spv locus aggravates Salmonella infection of zebrafish adult by inducing Th1/Th2 shift to Th2 polarization.

Salmonella enterica serovar typhimurium (S. typhimurium) are facultative intracellular enteric pathogens causing disease with a broad range of hosts. It was known that Th1-type cytokines such as IFN-γ, IL-12, and TNF-α etc. could induce protective immunity against intracellular pathogens, while Th2-type cytokines such as IL-4, IL-10, and IL-13 etc. are proved to help pathogens survive inside hosts and cause severe infection. One of the critical virulence factor attributes to the pathogenesis of S. typhimurium is Salmonella plasmid virulence genes (spv). Until now, the interaction between spv locus and the predictable generation of Th1 or Th2 immune responses to Salmonella has not been identified. In this study, zebrafish adults were employed to explore the effect of spv locus on Salmonella pathogenesis as well as host adaptive immune responses especially shift of Th1/Th2 balance. The pathological changes of intestines and livers in zebrafish were observed by hematoxylin-eosin (HE) staining and electron microscopy. Levels of the transcription factors of Th1 (Tbx21) and Th2 (GATA3) were measured by real-time quantitative PCR (RT-qPCR). Expression of cytokines were determined by using RT-qPCR and ELISA, respectively. Results showed that spv operon aggravates damage of zebrafish. Furthermore, it demonstrated that spv locus could inhibit the transcription of tbx21 gene and suppress the expression of cytokines IFN-γ, IL-12 and TNF-α. On the contrary, the transcription of gata3 gene could be promoted and the expression of cytokines IL-4, IL-10 and IL-13 were enhanced by spv locus. Taken together, our data revealed that spv locus could aggravate Salmonella infection of zebrafish adult by inducing an imbalance of Th1/Th2 immune response and resulting in a detrimental Th2 bias of host.

Salmonella spv locus suppresses host innate immune responses to bacterial infection.

Salmonella enterica serovar typhimurium (S. typhimurium) is globally distributed and causes massive morbidity and mortality in humans and animals. S. typhimurium carries Salmonella plasmid virulence (spv) locus, which is highly conserved and closely related to bacterial pathogenicity, while its exact role in host immune responses during infection remains to be elucidated. To counteract the invaders, the host has evolved numerous strategies, among which the innate immunity and autophagy act as the first defense. Recently, zebrafish has been universally accepted as a valuable and powerful vertebrate model in analyzing bacteria-host interactions. To investigate whether spv locus enhances the virulence of Salmonella by exerting an effect on the host early defense, zebrafish larvae were employed in this study. LD50 of S. typhimurium to zebrafish larvae and bacterial dissemination were analyzed. Sudan black B and neutral red staining were performed to detect the responses of neutrophils and macrophages to Salmonella infection. Autophagy agonist Torin1 and inhibitor Chloroquine were used to interfere in autophagic flux, and the protein level of Lc3 and p62 were measured by western blotting. Results indicated that spv locus could decrease the LD50 of S. typhimurium to zebrafish larvae, accelerate the reproduction and dissemination of bacteria by inhibiting the function of neutrophils and macrophages. Moreover, spv locus restrained the formation of autophagosomes in the earlier stage of autophagy. These findings suggested the virulence of spv locus involving in suppressing host innate immune responses for the first time, which shed new light on the role of spv operon in Salmonella pathogenicity.

Mediating roles of activities of daily living and depression on the relationship between sleep quality and health-related quality of life.

This study aimed to explore the mediating effects of ADL and depression on the relationship between sleep quality and HRQOL among older people in rural China, while also exploring the moderating impact of loneliness. The study gathered data from a household survey conducted among 1587 Chinese rural older adults (mean age = 73.63 years). The collected data was analyzed using SPSS version 23.0 software (IBM, New York, USA) and the PROCESS macro version 4.0 program. The findings indicated a significant correlation between sleep quality, ADL, depression, loneliness and HRQOL. ADL and depression exhibited a chain mediation effect on the relationship between sleep quality and HRQOL. Notably, the association between sleep quality and HRQOL was entirely mediated by ADL and depression. Additionally, loneliness acted as a moderator in the relationship between ADL and HRQOL. The findings of this study suggest that interventions focusing on sleep quality should prioritize strategies for enhancing older adults' ADL and depression as integral components of promoting older adults' HRQOL.

Efficient self-organizing multilayer neural network for nonlinear system modeling.

It has been shown extensively that the dynamic behaviors of a neural system are strongly influenced by the network architecture and learning process. To establish an artificial neural network (ANN) with self-organizing architecture and suitable learning algorithm for nonlinear system modeling, an automatic axon-neural network (AANN) is investigated in the following respects. First, the network architecture is constructed automatically to change both the number of hidden neurons and topologies of the neural network during the training process. The approach introduced in adaptive connecting-and-pruning algorithm (ACP) is a type of mixed mode operation, which is equivalent to pruning or adding the connecting of the neurons, as well as inserting some required neurons directly. Secondly, the weights are adjusted, using a feedforward computation (FC) to obtain the information for the gradient during learning computation. Unlike most of the previous studies, AANN is able to self-organize the architecture and weights, and to improve the network performances. Also, the proposed AANN has been tested on a number of benchmark problems, ranging from nonlinear function approximating to nonlinear systems modeling. The experimental results show that AANN can have better performances than that of some existing neural networks.