bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ensembling graph attention networks for human microbe–drug association prediction
Authors: Long Yahui , Wu Min , Liu Yong , Kwoh Chee Keong , Luo Jiawei , Li Xiaoli 
Published: October 2020

AbstractMotivationHuman microbes get closely involved in an extensive variety of complex human diseases and become new drug targets. In silico methods for identifying potential microbe–drug associations provide an effective complement to conventional experimental methods, which can not only benefit screening candidate compounds for drug development but also facilitate novel knowledge discovery for understanding microbe–drug interaction mechanisms. On the other hand, the recent increased availability of accumulated biomedical data for microbes and drugs provides a great opportunity for a machine learning approach to predict microbe–drug associations. We are thus highly motivated to integrate these data sources to improve prediction accuracy. In addition, it is extremely challenging to predict interactions for new drugs or new microbes, which have no existing microbe–drug associations.ResultsIn this work, we leverage various sources of biomedical information and construct multiple networks (graphs) for microbes and drugs. Then, we develop a novel ensemble framework of graph attention networks with a hierarchical attention mechanism for microbe–drug association prediction from the constructed multiple microbe–drug graphs, denoted as EGATMDA. In particular, for each input graph, we design a graph convolutional network with node-level attention to learn embeddings for nodes (i.e. microbes and drugs). To effectively aggregate node embeddings from multiple input graphs, we implement graph-level attention to learn the importance of different input graphs. Experimental results under different cross-validation settings (e.g. the setting for predicting associations for new drugs) showed that our proposed method outperformed seven state-of-the-art methods. Case studies on predicted microbe–drug associations further demonstrated the effectiveness of our proposed EGATMDA method.AvailabilitySource codes and supplementary materials are available at: https://github.com/longyahui/EGATMDA/Supplementary informationSupplementary data are available at Bioinformatics online.
GNET2: an R package for constructing gene regulatory networks from transcriptomic data
Authors: Chen Chen , Hou Jie , Shi Xiaowen , Yang Hua , Birchler James A , Cheng Jianlin 
Published: October 2020

Abstract

Motivation
The Gene Network Estimation Tool (GNET) is designed to build gene regulatory networks (GRNs) from transcriptomic gene expression data with a probabilistic graphical model. The data preprocessing, model construction and visualization modules of the original GNET software were developed on different programming platforms, which were inconvenient for users to deploy and use.

Results
Here, we present GNET2, an improved implementation of GNET as an integrated R package. GNET2 provides more flexibility for parameter initialization and regulatory module construction based on the core iterative modeling process of the original algorithm. The data exchange interface of GNET2 is handled within an R session automatically. Given the growing demand for regulatory network reconstruction from transcriptomic data, GNET2 offers a convenient option for GRN inference on large datasets.

Availability and implementation
The source code of GNET2 is available at https://github.com/jianlin-cheng/GNET2.

Supplementary information
Supplementary data are available at Bioinformatics online.
Role Stress and Depressive Symptoms Amongst Social Workers in China: The Moderating Effects of Social Support
Authors: Li Xin , Zhang Nannan , He Xuesong 
Published: October 2020

Abstract
This study aims to examine the association between role stress and depressive symptoms, as well as moderating effects of social support on the association between role stress and depressive symptoms. The data come from the baseline survey of the ‘China Social Work Longitudinal Study’ collected in 2019, which contains 5,965 social workers. Depressive symptoms were assessed with the Center for Epidemiologic Studies Depression Scale. Role stress was assessed by using two standardised scales of role conflict (RC) and role ambiguity (RA). Workplace support included organisational support, supervisor support and co-worker support. Family support was measured by assessing family’s attitude towards social work profession. Hierarchical regression analyses were employed. We found that after adjusting for covariates, RC and RA were positively associated with depressive symptoms, whereas co-worker support, organisational support and family support were negatively associated with depressive symptoms. In addition, family support was found to significantly moderate the association between role stress and depressive symptoms. However, workplace support was not found to act as a moderator against the negative effect of role stress on depressive symptoms. Findings demonstrate social service agencies need to make efforts to assist social workers in recognising and utilising any existing social support.
Latent Class Analysis for the Diagnosis of Clostridioides difficile Infection
Authors: Doolan Cody P , Louie Thomas , Lata Christopher , Larios Oscar E , Stokes William , Kim Joseph , Brown Kristen , Beck Paul , Deardon Rob , Pillai Dylan R 
Published: October 2020

Abstract

Background
Clostridioides difficile infection (CDI) is an opportunistic disease that lacks a gold-standard test. Nucleic acid amplification tests such as real-time polymerase chain reaction (PCR) demonstrate an excellent limit of detection (LOD), whereas antigenic methods are able to detect protein toxin. Latent class analysis (LCA) provides an unbiased statistical approach to resolving true disease.

Methods
A cross-sectional study was conducted in patients with suspected CDI (N = 96). Four commercial real-time PCR tests, toxin antigen detection by enzyme immunoassay (EIA), toxigenic culture, and fecal calprotectin were performed. CDI clinical diagnosis was determined by consensus majority of 3 experts. LCA was performed using laboratory and clinical variables independent of any gold standard.

Results
Six LCA models were generated to determine CDI probability using 4 variables including toxin EIA, toxigenic culture, clinical diagnosis, and fecal calprotectin levels. Three defined zones as a function of real-time PCR cycle threshold (Ct) were identified using LCA: CDI likely (&gt;90% probability), CDI equivocal (&lt;90% and &gt;10%), CDI unlikely (&lt;10%). A single model comprising toxigenic culture, clinical diagnosis, and toxin EIA showed the best fitness. The following Ct cutoffs for 4 commercial test platforms were obtained using this model to delineate 3 CDI probability zones: GeneXpert®: 24.00, 33.61; Simplexa®: 28.97, 36.85; Elite MGB®: 30.18, 37.43; and BD Max™: 27.60, 34.26.

Conclusions
The clinical implication of applying LCA to CDI is to report Ct values assigned to probability zones based on the commercial real-time PCR platform. A broad range of equivocation suggests clinical judgment is essential to the confirmation of CDI.
Network topology of the Argentine interbank money market
Authors: Forte Federico D 
Published: October 2020

AbstractThis article provides the first empirical network analysis of the Argentine interbank money market. Its main topological features are examined applying graph theory, focusing on the unsecured overnight loans settled from 2003 to 2017. The network, where banks are the nodes and the operations between them represent the links, exhibits low density, a higher reciprocity than comparable random graphs, short average distances and its clustering coefficient remains above that of a random network of equal size. Furthermore, the network is prominently disassortative. Its structural metrics experienced significant volatility, in correlation with the economic activity fluctuations and regulatory shifts. Signs of nodes’ random-like behaviour are detected during contractions. The degree distributions fit better to a Lognormal distribution than to a Poisson or a Power Law. Additionally, different node centrality measures are computed. It is found that a higher centrality enables a node to settle more convenient bilateral interest rates compared to the average market rate, identifying a statistical and economically significant effect by means of a regression analysis. These results constitute a relevant input for systemic risk assessment and provide solid empirical foundations for future theoretical modelling and shock simulations, especially in the context of underdeveloped financial systems.
The year 2019 in the European Heart Journal – Cardiovascular Imaging: part II
Authors: Cosyns Bernard , Haugaa Kristina H , Gerber Bernrhard , Gimelli Alessia , Sade Leyla Elif , Maurer Gerald , Popescu Bogdan A , Edvardsen Thor 
Published: October 2020

Abstract
The European Heart Journal – Cardiovascular Imaging was launched in 2012 and has during these years become one of the leading multimodality cardiovascular imaging journal. The journal is now established as one of the top cardiovascular journals and is the most important cardiovascular imaging journal in Europe. The most important studies published in our Journal from 2019 will be highlighted in two reports. Part II will focus on valvular heart disease, heart failure, cardiomyopathies, and congenital heart disease. While Part I of the review has focused on studies about myocardial function and risk prediction, myocardial ischaemia, and emerging techniques in cardiovascular imaging.
Front-of-pack nutrition labelling to promote healthier diets: current practice and opportunities to strengthen regulation worldwide
Authors: Jones A 
Published: October 2020

Abstract
Unhealthy diets are a leading cause of death and disability globally. The WHO recommends Member States implement front-of-pack (FOP) nutrition labels to guide consumers towards healthier food choices, as part of comprehensive strategies to prevent diet-related non-communicable diseases. Interest in FOP nutrition labelling is increasing, but there is limited guidance for policymakers developing regulations necessary for effective implementation. A rapidly evolving evidence base, limited regulatory capacity and possibility of legal challenge by affected food industry stakeholders can create ‘regulatory chill', whereby governments are dissuaded from progressive public health policymaking. We use a framework for analysing public health law and available best-practice guidance to evaluate key components of 31 FOP nutrition labelling regulations endorsed by governments up to June 2019. Analysis of regulatory form shows recent rapid uptake of label formats that are easier for consumers to understand and increasing use of mandatory legislation. However, policymakers must decide much more than whether to apply ‘stars', ‘traffic lights' or ‘stop signs'. The substance of effective regulation must contain strategic regulatory objectives, clear specifications for displaying the label on pack, a valid scoring mechanism and a justified scope for including foods. While there are limited data on current practice, good governance of FOP nutrition labelling regulation also requires transparency and accountability in processes of label development, implementation, evaluation and enforcement to promote continuous improvement and withstand undue commercial interference. Whether developing new FOP nutrition labels or reforming existing ones, our findings support policymakers to design and implement best-practice, evidence-informed regulation.
Recent trends of climate disasters: Lessons we can learn
Authors: Wannous C 
Published: October 2020

Abstract
Dr Chadia Wannous has more than twenty-five years of experience in program management, coordination, and research with particular focus on emergency preparedness and response and risk reduction of health threats. She is currently Coordinator and Senior Advisor at the Towards a Safer World Network for Pandemic Preparedness (TASW). For the past decade, Dr. Wannous served in the UN Office for Disaster Risk Reduction (UNISDR) in Switzerland as Senior Policy Advisor coordinating the implementation and advocacy for the health components of the Sendai Framework for Disaster Risk Reduction and the Science and Technology Partnership, to optimize UN work on global initiatives related to preparedness and response.
This data rich presentation provides a global scan of health impact of climate change and recent health mitigation and adaptation measures.
Dr Wannous will speak to specific examples, what led to these climate initiated disasters, what went wrong or served to exacerbate the catastrophes in terms of preparedness and responses. She will share the lessons learned providing real examples of both public health successes and ‘failures'.
Pharmacists’ one-to-one counseling succeeds in promoting flu shots among target population
Authors: Brunelli L , Morsanutto A , Tosolini M , Iob A , Schiava F , Degrassi L , Pancino C , Andreatti M , Tonutti G , Brusaferro S 
Published: October 2020

Abstract

Background
Vaccine hesitancy among general population can be even greater regarding flu than other vaccine preventable diseases, as complacency towards influenza is quite high and confidence can be reduced by the confounding effect of influenza-like-illnesses. Health professionals face hesitant people alleging many different motivations against flu vaccination, some of them being susceptible to tailored one-to-one health promotion.

Methods
During 2019/20 flu vaccination campaign, 44 trained pharmacists of Carnia District in Friuli Venezia Giulia Region (Italy) surveyed at-risk people accessing 25 pharmacies regarding beliefs on flu vaccination and offered one-to-one advice. As stated in the Italian national vaccination plan, subjects with comorbidities or older than 65 were considered at risk. Adherence to influenza vaccination during past flu season and reasons for that choice, as well as intention to be administered flu shots after counseling were registered.

Results
A total of 2,748 at-risk subjects adhered to the project with a mean age of 70±12 years, 57% of them being females; 1,702 (38%) did not adhere to flu vaccination campaign last year. Most of them confirmed a low complacency level, reporting to have refused flu vaccination because of “not getting ill” (43%) believing that vaccines are dangerous (12%) or not effective (5%); some did not know they could access flu vaccination (8%). After counseling, 2196 (80%) decided to adhere to flu vaccination, in particular 83% (1284/1555) of over 65 and 84% (684/816) of at-risk subjects.

Conclusions
More than one third of over 65 or at-risk surveyed subjects did not receive influenza vaccination during 2018/19 flu season. One-to-one tailored counseling conducted by pharmacists resulted to be effective in tackling vaccine hesitancy among 2019/20 flu shot target population.

Key messages
Motivations underlying vaccine hesitancy toward flu vaccination continue to impair health outcomes of target population. A one-to-one counseling intervention conducted by pharmacists with specific targets should be useful to improve seasonal flu vaccine coverage.
The RHD Endgame Strategy; the blueprint to eliminate rheumatic heart disease in Australia by 2031
Authors: Wyber R , Noonan K , Halkon C , Enkel S , Carapetis J 
Published: October 2020

Abstract

Background
Rheumatic heart disease (RHD) is a preventable yet deadly condition resulting from untreated Group A Streptococcus infection. Despite being eliminated from most high-income countries, RHD and its precursor acute rheumatic fever (ARF) persist in developing countries and settings of disadvantage. In Australia, Aboriginal and Torres Strait Islander people experience among the world's highest rates. Following five years of research, investigation and advocacy, the Endgame Strategy provides a technical foundation to eliminate RHD in Australia by 2031.

Methods
A range of potential strategies to reduce ARF and RHD were identified. Approaches at the social and environmental, primary, secondary and tertiary prevention levels were evaluated using the GRADE Evidence to Decision framework, together with structural review of the health system. Recommendations were made according to level of prevention opportunity and responsibility. Modelling was undertaken to estimate the health and economic impact of an indicative bundle of the most promising strategies.

Results
Reducing household crowding, improving health infrastructure, strengthening primary healthcare and enhancing delivery of secondary prophylaxis were identified as having the greatest potential impact on RHD. They are also largely acceptable, practical and readily implementable with investment. Modelling indicates that this approach would reduce ARF and RHD by 69% and 71% respectively, preventing 471 deaths and saving $188 million on healthcare expenditure to 2031.

Conclusions
Eliminating RHD is only possible with a holistic approach led by Aboriginal and Torres Strait Islander people with communities at the core. This will entail funding communities to develop programs, resourcing a national RHD unit to coordinate efforts across Australia, guaranteeing access to healthy housing and built environments, establishing comprehensive skin and throat programs and improving the health of those living with ARF and RHD.

Key messages
RHD demands responses from the health sector strengthened by political advocacy and engagement to drive evidence-based decision making. The evidence and collective experience now exist to eliminate RHD, an exemplar of the gap in health outcomes between Aboriginal and Torres Strait Islander peoples and the non-Indigenous population.
Coronavirus - Crisis Communication in Croatia
Authors: Grbic M , Grbic D Stimac , Stimac L , Sostar Z 
Published: October 2020

Abstract

Introduction
The coronavirus outbreak has set off alarms around the world, leading to border closures, trade controls, travel bans and other measures. The Wuhan coronavirus epidemic continues to spread globally to the new European hotspot in Italy. New information about the epidemic and the virus is changing rapidly as the virus spreads and appears in parts of the world. Although official announcements by the Croatian Government and Crisis Staff calmed the public with pictures and data on the disease, it showed something else that heightened public concern and caused two conflicting phenomena among citizens - on the one hand, the majority showed understandable doubt about the information that could have raised the concern for their own health while the rest of the population ignored the facts. The market showed complete unwillingness to cope with this epidemic and a chronic shortage of protective equipment (masks, disinfectants...) emerged. Most of the citizens' queries and concerns were moving in the direction of personal protection, child protection and justification for holding large gatherings.

Results
By March 8, 2020, twelve COVID-19 patients were recorded in Croatia, of which 5 were patients in Rijeka, 3 in Zagreb and 4 in VaraÅ¾din. The first sick person is a Croatian citizen from Zagreb who became infected during his stay in Italy (Milan, Lombardy province).

Conclusions
In this crisis, several basic principles of crisis communication with the public have been forgotten: The first source of communication often becomes the source against which everyone else is measured.Accuracy is crucial to credibility.Emotion cannot be countered by facts. People must first know that the government cares.The public should regain a sense of control over circumstances beyond control.A lack of public respect in a crisis undermines trust.Honesty is fundamental to maintaining trust.

Key messages
Accuracy is crucial to credibility. Emotion cannot be countered by facts.
COVID-19 and newspapers: a content & text mining analysis
Authors: Corvo E , De Caro W 
Published: October 2020

Abstract

Background
COVID-19 occurred in Italy in February, after its outbreak in China. The number of news on newspapers and on media was massive, however, this communication did not take into account properly the level of comprehension of general public of health related issues, which in turns can have a huge impact on public health and related policies. In the light of above this study aims to analyze press coverage during the COVID-19 pandemic/epidemic in Italy.

Methods
An analysis of the press and related online journal coverage during CoVID-19 was conducted. A total of 1512 articles in two months were analyzed. Two main analyses were carried out, a coding quantitative content analysis of newspapers article data and a textual analysis and a sentiment analysis using Taltac 2.10 and Voyant Tools.

Results
There was an overall similar idea among different newspapers, this means that both tabloids and broadsheet newspapers show an overall similar content, with a small difference on quality and tone. Results, moreover, displayed two different chronologically lead trends during the COVID-19 crisis. The first two week articles were mainly focused on the illness per se, in terms of prevention, care, cure but also fear, and anxiety; while after a while, around 2 months later newspapers were much more focused on the socio-political-economic impact that COVID-19 had on Italy and potentially could have in the closer future, also for the health organizations.

Conclusions
Newspaper attitude in publishing sensationalistic articles and titles show to take small account of the effect that could potentially have on general public understanding of the issues connected to the virus. This both in the outbreak in terms of what could be the effect of the virus on their health and later on the economy of the country. More attention should be paid in analysing the impact that newspaper communication has on general public behavior and reactions.

Key messages
Information is crucial for the management of epidemic/pandemic disease. Panic of population is the result of inaccurate information communication.