https://www.selleckchem.com/products/sant-1.html Inverse probability of treatment weighting (IPTW), which has been used to estimate average treatment effects (ATE) using observational data, tenuously relies on the positivity assumption and the correct specification of the treatment assignment model, both of which are problematic assumptions in many observational studies. Various methods have been proposed to overcome these challenges, including truncation, covariate-balancing propensity scores, and stable balancing weights. Motivated by an observational study in spine surgery, in which positivity is violated and the true treatment assignment model is unknown, we present the use of optimal balancing by kernel optimal matching (KOM) to estimate ATE. By uniformly controlling the conditional mean squared error of a weighted estimator over a class of models, KOM simultaneously mitigates issues of possible misspecification of the treatment assignment model and is able to handle practical violations of the positivity assumption, as shown in our simulation study. Using data from a clinical registry, we apply KOM to compare two spine surgical interventions and demonstrate how the result matches the conclusions of clinical trials that IPTW estimates spuriously refute. This validation study investigated a flow cytometric apoptosis assay according to good manufacturing practice (GMP). Extracorporeal photopheresis (ECP) is a treatment for various immunological diseases and cutaneous T-cell lymphomas. It is based on the induction of apoptosis by 8-methoxypsoralene and ultraviolet A light. The quantification of apoptosis is therefore essential for ECP improvements. However, despite numerous publications on apoptosis, validated technical details are lacking. Mononuclear cells were collected by apheresis and treated by ECP or camptothecin. Samples taken before and after ECP were cultured for 24, 48 and 72 h and analysed for apoptosis and viability of T cells and monocytes by flow cy