1,720,964 research outputs found
The complex combination of COVID-19 and diabetes: pleiotropic changes in glucose metabolism
Purpose: Angiotensin converting enzyme 2 (ACE2) is the door for SARS-CoV-2, expressed in critical metabolic tissues. So, it is rational that the new virus causes pleiotropic alterations in glucose metabolism, resulting in the complication of pre-existing diabetes’s pathophysiology or creating new disease mechanisms. However, it seems that less attention has been paid to this issue. This review aimed to highlight the importance of long-term consequences and pleiotropic alterations in glucose metabolism following COVID-19 and emphasize the need for basic and clinical research in metabolism and endocrinology. Results: SARS-CoV-2 shifts cellular metabolism from oxidative phosphorylation to glycolysis, which leads to a decrease in ATP generation. Together with metabolic imbalance, the impaired immune system elevates the susceptibility of patients with diabetes to this deadly virus. SARS-CoV-2-induced metabolic alterations in immune cells can result in hyper inflammation and a cytokine storm. Metabolic dysfunction may affect therapies against SARS-CoV-2 infection. The effective control of metabolic complications could prove useful therapeutic targets for combating COVID-19. It is also necessary to understand the long-term consequences that will affect patients with diabetes who survived COVID-19. Conclusions: Since the pathophysiology of COVID-19 is still mostly unknown, identifying the metabolic mechanisms contributing to its progression is essential to provide specific ways to prevent and improve this dangerous virus’s detrimental effects. The findings show that the new virus may induce new-onset diabetes with uncertain metabolic and clinical features, supporting a potential role of COVID-19 in the development of diabetes
Epigenetic alterations and genetic variations of angiotensin-converting enzyme 2 (ACE2) as a functional receptor for SARS-CoV-2: potential clinical implications
Receptor recognition is a crucial step in viral infection and is a critical factor for cell entry and tissue tropism. In several recent studies, angiotensin-converting enzyme 2 (ACE2) has been demonstrated to be the cellular receptor of SARS-CoV-2 as it was previously well known as the receptor of SARS-CoV. SARS-CoV-2 can bind with high affinity to human ACE2 and engages it as an entry receptor. It seems that the genetic, notably epigenetic variations of ACE2 are less known in different populations, indicating the need for its further investigation. These variations have the potential to affect its contribution to the pathogenicity of COVID-19. The contribution of epigenetics in the interindividual variability of ACE2 merits more attention because epigenetic processes can play important roles in ACE2 alterations in various tissues and different people and populations. Analyzing different DNA methylation patterns and microRNAs, contributing to the ACE2 modulation in the lungs will have a high priority. The epigenetic and genetic variations of ACE2 become even more important when considering that some people have mild clinical symptoms despite having COVID-19. The pathogenicity of SARS-CoV-2 infection is complex; therefore, a better understanding of the underlying pathobiology, especially binding the virus to its receptors, could help improve therapeutic and preventive approaches. This review aims to highlight the importance of evaluating both the epigenetic and genetic variations of ACE2 as a receptor for the deadly SARS-CoV-2
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
Author-wise bibliometric analysis based on entropy.</p
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