Correlation of CXCL10, tumor necrosis factor receptor type II, and galectin 9 with disease activity in juvenile dermatomyositis.

OBJECTIVE: Juvenile dermatomyositis (DM) is a systemic autoimmune disorder of unknown immunopathogenesis in which the immune system targets the microvasculature of skeletal muscles, skin, and other organs. The current mainstay of therapy is a steroid regimen in combination with other immunosuppressive treatments. To date, no validated markers for monitoring disease activity have been identified, which hampers personalized treatment. This study was undertaken to identify a panel of proteins specifically related to active disease in juvenile DM. METHODS: We performed a multiplex immunoassay for plasma levels of 45 proteins related to inflammation in 25 patients with juvenile DM in 4 clinically well-defined groups, as determined by clinical activity and treatment. We compared them to 14 age-matched healthy children and 8 age-matched children with nonautoimmune muscle disease. RESULTS: Cluster analysis of circulating proteins showed distinct profiles for juvenile DM patients and controls based on a group of 10 proteins. In addition to CXCL10, tumor necrosis factor receptor type II (TNFRII) and galectin 9 were significantly increased in active juvenile DM. The levels of these 3 proteins were tightly linked to active disease and correlated with clinical scores (as measured by the Childhood Myositis Assessment Scale and physician's global assessment of disease activity on a visual analog scale). CONCLUSION: Our findings indicate that CXCL10, TNFRII, and galectin 9 correspond to disease status in juvenile DM and thus could be helpful in monitoring disease activity and guiding treatment. Furthermore, they might provide new knowledge about the pathogenesis of this autoimmune disease.

Quantitative integration of high-resolution hydrogeophysical data through Monte-Carlo-type conditional simulations

Geophysical techniques can help to bridge the inherent gap with regard to spatial resolution and the range of coverage that plagues classical hydrological methods. This has lead to the emergence of the new and rapidly growing field of hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters and their inherent trade-off between resolution and range the fundamental usefulness of multi-method hydrogeophysical surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database in order to obtain a unified model of the probed subsurface region that is internally consistent with all available data. To address this problem, we have developed a strategy towards hydrogeophysical data integration based on Monte-Carlo-type conditional stochastic simulation that we consider to be particularly suitable for local-scale studies characterized by high-resolution and high-quality datasets. Monte-Carlo-based optimization techniques are flexible and versatile, allow for accounting for a wide variety of data and constraints of differing resolution and hardness and thus have the potential of providing, in a geostatistical sense, highly detailed and realistic models of the pertinent target parameter distributions. Compared to more conventional approaches of this kind, our approach provides significant advancements in the way that the larger-scale deterministic information resolved by the hydrogeophysical data can be accounted for, which represents an inherently problematic, and as of yet unresolved, aspect of Monte-Carlo-type conditional simulation techniques. We present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to corresponding field data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

Diabète de type 2: n'oubliez pas les troubles du comportement alimentaire [Patient with type 2 diabetes: don't forget eating disorders!]

The coexistence of diabetes and eating disorder (ED) is more prevalent than we think; indeed it seems to occur in 10 to 20% of cases. Therefore ED deserve attention to be detected and treated in order to permit a decreased in morbidity and better outcomes in body weight loss. The association of type 2 diabetes and ED is frequently seen in younger, overweighed or obese patients suffering of at least one psychiatric co-morbidities and frequently in a difficult psychosocial setting. To succeed in ED treatment, a multidisciplinary and specialised team in eating disorder is requested, however these patients are highly fragile and complex and therapeutic failure has to be feared.

Adipocytokines, Hepatic and Inflammatory Biomarkers and Incidence of Type 2 Diabetes. The CoLaus Study.

CONTEXT: There is contradictory information regarding the prognostic importance of adipocytokines, hepatic and inflammatory biomarkers on the incidence of type 2 diabetes. The objective was to assess the prognostic relevance of adipocytokine and inflammatory markers (C-reactive protein - CRP; interleukin-1beta - IL-1β; interleukin-6- IL-6; tumour necrosis factor-α - TNF-α; leptin and adiponectin) and gamma-glutamyl transpeptidase (γGT) on the incidence of type 2 diabetes. METHODS: Prospective, population-based study including 3,842 non-diabetic participants (43.3% men, age range 35 to 75 years), followed for an average of 5.5 years (2003-2008). The endpoint was the occurrence of type 2 diabetes. RESULTS: 208 participants (5.4%, 66 women) developed type 2 diabetes during follow-up. On univariate analysis, participants who developed type 2 diabetes had significantly higher baseline levels of IL-6, CRP, leptin and γGT, and lower levels of adiponectin than participants who remained free of type 2 diabetes. After adjusting for a validated type 2 diabetes risk score, only the associations with adiponectin: Odds Ratio and (95% confidence interval): 0.97 (0.64-1.47), 0.84 (0.55-1.30) and 0.64 (0.40-1.03) for the second, third and forth gender-specific quartiles respectively, remained significant (P-value for trend = 0.05). Adding each marker to a validated type 2 diabetes risk score (including age, family history of type 2 diabetes, height, waist circumference, resting heart rate, presence of hypertension, HDL cholesterol, triglycerides, fasting glucose and serum uric acid) did not improve the area under the ROC or the net reclassification index; similar findings were obtained when the markers were combined, when the markers were used as continuous (log-transformed) variables or when gender-specific quartiles were used. CONCLUSION: Decreased adiponectin levels are associated with an increased risk for incident type 2 diabetes, but they seem to add little information regarding the risk of developing type 2 diabetes to a validated risk score.