Maternal Baicalin Treatment Increases Fetal Lung Surfactant Phospholipids in Rats

Baicalin is a flavonoid compound purified from the medicinal plant Scutellaria baicalensis Georgi and has been reported to stimulate surfactant protein (SP)-A gene expression in human lung epithelial cell lines (H441). The aims of this study were to determine whether maternal baicalin treatment could increase lung surfactant production and induce lung maturation in fetal rats. This study was performed with timed pregnant Sprague-Dawley rats. One-day baicalin group mothers were injected intraperitoneally with baicalin (5 mg/kg/day) on Day 18 of gestation. Two-day baicalin group mothers were injected intraperitoneally with baicalin (5 mg/kg/day) on Days 17 and 18 of gestation. Control group mothers were injected with vehicle alone on Day 18 of gestation. On Day 19 of gestation, fetuses were delivered by cesarean section. Maternal treatment with 2-day baicalin significantly increased saturated phospholipid when compared with control group and total phospholipid in fetal lung tissue when compared with control and 1-day baicalin groups. Antenatal treatment with 2-day baicalin significantly increased maternal growth hormone when compared with control group. Fetal lung SP-A mRNA expression and maternal serum corticosterone levels were comparable among the three experimental groups. Maternal baicalin treatment increases pulmonary surfactant phospholipids of fetal rat lungs and the improvement was associated with increased maternal serum growth hormone. These results suggest that antenatal baicalin treatment might accelerate fetal rat lung maturation

Disordered Fe vacancies and superconductivity in potassium-intercalated iron selenide (K2-xFe4+ySe5)

The parent compound of an unconventional superconductor must contain unusual correlated electronic and magnetic properties of its own. In the high-Tc potassium intercalated FeSe, there has been significant debate regarding what the exact parent compound is. Our studies unambiguously show that the Fe-vacancy ordered K2Fe4Se5 is the magnetic, Mott insulating parent compound of the superconducting state. Non-superconducting K2Fe4Se5 becomes a superconductor after high temperature annealing, and the overall picture indicates that superconductivity in K2-xFe4+ySe5 originates from the Fe-vacancy order to disorder transition. Thus, the long pending question whether magnetic and superconducting state are competing or cooperating for cuprate superconductors may also apply to the Fe-chalcogenide superconductors. It is believed that the iron selenides and related compounds will provide essential information to understand the origin of superconductivity in the iron-based superconductors, and possibly to the superconducting cuprates

What do they eat? A survey of eat-out habit of university students in Taiwan

[EN] Main purpose of this research is trying to understand food likeliness of Taiwan college students, and probe whether these food are healthy. Three survey steps are taken as: step 1, market survey for what kind of foods are selling around the campuses; step 2, questionnaire investigation for students food preference; step 3, analyzing whether these favorite foods are healthy or not. The result shows: major consideration for students food selection are “taste” and “price”; 63% of students are taking food or snacks late at night at least once a week. Top three most favorite foods are: Taiwanese fries (yan su ji), carbon grilled chicken and fried fish steaks. Quantities of these foods are small, prices are low, and easy access from roadside food stands. Problems of them are high calories, easy to accumulate free radical in human body, plus insanitary food processing environment. They are harmful to student health. We suggest Taiwan government take it seriouslyShih, K.; Wang, M.; Shih, H.; Lee, S.; Lin, T. (2020). What do they eat? A survey of eat-out habit of university students in Taiwan. Editorial Universitat Politècnica de València. 421-430. https://doi.org/10.4995/INN2019.2019.10562OCS42143

Normative beliefs, attitudes, and social norms: people reduce waste as an index of social relationships when spending leisure time

This study has adopted and refined Ajzen’s theory of planned behavior, theory of reasoned action, and the value–belief–norm theory by Stern et al. to investigate the effects of normative beliefs, attitudes,andsocialnormsonpro-environmentalbehavioralintentions. Atotalof391validresponses were collected from visitors to a theme park in Taiwan. A structure equation analysis indicated that the overall fit of the proposed model was supported. It was also found that both attitudes and social norms had positive and significant influence on waste reduction. While the results did not reveal any direct relation between normative beliefs and behavioral intentions, normative beliefs had positive direct influence on social norms and attitudes, which in turn had an impact on behavioral intentions. The findings provided further insights about pro-environmental behavioral intentions from an Asia perspective and highlighted important implications for environmental policies and education to reduce waste

To Enhance the Fire Resistance Performance of High-Speed Steel Roller Door with Water Film System

The structure of high-speed roller door with water film has improved in this study. The flameproof water film system is equipped with a water circulating device to reduce the water consumption of water film system. The water film is generated at the roller box of the high-speed roller door in this study. The heating test is done with the full-scale heating furnace. Both cases of the water film on unexposed surface and water film on exposed surface passed the fire resistance test based on ISO 834, proving that the high-speed roller door with water film system has 120A fire resistance period. The main findings indicate that the water film on exposed surface shows that as the amount of water film evaporated by high temperature inside the furnace must be greater than the evaporation capacity of water film on unexposed surface, the required water supply is 660 L more than the water film on unexposed surface

A novel regulatory event-based gene set analysis method for exploring global functional changes in heterogeneous genomic data sets

<p>Abstract</p> <p>Background</p> <p>Analyzing gene expression data by assessing the significance of pre-defined gene sets, rather than individual genes, has become a main approach in microarray data analysis and this has promisingly derive new biological interpretations of microarray data. However, the detection power of conventional gene list or gene set-based approaches is limited on highly heterogeneous samples, such as tumors.</p> <p>Results</p> <p>We developed a novel method, the regulatory <b>e</b>vent-based <b>G</b>ene <b>S</b>et <b>A</b>nalysis (eGSA), which considers not only the consistently changed genes but also every gene regulation (event) of each sample to overcome the detection limit. In comparison with conventional methods, eGSA can detect functional changes in heterogeneous samples more precisely and robustly. Furthermore, by utilizing eGSA, we successfully revealed novel functional characteristics and potential mechanisms of very early hepatocellular carcinoma (HCC).</p> <p>Conclusion</p> <p>Our study creates a novel scheme to directly target the major cellular functional changes in heterogeneous samples. All potential regulatory routines of a functional change can be further analyzed by the regulatory event frequency. We also provide a case study on early HCCs and reveal a novel insight at the initial stage of hepatocarcinogenesis. eGSA therefore accelerates and refines the interpretation of heterogeneous genomic data sets in the absence of gene-phenotype correlations.</p

Image operator learning coupled with CNN classification and its application to staff line removal

Many image transformations can be modeled by image operators that are characterized by pixel-wise local functions defined on a finite support window. In image operator learning, these functions are estimated from training data using machine learning techniques. Input size is usually a critical issue when using learning algorithms, and it limits the size of practicable windows. We propose the use of convolutional neural networks (CNNs) to overcome this limitation. The problem of removing staff-lines in music score images is chosen to evaluate the effects of window and convolutional mask sizes on the learned image operator performance. Results show that the CNN based solution outperforms previous ones obtained using conventional learning algorithms or heuristic algorithms, indicating the potential of CNNs as base classifiers in image operator learning. The implementations will be made available on the TRIOSlib project site.Comment: To appear in ICDAR 201