National Cheng Kung University

About: National Cheng Kung University is a education organization based out in Tainan City, Taiwan. It is known for research contribution in the topics: Population & Thin film. The organization has 49723 authors who have published 69799 publications receiving 1437420 citations. The organization is also known as: NCKU.

Cortical and Leptomeningeal Cerebrovascular Amyloid and White Matter Pathology in Alzheimer’s Disease

Abstract: Alzheimer’s disease (AD) is characterized by neurofibrillary tangles and by the accumulation of β-amyloid (Aβ) peptides in senile plaques and in the walls of cortical and leptomeningeal arteries as cerebral amyloid angiopathy (CAA). There also is a significant increase of interstitial fluid (ISF) in cerebral white matter (WM), the pathological basis of which is largely unknown. We hypothesized that the accumulation of ISF in dilated periarterial spaces of the WM in AD correlates with the severity of CAA, with the total Aβ load in the cortex and with Apo E genotype. A total of 24 AD brains and 17 nondemented age-matched control brains were examined. CAA was seen in vessels isolated from brain by using EDTA-SDS lysis stained by Thioflavin-S. Total Aβ in gray matter and WM was quantified by immunoassay, ApoE genotyping by PCR, and dilatation of perivascular spaces in the WM was assessed by quantitative histology. The study showed that the frequency and severity of dilatation of perivascular spaces in the WM in AD were significantly greater than in controls (P < 0.001) and correlated with Aβ load in the cortex, with the severity of CAA, and with ApoE e4 genotype. The results of this study suggest that dilation of perivascular spaces and failure of drainage of ISF from the WM in AD may be associated with the deposition of Aβ in the perivascular fluid drainage pathways of cortical and leptomeningeal arteries. This failure of fluid drainage has implications for therapeutic strategies to treat Alzheimer’s disease.

Hepatitis B virus pre‐S mutants, endoplasmic reticulum stress and hepatocarcinogenesis

Abstract: Although hepatitis B virus (HBV) has been documented to cause hepatocellular carcinoma (HCC), the exact role of HBV in the development of HCC remains enigmatic. Several hypotheses have been proposed to explain the potential mechanism, including insertional mutagenesis of HBV genomes and transcriptional activators of HBV gene products such as hepatitis B x protein (HBx) and truncated middle S mutants. In the past few years, we have identified two types of large HBV surface antigens (LHBs) with deletions at the pre-S1 (DeltaS1-LHBs) and pre-S2 (DeltaS2-LHBs) regions in ground glass hepatocytes. The pre-S mutant LHBs are retained in the endoplasmic reticulum (ER) and escape from immune attack. The pre-S mutants, particularly DeltaS2-LHBs, are increasingly prevalent in patients with hepatitis B e antigen (HBeAg)-positive chronic HBV infection, ranging from 6% before the 3rd decade to 35% in the 6th decade. In HCC patients, the two pre-S mutants were detected in 60% of HCC patients, in the serum and in HCC tissues. Pre-S mutant LHBs can initiate ER stress to induce oxidative DNA damage and genomic instability. Furthermore, pre-S mutant LHBs can upregulate cyclooxygenase-2 and cyclin A to induce cell cycle progression and proliferation of hepatocytes. In transgenic mice, the pre-S mutants can induce dysplasia of hepatocytes and development of HCC. In a nested control study, the presence of pre-S mutants carried a high risk of developing HCC in HBV carriers. In summary, the findings we describe in this review suggest a potential role for HBV pre-S mutants in HBV-related hepatocarcinogenesis, providing a model of viral carcinogenesis associated with ER stress.

Building virtual cities, inspiring intelligent citizens: Digital games for developing students' problem solving and learning motivation

Abstract: This study investigates the effectiveness digital game-based learning (DGBL) on students' problem solving, learning motivation, and academic achievement. In order to provide substantive empirical evidence, a quasi-experimental design was implemented over the course of a full semester (23 weeks). Two ninth-grade Civics and Society classes, with a total of 44 students (15-16 years old), were randomly assigned to one of two conditions: an experimental group (incorporating DGBL) and a comparison group (taught using traditional instruction). Two-way mixed ANOVA was employed to evaluate changes in problem solving ability and compare the effectiveness the two strategies, while ANCOVA was used to analyze the effects on learning motivation and academic achievement. The results of this study are summarized as follows: (1) The DGBL strategy was clearly effective in promoting students' problem solving skills, while the control group showed no improvement. Additionally, data from the mid-test and post-test demonstrate that, as a higher order thinking skill, problem-solving requires a full semester to develop. (2). DGBL resulted in better learning motivation for students in the experimental group as compared to learners receiving TI. (3) Contrary to some suggestions that digital games could inhibit academic achievement, no statistically significant difference was found between the two groups. Most importantly, the quantitative improvement in problem-solving and learning motivation suggest that DGBL can be exploited as a useful and productive tool to support students in effective learning while enhancing the classroom atmosphere. Future research in DGBL should emphasize the evaluation of other higher order elements of the cognitive domain in terms of academic achievement outcomes and skills, such as critical and creative thinking.

Data envelopment analysis with common weights: the compromise solution approach

Abstract: A characteristic of data envelopment analysis (DEA) is to allow individual decision-making units (DMUs) to select the factor weights that are the most advantageous for them in calculating their efficiency scores. This flexibility in selecting the weights, on the other hand, deters the comparison among DMUs on a common base. In order to rank all the DMUs on the same scale, this paper proposes a compromise solution approach for generating common weights under the DEA framework. The efficiency scores calculated from the standard DEA model are regarded as the ideal solution for the DMUs to achieve. A common set of weights which produces the vector of efficiency scores for the DMUs closest to the ideal solution is sought. Based on the generalized measure of distance, a family of efficiency scores called ‘compromise solutions’ can be derived. The compromise solutions have the properties of unique solution and Pareto optimality not enjoyed by the solutions derived from the existing methods of common weights. An example of forest management illustrates that the compromise solution approach is able to generate a common set of weights, which not only differentiates efficient DMUs but also detects abnormal efficiency scores on a common base.