Search

Coix seed is a functional food in the Chinese diet that possesses the ability to alleviate ulcerative colitis clinically. However, the underlying mechanisms remain ambiguous. In this study, we investigated the protective effect of the Coix seed diet on experimental colitis mice. The mice were randomly divided into four groups: control group, model group, Coix seed feed group, and positive control group. The maintenance feed of the mice was replaced with Coix seed feed 10 days before orally administering the mice 5% (w/v) dextran sulfate sodium drink. As a result, the Coix seed feed alleviated colitis symptoms, maintained the complete blood count at a normal level, reduced the pathological score, relieved inflammatory cytokine secretion, and alleviated oxidative stress. Network pharmacology analysis was used for further exploration of the targets of Coix seed feed. The results showed that T-cell regulation is one of the targets of Coix seed feed, and the analysis of the T-lymphocyte subset and innate immune cell distribution of the colon tissue supported the network pharmacology results. In conclusion, Coix seed, as a staple food, can alleviate experimental colitis, and the mechanism may be related to the immune regulation effect of Coix seeds. [ABSTRACT FROM AUTHOR]

AbstractAlthough an increasing number of studies explore the factors influencing users’ privacy concerns regarding social robots, the existing understanding of this issue remains largely fragmented. Previous studies have mainly focused on the "net effect" between variables, leaving the complexity of causal configurations, and the holistic impact of design characteristics of social robots on user privacy concerns remains unclear. Based on the Stimuli-Organism-Response (S-O-R) framework and Communication Privacy Management Theory (CPMT), this study integrates social robot design characteristics such as Anthropomorphism, Warmth, Competence, and Transparency into causal configurations, and uses Perceived Privacy Risk and Perceived Privacy Control as mediating variables to propose a Comprehensive conceptual model. Based on valid data from a sample of 198 Chinese social robot users, this study conducted empirical analyses of the conceptual model using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (FsQCA). PLS-SEM results show that anthropomorphism, warmth, competence, and transparency are key factors influencing privacy concerns, and perceived privacy risk mediates the relationship between warmth, information transparency, and privacy concerns. The FsQCA results further validated the findings of PLS-SEM and identified five configurations of factor combinations that led to higher levels of user privacy concerns. Among them, the combination of high anthropomorphism design, high competence, and low warmth of social robots is the core configuration that leads to users’ privacy concerns. Overall, this study broadens our understanding of social robot users’ privacy concerns and reveals the causal complexity behind social robot users’ privacy concerns. It provides some theoretical and practical insights for subsequent scholars and designers. [ABSTRACT FROM AUTHOR]