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Since it was first recognized in bacteria and archaea as a mechanism for innate viral immunity in the early 2010 s,clustered regularly interspaced short palindromic repeats(CRISPR)/CRISPR-associated protein(Cas) has rapidly been developed into a robust, multifunctional genome editing tool with many uses. Following the discovery of the initial CRISPR/Cas-based system, the technology has been advanced to facilitate a multitude of different functions. These include development as a base editor, prime editor, epigenetic editor, and CRISPR interference(CRISPRi) and CRISPR activator(CRISPRa) gene regulators. It can also be used for chromatin and RNA targeting and imaging. Its applications have proved revolutionary across numerous biological fields, especially in biomedical and agricultural improvement. As a diagnostic tool, CRISPR has been developed to aid the detection and screening of both human and plant diseases, and has even been applied during the current coronavirus disease 2019(COVID-19) pandemic. CRISPR/Cas is also being trialed as a new form of gene therapy for treating various human diseases, including cancers, and has aided drug development. In terms of agricultural breeding, precise targeting of biological pathways via CRISPR/Cas has been key to regulating molecular biosynthesis and allowing modification of proteins, starch, oil, and other functional components for crop improvement. Adding to this, CRISPR/Cas has been shown capable of significantly enhancing both plant tolerance to environmental stresses and overall crop yield via the targeting of various agronomically important gene regulators. Looking to the future, increasing the efficiency and precision of CRISPR/Cas delivery systems and limiting off-target activity are two major challenges for wider application of the technology. This review provides an in-depth overview of current CRISPR development, including the advantages and disadvantages of the technology,recent applications, and future considerations.  相似文献   
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The main aim of this study was to investigate the relationships between life satisfaction, gender, social security, and depressive symptoms of the Turkish elderly. This cross-sectional study included 216 (female = 127, male = 89) participants with ages ranging from 60 to 93 years (mean = 71.60 ± 7.39). Information Gathering Form and Life Satisfaction and Geriatric Depression Scales were used for data collection. It was determined that 42.1% of the elderly who participated in this study had high depressive symptoms scores. Life satisfaction (OR = 0.63, 95% CI = 0.53–0.71), lack of social security benefits (OR = 3.52, 95% CI = 1.25–9.89), and gender (OR = 2.53, 95% CI = 1.17–5.50) predicted the depressive symptoms significantly. The results of the study indicate that while depression risk increases, life satisfaction decreases. In addition, lack of social security benefits and being female also increase the risk of depression in the Turkish elderly.  相似文献   
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IntroductionTo interpret test results correctly, understanding of the variations that affect test results is essential. The aim of this study is: 1) to evaluate the clinicians’ knowledge and opinion concerning biological variation (BV), and 2) to investigate if clinicians use BV in the interpretation of test results.Materials and methodsThis study uses a questionnaire comprising open-ended and close-ended questions. Questions were selected from the real-life numerical examples of interpretation of test results, the knowledge about main sources of variations in laboratories and the opinion of clinicians on BV. A total of 399 clinicians were interviewed, and the answers were evaluated using a scoring system ranked from A (clinician has the highest level of knowledge and the ability of using BV data) to D (clinician has no knowledge about variations in laboratory). The results were presented as number (N) and percentage (%).ResultsAltogether, 60.4% of clinicians have knowledge of pre-analytical and analytical variations; but only 3.5% of them have knowledge related to BV. The number of clinicians using BV data or reference change value (RCV) to interpret measurements results was zero, while 79.4% of clinicians accepted that the difference between two measurements results located within the reference interval may be significant.ConclusionsClinicians do not use BV data or tools derived from BV such as RCV to interpret test results. It is recommended that BV should be included in the medical school curriculum, and clinicians should be encouraged to use BV data for safe and valid interpretation of test results.  相似文献   
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