Browsing by Author "Dundar, Munis"

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Citation - WoS: 23
Citation - Scopus: 23
The Age Structure, Stringency Policy, Income, and Spread of Coronavirus Disease 2019: Evidence From 209 Countries
(Frontiers Media S.A., 2021) Bilgili, Faik; Dundar, Munis; Kuskaya, Sevda; Lorente, Daniel Balsalobre; Unlu, Fatma; Gencoglu, Pelin; Mugaloglu, Erhan
This article aims at answering the following questions: (1) What is the influence of age structure on the spread of coronavirus disease 2019 (COVID-19)? (2) What can be the impact of stringency policy (policy responses to the coronavirus pandemic) on the spread of COVID-19? (3) What might be the quantitative effect of development levelincome and number of hospital beds on the number of deaths due to the COVID-19 epidemic? By employing the methodologies of generalized linear model, generalized moments method, and quantile regression models, this article reveals that the shares of median age, age 65, and age 70 and older population have significant positive impacts on the spread of COVID-19 and that the share of age 70 and older people in the population has a relatively greater influence on the spread of the pandemic. The second output of this research is the significant impact of stringency policy on diminishing COVID-19 total cases. The third finding of this paper reveals that the number of hospital beds appears to be vital in reducing the total number of COVID-19 deaths, while GDP per capita does not affect much the level of deaths of the COVID-19 pandemic. Finally, this article suggests some governmental health policies to control and decrease the spread of COVID-19.
Citation - WoS: 3
Citation - Scopus: 3
Artificial Cells: A Potentially Groundbreaking Field of Research and Therapy
(Sciendo, 2024) Dundar, Mehmet Sait; Yildirim, A. Baki; Yildirim, Duygu T.; Akalin, Hilal; Dundar, Munis
Artificial cells are synthetic constructs that mimic the architecture and functions of biological cells. Artificial cells are designed to replicate the fundamental principles of biological systems while also have the ability to exhibit novel features and functionalities that have not been achieved before. Mainly, Artificial cells are made up of a basic structure like a cell membrane, nucleus, cytoplasm and cellular organelles. Nanotechnology has been used to make substances that possess accurate performance in these structures. There are many roles that artificial cells can play such as drug delivery, bio-sensors, medical applications and energy storage. An additional prominent facet of this technology is interaction with biological systems. The possibility of synthetic cells being compatible with living organisms opens up the potential for interfering with specific biological activities. This element is one of the key areas of research in medicine, aimed at developing novel therapies and comprehending life processes. Nevertheless, artificial cell technology is not exempt from ethical and safety concerns. The interplay between these structures and biological systems may give rise to questions regarding their controllability and safety. Hence, the pursuit of artificial cell research seeks to reconcile ethical and safety concerns with the potential advantages of this technology.
Citation - WoS: 11
Citation - Scopus: 10
Clinical and Molecular Evaluation of MEFV Gene Variants in the Turkish Population: A Study by the National Genetics Consortium
(Springer Heidelberg, 2022) Dundar, Munis; Fahrioglu, Umut; Yildiz, Saliha Handan; Bakir-Gungor, Burcu; Temel, Sehime Gulsun; Akin, Haluk; Erdem, Levent
Familial Mediterranean fever (FMF) is a monogenic autoinflammatory disorder with recurrent fever, abdominal pain, serositis, articular manifestations, erysipelas-like erythema, and renal complications as its main features. Caused by the mutations in the MEditerranean FeVer (MEFV) gene, it mainly affects people of Mediterranean descent with a higher incidence in the Turkish, Jewish, Arabic, and Armenian populations. As our understanding of FMF improves, it becomes clearer that we are facing with a more complex picture of FMF with respect to its pathogenesis, penetrance, variant type (gain-of-function vs. loss-of-function), and inheritance. In this study, MEFV gene analysis results and clinical findings of 27,504 patients from 35 universities and institutions in Turkey and Northern Cyprus are combined in an effort to provide a better insight into the genotype-phenotype correlation and how a specific variant contributes to certain clinical findings in FMF patients. Our results may help better understand this complex disease and how the genotype may sometimes contribute to phenotype. Unlike many studies in the literature, our study investigated a broader symptomatic spectrum and the relationship between the genotype and phenotype data. In this sense, we aimed to guide all clinicians and academicians who work in this field to better establish a comprehensive data set for the patients. One of the biggest messages of our study is that lack of uniformity in some clinical and demographic data of participants may become an obstacle in approaching FMF patients and understanding this complex disease.
Citation - WoS: 8
Citation - Scopus: 11
The Impact and Future of Artificial Intelligence in Medical Genetics and Molecular Medicine: An Ongoing Revolution
(Springer Heidelberg, 2024) Ozcelik, Firat; Dundar, Mehmet Sait; Yildirim, A. Baki; Henehan, Gary; Vicente, Oscar; Sanchez-Alcazar, Jose A.; Dundar, Munis
Artificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.