The discovery of clustered, regularly interspaced short palindromic repeats (CRISPR) and their cooperation with CRISPR-associated (Cas) genes is one of the greatest advances of the century and has marked their application as a powerful genome engineering tool. The CRISPR–Cas system was discovered as a part of the adaptive immune system in bacteria and archaea to defend from plasmids and phages. CRISPR has been found to be an advanced alternative to zinc-finger nucleases (ZFN) and transcription activator-like effector nucleases (TALEN) for gene editing and regulation, as the CRISPR–Cas9 protein remains the same for various gene targets and just a short guide RNA sequence needs to be altered to redirect the site-specific cleavage. Due to its high efficiency and precision, the Cas9 protein derived from the type II CRISPR system has been found to have applications in many fields of science. Although CRISPR–Cas9 allows easy genome editing and has a number of benefits, we should not ignore the important ethical and biosafety issues. Moreover, any tool that has great potential and offers significant capabilities carries a level of risk of being used for non-legal purposes. In this review, we present a brief history and mechanism of the CRISPR–Cas9 system. We also describe on the applications of this technology in gene regulation and genome editing; the treatment of cancer and other diseases; and limitations and concerns of the use of CRISPR–Cas9.
Our task is to examine the relationship between the SARS-CoV-2 arrival and the number of confirmed COVID-19 cases in the first wave (period from March 4 to May 22, 2020 (unofficial data)), and socio-economic variables at the powiat (county) level (NUTS-4) using simple statistical techniques such as data visualization, correlation analysis, spatial clustering and multiple linear regression. We showed that immigration and the logarithm of general mobility is the best predictor of SARS-CoV-2 arrival times, while emigration, industrialization and air quality explain the most of the size of the epidemic in poviats. On the other hand, infection dynamics is driven to a lesser extent by previously postulated variables such as population size and density, income or the size of the elderly population. Our analyses could support Polish authorities in preparation for the second wave of infections and optimal management of resources as we have provided a proposition of optimal distribution
of human resources between poviats.
Aim. Our task was to examine the relationship between the SARS–CoV–2 arrival and the number of confi rmed COVID–19 cases in the fi rst wave (period from March 4 to May 22, 2020 (unoffi cial data)), and socio–economic variables at the powiat (county) level.Methods. We were using simple statistical techniques such as data visualisation, correlation analysis, spatial clustering and multiple linear regression.Results. We showed that immigration and the logarithm of general mobility was the best predictor of SARS–CoV–2 arrival times, while emigration, industrialisation and air quality explain most of the size of the epidemic in poviats. On the other hand, infection dynamics is driven to a lesser extent by previously postulated variables such as population size and density, income or the size of the elderly population.Conclusions. Our analyses could support Polish authorities in preparation for the second wave of infections and optimal management of resources as we have provided a proposition of optimal distribution of human resources between poviats. Although this isa retrospective analysis of the initial phase of the epidemic, similar patterns could repeat in case of new variants of SARS–CoV–2 or new respiratory disease for immunologically naive populations.
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