Conventional inclusion criteria used in osteoarthritis clinical trials are not very effective in selecting patients who would benefit from a therapy being tested. Typically majority of selected patients show no or limited disease progression during a trial period. As a consequence, the effect of the tested treatment cannot be observed, and the efforts and resources invested in running the trial are not rewarded. This could be avoided, if selection criteria were more predictive of the future disease progression. In this article, we formulated the patient selection problem as a multi-class classification task, with classes based on clinically relevant measures of progression (over a time scale typical for clinical trials). Using data from two long-term knee osteoarthritis studies OAI and CHECK, we tested multiple algorithms and learning process configurations (including multi-classifier approaches, cost-sensitive learning, and feature selection), to identify the best performing machine learning models. We examined the behaviour of the best models, with respect to prediction errors and the impact of used features, to confirm their clinical relevance. We found that the model-based selection outperforms the conventional inclusion criteria, reducing by 20-25% the number of patients who show no progression. This result might lead to more efficient clinical trials. Knee osteoarthritis (OA) is a chronic degenerative joint disease characterised by cartilage loss and changes in bones underneath it, causing pain and functional disability. The main clinical symptoms of knee OA are pain and stiffness, particularly after activity 1 , leading to reduced mobility and quality of life, and eventually resulting in knee replacement surgery. OA is one of the leading causes of global disability in people aged 65 and older, and its burden is likely to increase in the future with the ageing of the population and rise in obesity worldwide 2. OA is a heterogeneous disease where progression spreads over several years with periods of fast changes and periods of stability 3. A major challenge in OA drug development is effective selection of patients to the clinical trials. In an ideal case, all selected patients would show disease progression within the trial period, and their response to the drug in trial would be properly assessed. However, identification of patients in need of treatment, that is those with a high probability of progression, is an open problem.

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Apocynin in vitro inhibits inflammation-mediated cartilage destruction without having adverse effects on cartilage. The latter may be an advantage of apocynin over many other non-steroidal anti-inflammatory drugs. Therefore, apocynin might have an added beneficial effect in protecting RA patients from joint destruction.

FLCs are abundantly present in inflamed joints and FLC levels correlate with disease activity. The correlation of FLC concentrations and disease activity indicates that FLCs may be relevant biomarkers for treatment response to rituximab in patients with RA and suggests that targeting FLC may be of importance in the therapy of RA.

In conclusion, we have found that B-cell depletion increases bone formation and decreases bone resorption in RA patients; this may be a direct effect on osteoblasts and osteoclasts, respectively, and be at least partially explained by the decreased inflammation and disease activity.

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Objective. Human Hsp60 is expressed in the joints of patients with rheumatoid arthritis (RA) and can elicit a regulatory T cell response in the peripheral blood and synovial fluid. However, Hsp60 can also trigger strong proinflammatory pathways. Thus, to understand the nature of these Hsp60-directed responses in RA, it is necessary to study such responses at the molecular, epitope-specific level. This study was undertaken to characterize the disease specificity and function of pan-DR-binding Hsp60-derived epitopes as possible modulators of autoimmune inflammation in RA.Methods. Lymphocyte proliferation assays (using 3 H-thymidine incorporation and carboxyfluorescein diacetate succinimidyl ester [CFSE] staining) and measurement of cytokine production (using multiplex immunoassay and intracellular staining) were performed after in vitro activation of peripheral blood mononuclear cells from patients with RA, compared with healthy controls. Results. A disease (RA)-specific immune recognition, characterized by T cell proliferation as well as increased production of tumor necrosis factor ␣ (TNF␣), interleukin-1␤ (IL-1␤), and IL-10, was found for 3 of the 8 selected peptides in patients with RA as compared with healthy controls (P < 0.05). Intracellular cytokine staining and CFSE labeling showed that CD4؉ T cells were the subset primarily responsible for both the T cell proliferation and the cytokine production in RA. Interestingly, the human peptides had a remarkably different phenotype, with a 5-10-fold higher IL-10:TNF␣ ratio, compared with that of the microbial peptides.Conclusion. These results suggest a diseasespecific immune-modulatory role of epitope-specific T cells in the inflammatory processes of RA. Therefore, these pan-DR-binding epitopes could be used as a tool to study the autoreactive T cell response in RA and might be suitable candidates for use in immunotherapy.

The analysis of cytokine production is increasingly important in defining the course of an immune response and in evaluating specific therapies of immune diseases. In rheumatoid arthritis (RA), a dysregulation in T1/T2 cell balance, as defined by the production of their specific cytokines, IFN-gamma and IL-4, respectively, is suggested. A predominance of T1-cell mediated macrophage activity in the joint plays a key role in the destruction of articular cartilage and subchondral bone, whereas local T2 cell activity, mitigating disease, fails. However, analysis of the cytokines defining both T cell subsets is difficult and spontaneous production is often below detection limits. Several stimuli are therefore used to increase cytokine production. In the present study we examined whether stimulation of peripheral blood T cells in the context of mononuclear cells (PB MNC) by CD3-CD28 is a reliable method for assessing IFN-gamma and IL-4 production and is representative for the spontaneous production of these cytokines. The production of IFN-gamma and IL-4 following CD3-CD28 stimulation of RA PB MNC correlated significantly in a ratio 1 : 1 with production following ionomycin-PMA stimulation. In samples with detectable spontaneous production of IFNgamma and IL-4, production following CD3-CD28 stimulation was significantly higher than in stimulated samples with undetectable spontaneous production. Moreover, in the case of spontaneous production there was a significant positive linear correlation between the CD3-CD28 stimulated and spontaneous IFNgamma and IL-4 production, although production of both cytokines was not equally enhanced. Serial sampling did not show significant daily or weekly variation in stimulated cytokine production. The results demonstrate that a pecific T-cell stimulation by CD3-CD28 is a reliable way to enhance IFN-gamma and IL-4 production above the detection limit and so measure the T1/T2 cell balance in RA.