Overall mean estimation of trace evidence in a two-level normal–normal model

In the evaluation of measurements on characteristics of forensic trace evidence, Aitken and Lucy (2004) model the data as a two-level model using assumptions of normality where likelihood ratios are used as a measure for the strength of evidence. A two-level model assumes two sources of variation: the variation within measurements in a group (first level) and the variation between different groups (second level). Estimates of the variation within groups, the variation between groups and the overall mean are required in this approach. This paper discusses three estimators for the overall mean. In forensic science, two of these estimators are known as the weighted and unweighted mean. For an optimal choice between these estimators, the within- and between-group covariance matrices are required. In this paper a generalization to the latter two mean estimators is suggested, which is referred to as the generalized weighted mean. The weights of this estimator can be chosen such that they minimize the variance of the generalized weighted mean. These optimal weights lead to a “toy estimator” because they depend on the unknown within- and between-group covariance matrices. Using these optimal weights with estimates for the within- and between-group covariance matrices leads to the third estimator, the optimal “plug-in” generalized weighted mean estimator. The three estimators and the toy estimator are compared through a simulation study. Under conditions generally encountered in practice, we show that the unweighted mean can be preferred over the weighted mean. Moreover, in these situations the unweighted mean and the optimal generalized weighted mean behave similarly. An artificial choice of parameters is used to provide an example where the optimal generalized weighted mean outperforms both the weighted and unweighted mean. Finally, the three mean estimators are applied to real XTC data to illustrate the impact of the choice of overall mean estimator.Accepted author manuscriptDelft Institute of Applied Mathematic

Breakdown of the FLT3-ITD/STAT5 axis and synergistic apoptosis induction by the histone deacetylase inhibitor panobinostat and FLT3-specific inhibitors.

Activating mutations of the class III receptor tyrosine kinase FLT3 are the most frequent molecular aberration in acute myeloid leukemia (AML). Mutant FLT3 accelerates proliferation, suppresses apoptosis, and correlates with poor prognosis. Therefore, it is a promising therapeutic target. Here, we show that RNA interference against FLT3 with an internal tandem duplication (FLT3-ITD) potentiates the efficacy of the histone deacetylase inhibitor (HDACi) panobinostat (LBH589) against AML cells expressing FLT3-ITD. Similar to RNA interference, tyrosine kinase inhibitors (TKI; AC220/cpd.102/PKC412) in combination with LBH589 exhibit superior activity against AML cells. Median dose-effect analyses of drug-induced apoptosis rates of AML cells (MV4-11 and MOLM-13) revealed combination index (CI) values indicating strong synergism. AC220, the most potent and FLT3-specific TKI, shows highest synergism with LBH589 in the low nanomolar range. A 4-hour exposure to LBH589 + AC220 already generates more than 50% apoptosis after 24 hours. Different cell lines lacking FLT3-ITD as well as normal peripheral blood mononuclear cells are not significantly affected by LBH589 + TKI, showing the specificity of this treatment regimen. Immunoblot analyses show that LBH589 + TKI induce apoptosis via degradation of FLT3-ITD and its prosurvival target STAT5. Previously, we showed the LBH589-induced proteasomal degradation of FLT3-ITD. Here, we show that activated caspase-3 also contributes to the degradation of FLT3-ITD and that STAT5 is a direct target of this protease. Our data strongly emphasize HDACi/TKI drug combinations as promising modality for the treatment of FLT3-ITD-positive AMLs

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