Classification of patients with knee osteoarthritis in clinical phenotypes: data from the osteoarthritis initiative

<div><p>Objectives</p><p>The existence of phenotypes has been hypothesized to explain the large heterogeneity characterizing the knee osteoarthritis. In a previous systematic review of the literature, six main phenotypes were identified: Minimal Joint Disease (MJD), Malaligned Biomechanical (MB), Chronic Pain (CP), Inflammatory (I), Metabolic Syndrome (MS) and Bone and Cartilage Metabolism (BCM). The purpose of this study was to classify a sample of individuals with knee osteoarthritis (KOA) into pre-defined groups characterized by specific variables that can be linked to different disease mechanisms, and compare these phenotypes for demographic and health outcomes.</p><p>Methods</p><p>599 patients were selected from the OAI database FNIH at 24 months’ time to conduct the study. For each phenotype, cut offs of key variables were identified matching the results from previous studies in the field and the data available for the sample. The selection process consisted of 3 steps. At the end of each step, the subjects classified were excluded from the further classification stages. Patients meeting the criteria for more than one phenotype were classified separately into a ‘complex KOA’ group.</p><p>Results</p><p>Phenotype allocation (including complex KOA) was successful for 84% of cases with an overlap of 20%. Disease duration was shorter in the MJD while the CP phenotype included a larger number of Women (81%). A significant effect of phenotypes on WOMAC pain (F = 16.736 p <0.001) and WOMAC physical function (F = 14.676, p < 0.001) was identified after controlling for disease duration.</p><p>Conclusion</p><p>This study signifies the feasibility of a classification of KOA subjects in distinct phenotypes based on subgroup-specific characteristics.</p></div

Determinants of Bacteriophage 933W Repressor DNA Binding Specificity

We reported previously that 933W repressor apparently does not cooperatively bind to adjacent sites on DNA and that the relative affinities of 933W repressor for its operators differ significantly from that of any other lambdoid bacteriophage. These findings indicate that the operational details of the lysis-lysogeny switch of bacteriophage 933W are unique among lambdoid bacteriophages. Since the functioning of the lysis-lysogeny switch in 933W bacteriophage uniquely and solely depends on the order of preference of 933W repressor for its operators, we examined the details of how 933W repressor recognizes its DNA sites. To identify the specificity determinants, we first created a molecular model of the 933W repressor-DNA complex and tested the predicted protein-DNA interactions. These results of these studies provide a picture of how 933W repressor recognizes its DNA sites. We also show that, opposite of what is normally observed for lambdoid phages, 933W operator sequences have evolved in such a way that the presence of the most commonly found base sequences at particular operator positions serves to decrease, rather than increase, the affinity of the protein for the site. This finding cautions against assuming that a consensus sequence derived from sequence analysis defines the optimal, highest affinity DNA binding site for a protein

Meta-omics approaches to understand and improve wastewater treatment systems

Biological treatment of wastewaters depends on microbial processes, usually carried out by mixed microbial communities. Environmental and operational factors can affect microorganisms and/or impact microbial community function, and this has repercussion in bioreactor performance. Novel high-throughput molecular methods (metagenomics, metatranscriptomics, metaproteomics, metabolomics) are providing detailed knowledge on the microorganisms governing wastewater treatment systems and on their metabolic capabilities. The genomes of uncultured microbes with key roles in wastewater treatment plants (WWTP), such as the polyphosphate-accumulating microorganism Candidatus Accumulibacter phosphatis, the nitrite oxidizer Candidatus Nitrospira defluvii or the anammox bacterium Candidatus Kuenenia stuttgartiensis are now available through metagenomic studies. Metagenomics allows to genetically characterize full-scale WWTP and provides information on the lifestyles and physiology of key microorganisms for wastewater treatment. Integrating metagenomic data of microorganisms with metatranscriptomic, metaproteomic and metabolomic information provides a better understanding of the microbial responses to perturbations or environmental variations. Data integration may allow the creation of predictive behavior models of wastewater ecosystems, which could help in an improved exploitation of microbial processes. This review discusses the impact of meta-omic approaches on the understanding of wastewater treatment processes, and the implications of these methods for the optimization and design of wastewater treatment bioreactors.Research was supported by the Spanish Ministry of Education and Science (Contract Project CTQ2007-64324 and CONSOLIDER-CSD 2007-00055) and the Regional Government of Castilla y Leon (Ref. VA038A07). Research of AJMS is supported by the European Research Council (Grant 323009

Independent variations of CH4 emissions and isotopic composition over the past 160,000 years

During the last glacial cycle, greenhouse gas concentrations fluctuated on decadal and longer timescales. Concentrations of methane, as measured in polar ice cores, show a close connection with Northern Hemisphere temperature variability, but the contribution of the various methane sources and sinks to changes in concentration is still a matter of debate. Here we assess changes in methane cycling over the past 160,000 years by measurements of the carbon isotopic composition δ13C of methane in Antarctic ice cores from Dronning Maud Land and Vostok. We find that variations in the δ13C of methane are not generally correlated with changes in atmospheric methane concentration, but instead more closely correlated to atmospheric CO2 concentrations. We interpret this to reflect a climatic and CO2-related control on the isotopic signature of methane source material, such as ecosystem shifts in the seasonally inundated tropical wetlands that produce methane. In contrast, relatively stable δ13C values occurred during intervals of large changes in the atmospheric loading of methane. We suggest that most methane sources—most notably tropical wetlands—must have responded simultaneously to climate changes across these periods