Use of the FACTS solvation model for protein-ligand docking calculations. Application to EADock.

Protein-ligand docking has made important progress during the last decade and has become a powerful tool for drug development, opening the way to virtual high throughput screening and in silico structure-based ligand design. Despite the flattering picture that has been drawn, recent publications have shown that the docking problem is far from being solved, and that more developments are still needed to achieve high successful prediction rates and accuracy. Introducing an accurate description of the solvation effect upon binding is thought to be essential to achieve this goal. In particular, EADock uses the Generalized Born Molecular Volume 2 (GBMV2) solvent model, which has been shown to reproduce accurately the desolvation energies calculated by solving the Poisson equation. Here, the implementation of the Fast Analytical Continuum Treatment of Solvation (FACTS) as an implicit solvation model in small molecules docking calculations has been assessed using the EADock docking program. Our results strongly support the use of FACTS for docking. The success rates of EADock/FACTS and EADock/GBMV2 are similar, i.e. around 75% for local docking and 65% for blind docking. However, these results come at a much lower computational cost: FACTS is 10 times faster than GBMV2 in calculating the total electrostatic energy, and allows a speed up of EADock by a factor of 4. This study also supports the EADock development strategy relying on the CHARMM package for energy calculations, which enables straightforward implementation and testing of the latest developments in the field of Molecular Modeling.

MALDI-TOF MS-based drug susceptibility testing of pathogens: The example of Candida albicans and fluconazole.

MALDI-TOF MS can be used for the identification of microorganism species. We have extended its application to a novel assay of Candida albicans susceptibility to fluconazole, based on monitoring modifications of the proteome of yeast cells grown in the presence of varying drug concentrations. The method was accurate, and reliable, and showed full agreement with the Clinical Laboratory Standards Institute's reference method. This proof-of-concept demonstration highlights the potential for this approach to test other pathogens.

Patients with AIDS-defining cancers are not universally screened for HIV: a 10-year retrospective analysis of HIV-testing practices in a Swiss university hospital.

OBJECTIVES: Kaposi's sarcoma (KS), invasive cervical carcinoma (ICC) and non-Hodgkin lymphoma (NHL) have been listed as AIDS-defining cancers (ADCs) by the Centers for Disease Control and Prevention since 1993. Despite this, HIV screening is not universally mentioned in ADC treatment guidelines. We examined screening practices at a tertiary centre serving a population where HIV seroprevalence is 0.4%. METHODS: Patients with KS, ICC, NHL and Hodgkin lymphoma (HL), treated at Lausanne University Hospital between January 2002 and July 2012, were studied retrospectively. HIV testing was considered part of the oncology work-up if performed between 90 days before and 90 days after the cancer diagnosis date. RESULTS: A total of 880 patients were examined: 10 with KS, 58 with ICC, 672 with NHL and 140 with HL. HIV testing rates were 100, 11, 60 and 59%, and HIV seroprevalence was 60, 1.7, 3.4 and 5%, respectively. Thirty-seven patients (4.2%) were HIV-positive, of whom eight (22%) were diagnosed at oncology work-up. All newly diagnosed patients had CD4 counts < 200 cells/μL and six (75%) had presented to a physician 12-236 weeks previously with conditions warranting HIV testing. CONCLUSIONS: In our institution, only patients with KS were universally screened. Screening rates for other cancers ranged from 11 to 60%. HIV seroprevalence was at least fourfold higher than the population average. As HIV-positive status impacts on cancer patient medical management, HIV screening should be included in oncology guidelines. Further, we recommend that opt-out screening should be adopted in all patients with ADCs and HL.

Cardiovascular and metabolic responses during isokinetic shoulder rotators strength testing in healthy subjects

Background: Although there have been many studies on isokinetic shoulder exercises in evaluation and rehabilitation programs, the cardiovascular and metabolic responses of those modes of muscle strength exercises have been poorly investigated. Objective: To analyze cardiovascular and metabolic responses during a standardized test used to study the internal (IR) and external (ER) rotators maximal isokinetic strength. Methods: Four days after an incremental exercise test on cycle ergometer, ten healthy subjects performed an isokinetic shoulder strength evaluation with cardiovascular (Heart rate, HR) and metabolic gas exchange (&Vdot;O_{2}) analysis. The IR and ER isokinetic strength, measured in seated position with 45° of shoulder abduction in scapular plane, was evaluated concentrically at 60, 120 and 240°/s and eccentrically at 60°/s, for both shoulder sides. An endurance test with 30 repetitions at 240°/s was performed at the end of each shoulder side testing. Results: There was a significant increase of mean HR with isokinetic exercise (P< 0.05). Increases of HR was 42-71% over the resting values. During endurance testing, increases of HR was 77-105% over the resting values, and corresponded to 85-86% of the maximal HR during incremental test. Increase of &Vdot;O_{2} during isokinetic exercises was from 6-11 ml/min/kg to 20-43 ml/min/kg. Conclusion: This study performed significant cardiovascular and metabolic responses to isokinetic exercise of rotators shoulder muscles. A warm-up should be performed before maximal high-intensity isokinetic shoulder testing. Our results indicated that observation and supervision are important during testing and/or training sessions, especially in subjects with risk for cardiovascular disorders.

Testing mouse mammary tumor virus superantigen as adjuvant in cytotoxic T-lymphocyte responses against a melanoma tumor antigen.

Cytotoxic T cells represent a powerful strategy for antitumor treatment. Depending on the route of injection, an important role for CD4 T cell-mediated help was observed in the induction of this response. For this reason, we investigated whether induction of a CTL response to the HLA-A2-restricted immunodominant peptide melanoma antigen Melan-A was improved by using rVVs expressing the CTL-defined epitope alone or in combination with an SAg. In the latter case, the few infected dendritic cells simultaneously presented an SAg and an antigen, i.e., peptide. Here, we show that the anti-Melan-A response was efficiently induced but not significantly improved by coexpression of the SAg.

Testing Spatial Autocorrelation in Weighted Networks : the Modes Permutation Test

In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

Tricky and terrible T-cell tumors: these are thrilling times for testing: molecular pathology of peripheral T-cell lymphomas.

Peripheral T-cell lymphomas (PTCLs) encompass a group of rare and usually clinically aggressive diseases. The classification and diagnosis of these diseases are compounded by their marked pathological heterogeneity and complex clinical features. With the exception of ALK-positive anaplastic large cell lymphoma (ALCL), which is defined on the basis of ALK rearrangements, genetic features play little role in the definition of other disease entities. In recent years, hitherto unrecognized chromosomal translocations have been reported in small subsets of PTCLs, and genome-wide array-based profiling investigations have provided novel insights into their molecular characteristics. This article summarizes the current knowledge on the best-characterized genetic and molecular alterations underlying the pathogenesis of PTCLs, with a focus on recent discoveries, their relevance to disease classification, and their management implications from a diagnostical and therapeutical perspective.

Candida species distribution and antifungal susceptibility testing according to European Committee on Antimicrobial Susceptibility Testing and new vs. old Clinical and Laboratory Standards Institute clinical breakpoints: a 6-year prospective candidaemia survey from the fungal infection network of Switzerland.

We analyzed the species distribution of Candida blood isolates (CBIs), prospectively collected between 2004 and 2009 within FUNGINOS, and compared their antifungal susceptibility according to clinical breakpoints defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST) in 2013, and the Clinical and Laboratory Standards Institute (CLSI) in 2008 (old CLSI breakpoints) and 2012 (new CLSI breakpoints). CBIs were tested for susceptiblity to fluconazole, voriconazole and caspofungin by microtitre broth dilution (Sensititre(®) YeastOne? test panel). Of 1090 CBIs, 675 (61.9%) were C. albicans, 191 (17.5%) C. glabrata, 64 (5.9%) C. tropicalis, 59 (5.4%) C. parapsilosis, 33 (3%) C. dubliniensis, 22 (2%) C. krusei and 46 (4.2%) rare Candida species. Independently of the breakpoints applied, C. albicans was almost uniformly (>98%) susceptible to all three antifungal agents. In contrast, the proportions of fluconazole- and voriconazole-susceptible C. tropicalis and F-susceptible C. parapsilosis were lower according to EUCAST/new CLSI breakpoints than to the old CLSI breakpoints. For caspofungin, non-susceptibility occurred mainly in C. krusei (63.3%) and C. glabrata (9.4%). Nine isolates (five C. tropicalis, three C. albicans and one C. parapsilosis) were cross-resistant to azoles according to EUCAST breakpoints, compared with three isolates (two C. albicans and one C. tropicalis) according to new and two (2 C. albicans) according to old CLSI breakpoints. Four species (C. albicans, C. glabrata, C. tropicalis and C. parapsilosis) represented >90% of all CBIs. In vitro resistance to fluconazole, voriconazole and caspofungin was rare among C. albicans, but an increase of non-susceptibile isolates was observed among C. tropicalis/C. parapsilosis for the azoles and C. glabrata/C. krusei for caspofungin according to EUCAST and new CLSI breakpoints compared with old CLSI breakpoints.

State-of-the-art of 3D cultures (organs-on-a-chip) in safety testing and pathophysiology.

Integrated approaches using different in vitro methods in combination with bioinformatics can (i) increase the success rate and speed of drug development; (ii) improve the accuracy of toxicological risk assessment; and (iii) increase our understanding of disease. Three-dimensional (3D) cell culture models are important building blocks of this strategy which has emerged during the last years. The majority of these models are organotypic, i.e., they aim to reproduce major functions of an organ or organ system. This implies in many cases that more than one cell type forms the 3D structure, and often matrix elements play an important role. This review summarizes the state of the art concerning commonalities of the different models. For instance, the theory of mass transport/metabolite exchange in 3D systems and the special analytical requirements for test endpoints in organotypic cultures are discussed in detail. In the next part, 3D model systems for selected organs--liver, lung, skin, brain--are presented and characterized in dedicated chapters. Also, 3D approaches to the modeling of tumors are presented and discussed. All chapters give a historical background, illustrate the large variety of approaches, and highlight up- and downsides as well as specific requirements. Moreover, they refer to the application in disease modeling, drug discovery and safety assessment. Finally, consensus recommendations indicate a roadmap for the successful implementation of 3D models in routine screening. It is expected that the use of such models will accelerate progress by reducing error rates and wrong predictions from compound testing.

Sex differences in urinary levels of several biological indicators of exposure: a simulation study using a compartmental based toxicokinetic model

Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study in order to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents, which were methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1,-trichloroethane, and to take into account sex differences. We assessed in a previous human volunteer study the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could even be more pronounced. In conclusion, a general and simple toxicokinetic model, adapted for three well known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variablity, an aspect that should have its place in the approaches for setting limits of occupational exposure.

Numerical simulation of gel electrophoresis of DNA knots in weak and strong electric fields.

Gel electrophoresis allows one to separate knotted DNA (nicked circular) of equal length according to the knot type. At low electric fields, complex knots, being more compact, drift faster than simpler knots. Recent experiments have shown that the drift velocity dependence on the knot type is inverted when changing from low to high electric fields. We present a computer simulation on a lattice of a closed, knotted, charged DNA chain drifting in an external electric field in a topologically restricted medium. Using a Monte Carlo algorithm, the dependence of the electrophoretic migration of the DNA molecules on the knot type and on the electric field intensity is investigated. The results are in qualitative and quantitative agreement with electrophoretic experiments done under conditions of low and high electric fields.

Prediction of Infant Drug Exposure Through Breastfeeding: Population PK Modeling and Simulation of Fluoxetine Exposure.

The likelihood of significant exposure to drugs in infants through breast milk is poorly defined, given the difficulties of conducting pharmacokinetics (PK) studies. Using fluoxetine (FX) as an example, we conducted a proof-of-principle study applying population PK (popPK) modeling and simulation to estimate drug exposure in infants through breast milk. We simulated data for 1,000 mother-infant pairs, assuming conservatively that the FX clearance in an infant is 20% of the allometrically adjusted value in adults. The model-generated estimate of the milk-to-plasma ratio for FX (mean: 0.59) was consistent with those reported in other studies. The median infant-to-mother ratio of FX steady-state plasma concentrations predicted by the simulation was 8.5%. Although the disposition of the active metabolite, norfluoxetine, could not be modeled, popPK-informed simulation may be valid for other drugs, particularly those without active metabolites, thereby providing a practical alternative to conventional PK studies for exposure risk assessment in this population.