scholarly journals Trends in biomedical informatics: automated topic analysis of JAMIA articles

2015 ◽  
Vol 22 (6) ◽  
pp. 1153-1163 ◽  
Author(s):  
Dong Han ◽  
Shuang Wang ◽  
Chao Jiang ◽  
Xiaoqian Jiang ◽  
Hyeon-Eui Kim ◽  
...  
Keyword(s):  
Language Processing ◽  
Biomedical Informatics ◽  
Tensor Decomposition ◽  
Medical Subject Headings ◽  
Topic Analysis ◽  
Interdisciplinary Field ◽  
Mesh Terms ◽  
Wide Range ◽  
Number Of Publications ◽  
Number Of Citations

Abstract Biomedical Informatics is a growing interdisciplinary field in which research topics and citation trends have been evolving rapidly in recent years. To analyze these data in a fast, reproducible manner, automation of certain processes is needed. JAMIA is a “generalist” journal for biomedical informatics. Its articles reflect the wide range of topics in informatics. In this study, we retrieved Medical Subject Headings (MeSH) terms and citations of JAMIA articles published between 2009 and 2014. We use tensors (i.e., multidimensional arrays) to represent the interaction among topics, time and citations, and applied tensor decomposition to automate the analysis. The trends represented by tensors were then carefully interpreted and the results were compared with previous findings based on manual topic analysis. A list of most cited JAMIA articles, their topics, and publication trends over recent years is presented. The analyses confirmed previous studies and showed that, from 2012 to 2014, the number of articles related to MeSH terms Methods , Organization & Administration , and Algorithms increased significantly both in number of publications and citations. Citation trends varied widely by topic, with Natural Language Processing having a large number of citations in particular years, and Medical Record Systems, Computerized remaining a very popular topic in all years.

Modeling the co-citation dependence on semantic layers of co-cited documents

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maryam Yaghtin ◽  
Hajar Sotudeh ◽  
Alireza Nikseresht ◽  
Mahdieh Mirzabeigi
Keyword(s):  
Peer Review ◽  
Language Processing ◽  
Opinion Mining ◽  
Citation Network ◽  
Test Collection ◽  
Medical Subject Headings ◽  
Content Type ◽  
Citation Frequency ◽  
Mesh Terms ◽  
Citation Measures

PurposeCo-citation frequency, defined as the number of documents co-citing two articles, is considered as a quantitative, and thus, an efficient proxy of subject relatedness or prestige of the co-cited articles. Despite its quantitative nature, it is found effective in retrieving and evaluating documents, signifying its linkage with the related documents' contents. To better understand the dynamism of the citation network, the present study aims to investigate various content features giving rise to the measure.Design/methodology/approachThe present study examined the interaction of different co-citation features in explaining the co-citation frequency. The features include the co-cited works' similarities in their full-texts, Medical Subject Headings (MeSH) terms, co-citation proximity, opinions and co-citances. A test collection is built using the CITREC dataset. The data were analyzed using natural language processing (NLP) and opinion mining techniques. A linear model was developed to regress the objective and subjective content-based co-citation measures against the natural log of the co-citation frequency.FindingsThe dimensions of co-citation similarity, either subjective or objective, play significant roles in predicting co-citation frequency. The model can predict about half of the co-citation variance. The interaction of co-opinionatedness and non-co-opinionatedness is the strongest factor in the model.Originality/valueIt is the first study in revealing that both the objective and subjective similarities could significantly predict the co-citation frequency. The findings re-confirm the citation analysis assumption claiming the connection between the cognitive layers of cited documents and citation measures in general and the co-citation frequency in particular.Peer reviewThe peer review history for this article is available at https://publons.com/publon/10.1108/OIR-04-2020-0126.

scholarly journals Automated literature mining and hypothesis generation through a network of Medical Subject Headings

2018 ◽  
Author(s):  
Stephen Joseph Wilson ◽  
Angela Dawn Wilkins ◽  
Matthew V. Holt ◽  
Byung Kwon Choi ◽  
Daniel Konecki ◽  
...  
Keyword(s):  
Language Processing ◽  
Scientific Literature ◽  
Growth Factor Receptor ◽  
Direct Interaction ◽  
Hypothesis Generation ◽  
Supervised Machine Learning ◽  
Literature Mining ◽  
Cancer Genes ◽  
Medical Subject Headings ◽  
Mesh Terms

ABSTRACTThe scientific literature is vast, growing, and increasingly specialized, making it difficult to connect disparate observations across subfields. To address this problem, we sought to develop automated hypothesis generation by networking at scale the MeSH terms curated by the National Library of Medicine. The result is a Mesh Term Objective Reasoning (MeTeOR) approach that tallies associations among genes, drugs and diseases from PubMed and predicts new ones.Comparisons to reference databases and algorithms show MeTeOR tends to be more reliable. We also show that many predictions based on the literature prior to 2014 were published subsequently. In a practical application, we validated experimentally a surprising new association found by MeTeOR between novel Epidermal Growth Factor Receptor (EGFR) associations and CDK2. We conclude that MeTeOR generates useful hypotheses from the literature (http://meteor.lichtargelab.org/).AUTHOR SUMMARYThe large size and exponential expansion of the scientific literature forms a bottleneck to accessing and understanding published findings. Manual curation and Natural Language Processing (NLP) aim to address this bottleneck by summarizing and disseminating the knowledge within articles as key relationships (e.g. TP53 relates to Cancer). However, these methods compromise on either coverage or accuracy, respectively. To mitigate this compromise, we proposed using manually-assigned keywords (MeSH terms) to extract relationships from the publications and demonstrated a comparable coverage but higher accuracy than current NLP methods. Furthermore, we combined the extracted knowledge with semi-supervised machine learning to create hypotheses to guide future work and discovered a direct interaction between two important cancer genes.

scholarly journals Using the strength coefficient(SC) to evaluate the most number of publications in research affiliations involving COVID-19 till April 14, 2020: A bibliometric analysis

2020 ◽  
Author(s):  
Wei-Chih Kan ◽  
Yu-Tsen Yeh ◽  
Jui-Chung John Lin ◽  
Tsair-Wei Chien
Keyword(s):  
Dominant Role ◽  
Journal Article ◽  
Objective Measure ◽  
Simulated Data ◽  
Medical Subject Headings ◽  
Pubmed Central ◽  
Strength Coefficient ◽  
Mesh Terms ◽  
Number Of Publications ◽  
Absolute Advantage

Abstract Background: When the COVID-19 outbreak spreads to the world, many articles related to it have been published in academics. Since the largest quantity of confirmed cases was reported in China till April 14, 2020, whether the number of Chinese articles of research associated with the COVID-19 topped globally is required to be examined. Thus, an objective measure determining the dominant role in a group should be defined. This study aims to propose an index (strength coefficient, SC) to evaluate the most influential research affiliations in publications of COVID-19. Methods: We simulated data to verify the separation index that can be viable in use for determining the dominant one that has the absolute advantage in a group. We selected 4,369 articles as of April 14, 2020, with abstracts from the Pubmed Central (PMC) based on the keywords COVID-19 or 2019-nCOV. An author-weighted scheme (AWS) was applied to quantify coauthor credits in the article byline. Social network analysis incorporated with SC(from 0 to 1.0 and cutoff=0/70) was applied to display the influential (1) article types, (2)countries, (3)medical subject headings(MeSH terms), and (4) research affiliations. Visual dashboards were created for displaying the results on Google Maps. Results: We observed that the top one(SC) in each topic consists of (1) journal article(0.81), (2) China(0.61),(3) Acad Radol, (4) betacoronavirus (0.66), and (5) Hazhong University of Science and Technology(0.77) in article types, countries, journals, MeSH terms, and research affiliations, respectively. Conclusion: We applied the SC to identify the strength of the top one over the next two. The SC was useful and viable in verifying the dominant role in a group. The implementation and application are worthy of further studies in the future.

Liraglutide for the Treatment of Obesity: Analyzing Published Reviews

2019 ◽  
Vol 25 (15) ◽  
pp. 1783-1790 ◽  
Author(s):  
Rosario Pastor ◽  
Josep A. Tur
Keyword(s):  
Weight Loss ◽  
Clinical Trials ◽  
Systematic Reviews ◽  
Randomized Clinical Trials ◽  
Statistical Tests ◽  
Overweight And Obesity ◽  
Cochrane Library ◽  
Medical Subject Headings ◽  
Mesh Terms ◽  
Treatment Of Obesity

Background: Several drugs have been currently approved for the treatment of obesity. The pharmacokinetic of liraglutide, as well as the treatment of type 2 diabetes mellitus, have been widely described. Objective: To analyze the published systematic reviews on the use of liraglutide for the treatment of obesity. Methods: Systematic reviews were found out through MEDLINE searches, through EBSCO host and the Cochrane Library based on the following terms: "liraglutide" as major term and using the following Medical Subject Headings (MesH) terms: "obesity", "overweight", "weight loss". A total of 3 systematic reviews were finally included to be analyzed. Results: From the three systematic reviews selected, only two included the randomized clinical trials, while the third study reviewed both randomized and non-randomized clinical trials. Only one review performed statistical tests of heterogeneity and a meta-analysis, combining the results of individual studies. Another review showed the results of individual studies with odds ratio and confidence interval, but a second one just showed the means and confidence intervals. In all studies, weight loss was registered in persons treated with liraglutide in a dose dependent form, reaching a plateau at 3.0 mg dose, which was reached just in men. Most usual adverse events were gastrointestinal. Conclusion: More powerful and prospective studies are needed to assess all aspects related to liraglutide in the overweight and obesity treatment.

Bibliometric Analysis of Current Drug Metabolism: The Twentieth Anniversary from 2000-2019

2020 ◽  
Vol 21 (9) ◽  
pp. 685-703
Author(s):  
Waseem Hassan ◽  
Jean Paul Kamdem ◽  
Mohammad Amjad Kamal ◽  
Joao Batista Teixeira da Rocha
Keyword(s):  
United States ◽  
Drug Metabolism ◽  
Bibliometric Analysis ◽  
Continuous Growth ◽  
H Index ◽  
Current Drug ◽  
The Usa ◽  
Twentieth Anniversary ◽  
Number Of Publications ◽  
Number Of Citations

Background: Scopus is regularly covering Current Drug Metabolism from 2000 onwards. Objective: The major objective is to perform the 1st bibliometric analysis of Current Drug Metabolism (CDM). Methods: The data was retrieved from Scopus in April-May 2020 for detail analysis. Results: The total number of publications was found to be 1551, with 955 reviews (61.57%) and 466 articles (30.05%). From 2000 onwards, we calculated the relative growth rate and doubling time. Based on the number of publications, total 4418 authors, 3235 institutions and 83 countries were directly involved in all publications. M.A. Kamal is the highly productive scientist with fifty-three (53 or 3.73%) publications, King Abdulaziz University is the top university with the highest number of publications (58 or 4.13%) and the USA is the top-ranked country with 365 publications (25.96%). We also provided the h-index, total citations (TC), h-index without self-citations (WSC) and total WSC of the top ten authors, universities and countries. In citations analysis, Prof. Zhou S.F. was the top scientist with the highest (1594) number of citations. In institutional category Department of Drug Metabolism, Merck Research Laboratories, Rahway, United States, is the top ranked institutes with 654 total citations. While, United States is the top-ranked country with 18409 total citations. In co-words analysis, 3387, 30564 and 17333 terms in titles of the manuscripts, abstracts and keywords were recorded, respectively. This indicated that CDM principally focused on understanding drug development ranging from its efficacy to delivery, metabolism, distribution, safety and mechanism of actions. Similarly, various specific drugs were thoroughly discussed in publications. Various enzymatic, genetics, proteins and cancer-related aspects were also described. For data presentations, we used VOSviewer graphical maps. Conclusion: The data confirm that CDM showed continuous growth in the number of publications and citations. However significant measures are needed to make overall progress and improve the rankings in relevant categories.

The chemistry of 4-(dicyanomethylene)-3-methyl-l-phenyl-2-pyrazoline-5- ones as a privileged scaffold in synthesis of heterocycles

2020 ◽  
Vol 17 ◽  
Author(s):  
Mohsen A.-M. Gomaa ◽  
Huda A. Ali
Keyword(s):  
Building Block ◽  
Heterocyclic Compounds ◽  
Recent Progress ◽  
Reaction Conditions ◽  
Azacrown Ethers ◽  
Wide Range ◽  
Privileged Scaffold ◽  
Number Of Publications ◽  
Near Future

Background : The reactivity of 4-(dicyanomethylene)-3-methyl-l-phenyl-2-pyrazoline-5-one DCNP 1 and its derivatives makes it valuable as a building block for the synthesis of heterocyclic compounds like pyrazolo-imidazoles, - thiazoles, spiropyridines, spiropyrroles, spiropyrans and others. As a number of publications have reported on the reactivity of DCNP and its derivatives, we compiled some features of this interesting molecule. Objective: This article aims to review the preparation of DCNP, its reactivity and application in heterocyclic and dyes synthesis. Conclusion: In this review we have provided an overview of recent progress in the chemistry of DCNP and its significance in synthesis of various classes of heterocyclic compounds and dyes. The unique reactivity of DCNP offers unprecedentedly mild reaction conditions for the generation of versatile cynomethylene dyes from a wide range of precursors including amines, α-aminocarboxylic acids, their esters, phenols, malononitriles and azacrown ethers. We anticipate that more innovative transformations involving DCNP will continue to emerge in the near future.

The Role of Leukotrienes Inhibitors in the Management of Chronic Inflammatory Diseases

2020 ◽  
Vol 14 (1) ◽  
pp. 15-31
Author(s):  
Deepak Meshram ◽  
Khushbo Bhardwaj ◽  
Charulata Rathod ◽  
Gail B. Mahady ◽  
Kapil K. Soni
Keyword(s):  
Respiratory Diseases ◽  
Inflammatory Diseases ◽  
Leukotriene B4 ◽  
Published Data ◽  
Free Text ◽  
Plant Origin ◽  
Medical Subject Headings ◽  
Leukotriene Antagonists ◽  
Mesh Terms ◽  
Mediators Of Inflammation

Background: Leukotrienes are powerful mediators of inflammation and interact with specific receptors in target cell membrane to initiate an inflammatory response. Thus, Leukotrienes (LTs) are considered to be potent mediators of inflammatory diseases including allergic rhinitis, inflammatory bowel disease and asthma. Leukotriene B4 and the series of cysteinyl leukotrienes (C4, D4, and E4) are metabolites of arachidonic acid metabolism that cause inflammation. The cysteinyl LTs are known to increase vascular permeability, bronco-constriction and mucus secretion. Objectives: To review the published data for leukotriene inhibitors of plant origin and the recent patents for leukotriene inhibitors, as well as their role in the management of inflammatory diseases. Methods: Published data for leukotrienes antagonists of plant origin were searched from 1938 to 2019, without language restrictions using relevant keywords in both free text and Medical Subject Headings (MeSH terms) format. Literature and patent searches in the field of leukotriene inhibitors were carried out by using numerous scientific databases including Science Direct, PubMed, MEDLINE, Google Patents, US Patents, US Patent Applications, Abstract of Japan, German Patents, European Patents, WIPO and NAPRALERT. Finally, data from these information resources were analyzed and reported in the present study. Results: Currently, numerous anti-histaminic medicines are available including chloropheneremine, brompheniramine, cetirizine, and clementine. Furthermore, specific leukotriene antagonists from allopathic medicines are also available including zileuton, montelukast, pranlukast and zafirlukast and are considered effective and safe medicines as compared to the first generation medicines. The present study reports leukotrienes antagonistic agents of natural products and certain recent patents that could be an alternative medicine in the management of inflammation in respiratory diseases. Conclusion: The present study highlights recent updates on the pharmacology and patents on leukotriene antagonists in the management of inflammation respiratory diseases.

scholarly journals Global research activity on antimicrobial resistance in food-producing animals

2021 ◽  
Vol 79 (1) ◽  
Author(s):  
Waleed M. Sweileh
Keyword(s):  
Antimicrobial Resistance ◽  
Hot Spots ◽  
One Health ◽  
Research Collaboration ◽  
Search Query ◽  
Scientific Publications ◽  
Research Theme ◽  
The Usa ◽  
Number Of Publications ◽  
Number Of Citations

Abstract Background Antimicrobial resistance (AMR) is a global challenge that requires a “One Health” approach to achieve better public health outcomes for people, animals, and the environment. Numerous bibliometric studies were published on AMR in humans. However, none was published in food-producing animals. The current study aimed at assessing and analyzing scientific publications on AMR in food-producing animals. Method A validated search query was developed and entered in Scopus advanced search function to retrieve and quantitatively analyze relevant documents. Bibliometric indicators and mapping were presented. The study period was from 2000 to 2019. Results The search query retrieved 2852 documents. During the period from 2015 to 2019, approximately 48% of the retrieved documents were published. The article about the discovery of plasmid-mediated colistin resistance in pigs received the highest number of citations (n = 1970). The Journal of Food Protection (n = 123; 4.3%) ranked first in the number of publications while the Applied and Environmental Microbiology journal ranked first in the number of citations per document. The USA led with 576 (20.2%) documents followed by China (n = 375; 13.1%). When the number of publications was standardized by income and population size, India (n = 51.5) ranked first followed by China (n = 38.3) and Brazil (n = 13.4). The growth of publications from China exceeded that of the USA in the last 3 years of the study period. Research collaboration in this field was inadequate. Mapping author keywords showed that E. coli, Salmonella, poultry, Campylobacter, chicken, cattle, and resistant genes were most frequent. The retrieved documents existed in five research themes. The largest research theme was about AMR in Salmonella in food-producing animals. The most recent research theme was about the dissemination and molecular transfer of AMR genes into the environment and among different bacterial strains. Conclusion Hot spots of research on AMR in food-producing animals match the world regions of reported hot spots of AMR in animals. Research collaboration in this field is of great importance, especially with low- and middle-income countries. Data on AMR need to be collected nationally and internationally to implement the “One Health” approach in the fight against AMR.

scholarly journals Evolution of knowledge on meniscal biomechanics: a 40 year perspective

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Amin Mohamadi ◽  
Kaveh Momenzadeh ◽  
Aidin Masoudi ◽  
Kempland C. Walley ◽  
Kenny Ierardi ◽  
...  
Keyword(s):  
Future Research ◽  
Fe Model ◽  
Cruciate Ligaments ◽  
Fe Modeling ◽  
Meniscal Tears ◽  
Medical Subject Headings ◽  
Model Studies ◽  
The Past ◽  
Mesh Terms ◽  
Kinematic Studies

Abstract Background Knowledge regarding the biomechanics of the meniscus has grown exponentially throughout the last four decades. Numerous studies have helped develop this knowledge, but these studies have varied widely in their approach to analyzing the meniscus. As one of the subcategories of mechanical phenomena Medical Subject Headings (MeSH) terms, mechanical stress was introduced in 1973. This study aims to provide an up-to-date chronological overview and highlights the evolutionary comprehension and understanding of meniscus biomechanics over the past forty years. Methods A literature review was conducted in April 2021 through PubMed. As a result, fifty-seven papers were chosen for this narrative review and divided into categories; Cadaveric, Finite element (FE) modeling, and Kinematic studies. Results Investigations in the 1970s and 1980s focused primarily on cadaveric biomechanics. These studies have generated the fundamental knowledge basis for the emergence of FE model studies in the 1990s. As FE model studies started to show comparable results to the gold standard cadaveric models in the 2000s, the need for understanding changes in tissue stress during various movements triggered the start of cadaveric and FE model studies on kinematics. Conclusion This study focuses on a chronological examination of studies on meniscus biomechanics in order to introduce concepts, theories, methods, and developments achieved over the past 40 years and also to identify the likely direction for future research. The biomechanics of intact meniscus and various types of meniscal tears has been broadly studied. Nevertheless, the biomechanics of meniscal tears, meniscectomy, or repairs in the knee with other concurrent problems such as torn cruciate ligaments or genu-valgum or genu-varum have not been extensively studied.

scholarly journals Newer Volatile Anesthetic Agents in Cardiac Anesthesia: Review of Literature

2021 ◽  
Author(s):  
Alka Mandke ◽  
Manjula Sarkar ◽  
Charulata Deshpande ◽  
Arun Maheshwari ◽  
Bhupesh Kumar ◽  
...  
Keyword(s):  
Volatile Anesthetic ◽  
Cochrane Library ◽  
Cochrane Central Register ◽  
Cardiac Anesthesia ◽  
Medical Subject Headings ◽  
Holistic View ◽  
Anesthetic Agents ◽  
Cardiac Anaesthesia ◽  
Mesh Terms ◽  
Inhalational Anaesthesia

AbstractMyocardial protection with volatile anesthetic agents have been suggested by multiple studies. These studies, however, are scattered and are often limited to a particular aspect of cardiac anesthesia. Older inhalational agents like halothane is known to cause significant hepatic damage in patients undergoing long duration surgeries while isoflurane is known to have marked vasodilating properties that also affects the coronary arteries leading to coronary “steal” phenomenon. Additionally, newer agents, like sevoflurane and desflurane, have shown more prominent cardioprotective effects than older agents. We searched ScholarOne, Medline, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library. The medical subject headings (MeSH) terms “anaesthesia, inhalational,” “anaesthesia, intravenous, or TIVA,” and “Cardiac anaesthesia or Cardiac Surgery” were used. Additional studies were identified by review of the reference sections of all eligible studies. The aim of this review article is to bring together the evidences with newer inhalational agents and provide a holistic view of their benefits and shortcomings in cardiac anesthesia.

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