12 research outputs found
Analysis of clusterin expression changes as a biomarker of osteoarthritis
Purpose: The discovery and validation of arthritis-related biomarkers and establishment of methodology for proteomic studies in osteoarthritis (OA) are needed. Proteomics strategies have identified many proteins that may relate to pathological mechanisms of OA, however targeted approaches are required to validate the roles of these proteins. This study aimed to use mass spectrometry and western blotting to identify peptides from several proteins in the secretome of chondrocytes, cartilage explants and osteochondral biopsies treated with inflammatory cytokines over a 2-week period, to evaluate their potential as biomarkers of OA progression.
Methods: Healthy cartilage was obtained from fetlock joints of skeletally mature horses, euthanized for unrelated veterinary reasons. Cartilage explants were isolated using a 6 mm biopsy, with discs placed into wells (3 discs per 1 ml DMEM + 1% Pen/Strep) before incubation for 24 hours (37 °C, 5% CO2). After this equilibration period, the media was removed and replaced with either fresh DMEM + 1% Pen/Strep or DMEM supplemented with 1% Pen/Strep containing TNFα and IL-1β both at 10ng/ml. Explants were culture for 7–14 days with the cytokines replaced every 4th day. For cell based assays chondrocytes were isolated from tissue using 70U pronase for 1hr at 37 °C and overnight digestion at 37°C using a 0.2% collagenase II solution. The cell suspension was filtered and washed before being seeded into culture flasks and cultured until confluence was reached (37°C, 5% CO2). Once cultures were established cells were split into two groups: healthy control (DMEM supplemented with 1% Pen/Strep and 10% foetal calf serum) or stimulated cells (DMEM as above plus TNFα and IL-1β both at 10ng/ml). Chondroyctes were cytokine-stimulated for up to one week. Cells were used in experiments up to the 2nd passage.
Results: Mass spectrometry data showed that peptides representative of clusterin were found to decrease following 7 days of inflammatory stimulation. Western blotting of secreted proteins in media of cartilage explants or chondrocyte showed that clusterin expression was reduced following 7 days of cytokine treatment. Catabolic matrix metalloproteinase enzymes MMP1, MMP3 and MMP13, as well the matrix component cartilage oligomeric protein (COMP) were all found to have an increased abundance in the media of the cytokine treated samples. This data was supported by qPCR for clusterin gene expression which showed initially mRNA levels increased 3 day after inflammatory stimulation but expression was lost after 7 days. Western blotting of media from the osteochondral biopsies showed an increase in clusterin expression after 7 days of inflammatory stimulation however clusterin protein expression could not be detected after 14 days of treatment, indicating a delayed response compared to cartilage tissue alone.
Conclusions: The equine chondrocytes, cartilage explant and osteochondral biopsy models exhibited highest clusterin secretion in untreated cultures. IL-1β and TNFα treatment caused a reduction in clusterin secretion. Clusterin acts as a chaperone to aid protein refolding in situations of stress and is constitutively secreted by mammalian cells. IL-1β and TNFα appear to interrupt clusterin secretion and therefore the protection it may offer healthy functioning cells. Previous studies have reported variable data, with some studies indicating a decrease in clusterin in OA, while others indicate an increase in clusterin expression. Our results suggest the clusterin increases immediately after inflammatory stimulation but is lost after prolonged exposure. Therefore, levels of secreted clusterin may be a candidate biomarker for OA progression
Knowledge discovery from post-project reviews
This article was published in the journal, Construction Management and Economics [© Taylor & Francis (Routledge)] and the definitive version is available at: http://dx.doi.org/10.1080/01446193.2011.588953Many construction companies conduct reviews on project completion to enhance learning and to fulfil quality management procedures. Often these reports are filed away never to be seen again. This means that potentially important knowledge that may assist other project teams is not exploited. In order to ascertain whether useful knowledge can be gleaned from such reports, Knowledge Discovery from Text (KDT) and text mining (TM) are applied. Text mining avoids the need for a manual search through a vast number of reports, potentially of different formats and foci, to seek trends that may be useful for current and future projects. Pilot tests were used to analyse 48 post-project review reports. The reports were first reviewed manually to identify key themes. They were then analysed using text mining software to investigate whether text mining could identify trends and uncover useful knowledge from the reports. Pilot tests succeeded in finding common occurrences across different projects that were previously unknown. Text mining could provide a potential solution and would aid project teams to learn from previous projects. However, a lot of work is currently required before the text mining tests are conducted and the results need to be examined carefully by those with domain knowledge to validate the results obtained