Increased autophagy in EphrinB2-deficient osteocytes is associated with elevated secondary mineralization and brittle bone

Mineralized bone forms when collagen-containing osteoid accrues mineral crystals. This is initiated rapidly (primary mineralization), and continues slowly (secondary mineralization) until bone is remodeled. The interconnected osteocyte network within the bone matrix differentiates from bone-forming osteoblasts; although osteoblast differentiation requires EphrinB2, osteocytes retain its expression. Here we report brittle bones in mice with osteocyte-targeted EphrinB2 deletion. This is not caused by low bone mass, but by defective bone material. While osteoid mineralization is initiated at normal rate, mineral accrual is accelerated, indicating that EphrinB2 in osteocytes limits mineral accumulation. No known regulators of mineralization are modified in the brittle cortical bone but a cluster of autophagy-associated genes are dysregulated. EphrinB2-deficient osteocytes displayed more autophagosomes in vivo and in vitro, and EphrinB2-Fc treatment suppresses autophagy in a RhoA-ROCK dependent manner. We conclude that secondary mineralization involves EphrinB2-RhoA-limited autophagy in osteocytes, and disruption leads to a bone fragility independent of bone mass

Building relationship innovation in global collaborative partnerships: big data analytics and traditional organizational powers

This study examines how relationship innovation can be developed in global collaborative partnerships (alliances, joint ventures, mergers, and acquisitions). The recently emerging theory of big data analytics linked with traditional organizational powers has attracted a growing interest, but surprisingly little research has been devoted to this important and complex topic. Therefore, after developing the theoretical foundations, our study empirically quantifies the links between the theoretical constructs based on the data collected from chief executive officers, managing directors, and heads of departments who work in contemporary global data-and-information driven collaborative partnerships. The results from structural equation modeling indicate that the relationship innovation depends on the power of big data analytics and non-mediated powers (expert and referent). The power of big data analytics also mediates the correlation between non-mediated powers and relationship innovation. However, mediated powers (coercive and manipulative) negatively affect the power of big data analytics and relationship innovation. The interaction effects further depict that analytically-powered partnerships have better relationship innovation compared to those which focus less on the analytical power. Consequently, the contributions of this study provide a deeper understanding of mechanisms of how modern collaborative partnerships can use big data analytics and traditional organizational powers to co-create relationship innovation

Innovation in the Safety Net: Integrating Community Health Centers Through Accountable Care

BACKGROUND: Safety net primary care providers, including as community health centers, have long been isolated from mainstream health care providers. Current delivery system reforms such as Accountable Care Organizations (ACOs) may either reinforce the isolation of these providers or may spur new integration of safety net providers. OBJECTIVE: This study examines the extent of community health center involvement in ACOs, as well as how and why ACOs are partnering with these safety net primary care providers. DESIGN: Mixed methods study pairing the cross-sectional National Survey of ACOs (conducted 2012 to 2013), followed by in-depth, qualitative interviews with a subset of ACOs that include community health centers (conducted 2013). PARTICIPANTS: One hundred and seventy-three ACOs completed the National Survey of ACOs. Executives from 18 ACOs that include health centers participated in in-depth interviews, along with leadership at eight community health centers participating in ACOs. MAIN MEASURES: Key survey measures include ACO organizational characteristics, care management and quality improvement capabilities. Qualitative interviews used a semi-structured interview guide. Interviews were recorded and transcribed, then coded for thematic content using NVivo software. KEY RESULTS: Overall, 28% of ACOs include a community health center (CHC). ACOs with CHCs are similar to those without CHCs in organizational structure, care management and quality improvement capabilities. Qualitative results showed two major themes. First, ACOs with CHCs typically represent new relationships or formal partnerships between CHCs and other local health care providers. Second, CHCs are considered valued partners brought into ACOs to expand primary care capacity and expertise. CONCLUSIONS: A substantial number of ACOs include CHCs. These results suggest that rather than reinforcing segmentation of safety net providers from the broader delivery system, the ACO model may lead to the integration of safety net primary care providers

Epigenomic evolution in diffuse large B-cell lymphomas

The contribution of epigenomic alterations to tumour progression and relapse is not well characterized. Here we characterize an association between disease progression and DNA methylation in diffuse large B-cell lymphoma (DLBCL). By profiling genome-wide DNA methylation at single-base pair resolution in thirteen DLBCL diagnosis–relapse sample pairs, we show that DLBCL patients exhibit heterogeneous evolution of tumour methylomes during relapse. We identify differentially methylated regulatory elements and determine a relapse-associated methylation signature converging on key pathways such as transforming growth factor-β (TGF-β) receptor activity. We also observe decreased intra-tumour methylation heterogeneity from diagnosis to relapsed tumour samples. Relapse-free patients display lower intra-tumour methylation heterogeneity at diagnosis compared with relapsed patients in an independent validation cohort. Furthermore, intra-tumour methylation heterogeneity is predictive of time to relapse. Therefore, we propose that epigenomic heterogeneity may support or drive the relapse phenotype and can be used to predict DLBCL relapse