Social support as a mediator of the relationship between forgiveness and post-traumatic growth in hemodialysis patients: A structural equation modeling approach

BackgroundPost-traumatic growth (PTG) refers to the positive psychological changes experienced with individuals after struggling with highly challenging life circumstances. Forgiveness can facilitate positive outcomes such as reduced distress, anxiety, and depression. Many studies have tested the relationships among forgiveness, social support, and PTG; however, a mechanism of social support has not been completely explored in hemodialysis patients.ObjectiveTo test the relationship between forgiveness and post-traumatic growth and verify the mediating factor of social support on the relationship between forgiveness and PTG in hemodialysis patients.Materials and methodsIn a descriptive cross-sectional study using convenience sampling from March to May 2021, 497 hemodialysis patients from nine hospitals filled out the Perceived Social Support Scale (PSSS), Heartland Forgiveness Scale (HFS), Post-traumatic Growth Inventory (PTGI), and general information. Data were analyzed using SPSS, and structural equation modeling was used to explore the relationships among forgiveness, social support, and PTG.ResultsForgiveness was significantly positively associated with PTG (P < 0.01). The proposed model provided a good fit to the data. Social support was found to play a partial mediating role between forgiveness and PTG (a*b = 0.122, BCa 95% CI: 0.078∼0.181).ConclusionThe results imply that forgiveness significantly directly and indirectly is related to PTG. Forgiveness in hemodialysis patients should be detected and effectively managed to ameliorate positive effects on PTG. It is necessary for nurses to consider implementing forgiveness interventions with an emphasis on building social support strategies to help hemodialysis patients enhance their PTG

Baicalein-corrected gut microbiota may underlie the amelioration of memory and cognitive deficits in APP/PS1 mice

Background: Baicalein is an active ingredient extracted from the root of S. baicalensis Georgi, which exhibits cardiovascular protection, anti-inflammatory, and anti-microbial properties. Our previous study showed that chronic treatment of Baicalein ameliorated cognitive dysfunction in a mouse model of Alzheimer's disease (AD). However, it remains unknown whether Baicalein ameliorates cognitive deficits in AD mouse models by altering gut microbiota and its metabolites.Methods: Behavioral tests, metagenomic and untargeted metabolomics analyses were used to evaluate the effects of Baicalein on the APP/PS1 mice.Results: Our research showed that treatment of Baicalein for 2 weeks ameliorated cognition and memory in a dose-dependent manner, as indicated by the significant increases in the Discrimination index and Number of crossings and decrease in latency to the previous platform location in 8-month of age APP/PS1 mice in novel object recognition and water maze tests. The metagenomic analysis showed the abundance of the dominant phyla in all groups, including Bacteroidetes (14.59%–67.02%) and Firmicutes (20.19%–61.39%). LEfSe analysis of metagenomics identified three species such as s__Roseburia_sp_1XD42_69, s__Muribaculaceae_bacterium_Isolate_104_HZI, s__Muribaculaceae_bacterium_Isolate_110_HZI as Baicalein-treated potential biomarkers. Metabolite analysis revealed the increment of metabolites, including glutamate, thymine and hexanoyl-CoA.Conclusion: The effects of Baicalein on memory and cognition may relate to the metabolism of nucleotides, lipids and glucose

Effects of Common Polymorphisms rs11614913 in miR-196a2 and rs2910164 in miR-146a on Cancer Susceptibility: A Meta-Analysis

BACKGROUND: MicroRNAs regulate gene expression at the post-transcriptional level and involved in diverse biological and pathological processes, including tumorigenesis. Rs11614913 in miR-196a2 and rs2910164 in miR-146a are shown to associate with increased/decreased cancer risk. We performed a meta-analysis to systematically summarize the possible association. METHODOLOGY/PRINCIPAL FINDINGS: We assessed published studies of the association between these microRNA polymorphisms and cancer risk from eleven studies with 16,771 subjects for miR-196a2 and from ten studies with 15,126 subjects for miR-146a. As for rs11614913, the contrast of homozygote (TT vs CC: OR = 0.92, 95% CI = 0.85-0.99, P(heterogeneity) = 0.45), allele (T vs C: OR = 0.96, 95% CI = 0.92-0.99, P(heterogeneity) = 0.61) and recessive model (OR = 0.90, 95% CI = 0.84-0.97, P(heterogeneity) = 0.50) produced statistically association. Subgroup analysis by ethnicity, statistically significantly decreased cancer risks were found among Asians for allele contrast (OR = 0.95, 95% CI = 0.90-0.99, P(heterogeneity) = 0.74) and the recessive genetic model (OR = 0.90, 95% CI = 0.82-0.98, P(heterogeneity) = 0.85). According to subgroup analysis by tumor types, the protective effect of C/T polymorphism was only found in breast cancer under allele contrast (T vs C: OR = 0.94, 95% CI = 0.88-0.99, P(heterogeneity) = 0.26). For rs2910164, no significant associations were found among overall analysis model with relatively large heterogeneity. Through the stratified analysis, heterogeneity decreased significantly. In the subgroup analyses by cancer types, the C allele of rs2910164 was associated with protection from digestive cancer in allele contrast (C vs G: OR = 0.86, 95% CI = 0.77-0.96, P(heterogeneity) = 0.51). CONCLUSIONS/SIGNIFICANCE: Our meta-analysis suggests that the rs11614913 most likely contributes to decreased susceptibility to cancer, especially in Asians and breast cancer. Besides, the C allele of the rs2910164 might be associated with a protection from digestive cancer

Image Encryption Scheme Based on a Generalized Arnold Map and RSA Algorithm

This study proposes a new image encryption scheme based on a generalized Arnold map and Rivest–Shamir–Adleman (RSA) algorithm. First, the parameters of the generalized Arnold map are generated by an asymmetric encryption-system RSA algorithm, and the keystream is produced iteratively. To change the distribution of pixel values, the image data are hidden by XOR diffusion. Second, both rows and columns of the image are cyclically confused to hide the image data again. Then, the additive mode diffusion operation is performed to realize third-layer hiding for image content. The overall diffusion and confusion operations are conducted twice to obtain the final cipher image. Test results prove that the encryption scheme proposed in this study is effective and has strong antiattack capabilities and key sensitivity. In addition, because the scheme security relies on the RSA algorithm, it has high security

Changes and Relationships of Climatic and Hydrological Droughts in the Jialing River Basin, China.

The comprehensive assessment of climatic and hydrological droughts in terms of their temporal and spatial evolutions is very important for water resources management and social development in the basin scale. To study the spatial and temporal changes of climatic and hydrological droughts and the relationships between them, the SPEI and SDI are adopted to assess the changes and the correlations of climatic and hydrological droughts by selecting the Jialing River basin, China as the research area. The SPEI and SDI at different time scales are assessed both at the entire Jialing River basin and at the regional levels of the three sub basins. The results show that the SPEI and SDI are very suitable for assessing the changes and relationships of climatic and hydrological droughts in large basins. Based on the assessment, for the Jialing River basin, climatic and hydrological droughts have the increasing tendency during recent several decades, and the increasing trend of climatic droughts is significant or extremely significant in the western and northern basin, while hydrological drought has a less significant increasing trend. Additionally, climatic and hydrological droughts tend to increase in the next few years. The results also show that on short time scales, climatic droughts have one or two months lag impact on hydrological droughts in the north-west area of the basin, and have one month lag impact in south-east area of the basin. The assessment of climatic and hydrological droughts based on the SPEI and SDI could be very useful for water resources management and climate change adaptation at large basin scale

Grammar-Supervised End-to-End Speech Recognition with Part-of-Speech Tagging and Dependency Parsing

For most automatic speech recognition systems, many unacceptable hypothesis errors still make the recognition results absurd and difficult to understand. In this paper, we introduce the grammar information to improve the performance of the grammatical deviation distance and increase the readability of the hypothesis. The reinforcement of word embedding with grammar embedding is presented to intensify the grammar expression. An auxiliary text-to-grammar task is provided to improve the performance of the recognition results with the downstream task evaluation. Furthermore, the multiple evaluation methodology of grammar is used to explore an expandable usage paradigm with grammar knowledge. Experiments on the small open-source Mandarin speech corpus AISHELL-1 and large private-source Mandarin speech corpus TRANS-M tasks show that our method can perform very well with no additional data. Our method achieves relative character error rate reductions of 3.2% and 5.0%, a relative grammatical deviation distance reduction of 4.7% and 5.9% on AISHELL-1 and TRANS-M tasks, respectively. Moreover, the grammar-based mean opinion score of our method is about 4.29 and 3.20, significantly superior to the baseline of 4.11 and 3.02