bluuebunny/crossref_metadata_2025_split huggingface dataset:
Power of Microbiome Beta-Diversity Analyses Based on Standard Reference Samples
Authors: Gail Mitchell H , Wan Yunhu , Shi Jianxin 
Published: September 2020

Abstract
A simple method to analyze microbiome beta-diversity computes mean beta-diversity distances from a test sample to standard reference samples. We used reference stool and nasal samples from the Human Microbiome Project and regressed an outcome on mean distances (2 degrees-of-freedom (df) test) or additionally on squares and cross-product of mean distances (5-df test). We compared the power of 2-df and 5-df tests with the microbiome regression-based kernel association test (MiRKAT). In simulations, MiRKAT had moderately greater power than the 2-df test for discriminating skin versus saliva and skin versus nasal samples, but differences were negligible for skin versus stool and stool versus nasal samples. The 2-df test had slightly greater power than MiRKAT for Dirichlet multinomial samples. In associating body mass index with beta-diversity in stool samples from the American Gut Project, the 5-df test yielded smaller P values than MiRKAT for most taxonomic levels and beta-diversity measures. Unlike procedures like MiRKAT that are based on the beta-diversity matrix, mean distances to reference samples can be analyzed with standard statistical tools and shared or meta-analyzed without sharing primary DNA data. Our data indicate that standard reference tests have power comparable to MiRKAT’s (and to permutational multivariate analysis of variance), but more simulations and applications are needed to confirm this.
Current Smoking Raises Risk of Incident Hypertension: Hispanic Community Health Study–Study of Latinos
Authors: Kaplan Robert C , Baldoni Pedro L , Strizich Garrett M , Pérez-Stable Eliseo J , Saccone Nancy L , Peralta Carmen A , Perreira Krista M , Gellman Marc D , Williams-Nguyen Jessica S , Rodriguez Carlos J , Lee David J , Daviglus Martha , Talavera Gregory A , Lash James P , Cai Jianwen , Franceschini Nora 
Published: September 2020

Abstract

Background
Hypertension has been implicated as a smoking-related risk factor for cardiovascular disease but the dose–response relationship is incompletely described. Hispanics, who often have relatively light smoking exposures, have been understudied in this regard.

Methods
We used data from a 6-year follow-up study of US Hispanic adults aged 18–76 to address the dose–response linking cigarette use with incident hypertension, which was defined by measured blood pressure above 140/90 mm Hg or initiation of antihypertensive medications. Adjustment was performed for potential confounders and mediators, including urinary albumin-to-creatinine ratio which worsened over time among smokers.

Results
Current smoking was associated with incident hypertension, with a threshold effect above 5 cumulative pack-years of smoking (vs. never smokers, hazard ratio for hypertension [95% confidence interval] of 0.95 [0.67, 1.35] for 0–5 pack-years, 1.47 [1.05, 2.06] for 5–10 pack-years, 1.40 [1.00, 1.96] for 10–20 pack-years, and 1.34 [1.09, 1.66] for ≥20 pack-years, P = 0.037). In contrast to current smokers, former smokers did not appear to have increased risk of hypertension, even at the highest cumulative pack-years of past exposure.

Conclusions
The results confirm that smoking constitutes a hypertension risk factor in Hispanic adults. A relatively modest cumulative dose of smoking, above 5 pack-years of exposure, raises risk of hypertension by over 30%. The increased hypertension risk was confined to current smokers, and did not increase further with higher pack-year levels. The lack of a smoking–hypertension association in former smokers underscores the value of smoking cessation.
Where Did ‘Human Dignity’ Come from? Drafting the Preamble to the Irish Constitution
Authors: McCrudden Christopher 
Published: September 2020

Abstract
This article addresses the correctness of Samuel Moyn’s contention that the inclusion of ‘dignity’ in the Irish Constitution of 1937 reflects a particularistic, sectarian and conservative Catholic viewpoint, rather than (as some other scholars do) seeing the inclusion of ‘dignity’ as the first tentative step towards the instantiation of a universalistic, liberal human rights ethic into the Irish Constitution. For Moyn, ‘dignity’s’ sectarian, political origins in Ireland add weight to his sceptical approach to human rights more generally, given the extent to which human dignity is now seen as underpinning the justification of human rights. In arguing against Moyn’s conclusions, the article provides a detailed re-examination, based on archival research, of the drafting of the Preamble to the Irish Constitution in which the term ‘dignity’ is located, situating it in the intellectual changes in political Catholicism and Irish nationalism at that time. In particular, the article examines for the first time to what extent insights can be gleaned from the contemporaneous translation of ‘dignity’ into the Irish language version of the Constitution, and the significance of the choice of ‘uaisleacht’ in the Irish text. Drawing from this, the article identifies the various different influences that appear to have contributed to the use and meaning of dignity in the Preamble, before returning to consider how far Moyn’s assessments are correct in light of the re-examination of the drafting history.
Future Alcohol-Attributable Mortality in France Using a Novel Generalizable Age-Period-Cohort Projection Methodology
Authors: Trias-Llimós Sergi , Bardoutsos Anastasios , Janssen Fanny 
Published: September 2020

Abstract

Aim
To forecast age- and sex-specific alcohol-attributable mortality in France for the period 2015–2050 using a novel generalizable methodology that includes different scenarios regarding period and cohort change.

Methods
For the French national population aged 25–90 years (1979–2014), we estimated alcohol-attributable mortality by mortality from the main causes of death wholly attributable to alcohol, plus liver cirrhosis mortality. We modelled sex-specific alcohol-attributable mortality by adjusting for age, period and birth cohort. We forecasted the model parameters to obtain future age- and sex-specific alcohol-attributable mortality up until 2050 using a conventional baseline, scenario I (favourable period change) and scenario II (unfavourable cohort change).

Results
Alcohol-attributable mortality is clearly declining in France, with the decline decelerating from 1992 onwards. In 2014, the age-standardized alcohol-attributable mortality rates, in deaths per 100,000, were 34.7 among men and 9.9 among women. In 2050, the estimated rates are between 10.5 (prediction interval: 7.6–14.4; scenario I) and 17.6 (13.1–23.7; scenario II) among men, and between 1.1 (0.7–1.7; scenario I) and 1.8 (1.2–2.9; scenario II) among women; which implies declines of 58% for men and 84% for women (baseline).

Conclusion
Alcohol-attributable mortality in France is expected to further decline in the coming decades, accompanied by age pattern changes. However, France’s levels are not expected to reach the current lower levels in Italy and Spain for 15 years or more. Our results point to the value of implementing preventive policy measures that discourage alcohol consumption among people of all ages, but especially among adolescents.
Vegetation structure drives mixed-species flock interaction strength and nuclear species roles
Authors: Jones Harrison H , Robinson Scott K 
Published: September 2020

Abstract
Mixed-species flocks are a key facilitative interaction for tropical birds. Forest fragmentation leads to species loss and spatial turnover in these flocks, yet it is unknown how these changes to composition influence within-flock species interactions. We used network analysis to characterize flocking interactions along a fragment-size gradient in the Colombian Western Andes. We asked 1) how patch size, edge density, and vegetation structure explained network measures indicative of flock cohesion, 2) whether changes were driven by flocking species turnover or changes to the frequency of species co-occurrence, and 3) whether nuclear species, those that maintain flock stability and cohesion, changed in importance across the gradient. We constructed weighted social networks from flock compositions observed on 500-m transects, and then calculated global network measures and the centrality of six nuclear species. Patch size and edge density did not correlate with interspecific co-occurrence patterns, but interaction strength increased with canopy height. Flocks contained numerous, weak interactions, and there were no flock subtypes, suggesting flock composition was dynamic and unstructured. Several redundant nuclear species were present and varied in importance based on ecological conditions. A chlorospingus (Passerellidae) was most central in old-growth forest, whereas several tanager (Thraupidae) species became more central in smaller fragments and disturbed forest. When partitioning network dissimilarity, we found that 66% of dissimilarity resulted from species turnover, whereas only 34% resulted from changes to species co-occurrence. This finding suggests that coherence of flocking behavior itself is maintained even as extensive species turnover occurs from continuous forest to small fragments.
IHP-PING—generating integrated human protein–protein interaction networks on-the-fly
Authors: Mazandu Gaston K , Hooper Christopher , Opap Kenneth , Makinde Funmilayo , Nembaware Victoria , Thomford Nicholas E , Chimusa Emile R , Wonkam Ambroise , Mulder Nicola J 
Published: September 2020

Abstract
Advances in high-throughput sequencing technologies have resulted in an exponential growth of publicly accessible biological datasets. In the ‘big data’ driven ‘post-genomic’ context, much work is being done to explore human protein–protein interactions (PPIs) for a systems level based analysis to uncover useful signals and gain more insights to advance current knowledge and answer specific biological and health questions. These PPIs are experimentally or computationally predicted, stored in different online databases and some of PPI resources are updated regularly. As with many biological datasets, such regular updates continuously render older PPI datasets potentially outdated. Moreover, while many of these interactions are shared between these online resources, each resource includes its own identified PPIs and none of these databases exhaustively contains all existing human PPI maps. In this context, it is essential to enable the integration of or combining interaction datasets from different resources, to generate a PPI map with increased coverage and confidence. To allow researchers to produce an integrated human PPI datasets in real-time, we introduce the integrated human protein–protein interaction network generator (IHP-PING) tool. IHP-PING is a flexible python package which generates a human PPI network from freely available online resources. This tool extracts and integrates heterogeneous PPI datasets to generate a unified PPI network, which is stored locally for further applications.
LipidFinder 2.0: advanced informatics pipeline for lipidomics discovery applications
Authors: Alvarez-Jarreta Jorge , Rodrigues Patricia R S , Fahy Eoin , O’Connor Anne , Price Anna , Gaud Caroline , Andrews Simon , Benton Paul , Siuzdak Gary , Hawksworth Jade I , Valdivia-Garcia Maria , Allen Stuart M , O’Donnell Valerie B 
Published: September 2020

Abstract

Summary
We present LipidFinder 2.0, incorporating four new modules that apply artefact filters, remove lipid and contaminant stacks, in-source fragments and salt clusters, and a new isotope deletion method which is significantly more sensitive than available open-access alternatives. We also incorporate a novel false discovery rate method, utilizing a target–decoy strategy, which allows users to assess data quality. A renewed lipid profiling method is introduced which searches three different databases from LIPID MAPS and returns bulk lipid structures only, and a lipid category scatter plot with color blind friendly pallet. An API interface with XCMS Online is made available on LipidFinder’s online version. We show using real data that LipidFinder 2.0 provides a significant improvement over non-lipid metabolite filtering and lipid profiling, compared to available tools.

Availability and implementation
LipidFinder 2.0 is freely available at https://github.com/ODonnell-Lipidomics/LipidFinder and http://lipidmaps.org/resources/tools/lipidfinder.

Supplementary information
Supplementary data are available at Bioinformatics online.
PredHPI: an integrated web server platform for the detection and visualization of host–pathogen interactions using sequence-based methods
Authors: Loaiza Cristian D , Kaundal Rakesh 
Published: September 2020

Abstract

Motivation
Understanding the mechanisms underlying infectious diseases is fundamental to develop prevention strategies. Host–pathogen interactions (HPIs) are actively studied worldwide to find potential genomic targets for the development of novel drugs, vaccines and other therapeutics. Determining which proteins are involved in the interaction system behind an infectious process is the first step to develop an efficient disease control strategy. Very few computational methods have been implemented as web services to infer novel HPIs, and there is not a single framework which combines several of those approaches to produce and visualize a comprehensive analysis of HPIs.

Results
Here, we introduce PredHPI, a powerful framework that integrates both the detection and visualization of interaction networks in a single web service, facilitating the apprehension of model and non-model host–pathogen systems to aid the biologists in building hypotheses and designing appropriate experiments. PredHPI is built on high-performance computing resources on the backend capable of handling proteome-scale sequence data from both the host as well as pathogen. Data are displayed in an information-rich and interactive visualization, which can be further customized with user-defined layouts. We believe PredHPI will serve as an invaluable resource to diverse experimental biologists and will help advance the research in the understanding of complex infectious diseases.

Availability and implementation
PredHPI tool is freely available at http://bioinfo.usu.edu/PredHPI/.

Supplementary information
Sup plementary data are available at Bioinformatics online.
Assessing the fit of the multi-species network coalescent to multi-locus data
Authors: Cai Ruoyi , Ané Cécile 
Published: September 2020

Abstract

Motivation
With growing genome-wide molecular datasets from next-generation sequencing, phylogenetic networks can be estimated using a variety of approaches. These phylogenetic networks include events like hybridization, gene flow or horizontal gene transfer explicitly. However, the most accurate network inference methods are computationally heavy. Methods that scale to larger datasets do not calculate a full likelihood, such that traditional likelihood-based tools for model selection are not applicable to decide how many past hybridization events best fit the data. We propose here a goodness-of-fit test to quantify the fit between data observed from genome-wide multi-locus data, and patterns expected under the multi-species coalescent model on a candidate phylogenetic network.

Results
We identified weaknesses in the previously proposed TICR test, and proposed corrections. The performance of our new test was validated by simulations on real-world phylogenetic networks. Our test provides one of the first rigorous tools for model selection, to select the adequate network complexity for the data at hand. The test can also work for identifying poorly inferred areas on a network.

Availability and implementation
Software for the goodness-of-fit test is available as a Julia package at https://github.com/cecileane/QuartetNetworkGoodnessFit.jl.

Supplementary information
Supplementary data are available at Bioinformatics online.
Financial Well-Being of the Non-Profit Social Service Workforce in China
Authors: Zhou Ling , Guo Baorong , Huang Jin 
Published: September 2020

Abstract
Using secondary data from the 2017 online survey of 736 non-profit social service employees in urban China, this study provides a complete description of the financial well-being of the non-profit social service workforce and examines correlates of financial well-being. Results show that non-profit employees’ household income is lower than the disposable income of a typical urban household. Nearly one-third of social service professionals have short-term unsecured debts, 10 per cent do not have public health insurance coverage and another 22 per cent report economic hardships caused by large unexpected expenses. Correlates of financial well-being include individual characteristics (e.g. age, education and marital status) and organizational characteristics (type, revenue and size). New services (e.g. employment-based programmes and financial services) are proposed to promote financial well-being of non-profit social service employees in China.
GDF15 serves as a coactivator to enhance KISS-1 gene transcription through interacting with Sp1
Authors: Zhou Bo , Huang Wen-he , Chen Shaoying , Chen Weibin , Peng Pei , Zhou Yanchun , Gu Wei 
Published: September 2020

Abstract
GDF15 has been recently recognized as a tumor-suppressive gene. However, the underlying mechanism by which GDF15 affects breast carcinogenesis is not well understood. Here, we showed that the inhibitory effect of GDF15 on cell proliferation was dependent on the nuclear localization of the protein. Dynamic translocation of GDF15 into the nucleus altered expression of a number of genes, including KISS-1, and resulted in inhibition of cell growth and invasive behavior. Using KISS-1 promoter-driven luciferase reporter and chromatin immunoprecipitation assays, we demonstrated that, in highly malignant breast cancer cells, GDF15 directly interacts with specific protein-1 (Sp1) at the Sp1-binding sites of the KISS-1 promoter, leading to upregulated KISS-1 expression. Our study indicates that nuclear GDF15 could serve as a transcriptional coactivator to mediate the expression of particular genes to reduce cell proliferation.
Exploration and practice of intelligent engineering in Dadu River hydropower construction
Authors: Duan Bin , Tu Yangju , Li Shanping , Yan Qinzhi 
Published: September 2020

Abstract
In view of the difficulties in promoting intelligent management in the field of engineering construction, based on the concept of intelligent enterprise and the actual situation of hydropower project-construction management, this paper puts forward the basic concept, main features and general idea of intelligent engineering. Based on a review of the exploration, pilot construction and comprehensive practice of intelligent engineering in the hydropower construction of Dadu River, the practical results of the intelligent engineering of Dagangshan, Houziyan, Shaping-II and Shuangjiangkou hydropower stations are summarized. The technical system and management model of engineering an early-warning decision centre, intelligent dam project, intelligent underground project, intelligent electromechanical project, intelligent security control, intelligent service guarantee, intelligent environmental and water protection, and intelligent resource control in Shuangjiangkou hydropower station are introduced. It is proposed that intelligent engineering is a high integration of information technology, industrial technology and management technology. And it is pointed out that intelligent engineering will lead in the new development of water conservancy and the hydropower industry, and even the engineering-construction field, throughout the world.
Prediction of Social Influence for Provenance of Misinformation in Online Social Network Using Big Data Approach
Authors: P Kumaran , Sridhar Rajeswari 
Published: September 2020

AbstractOnline social networks (OSNs) is a platform that plays an essential role in identifying misinformation like false rumors, insults, pranks, hoaxes, spear phishing and computational propaganda in a better way. Detection of misinformation finds its applications in areas such as law enforcement to pinpoint culprits who spread rumors to harm the society, targeted marketing in e-commerce to identify the user who originates dissatisfaction messages about products or services that harm an organizations reputation. The process of identifying and detecting misinformation is very crucial in complex social networks. As misinformation in social network is identified by designing and placing the monitors, computing the minimum number of monitors for detecting misinformation is a very trivial work in the complex social network. The proposed approach determines the top suspected sources of misinformation using a tweet polarity-based ranking system in tandem with sarcasm detection (both implicit and explicit sarcasm) with optimization approaches on large-scale incomplete network. The algorithm subsequently uses this determined feature to place the minimum set of monitors in the network for detecting misinformation. The proposed work focuses on the timely detection of misinformation by limiting the distance between the suspected sources and the monitors. The proposed work also determines the root cause of misinformation (provenance) by using a combination of network-based and content-based approaches. The proposed work is compared with the state-of-art work and has observed that the proposed algorithm produces better results than existing methods.
Predicting smartphone location-sharing decisions through self-reflection on past privacy behavior
Authors: Wisniewski Pamela , Safi Muhammad Irtaza , Patil Sameer , Page Xinru 
Published: September 2020

AbstractSmartphone location sharing is a particularly sensitive type of information disclosure that has implications for users’ digital privacy and security as well as their physical safety. To understand and predict location disclosure behavior, we developed an Android app that scraped metadata from users’ phones, asked them to grant the location-sharing permission to the app, and administered a survey. We compared the effectiveness of using self-report measures commonly used in the social sciences, behavioral data collected from users’ mobile phones, and a new type of measure that we developed, representing a hybrid of self-report and behavioral data to contextualize users’ attitudes toward their past location-sharing behaviors. This new type of measure is based on a reflective learning paradigm where individuals reflect on past behavior to inform future behavior. Based on data from 380 Android smartphone users, we found that the best predictors of whether participants granted the location-sharing permission to our app were: behavioral intention to share information with apps, the “FYI” communication style, and one of our new hybrid measures asking users whether they were comfortable sharing location with apps currently installed on their smartphones. Our novel, hybrid construct of self-reflection on past behavior significantly improves predictive power and shows the importance of combining social science and computational science approaches for improving the prediction of users’ privacy behaviors. Further, when assessing the construct validity of the Behavioral Intention construct drawn from previous location-sharing research, our data showed a clear distinction between two different types of Behavioral Intention: self-reported intention to use mobile apps versus the intention to share information with these apps. This finding suggests that users desire the ability to use mobile apps without being required to share sensitive information, such as their location. These results have important implications for cybersecurity research and system design to meet users’ location-sharing privacy needs.