bluuebunny/crossref_metadata_2025 huggingface dataset:
Level of Total Volatile Organic Compounds (TVOC) in the context of Indoor Air Quality (IAQ) in Office Buildings
Authors: Kraus Michal , Šenitková Ingrid Juhásová
Published: February 2020

This paper is focused on the quality of the indoor environment in terms of Total Volatile Organic Compounds (TVOC) in the office buildings. Working in the office is one of the most common occupations in developed countries of the world. Employees spend up to 25% of their time in the workplace each year. Obviously, the internal environment affects not only the health of workers but also their performance and productivity. Observe the long-term level of Total Volatile Organic Compounds in the context of Indoor Air Quality (IAQ) in a single cellular office is subjected within the presented study. IA-Quest (Indoor Air Quality Emission Simulation Tool) developed by the National Research Council is used for emission of VOCs from building surface materials and furnishings in time. The simulation and monitoring of TVOC concentration are carried out in two phases. In the first phase, only building materials such as walls, doors, floor, ceiling, window, etc. are considered. In the second phase, the basic furniture including the office table and chair, coffee table, 2 chairs and wardrobe are included in the calculation. TVOC concentration values in a furniture room are 10 - 15% higher than in a room without furniture.
Methodological Features of the Management of Modern Labour Protection in the Construction
Authors: Sugak E B
Published: February 2020

In the recent ten years, there has been a steady decline in industrial injuries and occupational diseases in the global economy. At the same time, against the background of favorable statistics on accidents, an increase in the overall incidence is observed, which are called «work related diseases». By decision of the Government of the Russian Federation to improve the production environment should ensure the reform of the management system of labour protection, focused on the prevention of the manifestation of dangerous and harmful factors. In this article there is analyse of the methodological aspects of occupational risk management, which imply a continuous and consistent cycle of activity from four stages, characterized as «the Deming-Shewhart cycle».
Effect of graphene on thermal stability and mechanical properties of ethylene-vinyl acetate: a molecular dynamics simulation
Authors: Shi Jingli , Yang Junsheng , Zhou Jingjing , Ji Hongfei , Tang Xin , Gao Tao
Published: February 2020

Graphene has an important positive impact on improving polymer material properties, making the application of composite materials widely available. This paper investigates the influence of graphene on the thermal and mechanical properties of Ethylene-vinyl acetate (EVA) by the molecular dynamics (MD) simulations. The thermostability and mechanical properties of the graphene/EVA nanocomposites are analyzed in terms of the glass transition temperature (T

g
), mean-square displacement (MSD), modulus, interfacial binding energy (IBE), stress-strain relationship, yield strength, and tensile strength. The influences of the size of graphene on the thermal stability and mechanical properties of EVA are analyzed and discussed. The simulation result indicated that the glass transition temperature, modulus, yield strength, and ultimate strength of the nanocomposites are higher than that of pristine EVA, which is in good consistent with recent experiments. We attribute this finding to the fact that the strong interfacial bonding of graphene to EVA limits the fluidity of the EVA chains and improves the thermal stability and strength of the graphene/EVA composites. The incorporation of graphene enhanced the thermal stability and mechanical properties of EVA.
Hertz model or Oliver & Pharr analysis? Tutorial regarding AFM nanoindentation experiments on biological samples
Authors: Kontomaris S V , Malamou A
Published: February 2020

The data processing regarding AFM nanoindentation experiments on biological samples relies on the basic contact mechanics models like the Hertz model and the Oliver & Pharr analysis. Despite the fact that the two aforementioned techniques are assumed to provide equivalent results since they are based on the same underlying theory of contact mechanics, significant differences regarding the Young’s modulus calculation even on the same tested sample have been presented in the literature. The differences can be even greater than 30% depending on the used model. In addition, when the Oliver & Pharr analysis is used, a systematic greater Young’s modulus value is always calculated compared to the Hertzian analysis. In this paper, the two techniques are briefly described and two possible reasons that accurately explain the observed differences in the calculated value of the Young’s modulus are presented.
Thermally induced phase transformations of Al93Fe4Nb3 and Al90Fe7Nb3 quenched alloys
Authors: Shved O V , Mudry S I , Kotsyubynsky V O , Boychuk V M
Published: February 2020

Al–based rapidly quenched alloys of composition Al90Fe7Nb3 and Al93Fe4Nb3 were studied by Mӧssbauer spectroscopy, X–ray powder diffraction and differential scanning calorimetry methods. The occurrence of thermally induced phase transformations has been established. It is shown that both ribbons reveal the structure in which Fe–atoms have an aluminum ones neighbors both in amorphous and annealed up to 653 K that corresponds to the atomic arrangement in Al6Fe metastable phase. At higher than 709.6 K annealing temperatures the structural transformations of this phase into mix of stable Al13Fe4 compound and aluminium were observed and at 893 K these transformations were completed.
Robustness-optimized quantum error correction
Authors: Layden David , Huang Louisa Ruixue , Cappellaro Paola
Published: February 2020

Quantum error correction (QEC) codes are usually designed to correct errors regardless of their physical origins. In large-scale devices, this is an essential feature. In smaller-scale devices, however, the main error sources are often understood, and this knowledge could be exploited for more efficient error correction. Optimizing the QEC protocol is therefore a promising strategy in smaller devices. Typically, this involves tailoring the protocol to a given decoherence channel by solving an appropriate optimization problem. Here we introduce a new optimization-based approach, which maximizes the robustness to faults in the recovery. Our approach is inspired by recent experiments, where such faults have been a significant source of logical errors. We illustrate this approach with a three-qubit model, and show how near-term experiments could benefit from more robust QEC protocols.
Bio-responsive materials for tissue regeneration
Authors: Wang Zuyong , Thian Eng San , Li Xiang , Best Serena
Published: February 2020

The field of tissue engineering brings together researchers from a broad range of multidisciplinary backgrounds with the common aim of pursuing continuous improvement in biomedical innovation. Advances in tissue repair and regeneration attempt to meet the gold standard offered by autografting while avoiding the issues associated with tissue harvesting. Over time, focus moved from the use of allografts and synthetic grafts (non-degradable) towards exploring the potential for engineered ‘living grafts’ to address tissue diseases and the treatment of organ failure. However, it is clear that tissue-engineered implants used in a wide range of therapeutic applications still require further improvement. Recent recognition of the limitations and challenges associated with tissue regeneration, has triggered a shift towards ready-to-use implants that can induce biological repair processes and this has highlighted the need for biomaterials that can promote optimised biological response. Rather than developing biomaterials for tissue replication and substitution in classical tissue engineering, there is a new focus on creating biomaterials that are bio-responsive and hence capable of guiding tissue and organ repair. Successful routes involve mimicking natural processes that occur during regeneration. This can be achieved through the use of emerging engineering and technological advances, with careful control of the intrinsic physical and chemical cues from the as-fabricated materials (e.g. modified biochemical motifs, stiffness, anisotropy etc) or stimulated by extrinsic factors (e.g. pH, heat, light, metabolites etc).
High-dimensional potential energy surfaces for molecular simulations: from empiricism to machine learning
Authors: Unke Oliver T , Koner Debasish , Patra Sarbani , Käser Silvan , Meuwly Markus
Published: February 2020

An overview of computational methods to describe high-dimensional potential energy surfaces suitable for atomistic simulations is given. Particular emphasis is put on accuracy, computability, transferability and extensibility of the methods discussed. They include empirical force fields, representations based on reproducing kernels, using permutationally invariant polynomials, neural network-learned representations and combinations thereof. Future directions and potential improvements are discussed primarily from a practical, application-oriented perspective.
Applying machine learning optimization methods to the production of a quantum gas
Authors: Barker A J , Style H , Luksch K , Sunami S , Garrick D , Hill F , Foot C J , Bentine E
Published: February 2020

We apply three machine learning strategies to optimize the atomic cooling processes utilized in the production of a Bose–Einstein condensate (BEC). For the first time, we optimize both laser cooling and evaporative cooling mechanisms simultaneously. We present the results of an evolutionary optimization method (differential evolution), a method based on non-parametric inference (Gaussian process regression) and a gradient-based function approximator (artificial neural network). Online optimization is performed using no prior knowledge of the apparatus, and the learner succeeds in creating a BEC from completely randomized initial parameters. Optimizing these cooling processes results in a factor of four increase in BEC atom number compared to our manually-optimized parameters. This automated approach can maintain close-to-optimal performance in long-term operation. Furthermore, we show that machine learning techniques can be used to identify the main sources of instability within the apparatus.
Determining optical constants of 2D materials with neural networks from multi-angle reflectometry data
Authors: Simsek Ergun
Published: February 2020

Synthetically generated multi-angle reflectometry data is used to train a neural network based learning system to estimate the refractive index of atomically thin layered materials in the visible part of the electromagnetic spectrum. Unlike previously developed regression based optical characterization methods, the prediction is achieved via classification by using the probabilities of each input element belonging to a label as weighting coefficients in a simple analytical formula. Various types of activation functions and gradient descent optimizers are tested to determine the optimum combination yielding the best performance. For the verification of the proposed method’s accuracy, four different materials are studied. In all cases, the maximum error is calculated to be less than 0.3%. Considering the highly dispersive nature of the studied materials, this result is a substantial improvement in terms of accuracy and efficiency compared to traditional approaches.
American Versus European Hypertension Guidelines: The Case of White Coat Hypertension
Authors: Cuspidi Cesare , Paoletti Federico , Tadic Marijana , Sala Carla , Dell’Oro Raffaella , Grassi Guido , Mancia Giuseppe
Published: February 2020

BACKGROUND

The impact of the 2017 American College Cardiology/American Heart Association guidelines on reclassification of white coat hypertension (WCH) and white coat uncontrolled hypertension (WUCH) phenotypes has not been thoroughly investigated, so far. The aim of the present analysis was to compare the prevalence rates of WCH and WUCH according to either 2018 European Society Hypertension/European Society Cardiology and 2017 ACC/AHA hypertension guidelines.

METHODS

A large database of individual 24-hour ambulatory blood pressure (BP) recordings from untreated and treated hypertensive individuals with office BP ≥140 and/or 90 mm Hg was analyzed.

RESULTS

As many as 3,223 (39% men) out of 7,353 (47% men) fulfilled diagnostic criteria for WCH (n = 1,281) and WUCH (n = 1,942) according to the 2018 ESH/ESC guidelines (mean 24-hour BP <130/80 mm Hg), the prevalence rate being 17.4% and 26.4%, respectively. The corresponding figures according to the 2017 ACC/AHA guidelines (mean 24-hour BP <125/75 mm Hg) were 15.6 and 9.4%, respectively. Thus, a total of 1,378 patients (42.7%) either defined as WCH and WUCH by ESH/ESC guidelines, were classifiable as untreated sustained and uncontrolled sustained hypertensives by ACC/AHA guidelines.

CONCLUSIONS

The ACC/AHA reclassification of patients with office BP ≥140/90 mm Hg leads to a marked decrease in the prevalence of WCH/WUCH. This may have relevant clinical implications because the prognostic significance of these phenotypes is often ignored in clinical practice and, consequently, contributes to the high burden of cardiovascular diseases worldwide.
Presence of same-sex kin promotes explorative behavior in subadult cichlid fish
Authors: Vitt Simon , Madge Pimentel Iris , Thünken Timo
Published: February 2020

While the importance of kin discrimination, that is, kin recognition and subsequent differential treatment of kin and nonkin, is well established for kin-directed cooperation or altruism, the role of kin discrimination in the context of kin competition and kin avoidance is largely unexplored. Theory predicts that individuals avoiding competition with kin should be favored by natural selection due to indirect fitness benefits. Using an experimental approach, we investigated whether the presence of same-sex kin affects avoidance and explorative behavior in subadult Pelvicachromis taeniatus, a West African cichlid fish with strong intrasexual competition in both sexes. Pelvicachromis taeniatus is capable of recognizing kin using phenotype matching and shows kin discrimination in diverse contexts. When exposed to a same-sex conspecific, both males and females tended to interact less with the related opponent. Moreover, individuals explored a novel environment faster after exposure to kin than to nonkin. This effect was more pronounced in females. Individuals avoiding the proximity of same-sex relatives may reduce kin competition over resources such as mating partners or food.
Siring success in kangaroos: size matters for those in the right place at the right time
Authors: Montana Luca , Rousseu François , Garant Dany , Festa-Bianchet Marco
Published: February 2020

In polygynous species, male reproductive success is predicted to be monopolized by a few dominant males. This prediction is often not supported, suggesting that ecological and alternative mating tactics influence siring success. The spatiotemporal distribution of individuals and the number of males competing for each receptive female are often overlooked because they are difficult to monitor in wild animals. We examined how spatial overlap of female–male pairs, the time spent by a male on the breeding site, number of competitors, and morphological traits influence siring probability in eastern gray kangaroos (Macropus giganteus). We compared home range overlap for 12 208 dam–male pairs and 295 known dam–sire pairs to define local competitive groups and to estimate every male’s opportunity to sire the young of each female. We compared models considering morphological traits relative to the entire population or to local competitive groups. Including local competition improved model performance because it estimated the intensity of competition and compared each male’s morphological traits to those of its competitive group. Regardless of size, males can increase their probability to sire a young by increasing their mating opportunity relative to the mother. We underline the importance of considering spatial structure to assess the intensity of competition in species where males cannot equally access all females in a population. The estimation of mating opportunity and intensity of local competition improves our understanding of how morphological traits affect siring success when each mating event involves a different set of competing males, a characteristic of most wild species.
TOD-CUP: a gene expression rank-based majority vote algorithm for tissue origin diagnosis of cancers of unknown primary
Authors: Shen Yifei , Chu Qinjie , Yin Xinxin , He Yinjun , Bai Panpan , Wang Yunfei , Fang Weijia , Timko Michael P , Fan Longjiang , Jiang Weiqin
Published: February 2020

Gene expression profiling holds great potential as a new approach to histological diagnosis and precision medicine of cancers of unknown primary (CUP). Batch effects and different data types greatly decrease the predictive performance of biomarker-based algorithms, and few methods have been widely applied to identify tissue origin of CUP up to now. To address this problem and assist in more precise diagnosis, we have developed a gene expression rank-based majority vote algorithm for tissue origin diagnosis of CUP (TOD-CUP) of most common cancer types. Based on massive tissue-specific RNA-seq data sets (10 553) found in The Cancer Genome Atlas (TCGA), 538 feature genes (biomarkers) were selected based on their gene expression ranks and used to predict tissue types. The top scoring pairs (TSPs) classifier of the tumor type was optimized by the TCGA training samples. To test the prediction accuracy of our TOD-CUP algorithm, we analyzed (1) two microarray data sets (1029 Agilent and 2277 Affymetrix/Illumina chips) and found 91% and 94% prediction accuracy, respectively, (2) RNA-seq data from five cancer types derived from 141 public metastatic cancer tumor samples and achieved 94% accuracy and (3) a total of 25 clinical cancer samples (including 14 metastatic cancer samples) were able to classify 24/25 samples correctly (96.0% accuracy). Taken together, the TOD-CUP algorithm provides a powerful and robust means to accurately identify the tissue origin of 24 cancer types across different data platforms. To make the TOD-CUP algorithm easily accessible for clinical application, we established a Web-based server for tumor tissue origin diagnosis (http://ibi. zju.edu.cn/todcup/).
Machine learning-based analysis of multi-omics data on the cloud for investigating gene regulations
Authors: Oh Minsik , Park Sungjoon , Kim Sun , Chae Heejoon
Published: February 2020

Gene expressions are subtly regulated by quantifiable measures of genetic molecules such as interaction with other genes, methylation, mutations, transcription factor and histone modifications. Integrative analysis of multi-omics data can help scientists understand the condition or patient-specific gene regulation mechanisms. However, analysis of multi-omics data is challenging since it requires not only the analysis of multiple omics data sets but also mining complex relations among different genetic molecules by using state-of-the-art machine learning methods. In addition, analysis of multi-omics data needs quite large computing infrastructure. Moreover, interpretation of the analysis results requires collaboration among many scientists, often requiring reperforming analysis from different perspectives. Many of the aforementioned technical issues can be nicely handled when machine learning tools are deployed on the cloud. In this survey article, we first survey machine learning methods that can be used for gene regulation study, and we categorize them according to five different goals: gene regulatory subnetwork discovery, disease subtype analysis, survival analysis, clinical prediction and visualization. We also summarize the methods in terms of multi-omics input types. Then, we explain why the cloud is potentially a good solution for the analysis of multi-omics data, followed by a survey of two state-of-the-art cloud systems, Galaxy and BioVLAB. Finally, we discuss important issues when the cloud is used for the analysis of multi-omics data for the gene regulation study.
Homoeologous gene expression and co-expression network analyses and evolutionary inference in allopolyploids
Authors: Hu Guanjing , Grover Corrinne E , Arick Mark A , Liu Meiling , Peterson Daniel G , Wendel Jonathan F
Published: February 2020

Polyploidy is a widespread phenomenon throughout eukaryotes. Due to the coexistence of duplicated genomes, polyploids offer unique challenges for estimating gene expression levels, which is essential for understanding the massive and various forms of transcriptomic responses accompanying polyploidy. Although previous studies have explored the bioinformatics of polyploid transcriptomic profiling, the causes and consequences of inaccurate quantification of transcripts from duplicated gene copies have not been addressed. Using transcriptomic data from the cotton genus (Gossypium) as an example, we present an analytical workflow to evaluate a variety of bioinformatic method choices at different stages of RNA-seq analysis, from homoeolog expression quantification to downstream analysis used to infer key phenomena of polyploid expression evolution. In general, EAGLE-RC and GSNAP-PolyCat outperform other quantification pipelines tested, and their derived expression dataset best represents the expected homoeolog expression and co-expression divergence. The performance of co-expression network analysis was less affected by homoeolog quantification than by network construction methods, where weighted networks outperformed binary networks. By examining the extent and consequences of homoeolog read ambiguity, we illuminate the potential artifacts that may affect our understanding of duplicate gene expression, including an overestimation of homoeolog co-regulation and the incorrect inference of subgenome asymmetry in network topology. Taken together, our work points to a set of reasonable practices that we hope are broadly applicable to the evolutionary exploration of polyploids.
StackCPPred: a stacking and pairwise energy content-based prediction of cell-penetrating peptides and their uptake efficiency
Authors: Fu Xiangzheng , Cai Lijun , Zeng Xiangxiang , Zou Quan
Published: February 2020

Motivation

Cell-penetrating peptides (CPPs) are a vehicle for transporting into living cells pharmacologically active molecules, such as short interfering RNAs, nanoparticles, plasmid DNAs and small peptides, thus offering great potential as future therapeutics. Existing experimental techniques for identifying CPPs are time-consuming and expensive. Thus, the prediction of CPPs from peptide sequences by using computational methods can be useful to annotate and guide the experimental process quickly. Many machine learning-based methods have recently emerged for identifying CPPs. Although considerable progress has been made, existing methods still have low feature representation capabilities, thereby limiting further performance improvements.

Results

We propose a method called StackCPPred, which proposes three feature methods on the basis of the pairwise energy content of the residue as follows: RECM-composition, PseRECM and RECM–DWT. These features are used to train stacking-based machine learning methods to effectively predict CPPs. On the basis of the CPP924 and CPPsite3 datasets with jackknife validation, StackDPPred achieved 94.5% and 78.3% accuracy, which was 2.9% and 5.8% higher than the state-of-the-art CPP predictors, respectively. StackCPPred can be a powerful tool for predicting CPPs and their uptake efficiency, facilitating hypothesis-driven experimental design and accelerating their applications in clinical therapy.

Availability and implementation

Source code and data can be downloaded from https://github.com/Excelsior511/StackCPPred.

Supplementary information

Supplementary data are available at Bioinformatics online.
PSORTm: a bacterial and archaeal protein subcellular localization prediction tool for metagenomics data
Authors: Peabody Michael A , Lau Wing Yin Venus , Hoad Gemma R , Jia Baofeng , Maguire Finlay , Gray Kristen L , Beiko Robert G , Brinkman Fiona S L
Published: February 2020

Motivation

Many methods for microbial protein subcellular localization (SCL) prediction exist; however, none is readily available for analysis of metagenomic sequence data, despite growing interest from researchers studying microbial communities in humans, agri-food relevant organisms and in other environments (e.g. for identification of cell-surface biomarkers for rapid protein-based diagnostic tests). We wished to also identify new markers of water quality from freshwater samples collected from pristine versus pollution-impacted watersheds.

Results

We report PSORTm, the first bioinformatics tool designed for prediction of diverse bacterial and archaeal protein SCL from metagenomics data. PSORTm incorporates components of PSORTb, one of the most precise and widely used protein SCL predictors, with an automated classification by cell envelope. An evaluation using 5-fold cross-validation with in silico-fragmented sequences with known localization showed that PSORTm maintains PSORTb’s high precision, while sensitivity increases proportionately with metagenomic sequence fragment length. PSORTm’s read-based analysis was similar to PSORTb-based analysis of metagenome-assembled genomes (MAGs); however, the latter requires non-trivial manual classification of each MAG by cell envelope, and cannot make use of unassembled sequences. Analysis of the watershed samples revealed the importance of normalization and identified potential biomarkers of water quality. This method should be useful for examining a wide range of microbial communities, including human microbiomes, and other microbiomes of medical, environmental or industrial importance.

Availability and implementation

Documentation, source code and docker containers are available for running PSORTm locally at https://www.psort.org/psortm/ (freely available, open-source software under GNU General Public License Version 3).

Supplementary information

Supplementary data are available at Bioinformatics online.
Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes
Authors: Cleemput Sara , Dumon Wim , Fonseca Vagner , Abdool Karim Wasim , Giovanetti Marta , Alcantara Luiz Carlos , Deforche Koen , de Oliveira Tulio
Published: February 2020

Genome detective is a web-based, user-friendly software application to quickly and accurately assemble all known virus genomes from next-generation sequencing datasets. This application allows the identification of phylogenetic clusters and genotypes from assembled genomes in FASTA format. Since its release in 2019, we have produced a number of typing tools for emergent viruses that have caused large outbreaks, such as Zika and Yellow Fever Virus in Brazil. Here, we present the Genome Detective Coronavirus Typing Tool that can accurately identify the novel severe acute respiratory syndrome (SARS)-related coronavirus (SARS-CoV-2) sequences isolated in China and around the world. The tool can accept up to 2000 sequences per submission and the analysis of a new whole-genome sequence will take approximately 1 min. The tool has been tested and validated with hundreds of whole genomes from 10 coronavirus species, and correctly classified all of the SARS-related coronavirus (SARSr-CoV) and all of the available public data for SARS-CoV-2. The tool also allows tracking of new viral mutations as the outbreak expands globally, which may help to accelerate the development of novel diagnostics, drugs and vaccines to stop the COVID-19 disease.

Availability and implementation

https://www.genomedetective.com/app/typingtool/cov

Contact

koen@emweb.be or deoliveira@ukzn.ac.za

Supplementary information

Supplementary data are available at Bioinformatics online.
CRAMER: a lightweight, highly customizable web-based genome browser supporting multiple visualization instances
Authors: Anastasiadi M , Bragin E , Biojoux P , Ahamed A , Burgin J , de Castro Cogle K , Llaneza-Lago S , Muvunyi R , Scislak M , Aktan I , Molitor C , Kurowski T , Mohareb F
Published: February 2020

In recent years, the ability to generate genomic data has increased dramatically along with the demand for easily personalized and customizable genome browsers for effective visualization of diverse types of data. Despite the large number of web-based genome browsers available nowadays, none of the existing tools provides means for creating multiple visualization instances without manual set up on the deployment server side. The Cranfield Genome Browser (CRAMER) is an open-source, lightweight and highly customizable web application for interactive visualization of genomic data. Once deployed, CRAMER supports seamless creation of multiple visualization instances in parallel while allowing users to control and customize multiple tracks. The application is deployed on a Node.js server and is supported by a MongoDB database which stored all customizations made by the users allowing quick navigation between instances. Currently, the browser supports visualizing a large number of file formats for genome annotation, variant calling, reads coverage and gene expression. Additionally, the browser supports direct Javascript coding for personalized tracks, providing a whole new level of customization both functionally and visually. Tracks can be added via direct file upload or processed in real-time via links to files stored remotely on an FTP repository. Furthermore, additional tracks can be added by users via simple drag and drop to an existing visualization instance.

Availability and implementation

CRAMER is implemented in JavaScript and is publicly available on GitHub on https://github.com/FadyMohareb/cramer. The application is released under an MIT licence and can be deployed on any server running Linux or Mac OS.

Contact

f.mohareb@cranfield.ac.uk

Supplementary information

Supplementary data are available at Bioinformatics online.
2DImpute: imputation in single-cell RNA-seq data from correlations in two dimensions
Authors: Zhu Kaiyi , Anastassiou Dimitris
Published: February 2020

We developed 2DImpute, an imputation method for correcting false zeros (known as dropouts) in single-cell RNA-sequencing (scRNA-seq) data. It features preventing excessive correction by predicting the false zeros and imputing their values by making use of the interrelationships between both genes and cells in the expression matrix. We showed that 2DImpute outperforms several leading imputation methods by applying it on datasets from various scRNA-seq protocols.

Availability and implementation

The R package of 2DImpute is freely available at GitHub (https://github.com/zky0708/2DImpute).

Contact

d.anastassiou@columbia.edu

Supplementary information

Supplementary data are available at Bioinformatics online.
‘Come Night-time, It’s a War Zone’: Women’s Experiences of Homelessness, Risk and Public Space
Authors: Menih Helena
Published: February 2020

This paper explores constructions of ‘risk’ in the lives of women experiencing homelessness in Brisbane, Australia. Drawing on ethnographic data, including in-depth interviews, informal conversations and participant observation field notes, two main themes emerged: the narratives or risk; women navigating risk on the streets by employing transiency, invisibility and squatting. The analysis indicates that women consider the ways in which risk calculations are spatially and temporally located and argues that risk is embedded in social and cultural discourses of gender. Women experiencing homelessness face particular risks due to gendered spatiality and have to manage their spatialized selves to avoid everyday risks on the streets.
Low genetic divergence and variation in coastal dune populations of the widespread terrestrial orchidEpipactis helleborine
Authors: Jacquemyn Hans , De Kort Hanne , Vanden Broeck An , Brys Rein
Published: February 2020

Reconstructing the early history of species divergence and quantifying the level of standing genetic variation in diverging populations are central to our understanding of ecotype formation and ultimately speciation. In this study, we used single nucleotide polymorphisms to reconstruct the evolutionary history of species divergence in coastal dune populations of the widespread terrestrial orchid Epipactis helleborine and to investigate the level of standing genetic variation in 29 coastal dune populations in a fragmented dune landscape along the Belgian and French coast. Additionally, we used seed introduction experiments to assess the potential for gene flow into existing populations after long-distance seed dispersal and the ability to colonize vacant sites. Our results showed that coastal dune populations diverged only recently from inland populations, went through a significant bottleneck and were most probably the result of a single colonization event. Current levels of population genetic diversity are low and not related to population size or spatial isolation. The sampled dune populations also showed little genetic differentiation, and no apparent spatial genetic structure was observed. Seed introduction experiments showed that seeds of coastal dune populations germinated easily in both occupied and unoccupied sites in dune habitat, indicating that the availability of suitable mycorrhizal fungi is not limiting the distribution of coastal dune populations and that gene flow through seeds has probably contributed to the observed low levels of genetic differentiation. Overall, these results are consistent with a process of genetic divergence after a single, recent colonization event, followed by extensive gene flow among populations.
Electrographic predictors of successful weaning from anaesthetics in refractory status epilepticus
Authors: Rubin Daniel B , Angelini Brigid , Shoukat Maryum , Chu Catherine J , Zafar Sahar F , Westover M Brandon , Cash Sydney S , Rosenthal Eric S
Published: February 2020

Intravenous third-line anaesthetic agents are typically titrated in refractory status epilepticus to achieve either seizure suppression or burst suppression on continuous EEG. However, the optimum treatment paradigm is unknown and little data exist to guide the withdrawal of anaesthetics in refractory status epilepticus. Premature withdrawal of anaesthetics risks the recurrence of seizures, whereas the prolonged use of anaesthetics increases the risk of treatment-associated adverse effects. This study sought to measure the accuracy of features of EEG activity during anaesthetic weaning in refractory status epilepticus as predictors of successful weaning from intravenous anaesthetics. We prespecified a successful anaesthetic wean as the discontinuation of intravenous anaesthesia without developing recurrent status epilepticus, and a wean failure as either recurrent status epilepticus or the resumption of anaesthesia for the purpose of treating an EEG pattern concerning for incipient status epilepticus. We evaluated two types of features as predictors of successful weaning: spectral components of the EEG signal, and spatial-correlation-based measures of functional connectivity. The results of these analyses were used to train a classifier to predict wean outcome. Forty-seven consecutive anaesthetic weans (23 successes, 24 failures) were identified from a single-centre cohort of patients admitted with refractory status epilepticus from 2016 to 2019. Spectral components of the EEG revealed no significant differences between successful and unsuccessful weans. Analysis of functional connectivity measures revealed that successful anaesthetic weans were characterized by the emergence of larger, more densely connected, and more highly clustered spatial functional networks, yielding 75.5% (95% confidence interval: 73.1–77.8%) testing accuracy in a bootstrap analysis using a hold-out sample of 20% of data for testing and 74.6% (95% confidence interval 73.2–75.9%) testing accuracy in a secondary external validation cohort, with an area under the curve of 83.3%. Distinct signatures in the spatial networks of functional connectivity emerge during successful anaesthetic liberation in status epilepticus; these findings are absent in patients with anaesthetic wean failure. Identifying features that emerge during successful anaesthetic weaning may allow faster and more successful anaesthetic liberation after refractory status epilepticus.
Connectivity Gradient in the Human Left Inferior Frontal Gyrus: Intraoperative Cortico-Cortical Evoked Potential Study
Authors: Nakae Takuro , Matsumoto Riki , Kunieda Takeharu , Arakawa Yoshiki , Kobayashi Katsuya , Shimotake Akihiro , Yamao Yukihiro , Kikuchi Takayuki , Aso Toshihiko , Matsuhashi Masao , Yoshida Kazumichi , Ikeda Akio , Takahashi Ryosuke , Lambon Ralph Matthew A , Miyamoto Susumu
Published: February 2020

In the dual-stream model of language processing, the exact connectivity of the ventral stream to the anterior temporal lobe remains elusive. To investigate the connectivity between the inferior frontal gyrus (IFG) and the lateral part of the temporal and parietal lobes, we integrated spatiotemporal profiles of cortico-cortical evoked potentials (CCEPs) recorded intraoperatively in 14 patients who had undergone surgical resection for a brain tumor or epileptic focus. Four-dimensional visualization of the combined CCEP data showed that the pars opercularis (Broca’s area) is connected to the posterior temporal cortices and the supramarginal gyrus, whereas the pars orbitalis is connected to the anterior lateral temporal cortices and angular gyrus. Quantitative topographical analysis of CCEP connectivity confirmed an anterior–posterior gradient of connectivity from IFG stimulus sites to the temporal response sites. Reciprocality analysis indicated that the anterior part of the IFG is bidirectionally connected to the temporal or parietal area. This study shows that each IFG subdivision has different connectivity to the temporal lobe with an anterior–posterior gradient and supports the classical connectivity concept of Dejerine; that is, the frontal lobe is connected to the temporal lobe through the arcuate fasciculus and also a double fan-shaped structure anchored at the limen insulae.
An Atypical Sulcal Pattern in Children with Disorders of the Corpus Callosum and Its Relation to Behavioral Outcomes
Authors: Vasung Lana , Yun Hyuk Jin , Feldman Henry A , Grant Patricia Ellen , Im Kiho
Published: February 2020

Hypogenesis (hCC) and dysgenesis (dCC) of the corpus callosum (CC) are characterized by its smaller size or absence. The outcomes of these patients vary considerably and are unrelated to the size of the CC abnormality. The aim of the current study was to characterize the sulcal pattern in children with hCC and dCC and to explore its relation to clinical outcome. We used quantitative sulcal pattern analysis that measures deviation (similarity index, SI) of the composite or individual sulcal features (position, depth, area, and graph topology) compared to the control group. We calculated SI for each hemisphere and lobe in 11 children with CC disorder (hCC = 4, dCC = 7) and 15 controls. hCC and dCC had smaller hemispheric SI compared to controls. dCC subjects had smaller regional SI in the frontal and occipital lobes, which were driven by a smaller SI in a position or a graph topology. The significantly decreased SI gradient was found across groups only in the sulcal graph topology of the temporal lobes (controls > hCC > dCC) and was related to clinical outcome. Our results suggest that careful examination of sulcal pattern in hCC and dCC patients could be a useful biomarker of outcome.
Molecular and Direct Detection Tests for Treponema pallidum Subspecies pallidum: A Review of the Literature, 1964–2017
Authors: Theel Elitza S , Katz Samantha S , Pillay Allan
Published: February 2020

Direct detection methods for Treponema pallidum include dark-field microscopy (DFM), direct fluorescence antibody (DFA) testing, immunohistochemistry (IHC), and nucleic acid amplification tests (NAATs). Here, we reviewed the relevant syphilis diagnostic literature to address 2 main questions with respect to T. pallidum direct detection techniques: “What are the performance characteristics for each direct detection test for T. pallidum and what are the optimal specimen types for each test?” and “What options are available for T. pallidum molecular epidemiology?” To answer these questions, we searched 5 electronic databases (OVID Medline, OVID Embase, CINAHL, Cochrane Library, and Scopus) from 1964 to 2017 using relevant search terms and identified 1928 articles, of which 37 met our inclusion criteria. DFM and DFA sensitivities ranged from 73% to 100% in cases of primary syphilis; and while sensitivity using silver stain histopathology for T. pallidum was generally low (0%–41%), higher performance characteristics were observed for T. pallidum–specific IHC (49–92%). Different genes have been targeted by T. pallidum–specific NAATs, with the majority of studies indicating that sensitivity is primarily dependent on the type of collected biological sample, with highest sensitivity observed in primary lesion exudate (75–95%). Given the rising incidence of syphilis, the development of direct, Food and Drug Administration–cleared T. pallidum NAATs should be considered an immediate priority.
Kidney Transplantation From Hepatitis B Surface Antigen (HBsAg)–Positive Living Donors to HBsAg-Negative Recipients: Clinical Outcomes at a High-Volume Center in China
Authors: Wang Xian-ding , Liu Jin-peng , Song Tu-run , Huang Zhong-li , Fan Yu , Shi Yun-ying , Chen Li-yu , Lv Yuan-hang , Xu Zi-lin , Li Xiao-hong , Wang Li , Lin Tao
Published: February 2020

Background

Data on kidney transplantation (KTx) from hepatitis B surface antigen (HBsAg)–positive (HBsAg+) donors to HBsAg-negative (HBsAg−) recipients [D(HBsAg+)/R(HBsAg-)] are limited. We aimed to report the outcomes of D(HBsAg+)/R(HBsAg−) KTx in recipients with or without hepatitis B surface antibody (HBsAb).

Methods

Eighty-three D(HBsAg+)/R(HBsAg−) living KTx cases were retrospectively identified. The 384 cases of KTx from hepatitis B core antibody–positive (HBcAb+) living donors to HBcAb-negative (HBcAb−) recipients [D(HBcAb+)/R(HBcAb−)] were used as the control group. The primary endpoint was posttransplant HBsAg status change from negative to postive (-− →+).

Results

Before KTx, 24 donors (28.9%) in the D(HBsAg+)/R(HBsAg−) group were hepatitis B virus (HBV) DNA positive, and 20 recipients were HBsAb−. All 83 D(HBsAg+)/R(HBsAg−) recipients received HBV prophylaxis, while no D(HBcAb+)/R(HBcAb−) recipients received prophylaxis. After a median follow-up of 36 months (range, 6–106) and 36 months (range, 4–107) for the D(HBsAg+)/R(HBsAg−) and D(HBcAb+)/R(HBcAb−) groups, respectively, 2 of 83 (2.41%) D(HBsAg+)/R(HBsAg−) recipients and 1 of 384 (0.26%) D(HBcAb+)/R(HBcAb−) became HBsAg+, accompanied by HBV DNA-positive (P = .083). The 3 recipients with HBsAg−→+ were exclusively HBsAb−/HBcAb− before KTx. Recipient deaths were more frequent in the D(HBsAg+)/R(HBsAg−) group (6.02% vs 1.04%, P = .011), while liver and graft function, rejection, infection, and graft loss were not significantly different. In univariate analyses, pretransplant HBsAb−/HBcAb− combination in the D(HBsAg+)/R(HBsAg−) recipients carried a significantly higher risk of HBsAg−→+, HBV DNA−→+, and death.

Conclusions

Living D(HBsAg+)/R(HBsAg−) KTx in HBsAb+ recipients provides excellent graft and patient survivals without HBV transmission. HBV transmission risks should be more balanced with respect to benefits of D(HBsAg+)/R(HBsAg−) KTx in HBsAb-/HBcAb− candidates.
Prevalence of Self-reported Neurologic and Ocular Symptoms in Early Syphilis Cases
Authors: Quilter Laura A S , de Voux Alex , Amiya Rachel M , Davies Erin , Hennessy Robin R , Kerani Roxanne P , Madera Robbie , Matthias James , Pearson Victoria M , Walters Jaime K , Wilson Craig , Kidd Sarah , Torrone Elizabeth
Published: February 2020

Background

Neurosyphilis, a complication of syphilis, can occur at any stage of infection. Measuring the prevalence of neurosyphilis is challenging, and there are limited data on the prevalence of neurologic or ocular symptoms among patients with syphilis. We sought to describe the prevalence of neurologic and/or ocular symptoms among early syphilis (ES) cases and the clinical management of symptomatic cases enrolled in the STD Surveillance Network (SSuN) Neuro/Ocular Syphilis Surveillance project.

Methods

Persons diagnosed with ES were selected for interviews based on current health department protocols in 5 participating SSuN jurisdictions from November 2016 through October 2017. All interviewed ES cases were screened for self-reported neurologic and/or ocular symptoms. Additional clinical information on diagnostic testing and treatment for cases concerning for neurosyphilis/ocular syphilis was obtained from providers.

Results

Among 9123 patients with ES who were interviewed, 151 (1.7%; 95% confidence interval [CI], 1.4%–1.9%) reported ≥ 1 neurologic or ocular symptom. Of the 53 (35%) who underwent lumbar puncture, 22 (42%) had documented abnormal cerebrospinal fluid, of which 21 (95%) were treated for neurosyphilis/ocular syphilis. Among the remaining 98 symptomatic patients with no documented lumbar puncture (65%), 12 (12%) were treated for and/or clinically diagnosed with neurosyphilis/ocular syphilis.

Conclusions

We observed a low prevalence of self-reported neurologic and/or ocular symptoms in interviewed ES cases. Approximately one-third of ES cases who self-reported symptoms underwent further recommended diagnostic evaluation. Understanding barriers to appropriate clinical evaluation is important to ensuring appropriate management of patients with possible neurologic and/or ocular manifestations of syphilis.
Inflammatory Phenotypes Predict Changes in Arterial Stiffness Following Antiretroviral Therapy Initiation
Authors: Kelly Christine , Tinago Willard , Alber Dagmar , Hunter Patricia , Luckhurst Natasha , Connolly Jake , Arrigoni Francesca , Abner Alejandro Garcia , Kamngona Ralph , Sheha Irene , Chammudzi Mishek , Jambo Kondwani , Mallewa Jane , Rapala Alicja , Heyderman Robert S , Mallon Patrick W G , Mwandumba Henry , Walker A Sarah , Klein Nigel , Khoo Saye
Published: February 2020

Background

Inflammation drives vascular dysfunction in HIV, but in low-income settings causes of inflammation are multiple, and include infectious and environmental factors. We hypothesized that patients with advanced immunosuppression could be stratified into inflammatory phenotypes that predicted changes in vascular dysfunction on ART.

Methods

We recruited Malawian adults with CD4 <100 cells/μL 2 weeks after starting ART in the REALITY trial (NCT01825031). Carotid femoral pulse-wave velocity (cfPWV) measured arterial stiffness 2, 12, 24, and 42 weeks post–ART initiation. Plasma inflammation markers were measured by electrochemiluminescence at weeks 2 and 42. Hierarchical clustering on principal components identified inflammatory clusters.

Results

211 participants with HIV grouped into 3 inflammatory clusters representing 51 (24%; cluster-1), 153 (73%; cluster-2), and 7 (3%; cluster-3) individuals. Cluster-1 showed markedly higher CD4 and CD8 T-cell expression of HLADR and PD-1 versus cluster-2 and cluster-3 (all P < .0001). Although small, cluster-3 had significantly higher levels of cytokines reflecting inflammation (IL-6, IFN-γ, IP-10, IL-1RA, IL-10), chemotaxis (IL-8), systemic and vascular inflammation (CRP, ICAM-1, VCAM-1), and SAA (all P < .001). In mixed-effects models, cfPWV changes over time were similar for cluster-2 versus cluster-1 (relative fold-change, 0.99; 95% CI, .86–1.14; P = .91), but greater in cluster-3 versus cluster-1 (relative fold-change, 1.45; 95% CI, 1.01–2.09; P = .045).

Conclusions

Two inflammatory clusters were identified: one defined by high T-cell PD-1 expression and another by a hyperinflamed profile and increases in cfPWV on ART. Further clinical characterization of inflammatory phenotypes could help target vascular dysfunction interventions to those at highest risk.

Clinical Trials Network

NCT01825031.