractModeling relations between components of 3D objects is essential for many geometry editing tasks. Existing techniques commonly rely on labeled components, which requires substantial annotation effort and limits components to a dictionary of predefined semantic parts. We propose a novel framework based on neural networks that analyzes an uncurated collection of 3D models from the same category and learns two important types of semantic relations among full and partial shapes: complementarity and interchangeability. The former helps to identify which two partial shapes make a complete plausible object, and the latter indicates that interchanging two partial shapes from different objects preserves the object plausibility. Our key idea is to jointly encode both relations by embedding partial shapes as fuzzy sets in dual embedding spaces. We model these two relations as fuzzy set operations performed across the dual embedding spaces, and within each space, respectively. We demonstrate the utility of our method for various retrieval tasks that are commonly needed in geometric modeling interfaces.
Effective Characterization of Relief Patterns
Authors: Giachetti A. 
Published: July 2019

AbstractIn this paper, we address the problem of characterizing relief patterns over surface meshes independently on the underlying shape. We propose to tackle the problem by estimating local invariant features and encoding them using the Improved Fisher Vector technique, testing both features estimated on 3D meshes and local descriptors estimated on raster images created by encoding local surface properties (e.g. mean curvature) over a surface parametrization. We compare the robustness of the obtained descriptors against noise and surface bending and evaluate retrieval performances on a specific benchmark proposed in a track of the Eurographics Shape REtrieval Contest 2017. Results show that, with the proposed framework, it is possible to obtain retrieval results largely improving the state of the art and that the image‐based approach is still effective when the underlying surface is heavily deformed.
A unified discrete framework for intrinsic and extrinsic Dirac operators for geometry processing
Authors: Ye Zi , Diamanti Olga , Tang Chengcheng , Guibas Leonidas , Hoffmann Tim 
Published: July 2019

AbstractSpectral mesh analysis and processing methods, namely ones that utilize eigenvalues and eigenfunctions of linear operators on meshes, have been applied to numerous geometric processing applications. The operator used predominantly in these methods is the Laplace‐Beltrami operator, which has the often‐cited property that it is intrinsic, namely invariant to isometric deformation of the underlying geometry, including rigid transformations. Depending on the application, this can be either an advantage or a drawback. Recent work has proposed the alternative of using the Dirac operator on surfaces for spectral processing. The available versions of the Dirac operator either only focus on the extrinsic version, or introduce a range of mixed operators on a spectrum between fully extrinsic Dirac operator and intrinsic Laplace operator. In this work, we introduce a unified discretization scheme that describes both an extrinsic and intrinsic Dirac operator on meshes, based on their continuous counterparts on smooth manifolds. In this discretization, both operators are very closely related, and preserve their key properties from the smooth case. We showcase various applications of our operators, with improved numerics over prior work.
Hierarchical Quad Meshing of 3D Scanned Surfaces
Authors: Bukenberger Dennis R. , Lensch Hendrik P. A. 
Published: July 2019

AbstractIn this paper we present a novel method to reconstruct watertight quad meshes on scanned 3D geometry. There exist many different approaches to acquire 3D information from real world objects and sceneries. Resulting point clouds depict scanned surfaces as sparse sets of positional information. A common downside is the lack of normals, connectivity or topological adjacency data which makes it difficult to actually recover a meaningful surface. The concept described in this paper is designed to reconstruct a surface mesh despite all this missing information. Even when facing varying sample density, our algorithm is still guaranteed to produce watertight manifold meshes featuring quad faces only. The topology can be set‐up to follow superimposed regular structures or align naturally to the point cloud's shape. Our proposed approach is based on an initial divide and conquer subsampling procedure: Surface samples are clustered in meaningful neighborhoods as leafs of a kd‐tree. A representative sample of the surface neighborhood is determined for each leaf using a spherical surface approximation. The hierarchical structure of the binary tree is utilized to construct a basic set of loose tiles and to interconnect them. As a final step, missing parts of the now coherent tile structure are filled up with an incremental algorithm for locally optimal gap closure. Disfigured or concave faces in the resulting mesh can be removed with a constrained smoothing operator.
Modular Latent Spaces for Shape Correspondences
Authors: Ganapathi‐Subramanian Vignesh , Diamanti Olga , Guibas Leonidas J. 
Published: July 2019

AbstractWe consider the problem of transporting shape descriptors across shapes in a collection in a modular fashion, in order to establish correspondences between them. A common goal when mapping between multiple shapes is consistency, namely that compositions of maps along a cycle of shapes should be approximately an identity map. Existing attempts to enforce consistency typically require recomputing correspondences whenever a new shape is added to the collection, which can quickly become intractable. Instead, we propose an approach that is fully modular, where the bulk of the computation is done on each shape independently. To achieve this, we use intermediate nonlinear embedding spaces, computed individually on every shape; the embedding functions use ideas from diffusion geometry and capture how different descriptors on the same shape inter‐relate. We then establish linear mappings between the different embedding spaces, via a shared latent space. The introduction of nonlinear embeddings allows for more nuanced correspondences, while the modularity of the construction allows for parallelizable calculation and efficient addition of new shapes. We compare the performance of our framework to standard functional correspondence techniques and showcase the use of this framework to simple interpolation and extrapolation tasks.