In Silico Prediction of Organ Level Toxicity: Linking Chemistry to Adverse Effects

In silico methods to predict toxicity include the use of (Quantitative) Structure-Activity Relationships ((Q)SARs as well as grouping (category formation) allowing for read-across. A challenging area for in silico modelling is the prediction of chronic toxicity and the No Observed (Adverse) Effect Level (NO(A)EL) in particular. A proposed solution to the prediction of chronic toxicity is to consider organ level effects, as opposed to modelling the NO(A)EL itself. This study has focussed on the use of structural alerts to identify potential liver toxicants. In silico profilers, or groups of structural alerts, were developed based on mechanisms of action and informed by current knowledge of Adverse Outcome Pathways. These profilers are robust and can be coded computationally to allow for prediction. However, they do not cover all mechanisms or modes of liver toxicity and recommendations for the improvement of these approaches are given

Introducing usability in a conceptual modeling-based software development process.

Usability plays an important role to satisfy users? needs. There are many recommendations in the HCI literature on how to improve software usability. Our research focuses on such recommendations that affect the system architecture rather than just the interface. However, improving software usability in aspects that affect architecture increases the analyst?s workload and development complexity. This paper proposes a solution based on model-driven development. We propose representing functional usability mechanisms abstractly by means of conceptual primitives. The analyst will use these primitives to incorporate functional usability features at the early stages of the development process. Following the model-driven development paradigm, these features are then automatically transformed into subsequent steps of development, a practice that is hidden from the analyst

From Analysis Model to Software Architecture: a PIM2PIM Mapping.

To our knowledge, no current software development methodology explicitly describes how to transit from the analysis model to the software architecture of the application. This paper presents a method to derive the software architecture of a system from its analysis model. To do this, we are going to use MDA. Both the analysis model and the architectural model are PIMs described with UML 2. The model type mapping designed consists of several rules (expressed using OCL and natural language) that, when applied to the analysis artifacts, generate the software architecture of the application. Specifically the rules act on elements of the UML 2 metamodel (metamodel mapping). We have developed a tool (using Smalltalk) that permits the automatic application of these rules to an analysis model defined in RoseTM to generate the application architecture expressed in the architectural style C2

Using Lightweight Activity Diagrams for Modeling and Generation of Web Information Systems

The development process of web information systems nowadays improved a lot regarding effectiveness and tool support, but still contains many redundant steps for similar tasks. In order to overcome this, we use a model-driven approach to specify a web information system in an agile way and generate a full- edged and runnable application from a set of models. The covered aspects of the system comprise data structure, page structure including view on data, page- and workflow within the system as well as overall application structure and user rights management. Appropriate tooling allows transforming these models to complete systems and thus gives us opportunity for a lightweight development process based on models. In this paper, we describe how we approach the page- and workflow aspect by using activity diagrams as part of the agile modeling approach MontiWIS. We give an overview of the defined syntax, describe the supported forms of action contents and finally explain how the behavior is realized in the generated application.Comment: 12 pages, 6 figure

Domain Wall Spacetimes: Instability of Cosmological Event and Cauchy Horizons

The stability of cosmological event and Cauchy horizons of spacetimes associated with plane symmetric domain walls are studied. It is found that both horizons are not stable against perturbations of null fluids and massless scalar fields; they are turned into curvature singularities. These singularities are light-like and strong in the sense that both the tidal forces and distortions acting on test particles become unbounded when theses singularities are approached.Comment: Latex, 3 figures not included in the text but available upon reques

A critical review of adverse effects to the kidney: mechanisms, data sources and in silico tools to assist prediction

Introduction: The kidney is a major target for toxicity elicited by pharmaceuticals and environmental pollutants. Standard testing which often does not investigate underlying mechanisms has proven not to be an adequate hazard assessment approach. As such, there is an opportunity for the application of computational approaches that utilise multi-scale data based on the Adverse Outcome Pathway (AOP) paradigm, coupled with an understanding of the chemistry underpinning the molecular initiating event (MIE) to provide a deep understanding of how structural fragments of molecules relate to specific mechanisms of nephrotoxicity. The aim of this investigation was to review the current scientific landscape related to computational methods, including mechanistic data, AOPs, publicly available knowledge bases and current in silico models, for the assessment of pharmaceuticals and other chemicals with regard to their potential to elicit nephrotoxicity. A list of over 250 nephrotoxicants enriched with, where possible, mechanistic and AOP-derived understanding was compiled. Expert opinion: Whilst little mechanistic evidence has been translated into AOPs, this review identified a number of data sources of in vitro, in vivo and human data that may assist in the development of in silico models which in turn may shed light on the inter-relationships between nephrotoxicity mechanisms

Quasi-Normal Modes of Schwarzschild Anti-De Sitter Black Holes: Electromagnetic and Gravitational Perturbations

We study the quasi-normal modes (QNM) of electromagnetic and gravitational perturbations of a Schwarzschild black hole in an asymptotically Anti-de Sitter (AdS) spacetime. Some of the electromagnetic modes do not oscillate, they only decay, since they have pure imaginary frequencies. The gravitational modes show peculiar features: the odd and even gravitational perturbations no longer have the same characteristic quasinormal frequencies. There is a special mode for odd perturbations whose behavior differs completely from the usual one in scalar and electromagnetic perturbation in an AdS spacetime, but has a similar behavior to the Schwarzschild black hole in an asymptotically flat spacetime: the imaginary part of the frequency goes as 1/r+, where r+ is the horizon radius. We also investigate the small black hole limit showing that the imaginary part of the frequency goes as r+^2. These results are important to the AdS/CFT conjecture since according to it the QNMs describe the approach to equilibrium in the conformal field theory.Comment: 2 figure

Progression from external pilot to definitive randomised controlled trial : a methodological review of progression criteria reporting

Objectives: Prespecified progression criteria can inform the decision to progress from an external randomised pilot trial to a definitive randomised controlled trial. We assessed the characteristics of progression criteria reported in external randomised pilot trial protocols and results publications, including whether progression criteria were specified a priori and mentioned in prepublication peer reviewer reports. Study design: Methodological review. Methods: We searched four journals through PubMed: British Medical Journal Open, Pilot and Feasibility Studies, Trials and Public Library of Science One. Eligible publications reported external randomised pilot trial protocols or results, were published between January 2018 and December 2019 and reported progression criteria. We double data extracted 25% of the included publications. Here we report the progression criteria characteristics. Results: We included 160 publications (123 protocols and 37 completed trials). Recruitment and retention were the most frequent indicators contributing to progression criteria. Progression criteria were mostly reported as distinct thresholds (eg, achieving a specific target; 133/160, 83%). Less than a third of the planned and completed pilot trials that included qualitative research reported how these findings would contribute towards progression criteria (34/108, 31%). The publications seldom stated who established the progression criteria (12/160, 7.5%) or provided rationale or justification for progression criteria (44/160, 28%). Most completed pilot trials reported the intention to proceed to a definitive trial (30/37, 81%), but less than half strictly met all of their progression criteria (17/37, 46%). Prepublication peer reviewer reports were available for 153/160 publications (96%). Peer reviewer reports for 86/153 (56%) publications mentioned progression criteria, with peer reviewers of 35 publications commenting that progression criteria appeared not to be specified. Conclusions: Many external randomised pilot trial publications did not adequately report or propose prespecified progression criteria to inform whether to proceed to a future definitive randomised controlled trial

Molecular Fingerprint-Derived Similarity Measures for Toxicological Read-Across: Recommendations for Optimal Use

Computational approaches are increasingly used to predict toxicity, in part due to pressures to find alternatives to animal testing. Read-across is the “new paradigm” which aims to predict toxicity by identifying similar, data rich, source compounds. This assumes that similar molecules tend to exhibit similar activities, i.e. molecular similarity is integral to read-across. Various molecular fingerprints and similarity measures may be used to calculate molecular similarity. This study investigated the value and concordance of the Tanimoto similarity values calculated using six widely used fingerprints within six toxicological datasets. There was considerable variability in the similarity values calculated from the various molecular fingerprints for diverse compounds, although they were reasonably concordant for homologous series acting via a common mechanism. The results suggest generic fingerprint-derived similarities are likely to be optimally predictive for local datasets, i.e. following sub-categorisation. Thus, for read-across, generic fingerprint-derived similarities are likely to be most predictive after chemicals are placed into categories (or groups), then similarity is calculated within those categories, rather than for a whole chemically diverse dataset