bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diagnosis value of aberrantly expressed microRNA profiles in lung squamous cell carcinoma: a study based on the Cancer Genome Atlas
Authors: Yang Sheng , Sui Jing , Liang Geyu 
Published: November 2017

Background
Lung cancer is considered as one of the most frequent and deadly cancers with high mortality all around the world. It is critical to find new biomarkers for early diagnosis of lung cancer, especially lung squamous cell carcinoma (LUSC). The Cancer Genome Atlas (TCGA) is a database which provides both cancer and clinical information. This study is a comprehensive analysis of a novel diagnostic biomarker for LUSC, based on TCGA.

Methods and Results
The present study investigated LUSC-specific key microRNAs (miRNAs) from large-scale samples in TCGA. According to exclusion criteria and inclusion criteria, the expression profiles of miRNAs with related clinical information of 332 LUSC patients were obtained. Most aberrantly expressed miRNAs were identified between tumor and normal samples. Forty-two LUSC-specific intersection miRNAs (fold change >2, p < 0.05) were obtained by an integrative computational method, among them six miRNAs were found to be aberrantly expressed concerning characteristics of patients (gender, lymphatic metastasis, patient outcome assessment) through Student t-test. Five miRNAs correlated with overall survival (log-rank p < 0.05) were obtained through the univariate Cox proportional hazards regression model and Mantel–Haenszel test. Then, five miRNAs were randomly selected to validate the expression in 47 LUSC patient tissues using quantitative real-time polymerase chain reaction. The results showed that the test findings were consistent with the TCGA findings. Also, the diagnostic value of the specific key miRNAs was determined by areas under receiver operating characteristic curves. Finally, 577 interaction mRNAs as the targets of 42 LUSC-specific intersection miRNAs were selected for further bioinformatics analysis.

Conclusion
This study indicates that this novel microRNA expression signature may be a useful biomarker of the diagnosis for LUSC patients, based on bioinformatics analysis.
Amplification of Earthquake Ground Motions in Washington, DC, and Implications for Hazard Assessments in Central and Eastern North America
Authors: Pratt Thomas L. , Horton J. Wright , Muñoz Jessica , Hough Susan E. , Chapman Martin C. , Olgun C. Guney 
Published: November 2017

AbstractThe extent of damage in Washington, DC, from the 2011 Mw 5.8 Mineral, VA, earthquake was surprising for an epicenter 130 km away; U.S. Geological Survey “Did‐You‐Feel‐It” reports suggest that Atlantic Coastal Plain and other unconsolidated sediments amplified ground motions in the city. We measure this amplification relative to bedrock sites using earthquake signals recorded on a temporary seismometer array. The spectral ratios show strong amplification in the 0.7 to 4 Hz frequency range for sites on sediments. This range overlaps with resonant frequencies of buildings in the city as inferred from their heights, suggesting amplification at frequencies to which many buildings are vulnerable to damage. Our results emphasize that local amplification can raise moderate ground motions to damaging levels in stable continental regions, where low attenuation extends shaking levels over wide areas and unconsolidated deposits on crystalline metamorphic or igneous bedrock can result in strong contrasts in near‐surface material properties.
Identifying Flow Networks in a Karstified Aquifer by Application of the Cellular Automata‐Based Deterministic Inversion Method (Lez Aquifer, France)
Authors: Fischer P. , Jardani A. , Wang X. , Jourde H. , Lecoq N. 
Published: November 2017

AbstractThe distributed modeling of flow paths within karstic and fractured fields remains a complex task because of the high dependence of the hydraulic responses to the relative locations between observational boreholes and interconnected fractures and karstic conduits that control the main flow of the hydrosystem. The inverse problem in a distributed model is one alternative approach to interpret the hydraulic test data by mapping the karstic networks and fractured areas. In this work, we developed a Bayesian inversion approach, the Cellular Automata‐based Deterministic Inversion (CADI) algorithm to infer the spatial distribution of hydraulic properties in a structurally constrained model. This method distributes hydraulic properties along linear structures (i.e., flow conduits) and iteratively modifies the structural geometry of this conduit network to progressively match the observed hydraulic data to the modeled ones. As a result, this method produces a conductivity model that is composed of a discrete conduit network embedded in the background matrix, capable of producing the same flow behavior as the investigated hydrologic system. The method is applied to invert a set of multiborehole hydraulic tests collected from a hydraulic tomography experiment conducted at the Terrieu field site in the Lez aquifer, Southern France. The emergent model shows a high consistency to field observation of hydraulic connections between boreholes. Furthermore, it provides a geologically realistic pattern of flow conduits. This method is therefore of considerable value toward an enhanced distributed modeling of the fractured and karstified aquifers.
Nanomaterial‐Enabled Wearable Sensors for Healthcare
Authors: Yao Shanshan , Swetha Puchakayala , Zhu Yong 
Published: November 2017

AbstractHighly sensitive wearable sensors that can be conformably attached to human skin or integrated with textiles to monitor the physiological parameters of human body or the surrounding environment have garnered tremendous interest. Owing to the large surface area and outstanding material properties, nanomaterials are promising building blocks for wearable sensors. Recent advances in the nanomaterial‐enabled wearable sensors including temperature, electrophysiological, strain, tactile, electrochemical, and environmental sensors are presented in this review. Integration of multiple sensors for multimodal sensing and integration with other components into wearable systems are summarized. Representative applications of nanomaterial‐enabled wearable sensors for healthcare, including continuous health monitoring, daily and sports activity tracking, and multifunctional electronic skin are highlighted. Finally, challenges, opportunities, and future perspectives in the field of nanomaterial‐enabled wearable sensors are discussed.
Toward High Uniformity of Photoresponse Broadband Hybrid Organic–Inorganic Photodiode Based on PVP‐Modified Perovskite
Authors: Zhao Feiyu , Xu Kun , Luo Xiao , Liang Yuanlong , Peng Yingquan , Lu Feiping 
Published: November 2017

AbstractBroadband photodiode based on Si/perovskite structure that combines the advantages of both silicon and perovskite is presented in this paper. This study addresses the issue of the absent of ultraviolet absorption of silicon and the near‐infrared absorption of perovskite. More significantly, the polyvinyl pyrrolidone (PVP) modification process on the perovskite film shows efficiency on morphology and crystallizing control that are important for high uniformity of responsivity and reproducibility. The result shows high spectral uniformity of responsivity (uSR = 0.85) on a wide spectrum ranging from 405 to 808 nm and the average of deviation of reproducibility is only 2.1%. Fast response time (645 µs), good on–off switching performance, and high photosensitivity (Ion/Ioff = 1322) of the as‐fabricated device are also achieved in this work. This research indicates that the high‐performance broadband photodiode can be realized by the novel organic–inorganic structure and PVP modification without compromising any of its performance.
Self‐Assembled Graphene‐Based Architectures and Their Applications
Authors: Yuan Zhongke , Xiao Xiaofen , Li Jing , Zhao Zhe , Yu Dingshan , Li Quan 
Published: November 2017

AbstractDue to unique planar structures and remarkable thermal, electronic, and mechanical properties, chemically modified graphenes (CMGs) such as graphene oxides, reduced graphene oxides, and the related derivatives are recognized as the attractive building blocks for “bottom‐up” nanotechnology, while self‐assembly of CMGs has emerged as one of the most promising approaches to construct advanced functional materials/systems based on graphene. By virtue of a variety of noncovalent forces like hydrogen bonding, van der Waals interaction, metal‐to‐ligand bonds, electrostatic attraction, hydrophobic–hydrophilic interactions, and π–π interactions, the CMGs bearing various functional groups are highly desirable for the assemblies with themselves and a variety of organic and/or inorganic species which can yield various hierarchical nanostructures and macroscopic composites endowed with unique structures, properties, and functions for widespread technological applications such as electronics, optoelectronics, electrocatalysis/photocatalysis, environment, and energy storage and conversion. In this review, significant recent advances concerning the self‐assembly of CMGs are summarized, and the broad applications of self‐assembled graphene‐based materials as well as some future opportunities and challenges in this vibrant area are elucidated.
Modelling of solid‐state fermentation over wide operational range for application in process optimization
Authors: Fonseca Rafael F. , Melo Caio C. B. , Sanches Beatriz B. C. P. , Bertucci‐Neto Victor , Farinas Cristiane S. , Kwong Wu H. 
Published: November 2017

AbstractThe major drawbacks in large‐scale solid‐state fermentation processes are related to difficulty in controlling the medium temperature and moisture content, which are variables that directly affect microbial growth and product formation. Several mathematical models have been developed to describe these effects, although none has simultaneously considered distinct growth phases, growth restrictions caused by large temperature variations at several distinct moisture content conditions, and product formation pathways. In this manner, the objectives of this paper were to develop a mathematical model to represent the process under different operational conditions and a model‐based optimization procedure to investigate the effects of varying temperature profiles to maximize a (hemi) cellulolytic enzyme production during cultivation of Aspergillus niger under solid state fermentation. The proposed model correlates fungal growth with the CO2 production rates and with enzymatic production by the Luedeking‐Piret function. It was developed with data acquired in a laboratory‐scale column‐type bioreactor in controlled conditions of aeration, temperature, and inlet air relative humidity. The developed model accurately predicted the respiration profile responses at all temperatures, under the most productive moisture content conditions. Incubation of the culture with the optimized temperature profile improved the enzymatic production, compared to the estimated optimum static temperature. These findings demonstrate the usefulness of this model for the optimization of larger‐scale SSF processes.
Quantifying the effects of ecological constraints on trait expression using novel trait‐gradient analysis parameters
Authors: Ottaviani Gianluigi , Tsakalos James L. , Keppel Gunnar , Mucina Ladislav 
Published: November 2017

AbstractComplex processes related to biotic and abiotic forces can impose limitations to assembly and composition of plant communities. Quantifying the effects of these constraints on plant functional traits across environmental gradients, and among communities, remains challenging. We define ecological constraint (Ci) as the combined, limiting effect of biotic interactions and environmental filtering on trait expression (i.e., the mean value and range of functional traits). Here, we propose a set of novel parameters to quantify this constraint by extending the trait‐gradient analysis (TGA) methodology. The key parameter is ecological constraint, which is dimensionless and can be measured at various scales, for example, on population and community levels. It facilitates comparing the effects of ecological constraints on trait expressions across environmental gradients, as well as within and among communities. We illustrate the implementation of the proposed parameters using the bark thickness of 14 woody species along an aridity gradient on granite outcrops in southwestern Australia. We found a positive correlation between increasing environmental stress and strength of ecological constraint on bark thickness expression. Also, plants from more stressful habitats (shrublands on shallow soils and in sun‐exposed locations) displayed higher ecological constraint for bark thickness than plants in more benign habitats (woodlands on deep soils and in sheltered locations). The relative ease of calculation and dimensionless nature of Ci allow it to be readily implemented at various scales and make it widely applicable. It therefore has the potential to advance the mechanistic understanding of the ecological processes shaping trait expression. Some future applications of the new parameters could be investigating the patterns of ecological constraints (1) among communities from different regions, (2) on different traits across similar environmental gradients, and (3) for the same trait across different gradient types.
Gut microbiota composition is associated with environmental landscape in honey bees
Authors: Jones Julia C , Fruciano Carmelo , Hildebrand Falk , Al Toufalilia Hasan , Balfour Nicholas J , Bork Peer , Engel Philipp , Ratnieks Francis LW , Hughes William OH 
Published: November 2017

AbstractThere is growing recognition that the gut microbial community regulates a wide variety of important functions in its animal hosts, including host health. However, the complex interactions between gut microbes and environment are still unclear. Honey bees are ecologically and economically important pollinators that host a core gut microbial community that is thought to be constant across populations. Here, we examined whether the composition of the gut microbial community of honey bees is affected by the environmental landscape the bees are exposed to. We placed honey bee colonies reared under identical conditions in two main landscape types for 6 weeks: either oilseed rape farmland or agricultural farmland distant to fields of flowering oilseed rape. The gut bacterial communities of adult bees from the colonies were then characterized and compared based on amplicon sequencing of the 16S rRNA gene. While previous studies have delineated a characteristic core set of bacteria inhabiting the honey bee gut, our results suggest that the broad environment that bees are exposed to has some influence on the relative abundance of some members of that microbial community. This includes known dominant taxa thought to have functions in nutrition and health. Our results provide evidence for an influence of landscape exposure on honey bee microbial community and highlight the potential effect of exposure to different environmental parameters, such as forage type and neonicotinoid pesticides, on key honey bee gut bacteria. This work emphasizes the complexity of the relationship between the host, its gut bacteria, and the environment and identifies target microbial taxa for functional analyses.
Application and Properties of Nano‐sized RDX in CMDB Propellant with Low Solid Content
Authors: Liu Jie , Ke Xiang , Xiao Lei , Hao Gazi , Rong Yuanbo , Jin Chengsu , Jiang Wei , Li Fengsheng 
Published: November 2017

AbstractComposite modified double‐base (CMDB) propellant, benefitting from the outstanding performances of high energy and low signature, has attracted increasing focus in the past decade. To improve the integrative performance, such as enhancing the mechanical property and decreasing the sensitivity, CMDB propellant with low solid content containing nano‐sized RDX has been prepared. The microstructure, mechanical properties, sensitivity and combustion performance of the prepared propellant are studied. Results have shown that the interface of the CMDB propellant contained nano‐sized RDX (N‐CMDB) is more compact and the internal defects are less than those of the CMDB propellant with micro‐sized RDX (M‐CMDB). Compared with the maximum tensile strength (σm) and the corresponding elongation at maximum tensile strength (ϵm) of M‐CMDB, the σm values of N‐CMDB are improved by 37.4 % at +50 °C, 27.5 % at +20 °C and 26.7 % at −40 °C, and the ϵm values are increased by 16.1 %, 19.4 % and 39.6 %, separately. Moreover, the friction and impact sensitivities of N‐CMDB propellant are decreased by 51.3 % and 50.4 %, respectively. In the range of 8–18 MPa, the combustion performance of N‐MCDB propellant has been demonstrated more attractive with higher burning rate coefficient (8.692→10.950) and lower pressure exponent (0.384→0.299). All these results lead us to believe that the usage of nano‐sized explosives will contribute to improve the comprehensive performance of CMDB propellants and promote their application in weapon system.
Die hypertrophe Kardiomyopathie
Authors: Kühl Constantin , Frey Norbert 
Published: November 2017

Zusammenfassung
Die hypertrophe Kardiomyopathie (HCM) ist die häufigste Kardiomyopathie mit mendelschem autosomal-dominanten Erbgang. Die Folgen der ausgeprägten Hypertrophie des Herzmuskels, in Verbindung mit (HOCM) oder ohne (HNCM) Obstruktion des linksventrikulären Ausflusstraktes reichen von benignen klinischen Verläufen bis hin zu schwersten Verläufen der Herzinsuffizienz und des plötzlichen Herztodes. Die neuen Leitlinien der Europäischen Gesellschaft für Kardiologie, veröffentlicht in 2014, fassen die aktuelle Evidenz beinahe aller Aspekte der Versorgung von Patienten zusammen. Erstmals werden hier klare Empfehlungen zum Vorgehen bei der genetischen Diagnostik ausgesprochen. Die genetische Testung unter Verwendung der Hochdurchsatzsequenzierung wird aktuell kontrovers und emotional diskutiert, könnte aber künftig das Verständnis der HCM und damit möglicherweise auch die Versorgung der Patienten mit HCM verbessern. Aus der Grundlagenforschung entspringen zudem neue translationale Ansätze, die Anlass zur Hoffnung geben, in der Zukunft bei HCM neue und gezielte Therapien (z. B. Gentherapie) anbieten zu können.
Identifying Patterns in Complex Field Data
Authors: White Andrew J. , Kleinböhl Dieter , Lang Thomas , Hamm Alfons O. , Gerlach Alexander L. , Alpers Georg W. 
Published: November 2017

Abstract. Ambulatory assessment methods are well suited to examine how patients with panic disorder and agoraphobia (PD/A) undertake situational exposure. But under complex field conditions of a complex treatment protocol, the variability of data can be so high that conventional analytic approaches based on group averages inadequately describe individual variability. To understand how fear responses change throughout exposure, we aimed to demonstrate the incremental value of sorting HR responses (an index of fear) prior to applying averaging procedures. As part of their panic treatment, 85 patients with PD/A completed a total of 233 bus exposure exercises. Heart rate (HR), global positioning system (GPS) location, and self-report data were collected. Patients were randomized to one of two active treatment conditions (standard exposure or fear-augmented exposure) and completed multiple exposures in four consecutive exposure sessions. We used latent class cluster analysis (CA) to cluster heart rate (HR) responses collected at the start of bus exposure exercises (5 min long, centered on bus boarding). Intra-individual patterns of assignment across exposure repetitions were examined to explore the relative influence of individual and situational factors on HR responses. The association between response types and panic disorder symptoms was determined by examining how clusters were related to self-reported anxiety, concordance between HR and self-report measures, and bodily symptom tolerance. These analyses were contrasted with a conventional analysis based on averages across experimental conditions. HR responses were sorted according to form and level criteria and yielded nine clusters, seven of which were interpretable. Cluster assignment was not stable across sessions or treatment condition. Clusters characterized by a low absolute HR level that slowly decayed corresponded with low self-reported anxiety and greater self-rated tolerance of bodily symptoms. Inconsistent individual factors influenced HR responses less than situational factors. Applying clustering can help to extend the conventional analysis of highly variable data collected in the field. We discuss the merits of this approach and reasons for the non-stereotypical pattern of cluster assignment across exposures.
Sensitivity analysis of coupled processes and parameters on the performance of enhanced geothermal systems
Authors: Pandey S. N. , Vishal Vikram 
Published: November 2017

Abstract3-D modeling of coupled thermo-hydro-mechanical (THM) processes in enhanced geothermal systems using the control volume finite element code was done. In a first, a comparative analysis on the effects of coupled processes, operational parameters and reservoir parameters on heat extraction was conducted. We found that significant temperature drop and fluid overpressure occurred inside the reservoirs/fracture that affected the transport behavior of the fracture. The spatio-temporal variations of fracture aperture greatly impacted the thermal drawdown and consequently the net energy output. The results showed that maximum aperture evolution occurred near the injection zone instead of the production zone. Opening of the fracture reduced the injection pressure required to circulate a fixed mass of water. The thermal breakthrough and heat extraction strongly depend on the injection mass flow rate, well distances, reservoir permeability and geothermal gradients. High permeability caused higher water loss, leading to reduced heat extraction. From the results of TH vs THM process simulations, we conclude that appropriate coupling is vital and can impact the estimates of net heat extraction. This study can help in identifying the critical operational parameters, and process optimization for enhanced energy extraction from a geothermal system.
In vivo evidence for homo- and heterodimeric interactions of Arabidopsis thaliana dehydrins AtCOR47, AtERD10, and AtRAB18
Authors: Hernández-Sánchez Itzell E. , Maruri-López Israel , Graether Steffen P. , Jiménez-Bremont Juan F. 
Published: November 2017

AbstractDehydrins (DHNs) are intrinsically disordered proteins that play central roles in plant abiotic stress responses; however, how they work remains unclear. Herein, we report the in planta subcellular localization of Arabidopsis thaliana DHNs AtCOR47, AtERD10, and AtRAB18 through GFP translational fusions. To explore the dimerization ability of the Arabidopsis acidic DHNs AtCOR47 and AtERD10, we conducted an in planta DHN binding assay using the Bimolecular Fluorescence Complementation (BiFC) technique. Our analyses revealed homodimeric interactions for AtCOR47 and AtERD10; interestingly, heterodimeric associations also occurred with these DHNs, and these interactions were observed in the cytosol of tobacco cells. Furthermore, we evaluated whether Arabidopsis basic DHNs, such as AtRAB18, could also interact with itself and/or with AtCOR47 and AtERD10 in the BiFC system. Our data revealed homodimeric RAB18 complexes in the nucleus and cytosol, while heterodimeric associations between AtRAB18 and acidic DHNs occurred only in the cytosol. Finally, we demonstrated the presence of heterodimeric complexes among Arabidopsis AtCOR47, AtERD10, and AtRAB18 DHNs with their acidic ortholog the OpsDHN1 from Opuntia streptacantha; these heterodimeric interactions showed different subcellular distributions. Our results guide DHN research toward a new scenario where DHN/DHN oligomerization could be explored as a part of their molecular mechanism.