COVID-19 enabled co-authoring networks: a country-case analysis.

In this paper we seek to examine the co-authoring pattern of a select group of researchers that are affiliated with a specific country. By way of making use of standard bibliometric analysis, we explore the publication evolution of all COVID-19-related peer reviewed papers that have been (co)-authored by researchers that are affiliated with Greek institutions. The aim is to identify its advancement over time, the institutions involved and the countries with which the co-authors are affiliated with. The timeframe of the study spans from the moment that WHO Director-General declared the novel coronavirus outbreak a public health emergency of international concern (WHO, 2020. Archived: WHO timeline-covid-19. Retrieved from Archived: Who Timeline-COVID-19. https://www.who.int/news/item/27-04-2020-who-timeline---covid-19. Accessed on 10 May 2020., Archived: WHO timeline-covid-19), January 2020, to October 2020. Findings indicate that there is a steady increase in the number of publications as well as the number of scientific collaborations over time. At a cross-country level, results suggest that the affiliated institutional sectors such as the Higher Education Sector (HES) and the Government Sector (GOV) contributed the most in terms of scientific output. On an international scale, the evolution of the scientific collaboration is imprinted and distributed as a chain of affiliations that linked nations together. Such chains are represented as clusters of countries, in which the scientific connections between different countries can be visualised. It can be reasoned that a significant amount of publications (20%) is affiliated with countries having "traditionally" major scientific impact on the field of Medicine. Supplementary Information: The online version contains supplementary material available at 10.1007/s11192-021-03952-9.

HbA1c levels in non-diabetic older adults - No J-shaped associations with primary cardiovascular events, cardiovascular and all-cause mortality after adjustment for confounders in a meta-analysis of individual participant data from six cohort studies.

BACKGROUND: To determine the shape of the associations of HbA1c with mortality and cardiovascular outcomes in non-diabetic individuals and explore potential explanations. METHODS: The associations of HbA1c with all-cause mortality, cardiovascular mortality and primary cardiovascular events (myocardial infarction or stroke) were assessed in non-diabetic subjects ≥50 years from six population-based cohort studies from Europe and the USA and meta-analyzed. Very low, low, intermediate and increased HbA1c were defined as <5.0, 5.0 to <5.5, 5.5 to <6.0 and 6.0 to <6.5% (equals <31, 31 to <37, 37 to <42 and 42 to <48 mmol/mol), respectively, and low HbA1c was used as reference in Cox proportional hazards models. RESULTS: Overall, 6,769 of 28,681 study participants died during a mean follow-up of 10.7 years, of whom 2,648 died of cardiovascular disease. Furthermore, 2,493 experienced a primary cardiovascular event. A linear association with primary cardiovascular events was observed. Adjustment for cardiovascular risk factors explained about 50% of the excess risk and attenuated hazard ratios (95 confidence interval) for increased HbA1c to 1.14 (1.03-1.27), 1.17 (1.00-1.37) and 1.19 (1.04-1.37) for all-cause mortality, cardiovascular mortality and cardiovascular events, respectively. The six cohorts yielded inconsistent results for the association of very low HbA1c levels with the mortality outcomes and the pooled effect estimates were not statistically significant. In one cohort with a pronounced J-shaped association of HbA1c levels with all-cause and cardiovascular mortality (NHANES), the following confounders of the association of very low HbA1c levels with mortality outcomes were identified: race/ethnicity; alcohol consumption; BMI; as well as biomarkers of iron deficiency anemia and liver function. Associations for very low HbA1c levels lost statistical significance in this cohort after adjusting for these confounders. CONCLUSIONS: A linear association of HbA1c levels with primary cardiovascular events was observed. For cardiovascular and all-cause mortality, the observed small effect sizes at both the lower and upper end of HbA1c distribution do not support the notion of a J-shaped association of HbA1c levels because a certain degree of residual confounding needs to be considered in the interpretation of the results.

Evolution versus "intelligent design": comparing the topology of protein-protein interaction networks to the Internet.

Recent research efforts have made available genome-wide, high-throughput protein-protein interaction (PPI) maps for several model organisms. This has enabled the systematic analysis of PPI networks, which has become one of the primary challenges for the system biology community. In this study, we attempt to understand better the topological structure of PPI networks by comparing them against man-made communication networks, and more specifically, the Internet. Our comparative study is based on a comprehensive set of graph metrics. Our results exhibit an interesting dichotomy. On the one hand, both networks share several macroscopic properties such as scale-free and small-world properties. On the other hand, the two networks exhibit significant topological differences, such as the cliqueishness of the highest degree nodes. We attribute these differences to the distinct design principles and constraints that both networks are assumed to satisfy. We speculate that the evolutionary constraints that favor the survivability and diversification are behind the building process of PPI networks, whereas the leading force in shaping the Internet topology is a decentralized optimization process geared towards efficient node communication.