RA-specific expression profiles and new candidate genes

Objective: To identify rheumatoid arthritis- (RA)-specific profiles of differentially expressed genes. Methods: Synovial tissues from RA and osteoarthritis (OA) patients and from normal joints were selected according to their disease-characteristic histology. Gene expression was analyzed using DNA microarrays (GeneChip; Unigene-array) and representational difference analysis (RDA). Data were validated on larger cohorts of patients by RT-PCR. Results: Nine hundred and eighty genes were significantly regulated in RA synovial tissue as compared with non-RA. Specialized cluster analysis identified a set of 312 genes as sufficient of unequivocally discriminating RA from non-RA patterns (class discovery). Genes of highest regulation were associated with leukocyte activation (chemokines, chemokine receptors, B- and T-cell genes), endothelial and angiogenic activation, tissue destruction and remodelling [MMP-3, BMP-4, TIMPs]. Interestingly, a large set of genes was down-regulated in RA (TGF-β superfamily, apoptosis-related genes, transcription factors). Osteopontin-like genes (n=46) — up-regulated in RA — and glutathione peroxidase-3-like genes (n=85) — down-regulated in RA — yielded the highest correlation coefficients (>0.94). Megakaryocyte stimulating factor (MSF), down-regulated in a subset of RA, may hold the key to subclassification: a loss-of-function mutation in the MSF-encoding gene leads to synovial hyperplasia in camptodactyly–arthropathy–coxa vara–pericarditis syndrome, and, as in RA, also to pericardial involvement. A further candidate, vitamin-D3-up-regulated protein-1 (VDUP-1), is regulated like MSF and predisposes to premature coronary artery disease when mutated, again a feature of a subset of RA. Conclusion: RA specific gene profiles were identified and are useful to improve diagnostics of the disease. Novel gene candidates not yet in the focus of RA pathogenesis have been identified that are likely to further the understanding of RA

Physiol Genomics

Rheumatoid arthritis (RA) is a chronic, inflammatory joint disease of unknown etiology and pronounced inter-patient heterogeneity. To characterize RA at the molecular level and to uncover pathomechanisms, we performed genome-wide gene expression analysis. We identified a set of 1054 genes significantly deregulated in pair-wise comparisons between RA and osteoarthritis (OA) patients, RA and normal donors (ND), or OA and ND. Correlation analysis revealed gene sets regulated identically in all three groups. As a prominent example secreted phosphoprotein 1 (SPP1) was identified to be significantly upregulated in RA as compared to both OA and ND. SPP1 expression was found to correlate with genes expressed during an inflammatory response, T cell activation and apoptosis, suggesting common underlying regulatory networks. A sub-classification of RA patients was achieved on the basis of proteoglycan 4 (PRG4) expression distinguishing PRG4 high- and low expressors and reflecting the heterogeneity of the disease. In addition, we found that low PRG4 expression was associated with a more aggressive disease stage, which is in accordance with PRG4 loss-of-function mutations causing camptodactyly-arthropathy-coxa vara-pericarditis syndrome. Altogether we provide evidence for molecular signatures of RA and RA subclasses, sets of new candidate genes as well as for candidate gene networks, which extend our understanding of disease mechanisms and may lead to an improved diagnosis

Life cycle assessment of three water systems in Copenhagen-a management tool of the future.

Environmental life-cycle assessment (LCA) was applied to evaluate three different water systems of the water sector in Copenhagen, Denmark, including technologies within water supply, facilities recycling water and treatment of sewer overflow. In these three water systems LCA was used to evaluate the environmental impacts of each of the processes involved. The overall conclusion was that LCA is suitable as a decision support tool in the water sector as it provides a holistic evaluation platform of the considered alternatives categorized in environmental impact categories. The use of LCA in the water sector of this region has limitation since it not yet considers impact categories assessing freshwater scarcity and ecological sustainability.</jats:p

Bettenkapazitätssteuerung in Zeiten der COVID-19-Pandemie: eine simulationsbasierte Prognose der Normal- und Intensivstationsbetten anhand der deskriptiven Daten des Universitätsklinikums Augsburg

BACKGROUND: Following the regional outbreak in China, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread all over the world, presenting the healthcare systems with huge challenges worldwide. In Germany the coronavirus diseases 2019 (COVID-19) pandemic has resulted in a slowly growing demand for health care with a sudden occurrence of regional hotspots. This leads to an unpredictable situation for many hospitals, leaving the question of how many bed resources are needed to cope with the surge of COVID-19 patients. OBJECTIVE: In this study we created a simulation-based prognostic tool that provides the management of the University Hospital of Augsburg and the civil protection services with the necessary information to plan and guide the disaster response to the ongoing pandemic. Especially the number of beds needed on isolation wards and intensive care units (ICU) are the biggest concerns. The focus should lie not only on the confirmed cases as the patients with suspected COVID-19 are in need of the same resources. MATERIAL AND METHODS: For the input we used the latest information provided by governmental institutions about the spreading of the disease, with a special focus on the growth rate of the cumulative number of cases. Due to the dynamics of the current situation, these data can be highly variable. To minimize the influence of this variance, we designed distribution functions for the parameters growth rate, length of stay in hospital and the proportion of infected people who need to be hospitalized in our area of responsibility. Using this input, we started a Monte Carlo simulation with 10,000 runs to predict the range of the number of hospital beds needed within the coming days and compared it with the available resources. RESULTS: Since 2 February 2020 a total of 306 patients were treated with suspected or confirmed COVID-19 at this university hospital. Of these 84 needed treatment on the ICU. With the help of several simulation-based forecasts, the required ICU and normal bed capacity at Augsburg University Hospital and the Augsburg ambulance service in the period from 28 March 2020 to 8 June 2020 could be predicted with a high degree of reliability. Simulations that were run before the impact of the restrictions in daily life showed that we would have run out of ICU bed capacity within approximately 1 month. CONCLUSION: Our simulation-based prognosis of the health care capacities needed helps the management of the hospital and the civil protection service to make reasonable decisions and adapt the disaster response to the realistic needs. At the same time the forecasts create the possibility to plan the strategic response days and weeks in advance. The tool presented in this study is, as far as we know, the only one accounting not only for confirmed COVID-19 cases but also for suspected COVID-19 patients. Additionally, the few input parameters used are easy to access and can be easily adapted to other healthcare systems

Proposal for a histopathological consensus classification of the periprosthetic interface membrane

AIMS: The introduction of clearly defined histopathological criteria for a standardised evaluation of the periprosthetic membrane, which can appear in cases of total joint arthroplasty revision surgery. METHODS: Based on histomorphological criteria, four types of periprosthetic membrane were defined: wear particle induced type (detection of foreign body particles; macrophages and multinucleated giant cells occupy at least 20% of the area; type I); infectious type (granulation tissue with neutrophilic granulocytes, plasma cells and few, if any, wear particles; type II); combined type (aspects of type I and type II occur simultaneously; type III); and indeterminate type (neither criteria for type I nor type II are fulfilled; type IV). The periprosthetic membranes of 370 patients (217 women, 153 men; mean age 67.6 years, mean period until revision surgery 7.4 years) were analysed according to the defined criteria. RESULTS: Frequency of histopathological membrane types was: type I 54.3%, type II 19.7%, type III 5.4%, type IV 15.4%, and not assessable 5.1%. The mean period between primary arthroplasty and revision surgery was 10.1 years for type I, 3.2 years for type II, 4.5 years for type III and 5.4 years for type IV. The correlation between histopathological and microbiological diagnosis was high (89.7%), and the inter‐observer reproducibility sufficient (85%). CONCLUSION: The classification proposed enables standardised typing of periprosthetic membranes and may serve as a tool for further research on the pathogenesis of the loosening of total joint replacement. The study highlights the importance of non‐infectious, non‐particle induced loosening of prosthetic devices in orthopaedic surgery (membrane type IV), which was observed in 15.4% of patients