The psychosocial burden of psoriasis and barriers to biologic therapy in Hong Kong: patients’ perspectives

This journal suppl. is proceedings of the 18th MRC 2013INTRODUCTION: Psoriatic skin lesions are often visible and have negative impact on patients’ quality of life (QoL). The introduction of biologic therapies has revolutionised the treatment of psoriasis. They are highly efficacious in clearing skin lesions and relieving joint symptoms. The use of biologics in psoriasis patients is associated with improved QoL and patient satisfaction. In Hong Kong, the psychosocial impacts of psoriasis on patients and their satisfaction towards various treatment modalities have not been well studied. Moreover, the ways local patients come to access the information on biologics and their concerns are unclear. METHODS: We conducted a survey of 85 psoriasis …published_or_final_versio

Effects of cold water immersion on muscle oxygenation during repeated bouts of fatiguing exercise : a randomized controlled study

2015-2016 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Intermittent hypoxia accelerates adipogenic differentiation in human subcutaneous preadipocytes in vitro

Poster Discussion Session - B30. Beast is Inside: What Causes the Adverse Outcomes of Sleep Disordered Breathing: no. A2704RATIONALE: Obstructive sleep apnea (OSA), characterized by intermittent hypoxia (IH), is highly associated with obesity. Depot-specific adipogenic differentiation, an important physiological mechanism in maintaining adipose tissue homeostasis, could be regulated by intracellular transcriptional factors, extracellular signaling pathways and inflammation in obesity. However, the impact of IH on adipogeneisis is unclear. This study aims at investigating the pathologic role of IH during the adipogenic differentiation process in human subcutaneous preadipocytes in …published_or_final_versio

Dermatitis flammeus - an emerging infection-related complication of atopic dermatitis

This journal suppl. contain abstracts of the 16th Medical Research Conference 2011OBJECTIVE: To investigate the clinical, microbiological, immunological and pathological features of a proposed novel complication of atopic dermatitis (AD) related to infection. DESIGN: Case series and retrospective analysis. SETTING: A tertiary university hospital and a private specialist dermatology clinic in Hong Kong. PATIENTS: Twenty patients were included between January 2008 and September 2010. MAIN OUTCOME MEASURES: Clinical characteristics, microbiological findings, therapeutic strategy and prognosis of the …published_or_final_versio

A man with a blistering eruption and tuberculosis.

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Geographical interdependence, international trade and economic dynamics: the Chinese and German solar energy industries

The trajectories of the German and Chinese photovoltaic industries differ significantly yet are strongly interdependent. Germany has seen a rapid growth in market demand and a strong increase in production, especially in the less developed eastern half of the country. Chinese growth has been export driven. These contrasting trajectories reflect the roles of market creation, investment and credit and the drivers of innovation and competitiveness. Consequent differences in competiveness have generated major trade disputes

Metric for Measuring the Effectiveness of Clustering of DNA Microarray Expression

BACKGROUND: The recent advancement of microarray technology with lower noise and better affordability makes it possible to determine expression of several thousand genes simultaneously. The differentially expressed genes are filtered first and then clustered based on the expression profiles of the genes. A large number of clustering algorithms and distance measuring matrices are proposed in the literature. The popular ones among them include hierarchal clustering and k-means clustering. These algorithms have often used the Euclidian distance or Pearson correlation distance. The biologists or the practitioners are often confused as to which algorithm to use since there is no clear winner among algorithms or among distance measuring metrics. Several validation indices have been proposed in the literature and these are based directly or indirectly on distances; hence a method that uses any of these indices does not relate to any biological features such as biological processes or molecular functions. RESULTS: In this paper we have proposed a metric to measure the effectiveness of clustering algorithms of genes by computing inter-cluster cohesiveness and as well as the intra-cluster separation with respect to biological features such as biological processes or molecular functions. We have applied this metric to the clusters on the data set that we have created as part of a larger study to determine the cancer suppressive mechanism of a class of chemicals called retinoids. We have considered hierarchal and k-means clustering with Euclidian and Pearson correlation distances. Our results show that genes of similar expression profiles are more likely to be closely related to biological processes than they are to molecular functions. The findings have been supported by many works in the area of gene clustering. CONCLUSION: The best clustering algorithm of genes must achieve cohesiveness within a cluster with respect to some biological features, and as well as maximum separation between clusters in terms of the distribution of genes of a behavioral group across clusters. We claim that our proposed metric is novel in this respect and that it provides a measure of both inter and intra cluster cohesiveness. Best of all, computation of the proposed metric is easy and it provides a single quantitative value, which makes comparison of different algorithms easier. The maximum cluster cohesiveness and the maximum intra-cluster separation are indicated by the metric when its value is 0. We have demonstrated the metric by applying it to a data set with gene behavioral groupings such as biological process and molecular functions. The metric can be easily extended to other features of a gene such as DNA binding sites and protein-protein interactions of the gene product, special features of the intron-exon structure, promoter characteristics, etc. The metric can also be used in other domains that use two different parametric spaces; one for clustering and the other one for measuring the effectiveness

FLAME, a novel fuzzy clustering method for the analysis of DNA microarray data

BACKGROUND: Data clustering analysis has been extensively applied to extract information from gene expression profiles obtained with DNA microarrays. To this aim, existing clustering approaches, mainly developed in computer science, have been adapted to microarray data analysis. However, previous studies revealed that microarray datasets have very diverse structures, some of which may not be correctly captured by current clustering methods. We therefore approached the problem from a new starting point, and developed a clustering algorithm designed to capture dataset-specific structures at the beginning of the process. RESULTS: The clustering algorithm is named Fuzzy clustering by Local Approximation of MEmbership (FLAME). Distinctive elements of FLAME are: (i) definition of the neighborhood of each object (gene or sample) and identification of objects with "archetypal" features named Cluster Supporting Objects, around which to construct the clusters; (ii) assignment to each object of a fuzzy membership vector approximated from the memberships of its neighboring objects, by an iterative converging process in which membership spreads from the Cluster Supporting Objects through their neighbors. Comparative analysis with K-means, hierarchical, fuzzy C-means and fuzzy self-organizing maps (SOM) showed that data partitions generated by FLAME are not superimposable to those of other methods and, although different types of datasets are better partitioned by different algorithms, FLAME displays the best overall performance. FLAME is implemented, together with all the above-mentioned algorithms, in a C++ software with graphical interface for Linux and Windows, capable of handling very large datasets, named Gene Expression Data Analysis Studio (GEDAS), freely available under GNU General Public License. CONCLUSION: The FLAME algorithm has intrinsic advantages, such as the ability to capture non-linear relationships and non-globular clusters, the automated definition of the number of clusters, and the identification of cluster outliers, i.e. genes that are not assigned to any cluster. As a result, clusters are more internally homogeneous and more diverse from each other, and provide better partitioning of biological functions. The clustering algorithm can be easily extended to applications different from gene expression analysis

Genome-Wide DNA Methylation Analysis of Chinese Patients with Systemic Lupus Erythematosus Identified Hypomethylation in Genes Related to the Type I Interferon Pathway

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