bluuebunny/crossref_metadata_2025_split huggingface dataset:
Combining statistical and neural network approaches to derive energy functions for completely flexible protein backbone design
Authors: Huang Bin , Xu Yang , Liu Haiyan 
Published: June 2019

AbstractA designable protein backbone is one for which amino acid sequences that stably fold into it exist. To design such backbones, a general method is much needed for continuous sampling and optimization in the backbone conformational space without specific amino acid sequence information. The energy functions driving such sampling and optimization must faithfully recapitulate the characteristically coupled distributions of multiplexes of local and non-local conformational variables in designable backbones. It is also desired that the energy surfaces are continuous and smooth, with easily computable gradients. We combine statistical and neural network (NN) approaches to derive a model named SCUBA, standing for Side-Chain-Unspecialized-Backbone-Arrangement. In this approach, high-dimensional statistical energy surfaces learned from known protein structures are analytically represented as NNs. SCUBA is composed as a sum of NN terms describing local and non-local conformational energies, each NN term derived by first estimating the statistical energies in the corresponding multi-variable space via neighbor-counting (NC) with adaptive cutoffs, and then training the NN with the NC-estimated energies. To determine the relative weights of different energy terms, SCUBA-driven stochastic dynamics (SD) simulations of natural proteins are considered. As initial computational tests of SCUBA, we apply SD simulated annealing to automatically optimize artificially constructed polypeptide backbones of different fold classes. For a majority of the resulting backbones, structurally matching native backbones can be found with Dali Z-scores above 6 and less than 2 Å displacements of main chain atoms in aligned secondary structures. The results suggest that SCUBA-driven sampling and optimization can be a general tool for protein backbone design with complete conformational flexibility. In addition, the NC-NN approach can be generally applied to develop continuous, noise-filtered multi-variable statistical models from structural data.Linux executables to setup and run SCUBA SD simulations are publicly available (http://biocomp.ustc.edu.cn/servers/download_scuba.php). Interested readers may contact the authors for source code availability.
Connexin 43 impacts the chick premigratory cranial neural crest cell population without affecting the neural crest cell epithelial-to-mesenchymal transition
Authors: Jourdeuil Karyn , Taneyhill Lisa A. 
Published: June 2019

ABSTRACTGap junctions are intercellular channels that allow for the diffusion of small ions and solutes between coupled cells. Connexin 43 (Cx43), also known as Gap Junction Protein α1, is the most broadly expressed gap junction protein in vertebrate development. Cx43 is strongly expressed in premigratory cranial neural crest cells and is maintained throughout the neural crest cell epithelial-to-mesenchymal transition (EMT), but its function in these cells is not known. To this end, we have used a combination ofin vivoandex vivolive imaging with confocal microscopy, immunohistochemistry, and functional assays to assess gap junction formation, and Cx43 function, in chick premigratory cranial neural crest cells. Our results demonstrate that gap junctions exist between chick premigratory and migratory cranial neural crest cells, with Cx43 depletion inhibiting the function of gap junctions. While a reduction in Cx43 levels just prior to neural crest cell EMT did not affect EMT and subsequent emigration of neural crest cells from the neural tube, the size of the premigratory neural crest cell domain was decreased in the absence of any changes in cell proliferation or death. Collectively, these data identify a role for Cx43 within the chick premigratory cranial neural crest cell population prior to EMT and migration.
Differential expression of cyclins mRNA in neural tissues of BoHV-1- and BoHV-5- infected cattle
Authors: Marin Maia , Burucúa Mercedes , Rensetti Daniel , Rosales Juan José , Odeón Anselmo , Pérez Sandra 
Published: June 2019

AbstractIntroductionBovine alphaherpesvirus types 1 (BoHV-1) and 5 (BoHV-5) are closely related alphaherpesviruses. BoHV-5 causes non-suppurative meningoencephalitis in calves. BoHV-1 is associated with several syndromes and, occasionally, can cause encephalitis. Although both viruses are neurotropic and they share similar biological properties, it is unknown why these alphaherpesviruses differ in their ability to cause neurological disease.Materials and MethodsNeural tissue samples were collected from BoHV-1- and BoHV-5-intranasally inoculated calves during acute infection, latency and reactivation. The levels of cyclins mRNA expression in neural tissue from calves infected with BoHV-1 or BoHV-5 were analyzed by qRT-PCR. Data were analyzed by Relative Expression Software Tool (REST).ResultsStriking differences in the levels of cyclins mRNA were observed between uninfected and infected tissues, particularly in trigeminal ganglion (TG). During acute infection, higher levels of cyclin A2, E1 and B1 were observed in BoHV-1 and BoHV-5-infected TG compared with uninfected TG. mRNA levels of cyclins A2 and E1 were downregulated in olfactory cortex. During latent infection with BoHV-1 and BoHV-5, cyclin A2 and E1 were downregulated in olfactory cortex and cervical medulla whereas cyclin B1 was upregulated in BoHV-1-infected olfactory and frontal cortex and in cervical medulla after BoHV-5 infection. A marked increase of cyclins A2 and E1mRNA levels was detected in TG of BoHV-5-latently-infected cattle. Unlike in uninfected TG, in BoHV-1 and BoHV-5-infected TG, cyclin B1expression was detectable. During reactivation, the levels of cyclin A2, B1 and E1 mRNA increased in TG. The expression levels of cyclins in TG during BoHV-5 latency suggest that these viruses utilize different strategies to persist in the host.ConclusionBovine alphaherpesviruses neuropathogenicity might be influenced by the differential control of cell cycle components by these herpesviruses. This is the first report on BoHV-5 modulation of cyclins expression in neural tissues from its natural host.
Comparison of Rosetta flexible-backbone computational protein design methods on binding interactions
Authors: Loshbaugh Amanda L. , Kortemme Tanja 
Published: June 2019

ABSTRACTComputational design of binding sites in proteins remains difficult, in part due to limitations in our current ability to sample backbone conformations that enable precise and accurate geometric positioning of side chains during sequence design. Here we present a benchmark framework for comparison between flexible-backbone design methods applied to binding interactions. We quantify the ability of different flexible backbone design methods in the widely used protein design software Rosetta to recapitulate observed protein sequence profiles assumed to represent functional protein/protein and protein/small molecule binding interactions. The CoupledMoves method, which combines backbone flexibility and sequence exploration into a single acceptance step during the sampling trajectory, better recapitulates observed sequence profiles than the BackrubEnsemble and FastDesign methods, which separate backbone flexibility and sequence design into separate acceptance steps during the sampling trajectory. Flexible-backbone design with the CoupledMoves method is a powerful strategy for reducing sequence space to generate targeted libraries for experimental screening and selection.
Coupling Wright-Fisher and coalescent dynamics for realistic simulation of population-scale datasets
Authors: Nelson Dominic , Kelleher Jerome , Ragsdale Aaron P. , McVean Gil , Gravel Simon 
Published: June 2019

1AbstractCoalescent simulations are widely used to examine the effects of evolution and demographic history on the genetic makeup of populations. Thanks to recent progress in algorithms and data structures, simulators such as the widely-usedmsprime[1] now provide genome-wide simulations for millions of individuals. However, this software relies on classic coalescent theory and the corresponding assumptions that sample sizes are small relative to effective population size and that the region being simulated is short. Here we show that coalescent simulations of long regions of the genome exhibit large biases in identity-by-descent (IBD), long-range linkage disequilibrium (LD), and ancestry patterns, particularly when sample size is large. We present a Wright-Fisher extension tomsprime, and show that it produces more realistic distributions of IBD, LD, and ancestry proportions, while also addressing more subtle biases of the coalescent. Further, these extensions are more computationally efficient than state-of-the-art coalescent simulations when simulating long regions, including whole-genome data. For shorter regions, efficiency and accuracy can be maintained via a flexible hybrid model which simulates the recent past under the Wright-Fisher model and uses coalescent simulations in the distant past.
Molecular subtyping improves prognostication of Stage 2 colorectal cancer
Authors: Purcell Rachel V , Schmeier Sebastian , Lau Yee Chen , Pearson John F , Frizelle Francis A 
Published: June 2019

AbstractPost-surgical staging is the mainstay of prognostic stratification for colorectal cancer (CRC). Here, we compare TNM staging to consensus molecular subtyping (CMS) and assess the value of subtyping in addition to stratification by TNM. Three hundred and eight treatment-naïve colorectal tumours were accessed from our institutional tissue bank. CMS was carried out using tumour gene-expression data. Staging and CMS were analysed with respect to clinicopathologic variables and patient outcome. CMS alone was not associated with survival, while TNM stage significantly explained mortality. Addition of CMS to TNM-stratified tumours showed a prognostic effect in stage 2 tumours; CMS3 tumours had a significantly lower overall survival (P= 0.006). Stage 2 patients with a good prognosis showed immune activation and up-regulation of tumour suppressor genes. Although stratification using CMS does not outperform TNM staging as a prognostic indicator, gene-expression based subtyping shows promise for improved prognostication in stage 2 CRC.
Cluster analysis on high dimensional RNA-seq data with applications to cancer research - An evaluation study
Authors: Vidman Linda , Källberg David , Rydén Patrik 
Published: June 2019

AbstractClustering of gene expression data is widely used to identify novel subtypes of cancer. Plenty of clustering approaches have been proposed, but there is a lack of knowledge regarding their relative merits and how data characteristics influence the performance. We evaluate how cluster analysis choices affect the performance by studying four publicly available human cancer data sets: breast, brain, kidney and stomach cancer. In particular, we focus on how the sample size, distribution of subtypes and sample heterogeneity affect the performance.In general, increasing the sample size had limited effect on the clustering performance, e.g. for the breast cancer data similar performance was obtained forn= 40 as forn= 330. The relative distribution of the subtypes had a noticeable effect on the ability of identifying the disease subtypes and data with heavily skewed distributions turned out to be difficult to cluster. Both the choice of clustering method and selection method affected the ability to identify the subtypes, but the relative performance varied between data sets, making it difficult to rank the approaches. For some data sets, the performance was substantially higher when the clustering was based on data from only one sex compared to data from a mixed population. This suggests that homogeneous data are easier to cluster than heterogeneous data and that clustering males and females individually may be beneficial and increase the chance to detect novel subtypes. It was also observed that the performance often differed substantially between females and males.The number of samples seems to have a limited effect on the performance while the heterogeneity, at least with respect to sex, is important for the performance. Hence, by analyzing the genders separately, the possible loss caused by having fewer samples could be outweighed by the benefit of a more homogeneous data.
Comparing detectability patterns of bird species in small ponds using multi-method hierarchical modelling
Authors: Zamora-Marín José M. , Zamora-López Antonio , Calvo José F. , Oliva-Paterna Francisco J. 
Published: June 2019

AbstractRobust knowledge of biodiversity distribution is essential for designing and developing effective conservation actions. However, monitoring programmes have historically assumed all species are detected equally with no spatial or temporal differences in their detection rates. However, recently, interest in accounting for imperfect detection has greatly increased in studies on animal diversity. In this respect, birds are the most widely used group for hierarchical occupancy-detection modelling, mainly due to the relative ease of sampling and the large number of bird datasets that are available. Nevertheless, there are no studies that have tried to evaluate the effectiveness of different bird sampling methods based on a hierarchical modelling approach. In an attempt to remedy this situation, we conducted point transects (PT), point transects plus video monitoring (PV) and mist netting (MN) in 19 small ponds located in the province of Murcia, southeastern Spain, one of the most arid regions of Europe. Multi-method hierarchical models were fitted to the detection histories of 36 common bird species with three main objectives: to compare the effectiveness of the three sampling methods for detecting the bird species using ponds, to assess the effect of sampling date on species detectability, and to establish the influence of body size and diet on species detectability. The results showed PV to be the most effective sampling method for detecting species occupancy, although detection rates ranged widely among bird groups, and some large species were weakly detected by all the methods. Average detectability increased during the breeding period, a pattern shown similarly by all sampling methods. Our approach is particularly applicable to both single- and multi-species bird monitoring programmes. We recommend evaluating the cost-effectiveness of available methods for sampling design in order to reduce costs and improve effectiveness.
CRL-based ultra-compact transfocator for X-ray focusing and microscopy
Authors: Narikovich Anton , Polikarpov Maxim , Barannikov Alexander , Klimova Nataliya , Lushnikov Anatoly , Lyatun Ivan , Bourenkov Gleb , Zverev Dmitrii , Panormov Igor , Sinitsyn Alexander , Snigireva Irina , Snigirev Anatoly 
Published: June 2019

A new ultra-compact transfocator (UCTF) based on X-ray compound refractive lenses (CRLs) is presented. The device can be used to change the number of one- and two-dimensional focusing CRLs by moving the individual parabolic lenses one-by-one independently, thus providing permanent energy and focal-length tunability for scanning and full-field X-ray microscopy applications. The small overall size and light weight of the device allow it to be integrated in any synchrotron beamline, while even simplifying the experimental layout. The UCTF was tested at the Excillium MetalJet microfocus X-ray source and at the P14 EMBL (PETRA-III) beamline, demonstrating high mechanical stability and lens positioning repeatability.
Driving forces for the US residential housing price: a predictive analysis
Authors: Jafari Amirhosein , Akhavian Reza 
Published: June 2019

PurposeThe purpose of this paper is to determine the key characteristics that determine housing prices in the USA. Data analytical models capable of predicting the driving forces of housing prices can be extremely useful in the built environment and real estate decision-making processes.Design/methodology/approachA data set of 13,771 houses is extracted from the 2013 American Housing Survey (AHS) data and used to develop a Hedonic Pricing Method (HPM). Besides, a data set of 22 houses in the city of San Francisco, CA is extracted from Redfin real estate brokerage database and used to test and validate the model. A correlation analysis is performed and a stepwise regression model is developed. Also, the best subsets regression model is selected to be used in HPM and a semi-log HPM is proposed to reduce the problem of heteroscedasticity.FindingsResults show that the main driving force for housing transaction price in the USA is the square footage of the unit, followed by its location, and its number of bathrooms and bedrooms. The results also show that the impact of neighborhood characteristics (such as distance to open spaces and business centers) on the housing prices is not as strong as the impact of housing unit characteristics and location characteristics.Research limitations/implicationsAn important limitation of this study is the lack of detailed housing attribute variables in the AHS data set. The accuracy of the prediction model could be increased by having a greater number of information regarding neighborhood and regional characteristics. Also, considering the macro business environment such as the inflation rate, the interest rates, the supply and demand for housing, and the unemployment rates, among others could increase the accuracy of the model. The authors hope that the presented study spurs additional research into this topic for further investigation.Practical implicationsThe developed framework which is capable of predicting the driving forces of housing prices and predict the market values based on those factors could be useful in the built environment and real estate decision-making processes. Researchers can also build upon the developed framework to develop more sophisticated predictive models that benefit from a more diverse set of factors.Social implicationsFinally, predictive models of housing price can help develop user-friendly interfaces and mobile applications for home buyers to better evaluate their purchase choices.Originality/valueIdentification of the key driving forces that determine housing prices on real-world data from the 2013 AHS, and development of a prediction model for housing prices based on the studied data have made the presented research original and unique.
Let’s talk about chemsex and pleasure: the missing link in chemsex services
Authors: Flores-Aranda Jorge , Goyette Mathieu , Aubut Valérie , Blanchette Maxime , Pronovost Frédérick 
Published: June 2019

Purpose
The purpose of this paper is to document the experience of current and former methamphetamine users on their crystal meth use patterns and on their use of services related to their chemsex practice.

Design/methodology/approach
For qualitative component, two focus groups were formed with nine current users of methamphetamine and eight former users. Thematic analysis was performed to know their experiences.

Findings
All participants were already engaging in chemsex with various substances before they first started using methamphetamine. Methamphetamine use led some to slam (methamphetamine or mephedrone injection). Some participants report that their sexual experiences were intensified early in their chemsex practice. They reported feeling more confident with their partners, feeling like they are sexually attractive and overcoming their barriers to sexuality. The intensification of methamphetamine use and, in particular, injection change the positive perception of sexual life. Thus, for some participants, substance use takes more space and their sexual experiences become less satisfactory.

Practical implications
Participants report the services that address the phenomenon of chemsex are still scarce in Quebec province. In addition, the few services available aim to relearn a sober sexuality. However, the mourning of the positive aspects of chemsex on sexual experiences seems still very little discussed. Greater consideration of positive chemsex experiences is needed in services that address this issue.

Originality/value
This project documented the perception of pleasure related to sexual practices among regular methamphetamine users. Their perception of pleasure will help develop services adapted to their reality.
DEM-aided method for predicting the hydraulic properties with particle-size distribution of porous media
Authors: Dan Han-Cheng , Zou Zhuo-Min , Chen Jia-Qi , Peng An-Ping 
Published: June 2019

Purpose
The soil water retention curve (SWRC) and unsaturated hydraulic conductivity (UHC) are crucial indices to assess hydraulic properties of porous media that primarily depend on the particle and pore size distributions. This study aims to present a method based on the discrete element model (DEM) and the typical Arya and Paris model (AP model) to numerically predict SWRC and UHC.

Design/methodology/approach
First, the DEM (PFC3D software) is used to construct the pore and particle size distributions in porous media. The number of particles is calculated according to the AP model, which can be applied to evaluate the relationship between the suction head and the moisture of porous media. Subsequently, combining critical path analysis (CPA) and fractal theory, the air entry value is applied to calculate the critical pore radius (CPR) and the critical volume fraction (CVF) for evaluating the unsaturated hydraulic conductivity.

Findings
This method is validated against the experimental results of 11 soils from the clay loam to the sand, and then the scaling parameter in the AP model and critical volume fraction value for many types of soils are presented for reference; subsequently, the gradation effect on hydraulic property of soils is analyzed. Furthermore, the calculation for unbound graded aggregate (UGA) material as a special case and a theoretical extension are provided.

Originality/value
The presented study provides an important insight into the relationship between the heterogeneous particle and hydraulic properties by the DEM and sheds light on the directions for future study of a method to investigate the hydraulic properties of porous media.
Adaptive finite element analysis with local mesh refinement based on a posteriori error estimate of element energy projection technique
Authors: Dong Yiyi , Yuan Si , Xing Qinyan 
Published: June 2019

Purpose
This study aims to propose a general and efficient adaptive strategy with local mesh refinement for two-dimensional (2D) finite element (FE) analysis based on the element energy projection (EEP) technique.

Design/methodology/approach
In view of the inflexibility of the existing global dimension-by-dimension (D-by-D) recovery method via EEP technique, in which displacements are recovered through element strips, an improved element D-by-D recovery strategy was proposed, which enables the EEP recovery of super-convergent displacements to be implemented mostly on a single element. Accordingly, a posteriori error estimate in maximum norm was established and an EEP-based adaptive FE strategy of h-version with local mesh refinement was developed.

Findings
Representative numerical examples, including stress concentration and singularity problems, were analyzed; the results of which show that the adaptively generated meshes reasonably reflect the local difficulties inherent in the physical problems and the proposed adaptive analysis can produce FE displacement solutions satisfying the user-specified tolerances in maximum norm with an almost optimal adaptive convergence rate.

Originality/value
The proposed element D-by-D recovery method is a more efficient and flexible displacement recovery method, which is implemented mostly on a single element. The EEP-based adaptive FE analysis can produce displacement solutions satisfying the specified tolerances in maximum norm with an almost optimal convergence rate and thus can be expected to apply to other 2D problems.