Deviation from Murray's law is associated with a higher degree of calcification in coronary bifurcations

Murray's law describes the optimal branching anatomy of vascular bifurcations. If Murray's law is obeyed, shear stress is constant over the bifurcation. Associations between Murray's law and intravascular ultrasound (IVUS) assessed plaque composition near coronary bifurcations have not been investigated previously.

Immune response deviation and enhanced expression of chemokine receptor CCR4 in TBI patients due to unknown serum factors

BACKGROUND: Severe brain trauma leads to an activation of the immune system. To this date, neither the exact perturbation of the specific immune reaction induced by the traumatic brain injury (TBI), nor the interactions leading to the infiltration of peripheral immune cells into the brain are fully understood. PATIENTS AND METHODS: Serum was collected from 17 patients with TBI and a long bone fracture, 24 patients with an isolated long bone fracture and from healthy individuals. The effect of the serum on normal human monocytes and T-lymphocytes was tested in vitro by assessing proliferation and expression of surface markers, chemokine receptors and cytokines. RESULTS: Serum collected from patients with a TBI and a long bone fracture increased the expression of the chemokine receptor CCR4 in monocytes when compared to patients with an isolated long bone fracture. Extending this comparison to T-lymphocytes, the serum from TBI patients induced lower proliferation rates and decreased expression of the pro-inflammatory cytokine TNF-alpha, while simultaneously increasing the secretion of immune-modulatory cytokines (IL-4, IL-10 and TGF-beta) (p<0.05). CONCLUSION: Patients with a TBI release currently unknown soluble factors into the circulating blood that up regulate expression of chemokine receptor CCR4 in peripheral blood monocytes whilst concurrently inducing expression of immunosuppressive cytokines by activated T-lymphocytes.

Estimating and quantifying uncertainties on level sets using the Vorob'ev expectation and deviation with Gaussian process models

Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.

DEVCON: Stata module to apply the deviation contrast transform to estimation results

devcon transforms the coefficients of 0/1 dummy variables so that they reflect deviations from the "grand mean" rather than deviations from the reference category (the transformed coefficients are equivalent to those obtained by the so called "effects coding") and adds the coefficient for the reference category. The variance-covariance matrix of the estimates is transformed accordingly. The transformed estimated can be used with post estimation procedures. In particular, devcon can be used to solve the identification problem for dummy variable effects in the so-called Blinder-Oaxaca decomposition (see the oaxaca package).