Physiological and transcriptomic analysis of OsLHCB3 knockdown lines in rice.

The photosystem II (PSII) outer antenna LHCB3 protein plays critical roles in distributing the excitation energy and modulating the rate of state transition for photosynthesis. Here, OsLHCB3 knockdown mutants were produced using the RNAi system. Phenotypic analyses showed that OsLHCB3 knockdown led to pale green leaves and lower chlorophyll contents at both tillering and heading stages. In addition, mutant lines exhibited decreased non-photochemical quenching (NPQ) capacity and net photosynthetic rate (Pn) by downregulating the expression of PSII-related genes. Moreover, RNA-seq experiments were performed at both tillering and heading stages. The differentially expressed genes (DEGs) mainly involved in chlorophyll binding response to abscisic acid, photosystem II, response to chitin, and DNA-binding transcription factor. Besides, our transcriptomic and physiological data indicated that OsLHCB3 was essential for binding chlorophyll, but not for the metabolism of chlorophyll in rice. OsLHCB3 RNAi knockdown plants affected the expression of PS II-related genes, but not PS I-related genes. Overall, these results suggest that OsLHCB3 also plays vital roles in regulating photosynthesis and antenna proteins in rice as well as responses to environment stresses. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-023-01387-z.

The Construction of Intelligent Emotional Analysis and Marketing Model of B&B Tourism Consumption Under the Perspective of Behavioral Psychology.

This manuscript constructs an intelligent sentiment analysis and marketing model for bed and breakfast (B&B) consumption based on a behavioral psychology perspective. Based on the LDA theme model, the theme features and keywords of the reviews covering user feedback are explored from the text data, and the theme framework of user sentiment perception is constructed by combining previous literature on user perception in the B&B market, and the themes of user online reviews are summarized in four dimensions: practical, sensory, cognitive, and emotional components of user experience. In this manuscript, GooSeeker software was selected for data crawling and ROST CM (ROST content mining) developed by Wuhan University was used for text processing. To improve the accuracy of text classification and improve the missing data, the online comment text is divided into sentences by symbols, and the text is divided into words based on sentences, and the spatial vector model and the text feature word weighting method of TF-IDF are used for vector representation, and the polynomial Bayesian classifier is called to identify the topics of sentences. The classical Theory of Planned Behavior (TPB) was used to analyze the influencing factors of the willingness to consume experiential B&B tourism, and countermeasure suggestions for the development of B&B tourism were proposed based on the research findings In the empirical testing stage, a questionnaire on the willingness to consume experiential B&B tourism was designed, and web research was chosen to collect the data. SPSS20.0 was used to conduct reliability analysis, factor analysis, correlation analysis, and regression analysis on the data, and AMOS statistics were used to establish a structural equation model to verify the influence path of willingness to consume experiential B&B tourism. Finally, the moderating path of willingness to consume experiential B&B tourism was verified by using multi-group analysis.

The effect of the COVID-19 pandemic on health care workers' anxiety levels: a meta-analysis.

Background: The COVID-19 pandemic has been declared a public health emergency of international concern, causing excessive anxiety among health care workers. Additionally, publication bias and low-quality publications have become widespread, which can result in the dissemination of unreliable information. A meta-analysis was performed for this study with the following two aims: (1) to examine the prevalence of anxiety among health care workers and determine whether it has increased owing to the COVID-19 pandemic and (2) to investigate whether there has been an increase in publication bias. Methods: All relevant studies published between 2015 and 2020 were searched in electronic databases (namely Web of Science, PubMed, Embase, PsycInfo, PsyArXiv, and medRxiv). The heterogeneity of the studies was assessed using the I 2 statistic. The effect size (prevalence rate of anxiety) and 95% CI for each study were also calculated. We used moderator analysis to test for the effect of the COVID-19 pandemic on health care workers' anxiety levels and to detect publication bias in COVID-19 studies. We assessed publication bias using funnel plots and Egger's regression. Results: A total of 122 studies with 118,025 participants met the inclusion criteria. Eighty-eight articles (75,066 participants) were related to COVID-19, 13 articles (9,222 participants) were unrelated to COVID-19 (i.e., articles related to other outbreaks, which were excluded), and 21 preprints (33,737 participants) were related to COVID-19. The pooled meta-analysis prevalence was 33.6% (95% CI [30.5-36.8]; 95% PI [6.5-76.3]). Moderator analysis revealed no significant differences between articles related to COVID-19 and those unrelated to COVID-19 (p = 0.824). Moreover, no significant differences were found between articles and preprints related to COVID-19 (p = 0.843). Significant heterogeneity was observed in each subgroup. An Egger's test revealed publication bias in both articles and preprints related to COVID-19 (p < 0.001). Conclusions: Determining whether the anxiety state of health care workers is altered by the COVID-19 pandemic is currently difficult. However, there is evidence that their anxiety levels may always be high, which suggests that more attention should be paid to their mental health. Furthermore, we found a substantial publication bias; however, the quality of the studies was relatively stable and reliable.

Safety Risk Assessment of Tourism Management System Based on PSO-BP Neural Network.

With the development of science and technology, system management is gradually applied to tourism management. How to correctly assess the security risks of the tourism management system has become an important means to maintain passenger information. The security risk index of the travel management system is input into the PSO-BP network as a sample, and the corresponding risk value of the index is used as the network output. The results show that the error results, accuracy (96.53%), training time (216 s), number of iterations (275 times), and convergence speed are all better than traditional BP network. The relative error of PSO-BP network (0.32%) is better than that of BP network, with 300 iterations, and the error is close to 10-5. The average evaluation accuracy of S based on PSO-BP network is 99.72%, and the average time consumed is 2.512 s. It is superior to the evaluation model based on fuzzy set and entropy weight theory and the evaluation model based on gray correlation analysis and radial basis function neural network. In conclusion, the security risk assessment of the tourism management system based on PSO-BP network can effectively assess the security risk of the tourism management system.

The Effect of the COVID-19 Pandemic on Health Care Workers' Anxiety Levels: Protocol for a Meta-Analysis.

BACKGROUND: The COVID-19 pandemic has been declared a public health emergency of international concern; this has caused excessive anxiety among health care workers. In addition, publication bias and low-quality publications have become widespread, which can result in the dissemination of unreliable findings. OBJECTIVE: This paper presents the protocol for a meta-analysis with the following two aims: (1) to examine the prevalence of anxiety among health care workers and determine whether it has increased due to the COVID-19 pandemic, and (2) to investigate whether there has been an increase in publication bias. METHODS: All related studies that were published/released from 2015 to 2020 will be searched in electronic databases (Web of Science, PubMed, PsyArXiv, and medRxiv). The risk of bias in individual studies will be assessed using the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist. The heterogeneity of the studies will be assessed using the I2 statistic. The effect size (prevalence rates of anxiety) and a 95% CI for each paper will also be calculated. We will use a moderator analysis to test for the effect of COVID-19 on health care workers' anxiety levels and detect publication bias in COVID-19 studies. We will also assess publication bias using the funnel plot and Egger regression. In case of publication bias, if studies have no homogeneity, the trim-and-fill procedure will be applied to adjust for missing studies. RESULTS: Database searches will commence in November 2020. The meta-analysis will be completed within 2 months of the start date. CONCLUSIONS: This meta-analysis aims to provide comprehensive evidence about whether COVID-19 increases the prevalence of anxiety among health care workers and whether there has been an increase in publication bias and a deterioration in the quality of publications due to the pandemic. The results of this meta-analysis can provide evidence to help health managers to make informed decisions related to anxiety prevention in health care workers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/24136.

[A point mutation of protein C gene in a congenital protein C deficiency pedigree].

OBJECTIVE: To study the phenotypes and genotypes of a protein C (PC) deficiency pedigree. METHODS: Immunoassay (ELISA) was used for PC antigen and activated PC (APC) detection, PCR for amplification of the fragment of protein C gene exon II to exon IX, single-strand conformation polymorphism (SSCP) for difference of denatured cDNA and DNA sequencing for gene mutation. RESULTS: Four members in the pedigree were found to be PC antigen levels between 34.3% - 67.8% and PC activity between 22% - 49% which are lower in comparison with normal references (80% - 120% and 70% - 130%, respectively). A G-to-A mutation in exon VII of the protein C gene at 6 219 position was identified in 9 members. This mutation resulted in the substitution of Arg for Gln at 169 amino acid. CONCLUSION: The proband is of heterozygosity. The G6219 A mutation in exon VII of the protein C gene leads to the substitution of Arg 169 Gln. This mutation is reported for the first time in China.