YiQi GuBen formula alleviates airway inflammation and airway remodeling in OVA-induced asthma mice through TLR4/NF-κB signaling pathway.

BACKGROUND: We aim to investigate the effect of YiQi GuBen formula (YQGB) on airway inflammation and airway remodeling in the ovalbumin (OVA)-induced asthma model to further explore the potential mechanisms of YQGB in treating allergic asthma. METHODS: Mice were divided into five groups randomly (n = 10): the control group, OVA group, OVA + Dex (0.1 mg/kg) group, OVA + low-dose (1.1 g/kg) YQGB group, and OVA + high-dose (2.2 g/kg) YQGB group. Inflammatory cell count and IgE were detected in bronchoalveolar lavage fluid (BALF). Lung tissue histopathology was observed by using H&E, PAS, Masson, and immunohistochemistry staining. qRT-PCR and western blot were applied to analyze key genes and proteins associated with TLR4 and NF-κB signaling pathways. RESULTS: In OVA-induced asthma mice, YQGB decreased eosinophils and IgE in BALF. YQGB alleviated the OVA-induced inflammatory infiltration and declined IL-4, IL-5, IL-13, Eotaxin, ECP, GM-CSF, LTC4, and LTD4. YQGB attenuated the OVA-induced goblet cell metaplasia and mucus hypersecretion. YQGB mitigated the OVA-induced subepithelial fibrosis and lowered TGF-ß1, E-Cadherin, Vimentin, and Fibronectin. YQGB ameliorated the OVA-induced airway smooth muscle thickening and lessened α-SMA and PDGF levels. YQGB reduced the expression of TLR4, MyD88, TRAF6, IκBα, and p65 mRNAs, and IκBα and p-p65 protein levels were also reduced. CONCLUSION: YQGB exhibits the anti-asthma effect by reducing airway inflammation and airway remodeling through suppressing TLR4/NF-κB signaling pathway, and is worth promoting clinically.

An empirical study on learners' learning emotion and learning effect in offline learning environment.

The application of non-cognitive factors represented by facial emotion in educational evaluation has attracted much attention in recent years. There are many existing studies on facial emotion assisted education evaluation, but most of them are based on virtual learning environments, which means that the research on facial emotion and learning effect in offline learning environments is sparse. In order to solve this problem, this study designed an emotion observation experiment based on the offline learning environment, obtained the type of learner facial emotion and learning effect of 127 college students, and further explored the relationship between the two. The results show that: 1) We obtained eight types of learner emotion through the combined description method: joy, relaxation, surprise, meekness, contempt, disgust, sadness, anxiety and their respective PAD emotional mean. 2) We obtained the correlation results of the six emotions of joy, relaxation, surprise, meekness, contempt, and anxiety with the learning effect and the predicted value of the learning effect. 3) We then constructed an explanatory model of learner emotion and learning effect based on the offline learning environment.