Prospects for a nonliving vaccine against Schistosomiasis based on cell-mediated immune resistance mechanisms

We have designed a vaccine model based on induction of cell-mediated immunity and shown that it protects mice against Schistosoma mansoni infection. Mice are immunized by intradermal injection with schistosome antigens plus BCG. Resistance is dependent on the route of antigen presentation and the adjuvant chosen. The pattern of resistance correlates with sensitization of T lymphocytes for production of gamma interferon, a macrophage activating lymphokine that stimulates the cellular effector mechanism of protection. Purified schistosome paramyosin, a muscle cell component present in soluble parasite antigenic preparations, is immunogenic for T lymphocytes and induces resistance when given intradermally with BCG. It is likely that this protein, and possibly other soluble molecules that are released by the parasites of a challenge infection, induce a cellular inflammatory response resulting in larval trapping and/or killing by activated macrophages. These results verify the feasibility of a vaccine against schistosomiasis based on induction of cell-mediated immune resistance mechanisms.

A control flow prototype for a dose recommending device for chronic myeloid leukemia patients

In this paper we present a prototype of a control flow for an a posteriori drug dose adaptation for Chronic Myelogenous Leukemia (CML) patients. The control flow is modeled using Timed Automata extended with Tasks (TAT) model. The feedback loop of the control flow includes the decision-making process for drug dose adaptation. This is based on the outputs of the body response model represented by the Support Vector Machine (SVM) algorithm for drug concentration prediction. The decision is further checked for conformity with the dose level rules of a medical guideline. We also have developed an automatic code synthesizer for the icycom platform as an extension of the TIMES tool.

An objective anisotropic elastic plastic model and Algorithm applicable to bone mechanics

The implicit projection algorithm of isotropic plasticity is extended to an objective anisotropic elastic perfectly plastic model. The recursion formula developed to project the trial stress on the yield surface, is applicable to any non linear elastic law and any plastic yield function.A curvilinear transverse isotropic model based on a quadratic elastic potential and on Hill's quadratic yield criterion is then developed and implemented in a computer program for bone mechanics perspectives. The paper concludes with a numerical study of a schematic bone-prosthesis system to illustrate the potential of the model.

Simulation-based systematic review of imatinib population pharmacokinetics and PK-PD relationships in chronic myeloid leukemia (CML) patients

Objectives: Several population pharmacokinetic (PPK) and pharmacokinetic-pharmacodynamic (PK-PD) analyses have been performed with the anticancer drug imatinib. Inspired by the approach of meta-analysis, we aimed to compare and combine results from published studies in a useful way - in particular for improving the clinical interpretation of imatinib concentration measurements in the scope of therapeutic drug monitoring (TDM). Methods: Original PPK analyses and PK-PD studies (PK surrogate: trough concentration Cmin; PD outcomes: optimal early response and specific adverse events) were searched systematically on MEDLINE. From each identified PPK model, a predicted concentration distribution under standard dosage was derived through 1000 simulations (NONMEM), after standardizing model parameters to common covariates. A "reference range" was calculated from pooled simulated concentrations in a semi-quantitative approach (without specific weighting) over the whole dosing interval. Meta-regression summarized relationships between Cmin and optimal/suboptimal early treatment response. Results: 9 PPK models and 6 relevant PK-PD reports in CML patients were identified. Model-based predicted median Cmin ranged from 555 to 1388 ng/ml (grand median: 870 ng/ml and inter-quartile range: 520-1390 ng/ml). The probability to achieve optimal early response was predicted to increase from 60 to 85% from 520 to 1390 ng/ml across PK-PD studies (odds ratio for doubling Cmin: 2.7). Reporting of specific adverse events was too heterogeneous to perform a regression analysis. The general frequency of anemia, rash and fluid retention increased however consistently with Cmin, but less than response probability. Conclusions: Predicted drug exposure may differ substantially between various PPK analyses. In this review, heterogeneity was mainly attributed to 2 "outlying" models. The established reference range seems to cover the range where both good efficacy and acceptable tolerance are expected for most patients. TDM guided dose adjustment appears therefore justified for imatinib in CML patients. Its usefulness remains now to be prospectively validated in a randomized trial.

Ultimate test bench for pediatric biventricular assist device based on artificial muscles.

Ventricular assist devices (VADs) are used in treatment for terminal heart failure or as a bridge to transplantation. We created biVAD using the artificial muscles (AMs) that supports both ventricles at the same time. We developed the test bench (TB) as the in vitro evaluating system to enable the measurement of performance. The biVAD exerts different pressure between left and right ventricle like the heart physiologically does. The heart model based on child's heart was constructed in silicone. This model was fitted with the biVAD. Two pipettes containing water with an ultrasonic sensor placed on top of each and attached to ventricles reproduced the preload and the after load of each ventricle by the real-time measurement of the fluid height variation proportionally to the exerted pressure. The LabVIEW software extrapolated the displaced volume and the pressure generated by each side of our biVAD. The development of a standardized protocol permitted the validation of the TB for in vitro evaluation, measurement of the performances of the AM biVAD herein, and reproducibility of data.

Dosing regimen of gentamicin in neonates: evaluation of current guidelines based on a large population pharmacokinetic analysis

Objectives: Gentamicin is among the most commonly prescribed antibiotics in newborns, but large interindividual variability in exposure levels exists. Based on a population pharmacokinetic analysis of a cohort of unselected neonates, we aimed to validate current dosing recommendations from a recent reference guideline (Neofax®). Methods: From 3039 concentrations collected in 994 preterm (median gestational age 32.3 weeks, range 24.2-36.5) and 455 term newborns, treated at the University Hospital of Lausanne between 2006 and 2011, a population pharmacokinetic analysis was performed with NONMEM®. Model-based simulations were used to assess the ability of dosing regimens to bring concentrations into targets: trough ≤ 1mg/L and peak ~ 8mg/L. Results: A two-compartment model best characterized gentamicin pharmacokinetics. Model parameters are presented in the table. Body weight, gestational age and postnatal age positively influence clearance, which decreases under dopamine administration. Body weight and gestational age influence the distribution volume. Model based simulations confirm that preterm infants need doses superior to 4 mg/kg, and extended dosage intervals, up to 48 hours for very preterm newborns, whereas most term newborns would achieve adequate exposure under 4 mg/kg q. 24 h. More than 90% of neonates would achieve trough concentrations below 2 mg/L and peaks above 6 mg/L following most recent guidelines. Conclusions: Simulated gentamicin exposure demonstrates good accordance with recent dosing recommendations for target concentration achievement.

Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model.

MOTIVATION: Combinatorial interactions of transcription factors with cis-regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. The construction of network models of cis-regulatory elements, therefore, has the potential to generate fundamental insights into cellular fate and differentiation. Haematopoiesis has long served as a model system to study mammalian differentiation, yet modelling based on experimentally informed cis-regulatory interactions has so far been restricted to pairs of interacting factors. Here, we have generated a Boolean network model based on detailed cis-regulatory functional data connecting 11 haematopoietic stem/progenitor cell (HSPC) regulator genes. RESULTS: Despite its apparent simplicity, the model exhibits surprisingly complex behaviour that we charted using strongly connected components and shortest-path analysis in its Boolean state space. This analysis of our model predicts that HSPCs display heterogeneous expression patterns and possess many intermediate states that can act as 'stepping stones' for the HSPC to achieve a final differentiated state. Importantly, an external perturbation or 'trigger' is required to exit the stem cell state, with distinct triggers characterizing maturation into the various different lineages. By focusing on intermediate states occurring during erythrocyte differentiation, from our model we predicted a novel negative regulation of Fli1 by Gata1, which we confirmed experimentally thus validating our model. In conclusion, we demonstrate that an advanced mammalian regulatory network model based on experimentally validated cis-regulatory interactions has allowed us to make novel, experimentally testable hypotheses about transcriptional mechanisms that control differentiation of mammalian stem cells. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Proposta d'un model predictiu del risc d'ingrés hospitalari amb l'ús d'algoritmes bayesians

Model predictiu basat en xarxes bayesianes que permet identificar els pacients amb major risc d'ingrés a un hospital segons una sèrie d'atributs de dades demogràfiques i clíniques.

Probabilistic base calling of Solexa sequencing data.

BACKGROUND: Solexa/Illumina short-read ultra-high throughput DNA sequencing technology produces millions of short tags (up to 36 bases) by parallel sequencing-by-synthesis of DNA colonies. The processing and statistical analysis of such high-throughput data poses new challenges; currently a fair proportion of the tags are routinely discarded due to an inability to match them to a reference sequence, thereby reducing the effective throughput of the technology. RESULTS: We propose a novel base calling algorithm using model-based clustering and probability theory to identify ambiguous bases and code them with IUPAC symbols. We also select optimal sub-tags using a score based on information content to remove uncertain bases towards the ends of the reads. CONCLUSION: We show that the method improves genome coverage and number of usable tags as compared with Solexa's data processing pipeline by an average of 15%. An R package is provided which allows fast and accurate base calling of Solexa's fluorescence intensity files and the production of informative diagnostic plots.

Dynamic diagnosis based on interval analytical redundancy relations and signs of the symptoms

A model-based approach for fault diagnosis is proposed, where the fault detection is based on checking the consistencyof the Analytical Redundancy Relations (ARRs) using an interval tool. The tool takes into account the uncertainty in theparameters and the measurements using intervals. Faults are explicitly included in the model, which allows for the exploitation of additional information. This information is obtained from partial derivatives computed from the ARRs. The signs in the residuals are used to prune the candidate space when performing the fault diagnosis task. The method is illustrated using a two-tank example, in which these aspects are shown to have an impact on the diagnosis and fault discrimination, since the proposed method goes beyond the structural methods

A double layer model of the gas bubble/water interface

Zeta potential is a physico-chemical parameter of particular importance to describe sorption of contaminants at the surface of gas bubbles. Nevertheless, the interpretation of electrophoretic mobilities of gas bubbles is complex. This is due to the specific behavior of the gas at interface and to the excess of electrical charge at interface, which is responsible for surface conductivity. We developed a surface complexation model based on the presence of negative surface sites because the balance of accepting and donating hydrogen bonds is broken at interface. By considering protons adsorbed on these sites followed by a diffuse layer, the electrical potential at the head-end of the diffuse layer is computed and considered to be equal to the zeta potential. The predicted zeta potential values are in very good agreement with the experimental data of H-2 bubbles for a broad range of pH and NaCl concentrations. This implies that the shear plane is located at the head-end of the diffuse layer, contradicting the assumption of the presence of a stagnant diffuse layer at the gas/water interface. Our model also successfully predicts the surface tension of air bubbles in a KCl solution. (c) 2012 Elsevier Inc. All rights reserved.

Revenue management under general discrete choice model of consumer behavior

Customer choice behavior, such as 'buy-up' and 'buy-down', is an importantphe-nomenon in a wide range of industries. Yet there are few models ormethodologies available to exploit this phenomenon within yield managementsystems. We make some progress on filling this void. Specifically, wedevelop a model of yield management in which the buyers' behavior ismodeled explicitly using a multi-nomial logit model of demand. Thecontrol problem is to decide which subset of fare classes to offer ateach point in time. The set of open fare classes then affects the purchaseprobabilities for each class. We formulate a dynamic program todetermine the optimal control policy and show that it reduces to a dynamicnested allocation policy. Thus, the optimal choice-based policy caneasily be implemented in reservation systems that use nested allocationcontrols. We also develop an estimation procedure for our model based onthe expectation-maximization (EM) method that jointly estimates arrivalrates and choice model parameters when no-purchase outcomes areunobservable. Numerical results show that this combined optimization-estimation approach may significantly improve revenue performancerelative to traditional leg-based models that do not account for choicebehavior.

An in vivo ultrahigh field 14.1 T (1) H-MRS study on 6-OHDA and α-synuclein-based rat models of Parkinson's disease: GABA as an early disease marker.

The detection of Parkinson's disease (PD) in its preclinical stages prior to outright neurodegeneration is essential to the development of neuroprotective therapies and could reduce the number of misdiagnosed patients. However, early diagnosis is currently hampered by lack of reliable biomarkers. (1) H magnetic resonance spectroscopy (MRS) offers a noninvasive measure of brain metabolite levels that allows the identification of such potential biomarkers. This study aimed at using MRS on an ultrahigh field 14.1 T magnet to explore the striatal metabolic changes occurring in two different rat models of the disease. Rats lesioned by the injection of 6-hydroxydopamine (6-OHDA) in the medial-forebrain bundle were used to model a complete nigrostriatal lesion while a genetic model based on the nigral injection of an adeno-associated viral (AAV) vector coding for the human α-synuclein was used to model a progressive neurodegeneration and dopaminergic neuron dysfunction, thereby replicating conditions closer to early pathological stages of PD. MRS measurements in the striatum of the 6-OHDA rats revealed significant decreases in glutamate and N-acetyl-aspartate levels and a significant increase in GABA level in the ipsilateral hemisphere compared with the contralateral one, while the αSyn overexpressing rats showed a significant increase in the GABA striatal level only. Therefore, we conclude that MRS measurements of striatal GABA levels could allow for the detection of early nigrostriatal defects prior to outright neurodegeneration and, as such, offers great potential as a sensitive biomarker of presymptomatic PD.

Modelling state dependence and feedback effects between poverty, employment and parental home emancipation among European youth

Youth is one of the phases in the life-cycle when some of the most decisivelife transitions take place. Entering the labour market or leaving parentalhome are events with important consequences for the economic well-beingof young adults. In this paper, the interrelationship between employment,residential emancipation and poverty dynamics is studied for eight Europeancountries by means of an econometric model with feedback effects. Resultsshow that youth poverty genuine state dependence is positive and highly significant.Evidence proves there is a strong causal effect between poverty andleaving home in Scandinavian countries, however, time in economic hardshipdoes not last long. In Southern Europe, instead, youth tend to leave theirparental home much later in order to avoid falling into a poverty state that ismore persistent. Past poverty has negative consequences on the likelihood ofemployment.

Atrial septal pacing for the termination of atrial fibrillation: study in a biophysical model of human atria.

AIMS: While successful termination by pacing of organized atrial tachycardias has been observed in patients, single site rapid pacing has not yet led to conclusive results for the termination of atrial fibrillation (AF). The purpose of this study was to evaluate a novel atrial septal pacing algorithm for the termination of AF in a biophysical model of the human atria. METHODS AND RESULTS: Sustained AF was generated in a model based on human magnetic resonance images and membrane kinetics. Rapid pacing was applied from the septal area following a dual-stage scheme: (i) rapid pacing for 10-30 s at pacing intervals 62-70% of AF cycle length (AFCL), (ii) slow pacing for 1.5 s at 180% AFCL, initiated by a single stimulus at 130% AFCL. Atrial fibrillation termination success rates were computed. A mean success rate for AF termination of 10.2% was obtained for rapid septal pacing only. The addition of the slow pacing phase increased this rate to 20.2%. At an optimal pacing cycle length (64% AFCL) up to 29% of AF termination was observed. CONCLUSION: The proposed septal pacing algorithm could suppress AF reentries in a more robust way than classical single site rapid pacing. Experimental studies are now needed to determine whether similar termination mechanisms and rates can be observed in animals or humans, and in which types of AF this pacing strategy might be most effective.