bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simulated mechanical properties of finite-size graphene nanoribbons
Authors: Aparicio E , Tangarife E , Munoz F , Gonzalez R I , Valencia F J , Careglio C , Bringa E M 
Published: October 2020

Abstract
There are many simulation studies of mechanical properties of graphene nanoribbons (GNR), but there is a lack of agreement regarding elastic and plastic behavior. In this paper we aim to analyze mechanical properties of finite-size GNR, including elastic modulus and fracture, as a function of ribbon size. We present classical molecular dynamics simulations for three different empirical potentials which are often used for graphene simulations: AIREBO, REBO-scr and REAXFF. Ribbons with and without H-passivation at the borders are considered, and the effects of strain rate and different boundaries are also explored. We focus on zig-zag GNR, but also include some armchair GNR examples. Results are strongly dependent on the empirical potential employed. Elastic modulus under uniaxial tension can depend on ribbon size, unlike predictions from continuum-scale models and from some atomistic simulations, and fracture strain and progress vary significantly amongst the simulated potentials. Because of that, we have also carried out quasi-static ab-initio simulations for a selected size, and find that the fracture process is not sudden, instead the wave function changes from Blöch states to a strong interaction between localized waves, which decreases continuously with distance. All potentials show good agreement with DFT in the linear elastic regime, but only the REBO-scr potential shows reasonable agreement with DFT both in the nonlinear elastic and fracture regimes. This would allow more reliable simulations of GNRs and GNR-based nanostructures, to help interpreting experimental results and for future technological applications.
Three-dimensionality shapes the dynamics of cortical interconnected to hippocampal networks
Authors: Brofiga Martina , Pisano Marietta , Tedesco Mariateresa , Raiteri Roberto , Massobrio Paolo 
Published: October 2020

Abstract

Objective. The goal of this work is to develop and characterize an innovative experimental framework to design interconnected (i.e. modular) heterogeneous (cortical-hippocampal) neuronal cultures with a three-dimensional (3D) connectivity and to record their electrophysiological activity using micro-electrode arrays (MEAs). Approach. A two-compartment polymeric mask for the segregation of different neuronal populations (cortex and hippocampus) was coupled to the MEA surface. Glass microbeads were used as a scaffold to mimic the 3D brain micro-architecture. Main results. We built a fully functional heterogeneous 3D neuronal network. From an electrophysiological point of view, we found that the heterogeneity induces a global increase of the activity rate, while the 3D connectivity modulates the duration and the organization of the bursting activity. Significance. In vivo, studies of network dynamics and interactions between neuronal populations are often time-consuming, low-throughput, complex, and suffer from reproducibility. On the other hand, most of the commonly used in vitro brain models are too simplified and thus far from the in vivo situation. The achieved results demonstrate the feasibility to build a more realistic and controllable experimental in vitro model of interconnected brain regions on-a-chip whose applications may have impacts on the study of neurological disorders that impair the connectivity between brain areas (e.g. Parkinson disease).
Spatial variation in household consumption-based carbon emission inventories for 1200 Japanese cities
Authors: Kanemoto Keiichiro , Shigetomi Yosuke , Hoang Nguyen Tien , Okuoka Keijiro , Moran Daniel 
Published: October 2020

Abstract
Given that national pledges are likely insufficient to meet Paris greenhouse gas (GHG) reduction targets (Fawcett et al 2015 Science
350), increasingly actors at the city and state level are looking for options on how local government can contribute to reducing GHG emissions. For a typical city only one third to half of their carbon footprint (CF) is emitted within the jurisdiction, while the majority is embodied in goods and services flowing into the city. To support well-informed mitigation efforts, administrators need robust inventories of both direct emissions as well as the supply chain emissions. Here we construct household CF inventories for 1172 Japanese cities using detailed consumer expenditure data and a Japanese domestic multi-regional input-output (MRIO) model. We identify the consumption activities which city policymakers can target to reduce CF. We observe a strong concentration of household CF in a few cities in Japan: 40% of the total Japanese CF is driven by 143 cities. Understanding a city’s consumption-based CF of households in addition to its direct emissions exposes additional policy options for each citizen to contribute to achieving national goals.
Onset of action of inhaled glucocorticoids on bronchial and alveolar nitric oxide output
Authors: Karvonen Tuomas , Sepponen-Lavikko Anna , Holm Kati , Schultz Rüdiger , Moilanen Eeva , Lehtimäki Lauri 
Published: October 2020

AbstractFractional exhaled nitric oxide (FENO) is a marker of airway inflammation. Measuring FENO at multiple flow rates enables calculation of NO parameters: bronchial NO output (JawNO), bronchial wall (CawNO) and alveolar (CANO) NO concentrations, and bronchial diffusion factor of NO (DawNO). FENO is known to rapidly reduce after the commencement of inhaled corticosteroid (ICS) treatment. However, little is known on the effect of ICS on the other NO parameters. We assessed (1) the onset of action of ICS treatment on the NO parameters and (2) whether the changes in bronchial NO output are due to changes in bronchial wall NO concentration or diffusion factor. FENO and other NO parameters were measured at baseline and after 1, 3 and 7 d of treatment with inhaled fluticasone propionate 250μg b.i.d. in 23 allergic children with a history of asthma-like symptoms. There was a decrease inJawNO (from 680 (244/1791) (median (1st/3rd quartile)) to 357 (165/753) pl s−1,p< 0.001) and FENO50( from 13.8 (7.5/35) to 8.3 (5.36/17.0) ppb,p< 0.001) in 3 d from the first dose of ICS. Also,CawNO seemed to reduce after 3 d (from 171 (89/328) to 79 (54/157) ppb,p= 0.041), whileDawNO remained unchanged. Furthermore,CANO reduced during the 7 d treatment (from 3.0 (2.0/5.0) to 2.3 (1.9/2.6) ppb,p= 0.004). ICS treatment reduced FENO50andJawNO rapidly and the decline was caused by decreased bronchial wall NO concentration while bronchial NO diffusion factor remained unchanged. These findings suggest thatCawNO could be a more specific marker of airway inflammation and treatment response thanJawNO or FENO50, which are both determined also byDawNO that seems to be resistant to the treatment with ICS.
‘Luminescent carbon nanodots: Current prospects on synthesis, properties and sensing applications’
Authors: Kottam Nagaraju , S P Smrithi 
Published: October 2020

Abstract
‘Nanocarbon science’ ignited interest owing to its substantial scope in biomedicine, energy and environment-beneficial applications. Carbon dots (C-dots), a multi-faceted nanocarbon material, emerged as a homologue to graphene and henceforth geared extensive investigation both on its properties and applications. Eximious properties like excitation-wavelength tunable fluorescence emission, up-converted photoluminescence, photon-induced electron transfer, low cytotoxicity, chiroptical behavior, high chemical and photostability set the ground for astounding applications of carbon dots. Abundant availability of raw ‘green’ precursors complementary to other molecular/graphitic precursors make them environmentally benign, inexpensive and ultimately ‘nanomaterials of the current decade’. This review focuses on the synthesis of carbon dots not only from natural sources but also from other carbonaceous precursors and contemplates the inherent but controversial properties. We also aim to garner the attention of readers to the recent progress achieved by C-dots in one of its prestantious area of applications as nanosensors.
A theoretical model of a wave: an efflux bounce of a solution-particle
Authors: Nemaura T 
Published: October 2020

Abstract
A description of a wave as a bounce is developed. A wave that carries a mass is characterised by a bounce and the mass-spring-damper system. Furthermore, an analogy of a wave/bounce to the mass-spring-damper system is suggested. The efflux bounce considered is responsible for dispersion and is part of the drug transportation wave network in the patient’s blood plasma. A four-dimensional length of tugs (wave) describing the efflux bounce is modelled by a system of differential equations. A single equivalent fourth-order differential equation system is suggested to model the same wave. The two systems are inferred to share a unique characteristic equation. The theoretical models developed are used to infer on the characterisation of the wave comprising of media and boundary components. The media is found to be rigid

(

ω

I

=
0

h

−
1

)

and the boundary as deformable

(

ω

E

=
0.1166154

h

−
1

)

. A loaded structure-wave-particle analogy is proposed.
A Descriptive and Quantitative Immunohistochemical Study Demonstrating a Spectrum of Platelet Recruitment Patterns Across Pulmonary Infections Including COVID-19
Authors: McMullen Phillip D , Cho Joseph H , Miller Jonathan L , Husain Aliya N , Pytel Peter , Krausz Thomas 
Published: October 2020

Abstract

Objectives
Pulmonary platelet deposition and microangiopathy are increasingly recognized components of coronavirus disease 2019 (COVID-19) infection. Thrombosis is a known component of sepsis and disseminated intravascular coagulation. We sought to compare the level of platelet deposition in the pulmonary vasculature in cases of confirmed COVID-19 infection to other lung injuries and infections.

Methods
Immunohistochemistry was performed on 27 autopsy cases and 2 surgical pathology cases targeting CD61. Multiple cases of normal lung, diffuse alveolar damage, COVID-19, influenza, and bacterial and fungal infections, as well as one case of pulmonary emboli, were included. The levels of CD61 staining were compared quantitatively in the autopsy cases, and patterns of staining were described.

Results
Nearly all specimens exhibited an increase in CD61 staining relative to control lung tissue. The area of CD61 staining in COVID-19 infection was higher than influenza but still comparable to many other infectious diseases. Cases of aspiration pneumonia, Staphylococcus aureus infection, and blastomycosis exhibited the highest levels of CD61 staining.

Conclusions
Platelet deposition is a phenomenon common to many pulmonary insults. A spectrum of staining patterns was observed, suggestive of pathogen-specific mechanisms of platelet deposition. Further study into the mechanisms driving platelet deposition in pulmonary injuries and infections is warranted.
Patient outcomes following state-mandated opioid dose reductions
Authors: Hill Gabrielle , Hughes-Stricklett Alisa 
Published: October 2020

Abstract

Purpose
Maine Public Law Chapter 488 required that all opioid doses be reduced to below 100 morphine milligram equivalent (MME) by July 1, 2017, and VA Maine Healthcare System implemented policies consistent with the state law. The purpose of this study was to assess self-reported pain scores over 2 years and overall utilization of alternative healthcare services for veterans who were using opioid doses in excess of 100 MME prior to the implementation of policies consistent with Maine PL Chapter 488 in the VA Maine Healthcare System.

Methods
In this retrospective chart review, veterans were selected for inclusion if they were receiving chronic opioid therapy at the VA Maine Healthcare System of at least 100 MME daily in March 2016 according to the opioid therapy risk report (OTRR). Self-reported pain scores and use of alternative healthcare services were evaluated using VA Computerized Patient Record System (CPRS) data.

Results
Of the 147 patients evaluated per protocol, 75 patients (51%) did not have a clinically significant change in self-reported pain scores, and the self-reported pain scores of 29 patients (20%) improved from March 2016 to March 2018 (P = 0.054).

Conclusion
We found that mandatory dose reductions of chronic opioid medications did not result in a clinically or statistically significant worsening of self-reported pain scores. Our study suggests that opioid dose reductions may not negatively impact a patient’s functioning and pain intensity and calls into question the use of long-term opioid therapy for pain given the safety implications.
Recent advances in network-based methods for disease gene prediction
Authors: Ata Sezin Kircali , Wu Min , Fang Yuan , Ou-Yang Le , Kwoh Chee Keong , Li Xiao-Li 
Published: October 2020

AbstractDisease–gene association through genome-wide association study (GWAS) is an arduous task for researchers. Investigating single nucleotide polymorphisms that correlate with specific diseases needs statistical analysis of associations. Considering the huge number of possible mutations, in addition to its high cost, another important drawback of GWAS analysis is the large number of false positives. Thus, researchers search for more evidence to cross-check their results through different sources. To provide the researchers with alternative and complementary low-cost disease–gene association evidence, computational approaches come into play. Since molecular networks are able to capture complex interplay among molecules in diseases, they become one of the most extensively used data for disease–gene association prediction. In this survey, we aim to provide a comprehensive and up-to-date review of network-based methods for disease gene prediction. We also conduct an empirical analysis on 14 state-of-the-art methods. To summarize, we first elucidate the task definition for disease gene prediction. Secondly, we categorize existing network-based efforts into network diffusion methods, traditional machine learning methods with handcrafted graph features and graph representation learning methods. Thirdly, an empirical analysis is conducted to evaluate the performance of the selected methods across seven diseases. We also provide distinguishing findings about the discussed methods based on our empirical analysis. Finally, we highlight potential research directions for future studies on disease gene prediction.
Computational prediction of species-specific yeast DNA replication origin via iterative feature representation
Authors: Manavalan Balachandran , Basith Shaherin , Shin Tae Hwan , Lee Gwang 
Published: October 2020

Abstract
Deoxyribonucleic acid replication is one of the most crucial tasks taking place in the cell, and it has to be precisely regulated. This process is initiated in the replication origins (ORIs), and thus it is essential to identify such sites for a deeper understanding of the cellular processes and functions related to the regulation of gene expression. Considering the important tasks performed by ORIs, several experimental and computational approaches have been developed in the prediction of such sites. However, existing computational predictors for ORIs have certain curbs, such as building only single-feature encoding models, limited systematic feature engineering efforts and failure to validate model robustness. Hence, we developed a novel species-specific yeast predictor called yORIpred that accurately identify ORIs in the yeast genomes. To develop yORIpred, we first constructed optimal 40 baseline models by exploring eight different sequence-based encodings and five different machine learning classifiers. Subsequently, the predicted probability of 40 models was considered as the novel feature vector and carried out iterative feature learning approach independently using five different classifiers. Our systematic analysis revealed that the feature representation learned by the support vector machine algorithm (yORIpred) could well discriminate the distribution characteristics between ORIs and non-ORIs when compared with the other four algorithms. Comprehensive benchmarking experiments showed that yORIpred achieved superior and stable performance when compared with the existing predictors on the same training datasets. Furthermore, independent evaluation showcased the best and accurate performance of yORIpred thus underscoring the significance of iterative feature representation. To facilitate the users in obtaining their desired results without undergoing any mathematical, statistical or computational hassles, we developed a web server for the yORIpred predictor, which is available at: http://thegleelab.org/yORIpred.
SSMD: a semi-supervised approach for a robust cell type identification and deconvolution of mouse transcriptomics data
Authors: Lu Xiaoyu , Tu Szu-Wei , Chang Wennan , Wan Changlin , Wang Jiashi , Zang Yong , Ramdas Baskar , Kapur Reuben , Lu Xiongbin , Cao Sha , Zhang Chi 
Published: October 2020

Abstract
Deconvolution of mouse transcriptomic data is challenged by the fact that mouse models carry various genetic and physiological perturbations, making it questionable to assume fixed cell types and cell type marker genes for different data set scenarios. We developed a Semi-Supervised Mouse data Deconvolution (SSMD) method to study the mouse tissue microenvironment. SSMD is featured by (i) a novel nonparametric method to discover data set-specific cell type signature genes; (ii) a community detection approach for fixing cell types and their marker genes; (iii) a constrained matrix decomposition method to solve cell type relative proportions that is robust to diverse experimental platforms. In summary, SSMD addressed several key challenges in the deconvolution of mouse tissue data, including: (i) varied cell types and marker genes caused by highly divergent genotypic and phenotypic conditions of mouse experiment; (ii) diverse experimental platforms of mouse transcriptomics data; (iii) small sample size and limited training data source and (iv) capable to estimate the proportion of 35 cell types in blood, inflammatory, central nervous or hematopoietic systems. In silico and experimental validation of SSMD demonstrated its high sensitivity and accuracy in identifying (sub) cell types and predicting cell proportions comparing with state-of-the-arts methods. A user-friendly R package and a web server of SSMD are released via https://github.com/xiaoyulu95/SSMD.
GalaxyCloudRunner: enhancing scalable computing for Galaxy
Authors: Goonasekera Nuwan , Mahmoud Alexandru , Chilton John , Afgan Enis 
Published: October 2020

AbstractSummaryThe existence of more than 100 public Galaxy servers with service quotas is indicative of the need for an increased availability of compute resources for Galaxy to use. The GalaxyCloudRunner enables a Galaxy server to easily expand its available compute capacity by sending user jobs to cloud resources. User jobs are routed to the acquired resources based on a set of configurable rules and the resources can be dynamically acquired from any of four popular cloud providers (AWS, Azure, GCP or OpenStack) in an automated fashion.Availability and implementationGalaxyCloudRunner is implemented in Python and leverages Docker containers. The source code is MIT licensed and available at https://github.com/cloudve/galaxycloudrunner. The documentation is available at http://gcr.cloudve.org/.
Abnormal Behavior and Cortical Connectivity Deficits in Mice Lacking Usp9x
Authors: Kasherman Maria A , Currey Laura , Kurniawan Nyoman D , Zalucki Oressia , Vega Michelle Sanchez , Jolly Lachlan A , Burne Thomas H J , Wood Stephen A , Piper Michael 
Published: October 2020

Abstract
Genetic association studies have identified many factors associated with neurodevelopmental disorders such as autism spectrum disorder (ASD). However, the way these genes shape neuroanatomical structure and connectivity is poorly understood. Recent research has focused on proteins that act as points of convergence for multiple factors, as these may provide greater insight into understanding the biology of neurodevelopmental disorders. USP9X, a deubiquitylating enzyme that regulates the stability of many ASD-related proteins, is one such point of convergence. Loss of function variants in human USP9X lead to brain malformations, which manifest as a neurodevelopmental syndrome that frequently includes ASD, but the underlying structural and connectomic abnormalities giving rise to patient symptoms is unknown. Here, we analyzed forebrain-specific Usp9x knockout mice (Usp9x−/y) to address this knowledge gap. Usp9x−/y mice displayed abnormal communication and social interaction behaviors. Moreover, the absence of Usp9x culminated in reductions to the size of multiple brain regions. Diffusion tensor magnetic resonance imaging revealed deficits in all three major forebrain commissures, as well as long-range hypoconnectivity between cortical and subcortical regions. These data identify USP9X as a key regulator of brain formation and function, and provide insights into the neurodevelopmental syndrome arising as a consequence of USP9X mutations in patients.
Early initiation of PD therapy in elderly patients is associated with increased risk of death
Authors: Peng Yuan , Ye Hongjian , Yi Chunyan , Xiao Xi , Huang Xuan , Liu Ruihua , Diao Xiangwen , Mao Haiping , Yu Xueqing , Yang Xiao 
Published: October 2020

Abstract

Background
The effect of early initiation of dialysis on outcomes of patients with end-stage renal disease (ESRD) remains controversial. We conducted this study to investigate the association between the timing of peritoneal dialysis (PD) initiation and mortality in different age groups.

Methods
In this single-centre cohort study, incident patients receiving PD from 1 January 2006 to 31 December 2016 were enrolled. Patients were categorized into three groups according to the estimated glomerular filtration rate (eGFR) at the initiation of PD, with early, mid and late initiation of PD defined as eGFR ≥7.5, 5–7.5 and &lt;5 mL/min/1.73 m2, respectively.

Results
A total of 2133 incident patients receiving PD were enrolled with a mean age of 47.1 years, 59.6% male and 25.3% with diabetes, of whom 1803 were young (age &lt;65 years) and 330 were elderly (age ≥65 years). After multivariable adjustment, the overall and cardiovascular (CV) mortality risks for young patients receiving PD were not significantly different between these three groups. However, for elderly patients, early initiation of PD therapy was associated with increased risks of all-cause {hazard ratio [HR} 1.54 [95% confidence interval (CI) 1.06–2.25]} and CV [HR 2.07 (95% CI 1.24–3.48)] mortality compared with late initiation of PD, while no significant difference was observed in overall or CV mortality between the mid- and late-start groups.

Conclusions
No significant difference in mortality risk was found among the three levels of eGFR at PD therapy initiation in young patients, while early initiation of PD was associated with a higher risk of overall and CV mortality among elderly patients.