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ObjectiveTo evaluate and compare the predictive value of Face, Arm, Speech Test (FAST) and Balance, Eyes, Face, Arm, Speech, Time (BEFAST) scale in the acute ischemic stroke (AIS).MethodsWe searched Medline and Ovid databases for relevant literature in the English language. There were no limitations on the date. The sensitivity, specificity, likelihood ratio, and diagnostic odds ratio were pooled for meta-analysis. The symmetric receiver operator characteristic curve and Fagan's Nomogram were drawn, and meta-regression and subgroup analysis were used to explore the source of heterogeneity.ResultsA total of 9 studies, including 6,151 participants, were analyzed. The combined sensitivity of FAST was 0.77 [95% CI (0.64–0.86)], specificity was 0.60 [95% CI (0.38–0.78)], the area under the ROC curve was 0.76, and the diagnostic ratio was 1.57, while the sensitivity of BEFAST was 0.68 [95% CI (0.23–0.93)], specificity was 0.85 [95% CI (0.72–0.92)], the area under the ROC curve was 0.86, and the diagnostic odds ratio was 2.44. No publication bias was detected in Deeks' funnel plot. For FAST, meta-regression analysis showed that the prospective design, satisfactory description of the index test, and a broad spectrum of disease contributed to the heterogeneity in sensitivity, while no sources contributed to the heterogeneity in sensitivity. When the pretest probability was set as 20%, the posterior probability in Fagan's Nomogram was 32%; however, when the pretest probability was set as 20% in BEFAST, the posterior probability in Fagan's Nomogram was 52%.ConclusionsOur findings indicated that FAST and BEFAST might be useful in the diagnosis of acute ischemic stroke. The diagnostic value of BEFAST in acute ischemic stroke was higher than in FAST; thus, it might have an important role in the fast recognition of acute ischemic stroke.

Circular RNA (circRNA) is a unique type of noncoding RNA molecule. Compared with traditional linear RNA, circRNA is a covalently closed circle produced by a process called backsplicing. CircRNA is abundant in many cells and has rich functions in cells, such as acting as miRNA sponge, protein sponge, protein scaffold, and mRNA regulator. With the continuous development of circRNA study, circRNA has also played an important role in medical applications, including circRNA vaccines and gene therapy. In this review, we illustrate the synthesis of circRNAs in vitro. We focus on biological ligation methods, such as enzymatic ligation from the bacteriophage T4 and ribozyme method. In addition, we summarize the current challenges in the design, synthesis, application, and production of circRNAs, and propose possible solutions in the future. CircRNA is expected to play an essential role in basic research and medical applications.

Cell-free gene expression systems with linear DNA expression templates (LDETs) have been widely applied in artificial cells, biochips, and high-throughput screening. However, due to the degradation caused by native nucleases in cell extracts, the transcription with linear DNA templates is weak, thereby resulting in low protein expression level, which greatly limits the development of cell-free systems using linear DNA templates. In this study, the protective sequences for stabilizing linear DNA and the transcribed mRNAs were rationally designed according to nucleases’ action mechanism, whose effectiveness was evaluated through computer simulation and cell-free gene expression. The cell-free experiment results indicated that, with the combined protection of designed sequence and GamS protein, the protein expression of LDET-based cell-free systems could reach the same level as plasmid-based cell-free systems. This study would potentially promote the development of the LDET-based cell-free gene expression system for broader applications.

This study aimed to explore the cognitive and affective factors that predict the Psychological capital (PsyCap) of Chinese primary school teachers. The participants were 1,384 teachers from 34 primary schools in Chengdu city, in southwestern part of China. A resource model of PsyCap was proposed and tested using structural equation modeling (SEM). The model was tested with two independent variables of growth mindset and well-being as predictors of PsyCap. Results showed that both cognitive construct (i.e., growth mindset) and affective construct (i.e., well-being) were positively and significantly related to the PsyCap. In addition, SEM results indicated a significant influence of both growth mindset and well-being on all the variables of PsyCap (i.e., Efficacy, Hope, Optimism, and Resilience). Explanations and implications were discussed for the findings, and some limitations were also discussed.