Stan is a free and open-source Cþþ program that performs Bayesian inference or optimization for arbitrary user-specified models and can be called from the command line, R, Python, Matlab, or Julia and has great promise for fitting large and complex statistical models in many areas of application. We discuss Stan from users' and developers' perspectives and illustrate with a simple but nontrivial nonlinear regression example.

The extracellular signal-regulated kinase 1/2 (ERK) pathway, part of the mitogen-activated protein kinase (MAPK) family, is well-known for its role in cell differentiation and proliferation. In the context of osteoclastogenesis, macrophage colony stimulating factor (M-CSF) is an upstream activator of ERK, which signals for the survival of osteoclast precursors prior to their differentiation into multinucleated osteoclasts. In addition, many recent studies have revealed the involvement of ERK in promoting osteolysis. In this study, we extended these existing findings linking ERK and osteolysis by identifying the ERK pathway as the primary pathway for osteolysis in osteoclasts and macrophages. We also elucidated the pro-inflammatory capacity of osteoblasts using the ERK pathway. Moreover, the ERK inhibitor, PD98059, inhibited the inflammatory reaction propagated by all three cell types at both a local and systemic level. The importance of ERK signaling in previously known cell types mediating inflammatory osteolysis as well as the discovery of osteoblastic innate immunity involving ERK signaling enhances our understanding of inflammatory osteolysis and supports further future investigation of targeted therapies against the ERK pathway for treating osteolytic diseases.

We use multilevel modeling to estimate support for health-care reform by age, income, and state. Opposition to reform is concentrated among higher-income voters and those over 65. Attitudes do not vary much by state. Unfortunately, our poll data only go to 2004, but we suspect that much can be learned from the relative positions of different demographic groups and different states, despite swings in national opinion. We speculate on the political implications of these findings.

Periprosthetic osteolysis poses a significant clinical problem for patients who have undergone total joint arthroplastic surgeries. It has been widely recognized that there is a strong correlation between wear particles from orthopedic implants and osteolysis. However, the molecular mechanism underlying osteolysis still remains unclear. Although wear particles interact with a mixed cellular environment, namely macrophages and immune cells, osteoblasts compose the majority of the cell population surrounding orthopedic implants. Osteoblasts are also one of the major sources of receptor activator of nuclear factor-kappa beta (NF-kappaB) ligand (RANKL), a factor necessary for osteoclastogenesis. However, macrophage colony-stimulating factor (M-CSF), another cytokine responsible for preosteoclast proliferation, must also be present with RANKL for osteoclastogenesis to occur. The purpose of our study is to determine the signal transduction pathway by which titanium (Ti) particles, a metallic component of many orthopedic implants, induce M-CSF expression in MC3T3.E1 murine calvarial preosteoblastic cells. Using reverse transcriptase-polymerase chain reaction (RT-PCR) and enzyme- linked immunosorbent assay (ELISA), our study demonstrated that submicron-sized Ti particles induce M-CSF expression via the extracellular signal-regulated kinase (ERK) pathway in a dose-dependent manner. Moreover, inhibition studies showed that a specific ERK inhibitor, PD98059, significantly downregulated M-CSF production. Our results support the hypothesis that submicron-sized Ti particles can induce M-CSF expression in osteoblasts and thus may have a significant role in contributing to the onset of periprosthetic osteolysis.

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