Hot topics and trends in cardiovascular research.

AIMS: Comprehensive data on research undertaken in cardiovascular medicine can inform the scientific community and can support policy building. We used the publication output from 2004 to 2013 and the 2014 references to these documents, to identify research topics and trends in the field of cardiovascular disease. METHODS AND RESULTS: Text fragments were extracted from the titles and abstracts of 478 000 publications using natural language processing. Through machine-learning algorithms, these text fragments combined to identify specific topics across all publications. A second method, which included cross-references, assigned each publication document to a specific cluster. Experts named the topics and document clusters based on various outputs from these semi-automatic methods. We identified and labelled 175 cardiovascular topics and 20 large document clusters, with concordance between the approaches. Overarching, strongly growing topics in clinical and population sciences are evidence-based guidance for treatment, research on outcomes, prognosis, and risk factors. 'Hot' topics include novel treatments in valve disease and in coronary artery disease, and imaging. Basic research decreases its share over time but sees substantial growth of research on stem cells and tissue engineering, as well as in translational research. Inflammation, biomarkers, metabolic syndrome, obesity, and lipids are hot topics across population, clinical and basic research, supporting integration across the cardiovascular field. CONCLUSION: Growth in clinical and population research emphasizes improving patient outcomes through novel treatments, risk stratification, and prevention. Translation and innovation redefine basic research in cardiovascular disease. Medical need, funding and publishing policies, and scientific opportunities are potential drivers for these evolutions.

Mapping cross-border collaboration and communication in cardiovascular research from 1992 to 2012.

AIMS: The growing burden of cardiovascular disease requires growth in research and innovation. We examine world-wide participation and citation impact across the cardiovascular research landscape from 1992 to 2012; we investigate cross-fertilization between countries and examine whether cross-border collaboration affects impact. METHODS AND RESULTS: State-of-the-art bibliometric methods and indicators are used to identify cardiovascular publications from the Web of Science, and to map trends over time in output, citation impact, and collaboration. The publication output in cardiovascular research has grown steadily from 1992 to 2012 with increased participation worldwide. China has the highest growth as relative share. The USA share initially predominated yet has reduced steadily. Over time, the EU-27 supra-national region has increased its participation above the USA, though on average it has not had greater citation impact than the USA. However, a number of European countries, as well as Australia and Canada, have improved their absolute and relative citation impact above that of the USA by 2006-2012. Europe is a hub of cross-fertilization with strengthening collaborations and strong citation links; the UK, Germany, and France remain central in this network. The USA has the highest number of strong citation links with other countries. All countries, but especially smaller, highly collaborative countries, have higher citation impact for their internationally collaborative research when compared with their domestic publications. CONCLUSION: Participation in cardiovascular research is growing but growth and impact show wide variability between countries. Cross-border collaboration is increasing, in particular within the EU, and is associated with greater citation impact.

[Is there protection against copying? Thoughts about plagiarism]. / Van-e védelem a másolás ellen? Gondolatok a plágiumról.

There are at least two reasons why more and more cases of suspected plagiarism are perceived in the scientific literature. On one hand, the ever increasing pressure for publication makes it easier for authors, reviewers and editors to infringe or overlook this serious ethical misdemeanor; on the other hand, with the development of text analysis software, detecting text similarities has become a simple task. The judgement of actual cases, however, requires well-grounded professional knowledge and prudent human decisions.

Optimized data fusion for K-means Laplacian clustering.

MOTIVATION: We propose a novel algorithm to combine multiple kernels and Laplacians for clustering analysis. The new algorithm is formulated on a Rayleigh quotient objective function and is solved as a bi-level alternating minimization procedure. Using the proposed algorithm, the coefficients of kernels and Laplacians can be optimized automatically. RESULTS: Three variants of the algorithm are proposed. The performance is systematically validated on two real-life data fusion applications. The proposed Optimized Kernel Laplacian Clustering (OKLC) algorithms perform significantly better than other methods. Moreover, the coefficients of kernels and Laplacians optimized by OKLC show some correlation with the rank of performance of individual data source. Though in our evaluation the K values are predefined, in practical studies, the optimal cluster number can be consistently estimated from the eigenspectrum of the combined kernel Laplacian matrix. AVAILABILITY: The MATLAB code of algorithms implemented in this paper is downloadable from http://homes.esat.kuleuven.be/~sistawww/bioi/syu/oklc.html.

How scientific research reacts to international public health emergencies: a global analysis of response patterns.

As of the middle of April 2020, the unprecedented COVID-19 pandemic has claimed more than 137,000 lives (https://coronavirus.jhu.edu/map.html). Because of its extremely fast spreading, the attention of the global scientific community is now focusing on slowing down, containing and finally stopping the spread of this disease. This requires the concerted action of researchers and practitioners of many related fields, raising, as always in such situations the question, of what kind of research has to be conducted, what are the priorities, how has research to be coordinated and who needs to be involved. In other words, what are the characteristics of the response of the global research community on the challenge? In the present paper, we attempt to characterise, quantify and measure the response of academia to international public health emergencies in a comparative bibliometric study of multiple outbreaks. In addition, we provide a preliminary review of the global research effort regarding the defeat of the COVID-19 pandemic. From our analysis of six infectious disease outbreaks since 2000, including COVID-19, we find that academia always responded quickly to public health emergencies with a sharp increase in the number of publications immediately following the declaration of an outbreak by the WHO. In general, countries/regions place emphasis on epidemics in their own region, but Europe and North America are also concerned with outbreaks in other, developed and less developed areas through conducting intensive collaborative research with the core countries/regions of the outbreak, such as in the case of Ebola in Africa. Researches in the fields of virology, infectious diseases and immunology are the most active, and we identified two characteristic patterns in global science distinguishing research in Europe and America that is more focused on public health from that conducted in China and Japan with more emphasis on biomedical research and clinical pharmacy, respectively. Universities contribute slightly less than half to the global research output, and the vast majority of research funding originates from the public sector. Our findings on how academia responds to emergencies could be beneficial to decision-makers in research and health policy in creating and adjusting anti-epidemic/-pandemic strategies.

A Changing Landscape in Cardiovascular Research Publication Output: Bridging the Translational Gap.

The concern about predominance of basic discovery research and lack of translation into clinical medicine, and segregation between these research communities, led the authors to study these research communities through mapping networks of publications and cross-references. Cardiovascular research from 1993 to 2013 was published in 565 journals, including 104 new journals. Only 50% were published in core cardiovascular journals, such as the Journal of the American College of Cardiology, whereas one-half of cardiovascular publications were found in broader biomedical/multidisciplinary journals. The growth of the clinical journal community and merging into one broad journal community suggests a decreasing dichotomy between basic/preclinical and clinical research, potentially contributing to bridging the translational gap.

Widespread Use of Misidentified Cell Line KB (HeLa): Incorrect Attribution and Its Impact Revealed through Mining the Scientific Literature.

Continuous cell lines are widely used, but can result in invalid, irreproducible research data. Cell line misidentification is a common problem that can be detected by authentication testing; however, misidentified cell lines continue to be used in publications. Here we explore the impact of one misidentified cell line, KB (HeLa), on the scientific literature. We identified 574 articles between 2000 and 2014 that provided an incorrect attribution for KB, in accordance with its false identity as oral epidermoid carcinoma, but only 57 articles that provided a correct attribution for KB, as HeLa or cervical adenocarcinoma. Statistical analysis of 57 correct and 171 incorrect articles showed that the number of citations to these articles increased over time. Content analysis of 200 citing articles showed there was a tendency to describe the cell line in accordance with the description in the cited paper. Analysis of journal impact factor showed no significant difference between correct and incorrect groups. Articles using KB or citing that usage were most frequently published in the subject areas of pharmacology, pharmacy, oncology, and medicinal chemistry. These findings are important for science policy and support the need for journals to require authentication testing as a condition of publication. Cancer Res; 77(11); 2784-8. ©2017 AACR.

Co-Citation Analysis of Articles Published in Substance Abuse Journals: Intellectual Structure and Research Fields (2001-2012).

OBJECTIVE: The purpose of this study is to introduce a new methodology in the field of substance abuse, namely, co-citation analysis, which uses the bibliographic references of publications to establish the main thematic areas being researched and to identify the seminal documents that have contributed to establishing the intellectual foundation of the discipline at the present time. METHOD: We identified all bibliographic references that were cited in documents published in the substance abuse journals included in the Journal Citation Reports in the 2001-2012 period, generating a co-citation matrix. This matrix was used to perform a co-citation network analysis. RESULTS: The co-citation network analysis led to the identification of 56 prominent research clusters that bring together 698 documents; their subject matter constitutes the foundation of the discipline in the field's journals. CONCLUSIONS: Substance abuse research is dominated by a few core topics; chief among them are tools for measuring and diagnosing dependence, as well as therapeutic approaches to treat alcohol abuse and nicotine addiction. Other areas of note include epidemiological studies, research on drug user motivation (particularly among young people), binge drinking, social support mediators and networks, opioid dependence, consumption and effects of cannabis, basic research on brain damage, genetic factors associated with substance use, and the physiological and neurological determinants of abstinence syndrome. The main works of reference that we identified were published in a small number of journals, which establish the intellectual, conceptual, and methodological basis of the discipline.

Interdisciplinarity and impact: distinct effects of variety, balance, and disparity.

Interdisciplinary research is increasingly recognized as the solution to today's challenging scientific and societal problems, but the relationship between interdisciplinary research and scientific impact is still unclear. This paper studies the association between the degree of interdisciplinarity and the number of citations at the paper level. Different from previous studies compositing various aspects of interdisciplinarity into a single indicator, we use factor analysis to uncover distinct dimensions of interdisciplinarity corresponding to variety, balance, and disparity. We estimate Poisson models with journal fixed effects and robust standard errors to analyze the divergent relationships between these three factors and citations. We find that long-term (13-year) citations (1) increase at an increasing rate with variety, (2) decrease with balance, and (3) increase at a decreasing rate with disparity. Furthermore, interdisciplinarity also affects the process of citation accumulation: (1) although variety and disparity have positive effects on long-term citations, they have negative effects on short-term (3-year) citations, and (2) although balance has a negative effect on long-term citations, its negative effect is insignificant in the short run. These findings have important implications for interdisciplinary research and science policy.

Bibliometric Evidence for a Hierarchy of the Sciences.

The hypothesis of a Hierarchy of the Sciences, first formulated in the 19(th) century, predicts that, moving from simple and general phenomena (e.g. particle dynamics) to complex and particular (e.g. human behaviour), researchers lose ability to reach theoretical and methodological consensus. This hypothesis places each field of research along a continuum of complexity and "softness", with profound implications for our understanding of scientific knowledge. Today, however, the idea is still unproven and philosophically overlooked, too often confused with simplistic dichotomies that contrast natural and social sciences, or science and the humanities. Empirical tests of the hypothesis have usually compared few fields and this, combined with other limitations, makes their results contradictory and inconclusive. We verified whether discipline characteristics reflect a hierarchy, a dichotomy or neither, by sampling nearly 29,000 papers published contemporaneously in 12 disciplines and measuring a set of parameters hypothesised to reflect theoretical and methodological consensus. The biological sciences had in most cases intermediate values between the physical and the social, with bio-molecular disciplines appearing harder than zoology, botany or ecology. In multivariable analyses, most of these parameters were independent predictors of the hierarchy, even when mathematics and the humanities were included. These results support a "gradualist" view of scientific knowledge, suggesting that the Hierarchy of the Sciences provides the best rational framework to understand disciplines' diversity. A deeper grasp of the relationship between subject matter's complexity and consensus could have profound implications for how we interpret, publish, popularize and administer scientific research.

Optimized data fusion for kernel k-means clustering.

This paper presents a novel optimized kernel k-means algorithm (OKKC) to combine multiple data sources for clustering analysis. The algorithm uses an alternating minimization framework to optimize the cluster membership and kernel coefficients as a nonconvex problem. In the proposed algorithm, the problem to optimize the cluster membership and the problem to optimize the kernel coefficients are all based on the same Rayleigh quotient objective; therefore the proposed algorithm converges locally. OKKC has a simpler procedure and lower complexity than other algorithms proposed in the literature. Simulated and real-life data fusion applications are experimentally studied, and the results validate that the proposed algorithm has comparable performance, moreover, it is more efficient on large-scale data sets. (The Matlab implementation of OKKC algorithm is downloadable from http://homes.esat.kuleuven.be/~sistawww/bio/syu/okkc.html.).

A new generation of relational charts for comparative assessment of citation impact.

A common problem in comparative bibliometric studies at the meso and micro level is the differentiation and specialization of research profiles of the objects of analysis at lower levels of aggregation. In this study, institutional profile clusters are used to examine which level of the hierarchical subject classification should preferably be used to build subject-normalized citation indicators. It is shown that a set of properly normalized indicators can serve as a basis of comparative assessment within and even among different clusters, provided that their profiles still overlap and such comparison is thus meaningful. Using the example of 24 European universities, a new version of relational charts is presented for the comparative assessment of citation impact.