Osteopenia Due to Enhanced Cathepsin K Release by BK Channel Ablation in Osteoclasts

BACKGROUND: The process of bone resorption by osteoclasts is regulated by Cathepsin K, the lysosomal collagenase responsible for the degradation of the organic bone matrix during bone remodeling. Recently, Cathepsin K was regarded as a potential target for therapeutic intervention of osteoporosis. However, mechanisms leading to osteopenia, which is much more common in young female population and often appears to be the clinical pre-stage of idiopathic osteoporosis, still remain to be elucidated, and molecular targets need to be identified. METHODOLOGY/PRINCIPAL FINDINGS: We found, that in juvenile bone the large conductance, voltage and Ca(2+)-activated (BK) K(+) channel, which links membrane depolarization and local increases in cytosolic calcium to hyperpolarizing K(+) outward currents, is exclusively expressed in osteoclasts. In juvenile BK-deficient (BK(-/-)) female mice, plasma Cathepsin K levels were elevated two-fold when compared to wild-type littermates. This increase was linked to an osteopenic phenotype with reduced bone mineral density in long bones and enhanced porosity of trabecular meshwork in BK(-/-) vertebrae as demonstrated by high-resolution flat-panel volume computed tomography and micro-CT. However, plasma levels of sRANKL, osteoprotegerin, estrogene, Ca(2+) and triiodthyronine as well as osteoclastogenesis were not altered in BK(-/-) females. CONCLUSION/SIGNIFICANCE: Our findings suggest that the BK channel controls resorptive osteoclast activity by regulating Cathepsin K release. Targeted deletion of BK channel in mice resulted in an osteoclast-autonomous osteopenia, becoming apparent in juvenile females. Thus, the BK(-/-) mouse-line represents a new model for juvenile osteopenia, and revealed the BK channel as putative new target for therapeutic controlling of osteoclast activity

CTCF Prevents the Epigenetic Drift of EBV Latency Promoter Qp

The establishment and maintenance of Epstein-Barr Virus (EBV) latent infection requires distinct viral gene expression programs. These gene expression programs, termed latency types, are determined largely by promoter selection, and controlled through the interplay between cell-type specific transcription factors, chromatin structure, and epigenetic modifications. We used a genome-wide chromatin-immunoprecipitation (ChIP) assay to identify epigenetic modifications that correlate with different latency types. We found that the chromatin insulator protein CTCF binds at several key regulatory nodes in the EBV genome and may compartmentalize epigenetic modifications across the viral genome. Highly enriched CTCF binding sites were identified at the promoter regions upstream of Cp, Wp, EBERs, and Qp. Since Qp is essential for long-term maintenance of viral genomes in type I latency and epithelial cell infections, we focused on the role of CTCF in regulating Qp. Purified CTCF bound ∼40 bp upstream of the EBNA1 binding sites located at +10 bp relative to the transcriptional initiation site at Qp. Mutagenesis of the CTCF binding site in EBV bacmids resulted in a decrease in the recovery of stable hygromycin-resistant episomes in 293 cells. EBV lacking the Qp CTCF site showed a decrease in Qp transcription initiation and a corresponding increase in Cp and Fp promoter utilization at 8 weeks post-transfection. However, by 16 weeks post-transfection, bacmids lacking CTCF sites had no detectable Qp transcription and showed high levels of histone H3 K9 methylation and CpG DNA methylation at the Qp initiation site. These findings provide direct genetic evidence that CTCF functions as a chromatin insulator that prevents the promiscuous transcription of surrounding genes and blocks the epigenetic silencing of an essential promoter, Qp, during EBV latent infection

Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the 21st century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include: warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land-use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia's role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large scale water withdrawals, land use and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that Integrated Assessment Models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

Daily Flood Forecasts with Intelligent Data Analytic Models: Multivariate Empirical Mode Decomposition-Based Modeling Methods

Flood causes massive damages to infrastructure, agriculture, livelihood and leads to loss of life. This chapter designs M5 tree-based machine learning model integrated with advanced multivariate empirical mode decomposition (i.e., MEMD-M5 Tree) for daily flood index (FI) forecasting for Lockyer Valley in southeast Queensland, Australia, using data from January 01, 1950, to December 31, 2012. The MEMD-M5 tree is evaluated against MEMD-RF, standalone M5 tree, and RF models via statistical metrics, diagnostic plots with error distributions between simulated and observed daily flood index. The results indicate that MEMD-M5 tree outperforms the comparative models by attaining maximum values of r = 0.990, WI = 0.992, ENS = 0.979, and L = 0.920. The MEMD-M5 tree outperforms other models by registering the least value of RMSE and MAE and can precisely emulate 97.94% of daily FI value. Graphical diagnostic analysis and forecast error histograms further reveal that the MEMD-M5 tree has a greater resemblance to that of the observed data supporting the outcomes of statistical evaluation. Such advancements in flood prediction models, attained through data intelligent analytical methods, are very vital and effective in ensuring better mitigation and civil protection in emergency providing an early warning system, disaster risk reduction, disaster policy suggestions, and reduction of the property damage