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Institution

National Cheng Kung University

EducationTainan City, Taiwan
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.


Papers
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Journal ArticleDOI
TL;DR: Different synthesis methodologies to prepare well-dispersed MSNs and hollow silica nanoparticles with tunable dimensions with good potential for use in high-performance catalysis, antireflection coating, transparent polymer-MSNs nanocomposites, drug-release and theranostic systems are discussed.
Abstract: Good control of the morphology, particle size, uniformity and dispersity of mesoporous silica nanoparticles (MSNs) is of increasing importance to their use in catalyst, adsorption, polymer filler, optical devices, bio-imaging, drug delivery, and biomedical applications. This review discusses different synthesis methodologies to prepare well-dispersed MSNs and hollow silica nanoparticles (HSNs) with tunable dimensions ranging from a few to hundreds of nanometers of different mesostructures. The methods include fast self-assembly, soft and hard templating, a modified Stober method, dissolving–reconstruction and modified aerogel approaches. In practical applications, the MSNs prepared by these methods demonstrate good potential for use in high-performance catalysis, antireflection coating, transparent polymer–MSNs nanocomposites, drug-release and theranostic systems.

1,180 citations

Journal ArticleDOI
TL;DR: The National Health Insurance Research Database (NHIRD) is commonly used for pharmacoepidemiological research in Taiwan and the validity of the database for patients with a principal diagnosis of ischemic stroke is evaluated.
Abstract: Objective The National Health Insurance Research Database (NHIRD) is commonly used for pharmacoepidemiological research in Taiwan. This study evaluated the validity of the database for patients with a principal diagnosis of ischemic stroke. Study design and methods This cross-sectional study compares records in the NHIRD with those in one medical center. Patients hospitalized for ischemic stroke in 1999 were identified from both databases. The discharge notes, laboratory data, and medication orders during admission and the first discharge visit were reviewed to validate ischemic stroke diagnoses and aspirin prescribing in the NHIRD. Agreement between the two databases in comorbidities of ischemic stroke diagnosis was evaluated using ICD-9 codes. Results Three hundred and seventy two cases were identified from the NHIRD; among them, 364 cases (97.85%) were confirmed as ischemic stroke by radiology examination and clinical presentation. Among these confirmed cases, 344 (94.51%) were assigned ‘ischemic stroke’ as the principal diagnosis in the NHIRD. The overall agreement of comorbid diagnoses between the databases was 48.39%. The PPV for selected conditions also varied widely, from 0.50 for fracture to 1.00 for colon cancer. The accuracy of recorded aspirin prescriptions was higher in first post-discharge visits (PPV = 0.94) than during hospitalization (PPV = 0.88). Conclusion The accuracy of the NHIRD in recording ischemic stroke diagnoses and aspirin prescriptions was high, and the NHIRD appears to be a valid resource for population research in ischemic stroke. Copyright © 2010 John Wiley & Sons, Ltd.

1,131 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

1,129 citations

Journal ArticleDOI
TL;DR: The relational model developed in this paper is more reliable in measuring the efficiencies and consequently is capable of identifying the causes of inefficiency more accurately.

1,112 citations


Authors

Showing all 49872 results

NameH-indexPapersCitations
Yi Chen2174342293080
Yang Yang1642704144071
R. E. Hughes1541312110970
Mercouri G. Kanatzidis1521854113022
Thomas J. Smith1401775113919
Hui Li1352982105903
Gerald M. Reaven13379980351
Chi-Huey Wong129122066349
Joseph P. Vacanti11944150739
Kai Nan An10995351638
Ding-Shinn Chen10477446068
James D. Neaton10133164719
David C. Christiani100105255399
Jo Shu Chang9963937487
Yu Shyr9854239527
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202373
2022315
20213,425
20203,154
20192,895
20182,764