The effects of topical triptolide in an animal model of contact dermatitis

published_or_final_versio

Increased apoptotic blood neutrophils and macrophages and decreased clearance of apoptotic neutrophils in systemic lupus erythematosus

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Osteopontin in rheumatoid arthritis and osteoarthrits

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B cells from SLE patients display accelerated apoptosis and reduced anti-apoptotic response to sIgM and CD40 ligation

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Effects of triptolide, an active ingredient of trypterygium Wilfordii Hook F (Thunder God Vine, a traditional Chinese herb), on rheumatoid synovial fibroblast function

published_or_final_versio

Allergy in Hong Kong: an unmet need in service provision and training

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Increased Set1 binding at the promoter induces aberrant epigenetic alterations and up-regulates cyclic adenosine 5'-monophosphate response element modulator alpha in systemic lupus erythematosus.

published_or_final_versio

Frequency and predictors of the lupus low disease activity state in a multi-national and multi-ethnic cohort

published_or_final_versio

A simpler method of preprocessing MALDI-TOF MS data for differential biomarker analysis: stem cell and melanoma cancer studies

<p>Abstract</p> <p>Introduction</p> <p>Raw spectral data from matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) with MS profiling techniques usually contains complex information not readily providing biological insight into disease. The association of identified features within raw data to a known peptide is extremely difficult. Data preprocessing to remove uncertainty characteristics in the data is normally required before performing any further analysis. This study proposes an alternative yet simple solution to preprocess raw MALDI-TOF-MS data for identification of candidate marker ions. Two in-house MALDI-TOF-MS data sets from two different sample sources (melanoma serum and cord blood plasma) are used in our study.</p> <p>Method</p> <p>Raw MS spectral profiles were preprocessed using the proposed approach to identify peak regions in the spectra. The preprocessed data was then analysed using bespoke machine learning algorithms for data reduction and ion selection. Using the selected ions, an ANN-based predictive model was constructed to examine the predictive power of these ions for classification.</p> <p>Results</p> <p>Our model identified 10 candidate marker ions for both data sets. These ion panels achieved over 90% classification accuracy on blind validation data. Receiver operating characteristics analysis was performed and the area under the curve for melanoma and cord blood classifiers was 0.991 and 0.986, respectively.</p> <p>Conclusion</p> <p>The results suggest that our data preprocessing technique removes unwanted characteristics of the raw data, while preserving the predictive components of the data. Ion identification analysis can be carried out using MALDI-TOF-MS data with the proposed data preprocessing technique coupled with bespoke algorithms for data reduction and ion selection.</p

Molecular marks for epigenetic identification of developmental and cancer stem cells

Epigenetic regulations of genes by reversible methylation of DNA (at the carbon-5 of cytosine) and numerous reversible modifications of histones play important roles in normal physiology and development, and epigenetic deregulations are associated with developmental disorders and various disease states, including cancer. Stem cells have the capacity to self-renew indefinitely. Similar to stem cells, some malignant cells have the capacity to divide indefinitely and are referred to as cancer stem cells. In recent times, direct correlation between epigenetic modifications and reprogramming of stem cell and cancer stem cell is emerging. Major discoveries were made with investigations on reprogramming gene products, also known as master regulators of totipotency and inducer of pluoripotency, namely, OCT4, NANOG, cMYC, SOX2, Klf4, and LIN28. The challenge to induce pluripotency is the insertion of four reprogramming genes (Oct4, Sox2, Klf4, and c-Myc) into the genome. There are always risks of silencing of these genes by epigenetic modifications in the host cells, particularly, when introduced through retroviral techniques. In this contribution, we will discuss some of the major discoveries on epigenetic modifications within the chromatin of various genes associated with cancer progression and cancer stem cells in comparison to normal development of stem cell. These modifications may be considered as molecular signatures for predicting disorders of development and for identifying disease states