Alpinate Oxyphyllae Fructus Inhibits IGFII-Related Signaling Pathway to Attenuate Ang II-Induced Pathological Hypertrophy in H9c2 Cardiomyoblasts

Chuan-Te Tsai,Yung-Ming Chang,Shu-Luan Lin,Yueh-Sheng Chen,Yu-Lan Yeh,Viswanadha Vijaya Padma,Chin-Chuan Tsai,Ray-Jade Chen,Tsung-Jung Ho,Chih-Yang Huang 한국식품영양과학회 2016 Journal of medicinal food Vol.19 No.3

Angiotensin II (Ang II) is a very important cardiovascular disease inducer and may cause cardiac pathological hypertrophy and remodeling. We evaluated a Chinese traditional medicine, alpinate oxyphyllae fructus (AOF), for therapeutic efficacy for treating Ang II-induced cardiac hypertrophy. AOF has been used to treat patients with various symptoms accompanying hypertension and cerebrovascular disorders in Korea. We investigated its protective effect against Ang II-induced cytoskeletal change and hypertrophy in H9c2 cells. The results showed that treating cells with Ang II resulted in pathological hypertrophy, such as increased expression of transcription factors NFAT-3/p-NFAT-3, hypertrophic response genes (atrial natriuretic peptide [ANP] and b-type natriuretic peptide [BNP]), and Gαq down-stream effectors (PLCβ3 and calcineurin). Pretreatment with AOF (60–100 μg/mL) led to significantly reduced hypertrophy. We also found that AOF pretreatment significantly suppressed the cardiac remodeling proteins, metalloproteinase (MMP9 and MMP2), and plasminogen activator, induced by Ang II challenge. In conclusion, we provide evidence that AOF protects against Ang II-induced pathological hypertrophy by specifically inhibiting the insulin-like growth factor (IGF) II/IIR-related signaling pathway in H9c2 cells. AOF might be a candidate for cardiac hypertrophy and ventricular remodeling prevention in chronic cardiovascular diseases.

Distinct Inflammation Biomarkers in Healthy Individuals and Patients with Schizophrenia: A Reliability Testing of Multiplex Cytokine Immunoassay by Bland-Altman Analysis

Ta-Chuan Yeh,Hsuan-Te Chu,Chia-Kuang Tsai,Hsin-An Chang,Fu-Chi Yang,San-Yuan Huang,Chih-Sung Liang 대한신경정신의학회 2019 PSYCHIATRY INVESTIGATION Vol.16 No.8

Objective Since the inflammatory process has been implicated in the pathophysiology of psychiatric disorder, an important issue emerging is to assess the test-retest reliability of cytokine measurement in healthy individuals and patients with schizophrenia. The objective of the present study was to investigate the test-retest reliability of bead-based multiplex immunoassay technology (BMIT) for cytokine measurement by using a Bland-Altman plot (BAP). Methods Twenty healthy individuals and twenty patients with schizophrenia were enrolled, and a 17-plex cytokine assay was used to measure inflammatory biomarkers at baseline and two weeks later. The test-retest reliability was examined by BAP, 95% limits of agreement (LOA), intraclass correlation coefficient (ICC), and coefficient of repeatability (CoR). Results In the healthy controls, only interleukin (IL)-2, IL-13, IL-10, IL-17, and macrophage inflammatory protein-1β showed excellent ICC. The BAP with 95% LOA determined that 13 cytokines showed acceptable 95% LOA for a 2-week test-retest reliability, and only IL-1β, IL-12 and tumor necrosis factor (TNF)-α had significant test-retest bias. The CoR of cytokines varied significantly, ranging from 1.72 to 218.1. Compared with healthy controls, patients with schizophrenia showed significantly higher levels of IL-5, IL-13, and TNF-α and significantly lower levels of IL-4, IL-12, and interferon-gamma (IFN-γ). Of these six cytokines, IL-12 and TNF-α were considered suboptimal reliability. Conclusion The findings from ICC and CoR implied that the test-retest reliability of BMIT for cytokine measurement were suboptimal. However, the BAP with 95% LOA confirmed that BMIT can reliably distinguish schizophrenia from healthy individuals in cytokine measurement, while significant within-subject variation and between-group overlapping were evident in cytokine expression.

The association of ambient air pollution with airway inflammation in schoolchildren.

Chen, Bing-Yu,Chan, Chang-Chuan,Lee, Chung-Te,Cheng, Tsun-Jen,Huang, Wen-Chuan,Jhou, Ji-Ci,Han, Yueh-Ying,Chen, Chu-Chih,Guo, Yue Leon School of Hygiene and Public Health of the Johns H 2012 American Journal of Epidemiology Vol.175 No.8

<P>The biologic mechanisms involved in airway inflammatory response to air pollution are not clearly understood. The authors conducted a longitudinal study to investigate whether exposure to ambient air pollutants affected inflammatory cells and mediators from nasal lavage in schoolchildren. Study participants were 100 elementary and middle-school students in New Taipei City, Taiwan. A structured respiratory health questionnaire was administered in September 2007, followed by monthly measurement of nasal inflammation from October 2007 to November 2009. During the study period, daily concentrations of air pollutants were obtained from the Environmental Protection Administration monitoring station and the Aerosol Supersite. Mixed-effects models were applied to examine the association between air pollution and nasal inflammatory cells and mediators, including percentages of neutrophils, eosinophils, and monocytes in lavaged cells and interleukin-8. A total of 824 measurements were obtained from 100 participants over a period of 10 months. The level of particulate matter with an aerodynamic diameter of 2.5 μm or less (PM(2.5)) was found to be associated with percentage of neutrophils (β = 3.45%, 95% confidence interval: 0.89, 6.01) and interleukin-8 level (β = 29.98 pg/mL, 95% confidence interval: 3.26, 56.69) in the nasal lavage on the day of exposure. In this longitudinal cohort study of schoolchildren, results indicated that exposure to PM(2.5) might induce nasal inflammation.</P>

Incongruent Expression of Brain-Derived Neurotrophic Factor and Cortisol in Schizophrenia: Results from a Randomized Controlled Trial of Laughter Intervention

Shu-Li Cheng,Fu-Chi Yang,Hsuan-Te Chu,Chia-Kuang Tsai,Shih-Chieh Ku,Yu-Ting Tseng,Ta-Chuan Yeh,Chih-Sung Liang 대한신경정신의학회 2020 PSYCHIATRY INVESTIGATION Vol.17 No.12

Objective Schizophrenia has been associated with dysfunction of the hypothalamic-pituitary-adrenal axis. Furthermore, alterations in neurotrophic factors might contribute to the pathogenesis of schizophrenia. We aimed to evaluate the effects of a simulated laughter intervention on the levels of cortisol and BDNF and to determine whether the effects associated with simulated laughter could be sustained after discontinuation of the intervention. Methods In this randomized controlled study, patients with schizophrenia according to DSM-IV clinical criteria were randomly assigned to receive either 8-week-long simulated laughter intervention (n=32) or treatment-as-usual group (control group, n=27). The serum levels of BDNF and cortisol were measured at baseline, week 8, and four weeks after discontinuation (week 12) of the intervention program. Results After an 8-week simulated laughter intervention, the laughter group had significantly higher levels of BDNF; however, four weeks after discontinuation of the intervention, the levels of BDNF significantly dropped. Interestingly, the levels of cortisol did not change significantly at week 8, but they were significantly elevated at week 12. The levels of BDNF and cortisol in the control group did not change significantly between week 0 and week 8. Conclusion These findings suggest that the simulated laughter intervention has an early effect on neurogenesis with a significant delayed effect on stress regulation in subjects with schizophrenia.

Localization and Size Estimation for Breaks in Nuclear Power Plants

Ting-Han Lin,Ching Chen,Shun-Chi Wu,Te-Chuan Wang,Yuh-Ming Ferng 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.1

Several algorithms for nuclear power plant (NPP) break event detection, isolation, localization, and size estimation are proposed. A break event can be promptly detected and isolated after its occurrence by simultaneously monitoring changes in the sensing readings and by employing an interquartile range-based isolation scheme. By considering the multi-sensor data block of a break to be rank-one, it can be located as the position whose lead field vector is most orthogonal to the noise subspace of that data block using the Multiple Signal Classification (MUSIC) algorithm. Owing to the flexibility of deep neural networks in selecting the best regression model for the available data, we can estimate the break size using multiple-sensor recordings of the break regardless of the sensor types. The efficacy of the proposed algorithms was evaluated using the data generated by Maanshan NPP simulator. The experimental results demonstrated that the MUSIC method could distinguish two near breaks. However, if the two breaks were close and of small sizes, the MUSIC method might wrongly locate them. The break sizes estimated by the proposed deep learning model were close to their actual values, but relative errors of more than 8% were seen while estimating small breaks’ sizes.