State of the art of nanocrystals – special features, production, nanotoxicology aspects and intracellular delivery

Drug nanocrystals are the latest, broadly introduced nanoparticulate carrier to the pharmaceutical market from the year 2000 onwards. The special features of nanocrystals for the delivery of poorly soluble drugs are briefly reviewed (saturation solubility, dissolution velocity, adhesiveness). The industrially relevant bottom up (precipitation) and top down production technologies (pearl milling, high pressure homogenization, combination technologies) are presented. As nanotoxicological aspects, the effect of size, degradability versus biopersistency and intracellular uptake are discussed, classifying the nanocrystals in the low/non-risk group. Intracellular uptake plays a minor or no role for dermal and oral nanocrystals, but it plays a key role for intravenously injected nanocrystals (e.g. nevirapine, paclitaxel, itraconazole). Uptake by the macrophages of the mononuclear phagocytic system (MPS, liver spleen) can modify/optimize blood profiles via prolonged release from the MPS (itraconazole), but also target toxicity by too high organ concentrations and thus cause nanotoxicity. The balance in the competitive intracellular uptake by MPS and the target cells (e.g. blood–brain barrier) decides about therapeutic efficiency. The concept of “differential protein adsorption” to modulate this balance is shown for its applicability to nanocrystals for intracellular delivery to the cells of the blood–brain barrier (atovaquone)

Automated Generation of Explicit Port-Hamiltonian Models from Multi-Bond Graphs

Port-Hamiltonian system theory is a well-known framework for the control of complex physical systems. The majority of port-Hamiltonian control design methods base on an \emph{explicit} input-state-output port-Hamiltonian model for the system under consideration. However in the literature, little effort has been made towards a systematic, automatable derivation of such explicit models. In this paper, we present a constructive, formally rigorous method for an explicit port-Hamiltonian formulation of multi-bond graphs. Two conditions, one necessary and one sufficient, for the existence of an explicit port-Hamiltonian formulation of a multi-bond graph are given. We summarise our approach in a fully automated algorithm of which we provide an exemplary implementation along with this publication. The theoretical and practical results are illustrated through an academic example

BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators

The parameters in Monte Carlo (MC) event generators are tuned on experimental measurements by evaluating the goodness of fit between the data and the MC predictions. The relative importance of each measurement is adjusted manually in an often time consuming, iterative process to meet different experimental needs. In this work, we introduce several optimization formulations and algorithms with new decision criteria for streamlining and automating this process. These algorithms are designed for two formulations: bilevel optimization and robust optimization. Both formulations are applied to the datasets used in the ATLAS A14 tune and to the dedicated hadronization datasets generated by the SHERPA generator, respectively. The corresponding tuned generator parameters are compared using three metrics. We compare the quality of our automatic tunes to the published ATLAS A14 tune. Moreover, we analyze the impact of a pre-processing step that excludes data that cannot be described by the physics models used in the MC event generators

Southeast of What? Reflections on SEALS\u27 Success

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model

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Apprentice for Event Generator Tuning

Apprentice is a tool developed for event generator tuning. It contains a range of conceptual improvements and extensions over the tuning tool Professor. Its core functionality remains the construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo event generator predictions. The surrogate model is used for numerical optimization in chi-square minimization and likelihood evaluation. Apprentice also introduces algorithms to automate the selection of observable weights to minimize the effect of mis-modeling in the event generators. We illustrate our improvements for the task of MC-generator tuning and limit setting.Comment: 9 pages, 2 figures, submitted to the 25th International Conference on Computing in High-Energy and Nuclear Physic

Comparative studies of TIMP-1 immunohistochemistry, TIMP-1 FISH analysis and plasma TIMP-1 in glioblastoma patients

Tissue inhibitor of metalloproteinases-1 (TIMP-1) has been associated with poor prognosis and resistance towards chemotherapy in several cancer forms. In a previous study we found an association between a low TIMP-1 tumor immunoreactivity and increased survival for glioblastoma patients, when compared to moderate and high TIMP-1 tumor immunoreactivity. The aim of the present study was to further evaluate TIMP-1 as a biomarker in gliomas by studying TIMP-1 gene copy numbers by fluorescence in situ hybridization (FISH) on 33 glioblastoma biopsies and by measuring levels of TIMP-1 in plasma obtained pre-operatively from 43 patients (31 gliomas including 21 glioblastomas) by enzyme-linked immunosorbent assay (ELISA). The results showed TIMP-1 gene copy numbers per cell ranging from 1 to 5 and the TIMP-1/CEN-X ratio ranging between 0.7 and 1.09, suggesting neither amplification nor loss of the TIMP-1 gene. The TIMP-1 protein levels measured in plasma were not significantly higher than TIMP-1 levels measured in healthy subjects. No correlation was identified between TIMP-1 tumor cell immunoreactivities and the TIMP-1 gene copy numbers or the plasma TIMP-1 levels. In conclusion, high immunohistochemical TIMP-1 protein levels in glioblastomas were not caused by TIMP-1 gene amplification and TIMP-1 in plasma was low and not directly related to tumor TIMP-1 immunoreactivity. The study suggests that TIMP-1 immunohistochemistry is the method of choice for future clinical studies evaluating TIMP-1 as a biomarker in glioblastomas. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11060-016-2252-4) contains supplementary material, which is available to authorized users