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Aim. The study is aimed at exploring the relationship between newly graduated nurses’ transition shock, negative coping, job satisfaction, and intent to stay during the time of COVID-19. Background. The shortage of nurses is a global dilemma aggravated by the COVID-19 pandemic. It has been a hot topic in recent years to help newly graduated nurses transition smoothly. Transition shock is one of the essential indicators to describe the transition state of newly graduated nurses, which has a far-reaching impact on the intention of newly graduated nurses to stay in their posts. However, few studies have studied the mechanism behind this relationship, which may affect the effectiveness of retention strategies. Methods. A descriptive cross-sectional study was conducted from July to August 2021 in 31 tertiary hospitals in Shanghai, China. Participants comprised a convenience sample of 759 newly graduated nurses for surveys. Structural equation models were used to examine the study’s hypothetical model. Results. The results showed that transition shock had a significant direct effect on job satisfaction (b = −0.412, p < 0.001 ) and intent to stay (b = −0.145, p < 0.001 ). Job satisfaction had a significant direct effect on intent to stay (b = 0.702, p < 0.001 ). The indirect effect of transition shock on intent to stay through job satisfaction was statistically significant (b = −0.289), the 95% C.I. was (−0.493, −0.357), and the proportion of mediating effect to total effect was 66.59%. Moreover, the moderated mediation analysis showed that the interaction effect of transition shock and negative coping style on job satisfaction was significant (b = −0.082, p < 0.001 ). Conclusion. This study revealed the impact of transition shock on intent to stay of newly graduated nurses during the time of COVID-19, and found that job satisfaction played a mediating role and negative coping played a moderating role. These findings are of great significance for nursing managers to take measures to improve the intention of newly graduated nurses to stay. Implication for Nursing Management. The level of transition shock is an important indicator reflecting the transition state of newly graduated nurses, and can further predict the job satisfaction and intention of newly graduated nurses to stay. Therefore, nursing managers should pay attention to taking corresponding measures to reduce the level of transition shock of newly graduated nurses.

In this paper, we consider the issue of the secure transmissions for the cognitive radio-based Internet of Medical Things (IoMT) with wireless energy harvesting. In these systems, a primary transmitter (PT) will transmit its sensitive medical information to a primary receiver (PR) by a multi-antenna-based secondary transmitter (ST), where we consider that a potential eavesdropper may listen to the PT’s sensitive information. Meanwhile, the ST also transmits its own information concurrently by utilizing spectrum sharing. We aim to propose a novel scheme for jointly designing the optimal parameters, i.e., energy harvesting (EH) time ratio and secure beamforming vectors, for maximizing the primary secrecy transmission rate while guaranteeing secondary transmission requirement. For solving the nonconvex optimization problem, we transfer the problem into convex optimization form by adopting the semidefinite relaxation (SDR) method and Charnes–Cooper transformation technique. Then, the optimal secure beamforming vectors and energy harvesting duration can be obtained easily by utilizing the CVX tools. According to the simulation results of secrecy transmission rate, i.e., secrecy capacity, we can observe that the proposed protocol for the considered system model can effectively promote the primary secrecy transmission rate when compared with traditional zero-forcing (ZF) scheme, while ensuring the transmission rate of the secondary system.

Background. Liver cirrhosis is one of the major drivers of hepatocellular carcinoma (HCC). In the present study, we aimed to identify and validate new biomarker for early prediction of HCC development in early-stage cirrhosis patients. Methods. mRNA expression and clinical parameters of GSE63898, GSE89377, GSE15654, GSE14520, and TCGA-HCC cohort and ICGC-HCC cohort were downloaded for analysis. Wilcoxon test was performed to identify DEGs. Univariate and multivariate Cox regression analysis were used to develop the risk signature, and ROC analysis was performed to analyze the predictive accuracy and sensitivity of the risk signature. Results. There were 42 DEGs (including 28 upregulated genes and 14 downregulated genes) found in early-stage liver cirrhosis patients before developing HCC from GSE1565442. Then, a risk signature consisting of 8 DEGs could effectively classify early-stage cirrhosis patients into high-risk group with shorter HCC development time and low-risk group with longer HCC development time from GSE15654. Multivariate Cox analysis indicated that the risk signature was an independent prognostic factor for the prediction of HCC development and ROC analysis showed that the signature exhibited good predictive efficiency in predicting 2-, 5-, and 10-year HCC development. Mechanistically, significantly higher proportions of CD8 T cells were found to be enriched in cirrhosis patients with low risk score, and higher CD8 T cells were associated with longer HCC development time. Besides, the signature was an independent prognostic factor for poorer prognosis of early-stage liver cirrhosis patients of GSE15654. Moreover, the signature could also separate HCC patients from healthy controls and was also associated with the poorer prognosis of HCC patients from three HCC cohorts. Finally, we also identified HDAC inhibitors, such as trichostatin A, to be a potential chemopreventive treatment for the prevention of HCC development by targeting risk signature based on CMap analysis. Conclusion. A risk signature was developed and validated for early prediction of HCC development, which may be a useful tool to set up individualized follow-up interval schedules.