Comparison of immortalized bEnd5 and primary mouse brain microvascular endothelial cells as in vitro blood-brain barrier models for the study of T cell extravasation

Important insights into the molecular mechanism of T cell extravasation across the blood-brain barrier (BBB) have already been obtained using immortalized mouse brain endothelioma cell lines (bEnd). However, compared with bEnd, primary brain endothelial cells have been shown to establish better barrier characteristics, including complex tight junctions and low permeability. In this study, we asked whether bEnd5 and primary mouse brain microvascular endothelial cells (pMBMECs) were equally suited as in vitro models with which to study the cellular and molecular mechanisms of T cell extravasation across the BBB. We found that both in vitro BBB models equally supported both T cell adhesion under static and physiologic flow conditions, and T cell crawling on the endothelial surface against the direction of flow. In contrast, distances of T cell crawling on pMBMECs were strikingly longer than on bEnd5, whereas diapedesis of T cells across pMBMECs was dramatically reduced compared with bEnd5. Thus, both in vitro BBB models are suited to study T cell adhesion. However, because pMBMECs better reflect endothelial BBB specialization in vivo, we propose that more reliable information about the cellular and molecular mechanisms of T cell diapedesis across the BBB can be attained using pMBMECs.

Methodology and models in erosion research: discussion and conclusions

This paper summarises the discussions which took place at the Workshop on Methodology in Erosion Research in Zürich, 2010, and aims, where possible, to offer guidance for the development and application of both in vitro and in situ models for erosion research. The prospects for clinical trials are also discussed. All models in erosion research require a number of choices regarding experimental conditions, study design and measurement techniques, and these general aspects are discussed first. Among in vitro models, simple (single- or multiple-exposure) models can be used for screening products regarding their erosive potential, while more elaborate pH cycling models can be used to simulate erosion in vivo. However, in vitro models provide limited information on intra-oral erosion. In situ models allow the effect of an erosive challenge to be evaluated under intra-oral conditions and are currently the method of choice for short-term testing of low-erosive products or preventive therapeutic products. In the future, clinical trials will allow longer-term testing. Possible methodologies for such trials are discussed.

Echinococcus metacestodes as laboratory models for the screening of drugs against cestodes and trematodes

Among the cestodes, Echinococcus granulosus, Echinococcus multilocularis and Taenia solium represent the most dangerous parasites. Their larval stages cause the diseases cystic echinococcosis (CE), alveolar echinococcosis (AE) and cysticercosis, respectively, which exhibit considerable medical and veterinary health concerns with a profound economic impact. Others caused by other cestodes, such as species of the genera Mesocestoides and Hymenolepis, are relatively rare in humans. In this review, we will focus on E. granulosus and E. multilocularis metacestode laboratory models and will review the use of these models in the search for novel drugs that could be employed for chemotherapeutic treatment of echinococcosis. Clearly, improved therapeutic drugs are needed for the treatment of AE and CE, and this can only be achieved through the development of medium-to-high throughput screening approaches. The most recent achievements in the in vitro culture and genetic manipulation of E. multilocularis cells and metacestodes, and the accessability of the E. multilocularis genome and EST sequence information, have rendered the E. multilocularis model uniquely suited for studies on drug-efficacy and drug target identification. This could lead to the development of novel compounds for the use in chemotherapy against echinococcosis, and possibly against diseases caused by other cestodes, and potentially also trematodes.

Simple beam models for Monte Carlo photon beam dose calculations in radiotherapy

Monte Carlo (code GEANT) produced 6 and 15 MV phase space (PS) data were used to define several simple photon beam models. For creating the PS data the energy of starting electrons hitting the target was tuned to get correct depth dose data compared to measurements. The modeling process used the full PS information within the geometrical boundaries of the beam including all scattered radiation of the accelerator head. Scattered radiation outside the boundaries was neglected. Photons and electrons were assumed to be radiated from point sources. Four different models were investigated which involved different ways to determine the energies and locations of beam particles in the output plane. Depth dose curves, profiles, and relative output factors were calculated with these models for six field sizes from 5x5 to 40x40cm2 and compared to measurements. Model 1 uses a photon energy spectrum independent of location in the PS plane and a constant photon fluence in this plane. Model 2 takes into account the spatial particle fluence distribution in the PS plane. A constant fluence is used again in model 3, but the photon energy spectrum depends upon the off axis position. Model 4, finally uses the spatial particle fluence distribution and off axis dependent photon energy spectra in the PS plane. Depth dose curves and profiles for field sizes up to 10x10cm2 were not model sensitive. Good agreement between measured and calculated depth dose curves and profiles for all field sizes was reached for model 4. However, increasing deviations were found for increasing field sizes for models 1-3. Large deviations resulted for the profiles of models 2 and 3. This is due to the fact that these models overestimate and underestimate the energy fluence at large off axis distances. Relative output factors consistent with measurements resulted only for model 4.

Human experimental pain models in drug development: translational pain research

Human experimental pain models require standardized stimulation and quantitative assessment of the evoked responses. This approach can be applied to healthy volunteers and pain patients before and after pharmacological interventions. Standardized stimuli of different modalities (ie, mechanical, chemical, thermal or electrical) can be applied to the skin, muscles and viscera for a differentiated and comprehensive assessment of various pain pathways and mechanisms. Using a multi-modal, multi-tissue approach, new and existing analgesic drugs can be profiled by their modulation of specific biomarkers. It has been shown that biomarkers, for example, those related to the central integration of repetitive nociceptive stimuli, can predict efficacy of a given drug in neuropathic pain conditions. Human experimental pain models can bridge animal and clinical pain research, and act as translational research providing new possibilities for designing successful clinical trials. Proof-of-concept studies provide cheap, fast and reliable information on dose-efficacy relationships and how pain sensed in the skin, muscles and viscera are inhibited.

On Graphically Checking Goodness-of-fit of Binary Logistic Regression Models

OBJECTIVES: This paper is concerned with checking goodness-of-fit of binary logistic regression models. For the practitioners of data analysis, the broad classes of procedures for checking goodness-of-fit available in the literature are described. The challenges of model checking in the context of binary logistic regression are reviewed. As a viable solution, a simple graphical procedure for checking goodness-of-fit is proposed. METHODS: The graphical procedure proposed relies on pieces of information available from any logistic analysis; the focus is on combining and presenting these in an informative way. RESULTS: The information gained using this approach is presented with three examples. In the discussion, the proposed method is put into context and compared with other graphical procedures for checking goodness-of-fit of binary logistic models available in the literature. CONCLUSION: A simple graphical method can significantly improve the understanding of any logistic regression analysis and help to prevent faulty conclusions.

Use of homeopathic preparations in phytopathological models and in field trails: a critical review

Background: The literature on the applications of homeopathy for controlling plant diseases in both plant pathological models and field trials was first reviewed by Scofield in 1984. No other review on homeopathy in plant pathology has been published since, though much new research has subsequently been carried out using more advanced methods. Objectives: To conduct an up-to-date review of the existing literature on basic research in homeopathy using phytopathological models and experiments in the field. Methods: A literature search was carried out on publications from 1969 to 2009, for papers that reported experiments on homeopathy using phytopathological models (in vitro and in planta) and field trials. The selected papers were summarized and analysed on the basis of a Manuscript Information Score (MIS) to identify those that provided sufficient information for proper interpretation (MIS ≥ 5). These were then evaluated using a Study Methods Evaluation Procedure (SMEP). Results: A total of 44 publications on phytopathological models were identified: 19 papers with statistics, 6 studies with MIS ≥ 5. Publications on field were 9, 6 with MIS ≥ 5. In general, significant and reproducible effects with decimal and centesimal potencies were found, including dilution levels beyond the Avogadro's number. Conclusions: The prospects for homeopathic treatments in agriculture are promising, but much more experimentation is needed, especially at a field level, and on potentisation techniques, effective potency levels and conditions for reproducibility. Phytopathological models may also develop into useful tools to answer pharmaceutical questions.

The STEREO/PLASTIC response to solar wind ions (Flight measurements and models)

The Plasma and Supra-Thermal Ion Composition (PLASTIC) instrument is one of four experiment packages on board of the two identical STEREO spacecraft A and B, which were successfully launched from Cape Canaveral on 26 October 2006. During the two years of the nominal STEREO mission, PLASTIC is providing us with the plasma characteristics of protons, alpha particles, and heavy ions. PLASTIC will also provide key diagnostic measurements in the form of the mass and charge state composition of heavy ions. Three measurements (E/qk, time of flight, ESSD) from the pulse height raw data are used to characterize the solar wind ions from the solar wind sector, and part of the suprathermal particles from the wide-angle partition with respect to mass, atomic number and charge state. In this paper, we present a new method for flight data analysis based on simulations of the PLASTIC response to solar wind ions. We present the response of the entrance system / energy analyzer in an analytical form. Based on stopping power theory, we use an analytical expression for the energy loss of the ions when they pass through a thin carbon foil. This allows us to model analytically the response of the time of flight mass spectrometer to solar wind ions. Thus we present a new version of the analytical response of the solid state detectors to solar wind ions. Various important parameters needed for our models were derived, based on calibration data and on the first flight measurements obtained from STEREO-A. We used information from each measured event that is registered in full resolution in the Pulse Height Analysis words and we derived a new algorithm for the analysis of both existing and future data sets of a similar nature which was tested and works well. This algorithm allows us to obtain, for each measured event, the mass, atomic number and charge state in the correct physical units. Finally, an important criterion was developed for filtering our Fe raw flight data set from the pulse height data without discriminating charge states.

Extracting models from IDEs

Systems must co-evolve with their context. Reverse engineering tools are a great help in this process of required adaption. In order for these tools to be flexible, they work with models, abstract representations of the source code. The extraction of such information from source code can be done using a parser. However, it is fairly tedious to build new parsers. And this is made worse by the fact that it has to be done over and over again for every language we want to analyze. In this paper we propose a novel approach which minimizes the knowledge required of a certain language for the extraction of models implemented in that language by reflecting on the implementation of preparsed ASTs provided by an IDE. In a second phase we use a technique referred to as Model Mapping by Example to map platform dependent models onto domain specific model.

Neural network based glucose - insulin metabolism models for children with Type 1 diabetes

In this paper two models for the simulation of glucose-insulin metabolism of children with Type 1 diabetes are presented. The models are based on the combined use of Compartmental Models (CMs) and artificial Neural Networks (NNs). Data from children with Type 1 diabetes, stored in a database, have been used as input to the models. The data are taken from four children with Type 1 diabetes and contain information about glucose levels taken from continuous glucose monitoring system, insulin intake and food intake, along with corresponding time. The influences of taken insulin on plasma insulin concentration, as well as the effect of food intake on glucose input into the blood from the gut, are estimated from the CMs. The outputs of CMs, along with previous glucose measurements, are fed to a NN, which provides short-term prediction of glucose values. For comparative reasons two different NN architectures have been tested: a Feed-Forward NN (FFNN) trained with the back-propagation algorithm with adaptive learning rate and momentum, and a Recurrent NN (RNN), trained with the Real Time Recurrent Learning (RTRL) algorithm. The results indicate that the best prediction performance can be achieved by the use of RNN.

Transferability of geoscientific information from various sources (study sites, underground rock laboratories, natural analogues) to support safety cases for radioactive waste repositories in argillaceous formations

In studies related to deep geological disposal of radioactive waste, it is current practice to transfer external information (e.g. from other sites, from underground rock laboratories or from natural analogues) to safety cases for specific projects. Transferable information most commonly includes parameters, investigation techniques, process understanding, conceptual models and high-level conclusions on system behaviour. Prior to transfer, the basis of transferability needs to be established. In argillaceous rocks, the most relevant common feature is the microstructure of the rocks, essentially determined by the properties of clay–minerals. Examples are shown from the Swiss and French programmes how transfer of information was handled and justified. These examples illustrate how transferability depends on the stage of development of a repository safety case and highlight the need for adequate system understanding at all sites involved to support the transfer.

Investigating the consistency between proxy-based reconstructions and climate models using data assimilation: a mid-Holocene case study

The mid-Holocene (6 kyr BP; thousand years before present) is a key period to study the consistency between model results and proxy-based reconstruction data as it corresponds to a standard test for models and a reasonable number of proxy-based records is available. Taking advantage of this relatively large amount of information, we have compared a compilation of 50 air and sea surface temperature reconstructions with the results of three simulations performed with general circulation models and one carried out with LOVECLIM, a model of intermediate complexity. The conclusions derived from this analysis confirm that models and data agree on the large-scale spatial pattern but the models underestimate the magnitude of some observed changes and that large discrepancies are observed at the local scale. To further investigate the origin of those inconsistencies, we have constrained LOVECLIM to follow the signal recorded by the proxies selected in the compilation using a data-assimilation method based on a particle filter. In one simulation, all the 50 proxy-based records are used while in the other two only the continental or oceanic proxy-based records constrain the model results. As expected, data assimilation leads to improving the consistency between model results and the reconstructions. In particular, this is achieved in a robust way in all the experiments through a strengthening of the westerlies at midlatitude that warms up northern Europe. Furthermore, the comparison of the LOVECLIM simulations with and without data assimilation has also objectively identified 16 proxy-based paleoclimate records whose reconstructed signal is either incompatible with the signal recorded by some other proxy-based records or with model physics.

Bone healing around titanium implants in two rat colitis models

OBJECTIVE Crohn's disease is a chronic inflammatory process that has recently been associated with a higher risk of early implant failure. Herein we provide information on the impact of colitis on peri-implant bone formation using preclinical models of chemically induced colitis. METHODS Colitis was induced by intrarectal instillation of 2,4,6-trinitro-benzene-sulfonic-acid (TNBS). Colitis was also induced by feeding rats dextran-sodium-sulfate (DSS) in drinking water. One week after disease induction, titanium miniscrews were inserted into the tibia. Four weeks after implantation, peri-implant bone volume per tissue volume (BV/TV) and bone-to-implant contacts (BIC) were determined by histomorphometric analysis. RESULTS Cortical histomorphometric parameters were similar in the control (n = 10), DSS (n = 10) and TNBS (n = 8) groups. Cortical BV/TV was 92.2 ± 3.7%, 92.0 ± 3.0% and 92.6 ± 2.7%. Cortical BIC was 81.3 ± 8.8%, 83.2 ± 8.4% and 84.0 ± 7.0%, respectively. No significant differences were observed when comparing the medullary BV/TV and BIC (19.5 ± 6.4%, 16.2 ± 5.6% and 15.4 ± 9.0%) and (48.8 ± 12.9%, 49.2 ± 6.2 and 41.9 ± 11.7%), respectively. Successful induction of colitis was confirmed by loss of body weight and colon morphology. CONCLUSIONS The results suggest bone regeneration around implants is not impaired in chemically induced colitis models. Considering that Crohn's disease can affect any part of the gastrointestinal tract including the mouth, our model only partially reflects the clinical situation.