31 research outputs found

    여성친화적 사회적기업 발전에 관한 소고(Case study on the development of female-friendly social enterprise)

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    Ischemic brain injury in diabetes and endoplasmic reticulum stress

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    Diabetes is a widespread disease characterized by high blood glucose levels due to abnormal insulin activity, production, or both. Chronic diabetes causes many secondary complications including cardiovascular disease: a life-threatening complication. Cerebral ischemia-related mortality, morbidity, and the extent of brain injury are high in diabetes. However, the mechanism of increase in ischemic brain injury during diabetes is not well understood. Multiple mechanisms mediate diabetic hyperglycemia and hypoglycemia-induced increase in ischemic brain injury. Endoplasmic reticulum (ER) stress mediates both brain injury as well as brain protection after ischemia-reperfusion injury. The pathways of ER stress are modulated during diabetes. Free radical generation and mitochondrial dysfunction, two of the prominent mechanisms that mediate diabetic increase in ischemic brain injury, are known to stimulate the pathways of ER stress. Increased ischemic brain injury in diabetes is accompanied by a further increase in the activation of ER stress. As there are many metabolic changes associated with diabetes, differential activation of the pathways of ER stress may mediate pronounced ischemic brain injury in subjects suffering from diabetes. We presently discuss the literature on the significance of ER stress in mediating increased ischemia-reperfusion injury in diabetes. [Display omitted] •The mechanism of increased ischemic brain injury in diabetes is not well understood.•Endoplasmic reticulum (ER) stress is an important mechanism of ischemic brain injury.•The pathways of ER stress are modulated during diabetes.•Diabetic increase in ischemic injury occurs along with enhanced ER stress activation.•ER stress activation may mediate pronounced ischemic brain injury in diabetes

    Factors influencing nutritional practices among mothers in Dakar, Senegal.

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    BACKGROUND:Maternal undernutrition is a leading cause of maternal mortality. Furthermore, health statuses and habits of mothers influence health statuses of newborns as well as healthy habits and mortality of children. The Senegal government is aware of the severity of these issues and has devised a national policy goal of reducing maternal, infant, and adolescent mortality rates by the end of 2018. This study aimed to identify nutritional knowledge, attitudes, and practices of lactating women in Senegal, and determine factors related to nutritional practices to obtain basic data for developing a maternal and child nutrition project. METHOD:This study used a mixed-method approach, collecting data via structured questionnaires administered to lactating women in Senegal and semistructured interviews with seven stake-holders. Questions for stuctured questionnaires were about nutritional knowledge, attitudes, and practices. For the quantitative analysis of the structured questionnaires, data from 171 participants analyzed using independent t-tests, Pearson's correlation coefficients, and multiple linear regression analysis. Interview data were analyzed using an inductive thematic analysis approach. The questions for the interviews concerned maternal and child nutritional status, causes of undernutrition, and restrictions. RESULTS:Factors significantly related to healthy nutritional practices(explaining 27.1% of variance) included having a household (B = 1.03, p = .015) and a mother (B = 0.96, p = .017) with an above primary school education, and being in the 5th quintile of income level (B = 1.24, p = .014). The interviews with seven stakeholders revealed obstructive factors of nutritional management were insufficient nutritional programs within health centers, incomplete national policy on nutrition, lack of general interest in undernutrition-related topics, inadequate economic environment, and the absence of partnerships to produce sustainable solutions. CONCLUSION:Education and income levels, rather than knowledge and attitudes, had a strong relationship with healthy nutritional practices. Therefore, economic factors and educational background must be considered to succeed in Senegalese nutrition projects

    Synthesis and side-chain engineering of phenylnaphthalenediimide (PNDI)-based n-type polymers for efficient all-polymer solar cells

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    We designed and synthesized a series of n-type conjugated polymers by introducing phenylnaphthalenediimide (PNDI) as a novel n-type building block, and investigated the effect of side-chain engineering of the polymer acceptors on the performance of all-polymer solar cells (all-PSCs). The optical, electrochemical, and structural properties of the polymers with three different side chains of 2-ethylhexyl (PPNDI-EH), 2-butyloctyl (PPNDI-BO), and 2-hexyldecyl (PPNDI-HD) groups were examined. Interestingly, the PNDI-based polymer having the longest side chain showed a higher degree of edge-on oriented intermolecular assembly in thin films, thereby resulting in the highest field-effect electron mobility among the three polymers. Also, we examined the performance of PNDI-based polymers as polymer acceptors in all-PSCs. Unlike the trend in the field-effect transistor, the PPNDI-BO-based all-PSCs exhibited the highest power conversion efficiency (PCE) of 4.25% among the three polymer blends. This was attributed to the well-balanced hole/electron transport and higher exciton dissociation probability in the PPNDI-BO-based all-PSCs, benefitted from the well-intermixed blend morphology between the polymer donor and PPNDI-BO

    Automated Assessment of Hematoma Volume of Rodents Subjected to Experimental Intracerebral Hemorrhagic Stroke by Bayes Segmentation Approach

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    Simulating a clinical condition of intracerebral hemorrhage (ICH) in animals is key to research on the development and testing of diagnostic or treatment strategies for this high mortality disease. In order to study the mechanism, pathology, and treatment for hemorrhagic stroke, various animal models have been developed. Measurement of hematoma volume is an important assessment parameter to evaluate post-ICH outcomes. However, due to tissue preservation conditions and variables in digitization, quantification of hematoma volume is usually labor intensive and sometimes even subjective. The objective of this study is to develop an automated method that can accurately and efficiently obtain unbiased cerebral hematoma volume. We developed an application (MatLab program) that can delineate the brain slice from the background and use the Hue information in the Hue/Saturation/Value (HSV) color space to segment the hematoma region. The segmentation threshold of Hue is calculated based on the Bayes classifier theorem so that the minimum error is mathematically ensured and automated processing is enabled. To validate the developed method, we compared the outcomes from the developed method with the hemoglobin content by the spectrophotometric assay method. The results were linearly correlated with statistical significance. The method was also validated by digital phantoms with an error less than 5% compared with the ground truth from the phantoms. Hematoma volumes yielded by the automated processing and those obtained by the operator’s manual operation are highly correlated. This automated segmentation approach can be potentially used to quantify hemorrhagic outcomes in rodent stroke models in an unbiased and efficient way
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