High salt diet impairs cerebral blood flow regulation via salt-induced angiotensin II suppression.

OBJECTIVES: This study sought to determine whether salt-induced ANG II suppression contributes to impaired CBF autoregulation. METHODS: Cerebral autoregulation was evaluated with LDF during graded reductions of blood pressure. Autoregulatory responses in rats fed HS (4% NaCl) diet vs LS (0.4% NaCl) diet were analyzed using linear regression analysis, model-free analysis, and a mechanistic theoretical model of blood flow through cerebral arterioles. RESULTS: Autoregulation was intact in LS-fed animals as MAP was reduced via graded hemorrhage to approximately 50 mm Hg. Short-term (3 days) and chronic (4 weeks) HS diet impaired CBF autoregulation, as evidenced by progressive reductions of laser Doppler flux with arterial pressure reduction. Chronic low dose ANG II infusion (5 mg/kg/min, i.v.) restored CBF autoregulation between the pre-hemorrhage MAP and 50 mm Hg in rats fed short-term HS diet. Mechanistic-based model analysis showed a reduced myogenic response and reduced baseline VSM tone with short-term HS diet, which was restored by ANG II infusion. CONCLUSIONS: Short-term and chronic HS diet lead to impaired autoregulation in the cerebral circulation, with salt-induced ANG II suppression as a major factor in the initiation of impaired CBF regulation.

SemGen: a tool for semantics-based annotation and composition of biosimulation models.

SUMMARY: As the number and complexity of biosimulation models grows, so do demands for tools that can help users understand models and compose more comprehensive and accurate systems from existing models. SemGen is a tool for semantics-based annotation and composition of biosimulation models designed to address this demand. A key SemGen capability is to decompose and then integrate models across existing model exchange formats including SBML and CellML. To support this capability, we use semantic annotations to explicitly capture the underlying biological and physical meanings of the entities and processes that are modeled. SemGen leverages annotations to expose a model's biological and computational architecture and to help automate model composition. AVAILABILITY AND IMPLEMENTATION: SemGen is freely available at https://github.com/SemBioProcess/SemGen. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Psychological interventions for post-traumatic stress disorder in refugees and asylum seekers: A systematic review and meta-analysis.

There is a high prevalence of post-traumatic stress disorder (PTSD) in refugee and asylum seeker populations which can pose distinct challenges for mental health professionals. This review included 16 randomised controlled trials (RCTs) with 1111 participants investigating the effect of psychological interventions on PTSD in these populations. We searched PsychInfo, ProQuest (including selected databases ASSIA, IBSS, PILOTS), Web of Science, the Cochrane Central Database of Controlled Studies (CENTRAL) and Cochrane Database for Systematic Reviews (CDSR) to identify peer-reviewed, primary research articles up to May 2018. We used rigorous methods to assess the quality of included trials and evidence using Cochrane, SURE and GRADE systems. 525 trials were reviewed, 16 were included with 15 contributed to meta-analyses. Despite the challenges of conducting research in this field we found evidence for trauma-focused psychological interventions for PTSD in this population. Following sub-group analyses, we found evidence to support the use of EMDR and Narrative Exposure Therapy for PTSD symptoms. We considered these findings in relation to the broader PTSD treatment literature and related literature from survivors of large scale conflict. These findings suggest that trauma focused psychological therapies can be effective in improving symptoms for refugees and asylum seekers with PTSD.

Semantics-Based Composition of Integrated Cardiomyocyte Models Motivated by Real-World Use Cases.

Semantics-based model composition is an approach for generating complex biosimulation models from existing components that relies on capturing the biological meaning of model elements in a machine-readable fashion. This approach allows the user to work at the biological rather than computational level of abstraction and helps minimize the amount of manual effort required for model composition. To support this compositional approach, we have developed the SemGen software, and here report on SemGen's semantics-based merging capabilities using real-world modeling use cases. We successfully reproduced a large, manually-encoded, multi-model merge: the "Pandit-Hinch-Niederer" (PHN) cardiomyocyte excitation-contraction model, previously developed using CellML. We describe our approach for annotating the three component models used in the PHN composition and for merging them at the biological level of abstraction within SemGen. We demonstrate that we were able to reproduce the original PHN model results in a semi-automated, semantics-based fashion and also rapidly generate a second, novel cardiomyocyte model composed using an alternative, independently-developed tension generation component. We discuss the time-saving features of our compositional approach in the context of these merging exercises, the limitations we encountered, and potential solutions for enhancing the approach.

Multiscale modeling and data integration in the virtual physiological rat project.

It has become increasingly evident that the descriptions of many complex diseases are only possible by taking into account multiple influences at different physiological scales. To do this with computational models often requires the integration of several models that have overlapping scales (genes to molecules, molecules to cells, cells to tissues). The Virtual Physiological Rat (VPR) Project, a National Institute of General Medical Sciences (NIGMS) funded National Center of Systems Biology, is tasked with mechanistically describing several complex diseases and is therefore identifying methods to facilitate the process of model integration across physiological scales. In addition, the VPR has a considerable experimental component and the resultant data must be integrated into these composite multiscale models and made available to the research community. A perspective of the current state of the art in model integration and sharing along with archiving of experimental data will be presented here in the context of multiscale physiological models. It was found that current ontological, model and data repository resources and integrative software tools are sufficient to create composite models from separate existing models and the example composite model developed here exhibits emergent behavior not predicted by the separate models.