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Mice that have been genetically humanized for proteins involved in drug metabolism and toxicity and mice engrafted with human hepatocytes are emerging and promising in vivo models for an improved prediction of the pharmacokinetic, drug–drug interaction and safety characteristics of compounds in humans. The specific advantages and disadvantages of these models should be carefully considered when using them for studies in drug discovery and development. Here, an overview on the corresponding genetically humanized and chimeric liver humanized mouse models described to date is provided and illustrated with examples of their utility in drug metabolism and toxicity studies. We compare the strength and weaknesses of the two different approaches, give guidance for the selection of the appropriate model for various applications and discuss future trends and perspectives.
Breast cancer resistance protein (BCRP) is expressed in various tissues, such as the gut, liver, kidney and blood brain barrier (BBB), where it mediates the unidirectional transport of substrates to the apical/luminal side of polarized cells. Thereby BCRP acts as an efflux pump, mediating the elimination or restricting the entry of endogenous compounds or xenobiotics into tissues and it plays important roles in drug disposition, efficacy and safety. Bcrp knockout mice (Bcrp−/−) have been used widely to study the role of this transporter in limiting intestinal absorption and brain penetration of substrate compounds. Here we describe the first generation and characterization of a mouse line humanized for BCRP (hBCRP), in which the mouse coding sequence from the start to stop codon was replaced with the corresponding human genomic region, such that the human transporter is expressed under control of the murine Bcrp promoter. We demonstrate robust human and loss of mouse BCRP/Bcrp mRNA and protein expression in the hBCRP mice and the absence of major compensatory changes in the expression of other genes involved in drug metabolism and disposition. Pharmacokinetic and brain distribution studies with several BCRP probe substrates confirmed the functional activity of the human transporter in these mice. Furthermore, we provide practical examples for the use of hBCRP mice to study drug-drug interactions (DDIs). The hBCRP mouse is a promising model to study the in vivo role of human BCRP in limiting absorption and BBB penetration of substrate compounds and to investigate clinically relevant DDIs involving BCRP.
NVS123 is a poorly water-soluble protease 56 inhibitor in clinical development. Data from in vitro hepatocyte studies suggested that NVS123 is mainly metabolized by CYP3A4. As a consequence of limited solubility, NVS123 therapeutic plasma exposures could not be achieved even with high doses and optimized formulations. One approach to overcome NVS123 developability issues was to increase plasma exposure by coadministrating it with an inhibitor of CYP3A4 such as ritonavir. A clinical boost effect was predicted by using physiologically based pharmacokinetic (PBPK) modeling. However, initial boost predictions lacked sufficient confidence because a key parameter, fraction of drug metabolized by CYP3A4 (ƒₘCYP3A4), could not be estimated with accuracy on account of disconnects between in vitro and in vivo preclinical data. To accurately estimate ƒₘCYP3A4 in human, an in vivo boost effect study was conducted using CYP3A4-humanized mouse model which showed a 33- to 56-fold exposure boost effect. Using a top-down approach, human ƒₘCYP3A4 for NVS123 was estimated to be very high and included in the human PBPK modeling to support subsequent clinical study design. The combined use of the in vivo boost study in CYP3A4-humanized mouse model mice along with PBPK modeling accurately predicted the clinical outcome and identified a significant NVS123 exposure boost (∼42-fold increase) with ritonavir.
Divided government is often thought of as causing legislative deadlock. I investigate the link between divided government and economic reforms using a novel data set on welfare reforms in US states between 1978 and 2010. Panel data regressions show that, under divided government, a US state is around 25% more likely to adopt a welfare reform than under unified government. Several robustness checks confirm this counter-intuitive finding. Case study evidence suggests an explanation based on policy competition between governor, senate, and house.
Given the strong increase in regulatory requirements for business processes the management of business process compliance becomes a more and more regarded field in IS research. Several methods have been developed to support compliance checking of conceptual models. However, their focus on distinct modeling languages and mostly linear (i.e., predecessor-successor related) compliance rules may hinder widespread adoption and application in practice. Furthermore, hardly any of them has been evaluated in a real-world setting. We address this issue by applying a generic pattern matching approach for conceptual models to business process compliance checking in the financial sector. It consists of a model query language, a search algorithm and a corresponding modelling tool prototype. It is (1) applicable for all graph-based conceptual modeling languages and (2) for different kinds of compliance rules. Furthermore, based on an applicability check, we (3) evaluate the approach in a financial industry project setting against its relevance for decision support of audit and compliance management tasks.
The stimulation and dominance of potentially harmful phytoplankton taxa at a given locale and time are determined by local environmental conditions as well as by transport to or from neighboring regions. The present study investigated the occurrence of common harmful algal bloom (HAB) taxa within the Southern California Bight, using cross-correlation functions to determine potential dependencies between HAB taxa and environmental factors, and potential links to algal transport via local hydrography and currents. A simulation study, in which Lagrangian particles were released, was used to assess travel times due to advection by prevailing ocean currents in the bight. Our results indicate that transport of some taxa may be an important mechanism for the expansion of their distributions into other regions, which was supported by mean travel times derived from our simulation study and other literature on ocean currents in the Southern California Bight. In other cases, however, phytoplankton dynamics were rather linked to local environmental conditions, including coastal upwelling events. Overall, our study shows that complex current patterns in the Southern California Bight may contribute significantly to the formation and expansion of HABs in addition to local environmental factors determining the spatiotemporal dynamics of phytoplankton blooms.
We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.
The Monte Carlo code FLUKA is used to simulate the production of a number of positron emitting radionuclides, ¹⁸F, ¹³N, ⁹⁴Tc, ⁴⁴Sc, ⁶⁸Ga, ⁸⁶Y, ⁸⁹Zr, ⁵²Mn, ⁶¹Cu and ⁵⁵Co, on a small medical cyclotron with a proton beam energy of 13 MeV. Experimental data collected at the TR13 cyclotron at TRIUMF agree within a factor of 0.6 ± 0.4 with the directly simulated data, except for the production of ⁵⁵Co, where the simulation underestimates the experiment by a factor of 3.4 ± 0.4. The experimental data also agree within a factor of 0.8 ± 0.6 with the convolution of simulated proton fluence and cross sections from literature. Overall, this confirms the applicability of FLUKA to simulate radionuclide production at 13 MeV proton beam energy.
[⁶⁸Ga(DOTATATE)] has demonstrated its clinical usefulness. Both Fe³⁺ and Cu²⁺, potential contaminants in Gallium-68 generator eluent, substantially reduce the radiochemical (RC) yield of [⁶⁸Ga(DOTATATE)] if the metal/ligand ratio of 1:1 is exceeded. A variety of compounds were examined for their potential ability to reduce this effect. Most had no effect on RC yield. However, addition of phosphate diminished the influence of Fe³⁺ by likely forming an insoluble iron salt. Addition of ascorbic acid reduced Cu²⁺ and Fe³⁺ to Cu⁺ and Fe²⁺ respectively, both of which have limited impact on RC yields. At low ligand amounts (5 nmol DOTATATE), the addition of 30 nmol phosphate (0.19 mM) increased the tolerance of Fe3⁺ from 4 nmol to 10 nmol (0.06 mM), while the addition of ascorbic acid allowed high RC yields (>95%) in the presence of 40 nmol Fe³⁺ (0.25 mM) and 100 nmol Cu²⁺ (0.63 mM). The effect of ascorbic acid was highly pH-dependant, and gave optimal results at pH 3.
The potential of SMART climbing robot combined with a weatherproof cabin for rotor blade maintenance
(2016)
In this paper we present an extension of the action language Golog that allows for using fuzzy notions in non-deterministic argument choices and the reward function in decision-theoretic planning. Often, in decision-theoretic planning, it is cumbersome to specify the set of values to pick from in the non-deterministic-choice-of-argument statement. Also, even for domain experts, it is not always easy to specify a reward function. Instead of providing a finite domain for values in the non-deterministic-choice-of-argument statement in Golog, we now allow for stating the argument domain by simply providing a formula over linguistic terms and fuzzy uents. In Golog’s forward-search DT planning algorithm, these formulas are evaluated in order to find the agent’s optimal policy. We illustrate this in the Diner Domain where the agent needs to calculate the optimal serving order.
20 Years of RoboCup
(2016)