bluuebunny/crossref_metadata_2025_split huggingface dataset:
Differential attenuation of β2 integrin-dependent and -independent neutrophil migration by Ly6G ligation
Authors: Cunin Pierre , Lee Pui Y. , Kim Edy , Schmider Angela B. , Cloutier Nathalie , Pare Alexandre , Gunzer Matthias , Soberman Roy J. , Lacroix Steve , Boilard Eric , Lefort Craig T. , Nigrovic Peter A. 
Published: November 2018

AbstractAntibody ligation of the murine neutrophil surface protein Ly6G disrupts neutrophil migration in some contexts but not others. We tested whether this variability reflected divergent dependence of neutrophil migration on β2 integrins, adhesion molecules that interact with Ly6G at the neutrophil surface. In integrin-dependent murine arthritis, Ly6G ligation attenuated joint inflammation, even though mice lacking Ly6G altogether developed arthritis normally. By contrast, Ly6G ligation had no impact on integrin- independent neutrophil migration into inflamed lung. In peritoneum, the role of β2 integrins varied with stimulus, proving dispensable for neutrophil entry inE. coliperitonitis but contributory in IL-1-mediated sterile peritonitis. Correspondingly, Ly6G ligation attenuated only IL-1 peritonitis, disrupting the molecular association between integrins and Ly6G and inducing cell-intrinsic blockade restricted to integrin-dependent migration. Consistent with this observation, Ly6G ligation impaired integrin-mediated postadhesion strengthening for neutrophils arresting on activated cremaster endotheliumin vivo. Together, these findings identify selective inhibition of integrin- mediated neutrophil emigration through Ly6G ligation, highlighting the marked site and stimulus specificity of β2 integrin dependence in neutrophil migration.KEY POINTSThe contribution of β2 integrins to neutrophil migration into inflamed tissues varies with site and stimulus.Ligation of Ly6G, a GPI-linked neutrophil surface protein, selectively attenuates β2 integrin-dependent neutrophil migration in vivo.Blockade correlates with disrupted interaction between Ly6G and β2 integrins and impaired integrin-mediated postadhesion strengthening.
Comparison of Approaches to the identification of Symptom Burden in Hemodialysis Patients Utilizing Electronic Health Records
Authors: Chan Lili , Beers Kelly , Chauhan Kinsuk , Debnath Neha , Saha Aparna , Pattharanitima Pattharawin , Cho Judy , Kotanko Peter , Federman Alex , Coca Steven , Vleck Tielman Van , Nadkarni Girish N. 
Published: November 2018

AbstractBackgroundIdentification of symptoms is challenging with surveys, which are time-intensive and low-throughput. Natural language processing (NLP) could be utilized to identify symptoms from narrative documentation in the electronic health record (EHR).MethodsWe utilized NLP to parse notes for maintenance hemodialysis (HD) patients from two EHR databases (BioMe and MIMIC-III) to identify fatigue, nausea/vomiting, anxiety, depression, cramping, itching, and pain. We compared NLP performance with International Classification of Diseases (ICD) codes and validated the performance of both NLP and codes against manual chart review in a representative subset.ResultsWe identified 1034 and 929 HD patients from BioMe and MIMIC-III respectively. The most frequently identified symptoms by NLP from both cohorts were fatigue, pain, and nausea and/or vomiting. NLP was significantly more sensitive than ICD codes for nearly all symptoms. In the BioMe dataset, sensitivity for NLP ranged from 0.85-0.99 vs. 0.09-0.59 for ICD codes. In the MIMIC-III dataset, NLP sensitivity was 0.8-0.98 vs. 0.02-0.53 for ICD. ICD codes were significantly more specific for nausea and/or vomiting (NLP 0.57 vs. ICD 0.97, P=0.03) in BioMe and for depression (NLP 0.67 vs. ICD 0.99, P=0.002) in MIMIC-III. A majority of patients in both cohorts had ?4 symptoms. The more encounters available for a patient the more likely NLP was to identify a symptom.ConclusionsNLP out performed ICD codes for identification of symptoms on several tests parameters including sensitivity for a majority of symptoms. NLP may be useful for the high-throughput identification of patient centered outcomes from EHR.Significance StatementPatients on maintenance hemodialysis experience a high frequency of symptoms. However, symptoms have been measured utilizing time-intensive surveys. This paper compares natural language processing (NLP) to administrative codes for the identification of seven key symptoms from two cohorts with electronic health records and validation through manual chart review. NLP identified high rates of symptoms; the most common were fatigue, pain, and nausea and/or vomiting. A majority of patients had ≥4 symptoms. NLP was significantly more sensitive at identifying symptoms compared to administrative codes for nearly all symptoms but specificity was not significantly different compared to codes. This paper demonstrates utility of a high throughput method of identifying symptoms from EHR which may advance the field of patient centered research in nephrology.
Instantaneous isotropic volumetric imaging of fast biological processes
Authors: Wagner Nils , Norlin Nils , Gierten Jakob , de Medeiros Gustavo , Balázs Bálint , Wittbrodt Joachim , Hufnagel Lars , Prevedel Robert 
Published: November 2018

AbstractCapturing highly dynamic biological processes at sub-cellular resolution is a recurring challenge in biology. Here we show that combining selective volume illumination with simultaneous acquisition of orthogonal light-fields yields 3D images with high, isotropic spatial resolution and free of reconstruction artefacts, thereby overcoming current limitations of light-field microscopy implementations. We demonstrate Medaka heart and blood flow imaging with single-cell resolution and free of motion artefacts at volume rates up to 200Hz.
Discrete Mechanical Growth Model for Plant Tissue
Authors: Weise Louis D. , ten Tusscher Kirsten H. W. J. 
Published: November 2018

AbstractWe present a discrete mechanical model to study plant development. The method is built up of mass points, springs and hinges mimicking the plant cell wall’s microstructure. To model plastic growth the resting lengths of springs are adjusted; when springs exceed a threshold length, new mass points, springs and hinges, are added. We formulate a stiffness tensor for the springs and hinges as a function of the fourth rank tensor of elasticity and the geometry of the mesh. This allows us to approximate the material law as a generalized orthotropic Hooke’s law, and control material properties during growth. The material properties of the model are illustrated in numerical simulations for finite strain and plastic growth. To solve the equations of motion of mass points we assume elastostatics and use Verlet integration. The method is demonstrated in simulations when anisotropic growth causes emergent residual strain fields in cell walls and a bending of bulk tissue. The method can be used in multilevel models to study plant development, for example by coupling it to models for cytoskeletal, hormonal and gene regulatory processes.
One Model to Rule Them All: An Integrative Approach to Matrix-Based Analyses in Neuroimaging Connectomics
Authors: Chen Gang , Bürkner Paul-Christian , Taylor Paul A. , Li Zhihao , Yin Lijun , Glen Daniel R. , Kinniso Joshua , Cox Robert W. , Pessoa Luiz 
Published: November 2018

AbstractNetwork modeling in neuroimaging holds promise in probing the interrelationships among brain regions and potential clinical applications. Two types of matrix-based analysis (MBA) are usually seen in neuroimaging connectomics: one is the functional attribute matrix (FAM) of, for example, correlations, that measures the similarity of BOLD response patterns among a list of predefined regions of interest (ROIs). Another type of MBA involves the structural attribute matrix (SAM), e.g., describing the properties of white matter between any pair of gray-matter regions such as fractional anisotropy, mean diffusivity, axial and radial diffusivity. There are different methods that have been developed or adopted to summarize such matrices across subjects, including general linear models (GLMs) and various versions of graph theoretic analysis. We argue that these types of modeling strategies tend to be “inefficient” in statistical inferences and have many pitfalls, such as having strong dependence on arbitrary thresholding under conventional statistical frameworks.Here we offer an alternative approach that integrates the analyses of all the regions, region pairs (RPs) and subjects into one framework, called Bayesian multilevel (BML) modeling. In this approach, the intricate relationships across regions as well as across RPs are quantitatively characterized. This integrative approach avoids the multiple testing issue that typically plagues the conventional statistical analysis in neuroimaging, and it provides a principled way to quantify both the effect and its uncertainty at each region as well as for each RP. As a result, a unique feature of BML is that the effect at each region and the corresponding uncertainty can be estimated, revealing the relative strength or importance of each region; in addition, the effect at each RP is obtained along with its uncertainty as statistical evidence. Most importantly, the BML approach can be scrutinized for consistency through validation and comparisons with alternative assumptions or models. We demonstrate the BML methodology with a real dataset with 16 ROIs from 41 subjects, and compare it to the conventional GLM approach in terms of model efficiency, performance and inferences. Furthermore, we emphasize the notion of full results reporting through “highlighting,” instead of through the common practice of “hiding.” The associated program will be available as part of the AFNI suite for general use.
Taxonomy, ecology and distribution of Juniperus oxycedrus L. group in the Mediterranean Region using morphometric, phytochemical and bioclimatic approaches
Authors: Cano Ortiz Ana , Musarella Carmelo M. , Piñar Fuentes José C. , Pinto Gomes Carlos J. , Spampinato Giovanni , Cano Eusebio 
Published: November 2018

AbstractThe ecology, taxonomy and distribution of the Juniperus oxycedrus L. group of taxa are studied. From an ecological aspect, this work proposes a new ombroedaphoxeric index to explain the presence of populations of Juniperus in ombrotypes that are not the optimum for these taxa. The controversy among various authors on the taxonomy of the oxycedrus group with regard to J. oxycedrus subsp. badia and J. oxycedrus subsp. lagunae is clarified. The phytochemical differences in essential oils are addressed, and their similarities analysed; greater similarities are observed between oxycedrus and badia (H. Gay) Debeaux, and between navicularis Grand. and macrocarpa (Sm.) Ball. The phytochemical, molecular and distribution differences allow J. macrocarpa and J. navicularis to be maintained as species.
Single-Cell Modeling of CD8+ T Cell Exhaustion Predicts Response to Cancer Immunotherapy
Authors: Jin Guangxu , Xue Gang , Wang Rui-Sheng , Wu Ling-Yun , Miller Lance , Lu Yong , Zhang Wei 
Published: November 2018

AbstractAccurate prediction of response to immune checkpoint blockade (ICB) and simultaneous development of new efficacious ICB strategy are unmet needs for cancer immunotherapy1-5. Despite the advance of existing clinical or computational biomarkers6-10, it is very limited in explicating phenotypic variability of tumor-infiltrating CD8+ T lymphocytes (TILs) at the single-cell level, including tumor-specificity11,12 and distinct exhaustion profiles13-16, that are crucial for the responsiveness to ICB. Here we show that a quantitative criterion, D value, for evaluating tumor-specific TIL exhaustion, identified by our new high-dimensional single-cell-based computational method, called HD-scMed, accurately predicts response to the ICB, i.e., αPD-1, αCTLA-4, and αPD-1+αCTLA-4, with the performance of AUC=100% in human tumors. D-value is the Euclidean distance from a subset of exhausted CD8+ TILs, identified as Pareto Front (PF)18-21 by HD-scMed within the high-dimensional expression space of a variety of exhaustion markers, to the baseline TILs excluded by the PF. We phenotypically distinguished two types of TIL “exhaustion” by the D value, namely “D Extremely-high” in non-responders, associating with high tumor-specificity imprinted with enhanced exhaustion and inactivated effector and cytotoxic signatures; and “D low” specific to responders, alternatively enriched with T cell activation and cytolytic effector T cell signatures. We also observed a large portion of “D negative” bystander T cells irrelevant to response. Notably, D-low TILs in clinical responders display very low LAG3 expression. To reverse the functionality of the LAG3-high TILs after receiving αPD-1+αCTLA-4, we combined αLAG3 with αPD-1+αCTLA-4 in treating a murine tumor model. Remarkably, αLAG3+αPD-1+αCTLA-4 displays extraordinary antitumor efficacy to eradicate advanced tumors, which is associated with burst GZMBhi TIL populations; whereas αPD-1+αCTLA-4 or αPD-1+αCTLA-4 plus other ICBs as control only induce moderate tumor growth inhibition. Our study has important implications for cancer immunotherapy as providing both accurate predictions of ICB response and alternative strategy to reverse ICB resistance.
GANai: Standardizing CT Images using Generative Adversarial Network with Alternative Improvement
Authors: Liang Gongbo , Fouladvand Sajjad , Zhang Jie , Brooks Michael A. , Jacobs Nathan , Chen Jin 
Published: November 2018

AbstractComputed tomography (CT) is a widely-used diag-reproducibility regarding radiomic features, such as intensity, nostic image modality routinely used for assessing anatomical tissue characteristics. However, non-standardized imaging pro-tocols are commonplace, which poses a fundamental challenge in large-scale cross-center CT image analysis. One approach to address the problem is to standardize CT images using generative adversarial network models (GAN). GAN learns the data distribution of training images and generate synthesized images under the same distribution. However, existing GAN models are not directly applicable to this task mainly due to the lack of constraints on the mode of data to generate. Furthermore, they treat every image equally, but in real applications, some images are more difficult to standardize than the others. All these may lead to the lack-of-detail problem in CT image synthesis. We present a new GAN model called GANai to mitigate the differences in radiomic features across CT images captured using non-standard imaging protocols. Given source images, GANai composes new images by specifying a high-level goal that the image features of the synthesized images should be similar to those of the standard images. GANai introduces an alternative improvement training strategy to alternatively and steadily improve model performance. The new training strategy enables a series of technical improvements, including phase-specific loss functions, phase-specific training data, and the adoption of ensemble learning, leading to better model performance. The experimental results show that GANai is significantly better than the existing state-of-the-art image synthesis algorithms on CT image standardization. Also, it significantly improves the efficiency and stability of GAN model training.
Resilience to oxidative and nitrosative stress is mediated by the stressosome, RsbP and SigB inBacillus subtilis.
Authors: Tran Vina , Geraci Kara , Midili Giovanni , Satterwhite William , Wright Rachel , Bonilla Carla Yaneth 
Published: November 2018

AbstractA bacterium’s ability to thrive in the presence of multiple environmental stressors simultaneously determines its resilience. We showed that activation of the SigB-controlled general stress response by mild environmental or nutritional stress provided significant cross-protection to subsequent lethal oxidative, disulfide and nitrosative stress exposure. SigB activation is mediated via the stressosome and RsbP, the main conduits of environmental and nutritional stress, respectively. Cells exposed to mild environmental stress while lacking the major stressosome components RsbT or RsbRA were highly sensitive to subsequent oxidative stress, whereasrsbRB, rsbRC, rsbRDandytvAnull mutants showed a spectrum of sensitivity, confirming their redundant roles and suggesting they could modulate the signal generated by environmental stress or oxidative stress. Furthermore, from mutant analysis we infer that RsbRA phosphorylation by RsbT was important for this cross-resistance to oxidative stress. By contrast, cells encountering stationary phase stress required RsbP but not RsbT to survive subsequent oxidative stress caused by hydrogen peroxide and diamide. Interestingly, optimum cross-protection against nitrosative stress caused by SNP required SigB but not the known regulators, RsbT and RsbP, suggesting an additional and as yet uncharacterized route of SigB activation independent of the known environmental and energy-stress pathways. Together, these results provide a mechanism for howBacillus subtilispromotes enhanced resistance against lethal oxidative stress during likely physiologically relevant conditions such as mild environmental or nutrient stress.
Crystal structure of human endothelin ETb receptor in complex with peptide inverse agonist IRL2500
Authors: Nagiri Chisae , Shihoya Wataru , Inoue Asuka , Ngako Kadji Francois Marie , Aoki Junken , Nureki Osamu 
Published: November 2018

AbstractEndothelin receptors (ET A and ET B) are G-protein coupled receptors activated by endothelin-1 and are involved in blood pressure regulation. IRL2500 is a peptide-mimetic of the C-terminal tripeptide of endothelin-1, and has been characterized as a potent ET B-selective antagonist, which has preventive effects against brain edema. Here, we report the crystal structure of the human ET B receptor in complex with IRL2500 at 2.7 A-resolution. The structure revealed the different binding modes between IRL2500 and ET-1, and provides structural insights into its ET B-selectivity. Notably, the biphenyl group of IRL2500 penetrates into the transmembrane core proximal to D2.50, stabilizing the inactive conformation. Using the newly-established constitutively active mutant, we clearly demonstrate that IRL2500 functions as an inverse agonist for the ET B receptor. The current findings will expand the chemical space of ETR antagonists and facilitate the design of inverse agonists for other class A GPCRs.
Solid riveting process optimization for the reduction of key point distortions caused by locating
Authors: Ni Jun , Ding Wuxue 
Published: November 2018

Purpose
Determinative locating and riveting distortions are highly coupled at assembly locale. Recent methods only take every tested or assumed locating errors at the mating surface into the process planning for the assemblies in a simple form. However, the growth of part number makes it nearly infeasible to take every locating error at every mating surface into the dimensional precision calculation. This paper aims to provide a solid riveting process planning for the reduction of practical locating-related distortions.

Design/methodology/approach
Large-scale metrology firstly measures the determinative coordinates for the locating-deviated key points. Iterative finite element (FE) analyses then calculate the riveting-related key point distortions from every rivet upsetting directions (UDs) and assembly sequence. These key points on the actual assembly contour and relative FE nodes yield two virtual planes. Virtual plane manipulation adds the riveting distortions into the locating-deviated coordinates. Finally, optimal algorithm integrates the iterative FE analyses with virtual plane manipulation.

Findings
Case studies validate that the virtual plane manipulation coincides with the test well, and the proposed method has good compensation of practical locating distortion.

Research limitations/implications
The optimized rivet UDs may be set in a chaotic distribution, which may complicate the abundant riveting operations and the assembly appearance. Therefore, the use of automatic riveting systems can overcome the operational complexity, and the industrial design of rivet UD distribution will improve the assembly appearance.

Practical implications
The optimized UDs and assembly sequence are for assembly workers or automatic riveting systems.

Originality/value
The proposed method is the first to reduce the determinative locating distortion by a novel and efficient solid riveting process planning in detail, and the solid riveting process designed is conservative and accurate for practice.
Wall distance effect on heat transfer at high flow velocity
Authors: Kurowski Marcin , Szwaba Ryszard , Telega Janusz , Flaszynski Pawel , Tejero Fernando , Doerffer Piotr 
Published: November 2018

PurposeThis paper aims to present the results of experimental and numerical research on heat transfer distribution under the impinging jets at various distances from the wall and high jet velocity. This work is a part of the INNOLOT Program financed by National Centre for Research and Development.Design/methodology/approachThe air jets flow out from the common pipe and impinge on a surface which is cooled by them, and in this way, all together create a model of external cooling system of low-pressure gas turbine casing. Measurements were carried out for the arrangement of 26 in-line jets with orifice diameter of 0.9 mm. Heat transfer distribution was investigated for various Reynolds and Mach numbers. The cooled wall, made of transparent PMMA, was covered with a heater foil on which a layer of self-adhesive liquid crystal foil was placed. The jet-to-wall distance was set to h = from 4.5 to 6 d.FindingsThe influence of various Reynolds and Mach numbers on cooled flat plate and jet-to-wall distance in terms of heat transfer effectiveness is presented. Experimental results used for the computational fluid dynamics (CFD) model development, validation and comparison with numerical results are presented.Practical implicationsImpinging air jets is a commonly used technique to cool advanced turbines elements, as it produces large convection enhancing the local heat transfer, which is a critical issue in the development of aircraft engines.Originality/valueThe achieved results present experimental investigations carried out to study the heat transfer distribution between the orthogonally impinging jets from long round pipe and flat plate. Reynolds number based on the jet orifice exit conditions was varied between 2,500 and 4,000; meanwhile, for such Re, the flow velocity in jets was particularly very high, changing from M = 0.56 to M = 0.77. Such flow conditions combination, i.e. the low Reynolds number and very high flow velocity cannot be found in the existing literature.