Dictamnus dasycarpus Turcz. attenuates airway inflammation and mucus hypersecretion by modulating the STAT6-STAT3/FOXA2 pathway.

BACKGROUND: Effects of Dictamnus dasycarpus Turcz. on allergic asthma and their underlying mechanisms remain unclarified. Thus, we investigated the effects of D. dasycarpus Turcz. water extract (DDW) on mucus hypersecretion in mice with ovalbumin (OVA)-induced asthma and human bronchial epithelial cells. METHODS: BALB/c mice were used to establish an OVA-induced allergic asthma model. Mice were grouped into the OVA sensitization/challenge, 100 and 300 mg/kg DDW treatment, and dexamethasone groups. In mice, cell counts in bronchoalveolar lavage fluid (BALF), serum and BALF analyses, and histopathological lung tissue analyses were performed. Furthermore, we confirmed the basic mechanism in interleukin (IL)-4/IL-13-treated human bronchial epithelial cells through western blotting. RESULTS: In OVA-induced asthma mice, DDW treatment reduced inflammatory cell number and airway hyperresponsiveness and ameliorated histological changes (immune cell infiltration, mucus secretion, and collagen deposition) in lung tissues and serum total immunoglobulin E levels. DDW treatment lowered BALF IL-4, IL-5, and IL-13 levels; reduced levels of inflammatory mediators, such as thymus- and activation-regulated chemokine, macrophage-derived chemokine, and interferon gamma-induced protein; decreased mucin 5AC (MUC5AC) production; decreased signal transducer and activator of transcription (STAT) 6 and STAT3 expression; and restored forkhead box protein A2 (FOXA2) expression. In IL-4/IL-13-treated human bronchial epithelial cells, DDW treatment inhibited MUC5AC production, suppressed STAT6 and STAT3 expression (related to mucus hypersecretion), and increased FOXA2 expression. CONCLUSIONS: DDW treatment modulates MUC5AC expression and mucus hypersecretion by downregulating STAT6 and STAT3 expression and upregulating FOXA2 expression. These findings provide a novel approach to manage mucus hypersecretion in asthma using DDW.

Optimization design of the sound absorbing structure of double-layer porous metal material with air layer based on genetic algorithm.

An acoustic absorption structure of a double-layer porous metal material with air layers is proposed. The Johnson-Champoux-Allard (JCA) model combined with the transfer matrix method (TMM) was used to establish the theoretical calculation model of the sound absorption coefficient (SAC). Meanwhile, the SAC between 500 and 6300 Hz were measured with an impedance tube. The errors between the theoretical and experimental values were compared to illustrate the good predictability of the theoretical model within the inverse estimations of the transport properties. The effects of the material placement order, material thickness, and cavity depth on the sound absorption performance from 200 to 5000 Hz were analyzed using the theoretical model. Further, a multi-objective function genetic algorithm was used to optimize the porous material's thickness and SAC to obtain an acoustic structure with a smaller thickness and higher sound absorption. A series of optimal solutions were obtained for acoustic structures with a total thickness of less than 70 mm. When the total thickness of the foam metal was 33.57 mm, the average SAC reached 0.853, which was significantly lower than the total thickness of the previous experiments. The multi-objective function genetic algorithm can provide a reliable solution for the optimal design of most sound-absorbing structures.

Prediction of the Sound Absorption Coefficient of Three-Layer Aluminum Foam by Hybrid Neural Network Optimization Algorithm.

The combination of multilayer aluminum foam can have high sound absorption coefficients (SAC) at low and medium frequencies, and predicting its absorption coefficient can help the optimal structural design. In this study, a hybrid EO-GRNN model was proposed for predicting the sound absorption coefficient of the three-layer composite structure of the aluminum foam. The generalized regression neural network (GRNN) model was used to predict the sound absorption coefficient of three-layer composite structural aluminum foam due to its outstanding nonlinear problem-handling capability. An equilibrium optimization (EO) algorithm was used to determine the parameters in the neuronal network. The prediction results show that this method has good accuracy and high precision. The calculation result shows that this proposed hybrid model outperforms the single GRNN model, the GRNN model optimized by PSO (PSO-GRNN), and the GRNN model optimized by FOA(FOA-GRNN). The prediction results are expressed in terms of root mean square error (RMSE), absolute error, and relative error, and this method performs well with an average RMSE of only 0.011.

Effect of complex treatment using visual and auditory stimuli on the symptoms of attention deficit/hyperactivity disorder in children.

We investigated the effects of complex treatment using visual and auditory stimuli on the symptoms of attention deficit/hyperactivity disorder (ADHD) in children. Forty-seven male children (7-13 yr old), who were clinically diagnosed with ADHD at the Balance Brain Center in Seoul, Korea, were included in this study. The complex treatment consisted of visual and auditory stimuli, core muscle exercise, targeting ball exercise, ocular motor exercise, and visual motor integration. All subjects completed the complex treatment for 60 min/day, 2-3 times/week for more than 12 weeks. Data regarding visual and auditory reaction time and cognitive function were obtained using the Neurosync program, Stroop Color-Word Test, and test of nonverbal intelligence (TONI) at pre- and post-treatment. The complex treatment significantly decreased the total reaction time, while it increased the number of combo actions on visual and auditory stimuli (P< 0.05). The Stroop color, word, and color-word scores were significantly increased at post-treatment compared to the scores at pretreatment (P< 0.05). There was no significant change in the TONI scores, although a tendency toward an increase in these scores was observed. In conclusion, complex treatment using visual and auditory stimuli alleviated the symptoms of ADHD and improved cognitive function in children. In addition, visual and auditory function might be possible indicators for demonstrating effective ADHD intervention.

Diabetes reduces the cognitive function with the decrease of the visual perception and visual motor integration in male older adults.

This study investigated the influence of diabetes on cognitive decline between the diabetes and non- diabetes patients and identified the associations between diabetes and cognitive function, visual perception (VP), and visual motor integration (VMI). Sixty elderly men (67.10± 1.65 yr) with and without diabetes (n= 30 in each group) who were surveyed by interview and questionnaire in South Korea were enrolled in this study. The score of Mini-Mental State Examination of Korean version (MMSE-KC), Motor-free Visual Perception Test-Vertical Format (MVPT-V), and Visual-Motor Integration 3rd Revision (VMI-3R) were assessed in all of the participants to evaluate cognitive function, VP, and VMI in each. The score of MMSE-KC in the diabetic group was significantly lower than that of the non-diabetes group (P< 0.01). Participants in the diabetes group also had lower MVPT-V and VMI-3R scores than those in the non-diabetes group (P< 0.01, respectively). Especially, the scores of figure-ground and visual memory among the subcategories of MVPT-V were significantly lower in the diabetes group than in the non-diabetes group (P< 0.01). These findings indicate that the decline in cognitive function in individuals with diabetes may be greater than that in non-diabetics. In addition, the cognitive decline in older adults with diabetes might be associated with the decrease of VP and VMI. In conclusion, we propose that VP and VMI will be helpful to monitor the change of cognitive function in older adults with diabetes as part of the routine management of diabetes-induced cognitive declines.

[Self-care behaviors and depressive symptoms of low-income elderly women with hypertension].

PURPOSE: This study aimed to compare self-care behaviors and depressive symptoms between the young old (65-74 yr) and the old-old (75-84 yr) in low-income women with hypertension. METHODS: This study used a descriptive research design. The subjects of this study were 136 elderly women over 65 yr living in D city. Data was collected from September to December 2007 through personal interviews using a questionnaire. The collected data was analyzed using the SPSS WIN 12.0 Program. RESULTS: Self-care behaviors, functional status, and number of medications showed a significant difference between young elderly and middle elderly. There was a negative correlation between self-care behaviors and depressive symptoms. 52.2% of variance in self-care behaviors of young elderly and 76.8% of variance in self-care behaviors of middle elderly were explained by depressive symptoms, number of medications, and functional status. CONCLUSION: It is necessary to manage depressive symptoms to improve the self-care behaviors of low-income elderly with hypertension. Depressive symptoms need to be considered in planning hypertension programs for low-income elderly women.