Towards Model Checking Executable UML Specifications in mCRL2

We describe a translation of a subset of executable UML (xUML) into the process algebraic specification language mCRL2. This subset includes class diagrams with class generalisations, and state machines with signal and change events. The choice of these xUML constructs is dictated by their use in the modelling of railway interlocking systems. The long-term goal is to verify safety properties of interlockings modelled in xUML using the mCRL2 and LTSmin toolsets. Initial verification of an interlocking toy example demonstrates that the safety properties of model instances depend crucially on the run-to-completion assumptions

COVID-19-related suicides in Bangladesh due to lockdown and economic factors: case study evidence from media reports

The incidence and mortality of the coronavirus-2019 disease (COVID-19) have increased dramatically around the world. The effects of COVID-19 pandemic are not limited to health, but also have a major impact on the social and economic aspects. Meanwhile, developing and less developed countries are arguably experiencing more severe crises than developed countries, with many small and medium-sized businesses being disrupted and even bankrupt (Fernandes 2020). Consequently, some individuals’ mental health is very fragile (Lin 2020). Sahoo et al. (2020) reported some of the psychological consequences in India (the neighboring country of Bangladesh) including self-harm due to COVID-19 misinformation. Moreover, impacts on mental health (e.g., depression, anxiety, panic, and traumatic stress) can also occur due to the lack of accurate information (Rajkumar 2020; Sahoo et al. 2020; Tandon 2020). In addition, pandemic-related restraints (e.g., spatial distancing, isolation, home quarantine, etc.) is impacting on economic sustainability and well-being, which may induce psychological mediators, such as sadness, worry, fear, anger, annoyance, frustration, guilt, helplessness, loneliness, and nervousness (Mukhtar 2020; Mamun and Griffiths 2020a). These mediators are also distinctive features of psychological suffering that individuals can experience during and after pandemics (Ahorsu et al. 2020; Pakpour and Griffiths 2020). Without early economic interventions, such mental health issues can facilitate suicidal behaviors among some individuals (Arafat and Mamun 2019; Mamun and Griffiths 2020b, c; Jahan et al. 2020), because economic recession, unemployment, and poverty are strongly associated with severe psychological comorbidities such as suicidal behaviors (Goldman-Mellor et al. 2010; Oyesanya et al. 2015; Rafi et al. 2019). There is one prior study that has examined COVID-19-related suicide in Bangladesh (Mamun and Griffiths 2020a)

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

Magnetic Field Mapping and Correction for Moving OP-MEG

Background: Optically pumped magnetometers (OPMs) have made moving, wearable magnetoencephalography (MEG) possible. The OPMs typically used for MEG require a low background magnetic field to operate, which is achieved using both passive and active magnetic shielding. However, the background magnetic field is never truly zero Tesla, and so the field at each of the OPMs changes as the participant moves. This leads to position and orientation dependent changes in the measurements, which manifest as low frequency artefacts in MEG data. Objective: We modelled the spatial variation in the magnetic field and used the model to predict the movement artefact found in a dataset. Methods: We demonstrate a method for modelling this field with a triaxial magnetometer, then showed that we can use the same technique to predict the movement artefact in a real OPM-based MEG (OP-MEG) dataset. Results: Using an 86-channel OP-MEG system, we found that this modelling method maximally reduced the power spectral density of the data by 27.8 0.6 dB at 0 Hz, when applied over 5 s non-overlapping windows. Conclusion: The magnetic field inside our state-of-the art magnetically shielded room can be well described by low-order spherical harmonic functions. We achieved a large reduction in movement noise when we applied this model to OP-MEG data. Significance: Real-time implementation of this method could reduce passive shielding requirements for OP-MEG recording and allow the measurement of low-frequency brain activity during natural participant movement

The role of lumbar puncture in children with suspected central nervous system infection

BACKGROUND: The use of the lumbar puncture in the diagnosis of central nervous system infection in acutely ill children is controversial. Recommendations have been published but it is unclear whether they are being followed. METHODS: The medical case notes of 415 acute medical admissions in a children's hospital were examined to identify children with suspected central nervous system infection and suspected meningococcal septicaemia. We determined whether lumbar punctures were indicated or contraindicated, whether they had been performed, and whether the results contributed to the patients' management. RESULTS: Fifty-two children with suspected central nervous system infections, and 43 with suspected meningococcal septicaemia were identified. No lumbar punctures were performed in patients with contraindications, but only 25 (53%) of 47 children with suspected central nervous system infection and no contraindications received a lumbar puncture. Lumbar puncture findings contributed to the management in 18 (72%) of these patients, by identifying a causative organism or excluding bacterial meningitis. CONCLUSION: The recommendations for undertaking lumbar punctures in children with suspected central nervous system infection are not being followed because many children that should receive lumbar punctures are not getting them. When they are performed, lumbar puncture findings make a useful contribution to the patients' management

Saliva Proteins of Vector Culicoides Modify Structure and Infectivity of Bluetongue Virus Particles

Bluetongue virus (BTV) and epizootic haemorrhagic disease virus (EHDV) are related orbiviruses, transmitted between their ruminant hosts primarily by certain haematophagous midge vectors (Culicoides spp.). The larger of the BTV outer-capsid proteins, ‘VP2’, can be cleaved by proteases (including trypsin or chymotrypsin), forming infectious subviral particles (ISVP) which have enhanced infectivity for adult Culicoides, or KC cells (a cell-line derived from C. sonorensis). We demonstrate that VP2 present on purified virus particles from 3 different BTV strains can also be cleaved by treatment with saliva from adult Culicoides. The saliva proteins from C. sonorensis (a competent BTV vector), cleaved BTV-VP2 more efficiently than those from C. nubeculosus (a less competent / non-vector species). Electrophoresis and mass spectrometry identified a trypsin-like protease in C. sonorensis saliva, which was significantly reduced or absent from C. nubeculosus saliva. Incubating purified BTV-1 with C. sonorensis saliva proteins also increased their infectivity for KC cells ∼10 fold, while infectivity for BHK cells was reduced by 2–6 fold. Treatment of an ‘eastern’ strain of EHDV-2 with saliva proteins of either C. sonorensis or C. nubeculosus cleaved VP2, but a ‘western’ strain of EHDV-2 remained unmodified. These results indicate that temperature, strain of virus and protein composition of Culicoides saliva (particularly its protease content which is dependent upon vector species), can all play a significant role in the efficiency of VP2 cleavage, influencing virus infectivity. Saliva of several other arthropod species has previously been shown to increase transmission, infectivity and virulence of certain arboviruses, by modulating and/or suppressing the mammalian immune response. The findings presented here, however, demonstrate a novel mechanism by which proteases in Culicoides saliva can also directly modify the orbivirus particle structure, leading to increased infectivity specifically for Culicoides cells and, in turn, efficiency of transmission to the insect vector

Promoting fit bodies, healthy eating and physical activity among Indigenous Australian men: a study protocol

Background: Overall the physical health of Indigenous men is among the worst in Australia. Research has indicated that modifiable lifestyle factors, such as poor nutrition and physical inactivity, appear to contribute strongly to these poor health conditions. To effectively develop and implement strategies to improve the health of Australia&rsquo;s Indigenous peoples, a greater understanding is needed of how Indigenous men perceive health, and how they view and care for their bodies. Further, a more systematic understanding of how sociocultural factors affect their health attitudes and behaviours is needed. This article presents the study protocol of a communitybased investigation into the factors surrounding the health and body image of Indigenous Australian men.Methods and design: The study will be conducted in a collaborative manner with Indigenous Australian men using a participatory action research framework. Men will be recruited from three locations around Australia (metropolitan, regional, and rural) and interviewed to understand their experiences and perspectives on a number of issues related to health and health behaviour. The information that is collected will be analysed using modified grounded theory and thematic analysis. The results will then be used to develop and implement community events in each location to provide feedback on the findings to the community, promote health enhancing strategies, and determine future action and collaboration.Discussion: This study will explore both risk and protective factors that affect the health of Indigenous Australian men. This knowledge will be disseminated to the wider Indigenous community and can be used to inform future health promotion strategies. The expected outcome of this study is therefore an increased understanding of health and health change in Indigenous Australian men, the development of strategies that promote healthy eating and positive patterns of physical activity and, in the longer term, more effective and culturally-appropriate interventions to improve health.<br /

A Mechanistic Framework for Integrating Chemical Structure and High-Throughput Screening Results to Improve Toxicity Predictions

Adverse Outcome Pathways (AOPs) establish a connection between a molecular initiating event (MIE) and an adverse outcome. Detailed understanding of the MIE provides the ideal data for determining chemical properties required to elicit the MIE. This study utilized high-throughput screening data from the ToxCast program, coupled with chemical structural information, to generate chemical clusters using three similarity methods pertaining to nine MIEs within an AOP network for hepatic steatosis. Three case studies demonstrate the utility of the mechanistic information held by the MIE for integrating biological and chemical data. Evaluation of the chemical clusters activating the glucocorticoid receptor identified activity differences in chemicals within a cluster. Comparison of the estrogen receptor results with previous work showed that bioactivity data and structural alerts can be combined to improve predictions in a customizable way where bioactivity data are limited. The aryl hydrocarbon receptor (AHR) highlighted that while structural data can be used to offset limited data for new screening efforts, not all ToxCast targets have sufficient data to define robust chemical clusters. In this context, an alternative to additional receptor assays is proposed where assays for proximal key events downstream of AHR activation could be used to enhance confidence in active calls. These case studies illustrate how the AOP framework can support an iterative process whereby in vitro toxicity testing and chemical structure can be combined to improve toxicity predictions. In vitro assays can inform the development of structural alerts linking chemical structure to toxicity. Consequently, structurally related chemical groups can facilitate identification of assays that would be informative for a specific MIE. Together, these activities form a virtuous cycle where the mechanistic basis for the in vitro results and the breadth of the structural alerts continually improve over time to better predict activity of chemicals for which limited toxicity data exist

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