IgA nephropathy is the most common glomerular disease worldwide, yet there is no international consensus for its pathological or clinical classification. Here a new classification for IgA nephropathy is presented by an international consensus working group. The goal of this new system was to identify specific pathological features that more accurately predict risk of progression of renal disease in IgA nephropathy, thus enabling both clinicians and pathologists to improve individual patient prognostication. In a retrospective analysis, sequential clinical data were obtained on 265 adults and children with IgA nephropathy who were followed for a median of 5 years. Renal biopsies from all patients were scored by pathologists blinded to the clinical data for pathological variables identified as reproducible by an iterative process. Four of these variables: (1) the mesangial hypercellularity score, (2) segmental glomerulosclerosis, (3) endocapillary hypercellularity, and (4) tubular atrophy/interstitial fibrosis were subsequently shown to have independent value in predicting renal outcome. These specific pathological features withstood rigorous statistical analysis even after taking into account all clinical indicators available at the time of biopsy as well as during follow-up. The features have prognostic significance and we recommended they be taken into account for predicting outcome independent of the clinical features both at the time of presentation and during follow-up. The value of crescents was not addressed due to their low prevalence in the enrolled cohort.

Pathological classifications in current use for the assessment of glomerular disease have been typically opinion-based and built on the expert assumptions of renal pathologists about lesions historically thought to be relevant to prognosis. Here we develop a unique approach for the pathological classification of a glomerular disease, IgA nephropathy, in which renal pathologists first undertook extensive iterative work to define pathologic variables with acceptable inter-observer reproducibility. Where groups of such features closely correlated, variables were further selected on the basis of least susceptibility to sampling error and ease of scoring in routine practice. This process identified six pathologic variables that could then be used to interrogate prognostic significance independent of the clinical data in IgA nephropathy (described in the accompanying article). These variables were (1) mesangial cellularity score; percentage of glomeruli showing (2) segmental sclerosis, (3) endocapillary hypercellularity, or (4) cellular/fibrocellular crescents; (5) percentage of interstitial fibrosis/tubular atrophy; and finally (6) arteriosclerosis score. Results for interobserver reproducibility of individual pathological features are likely applicable to other glomerulonephritides, but it is not known if the correlations between variables depend on the specific type of glomerular pathobiology. Variables identified in this study withstood rigorous pathology review and statistical testing and we recommend that they become a necessary part of pathology reports for IgA nephropathy. Our methodology, translating a strong evidence-based dataset into a working format, is a model for developing classifications of other types of renal disease.

Abstract. The European Aerosol Research Lidar Network, EARLINET, was founded in 2000 as a research project for establishing a quantitative, comprehensive, and statistically significant database for the horizontal, vertical, and temporal distribution of aerosols on a continental scale. Since then EARLINET has continued to provide the most extensive collection of ground-based data for the aerosol vertical distribution over Europe. This paper gives an overview of the network's main developments since 2000 and introduces the dedicated EAR-LINET special issue, which reports on the present innovative and comprehensive technical solutions and scientific results related to the use of advanced lidar remote sensing techniques for the study of aerosol properties as developed within the network in the last 13 years.Since 2000, EARLINET has developed greatly in terms of number of stations and spatial distribution: from 17 stations in 10 countries in 2000 to 27 stations in 16 countries in 2013. EARLINET has developed greatly also in terms of technological advances with the spread of advanced multiwavelength Raman lidar stations in Europe. The developments for the quality assurance strategy, the optimization of instruments and data processing, and the dissemination of data have contributed to a significant improvement of the network towards a more sustainable observing system, with an increase in the observing capability and a reduction of operational costs.Consequently, EARLINET data have already been extensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from volcanic eruptions, and for model evaluation and satellite data validation and integration.Future plans are aimed at continuous measurements and near-real-time data delivery in close cooperation with other ground-based networks, such as in the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) www.actris.net, and with the modeling and satellite community, linking the research community with the operational world, with the aim of establishing of the atmospheric part of the European component of the integrated global observing system.

Our results suggest that, via transition to a mesenchymal phenotype, TEC can produce ECM proteins in human disease and directly intervene in the fibrotic processes. Moreover, the association of EMT features with serum creatinine supports the value of these markers in the assessment of disease severity.

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