Validating archetypes for the Multiple Sclerosis Functional Composite

Background Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions. Methods A standard archetype development approach was applied on a case set of three clinical tests for multiple sclerosis assessment: After an analysis of the tests, the obtained data elements were organised and structured. The appropriate archetype class was selected and the data elements were implemented in an iterative refinement process. Clinical and information modelling experts validated the models in a structured review process. Results Four new archetypes were developed and publicly deployed in the openEHR Clinical Knowledge Manager, an online platform provided by the openEHR Foundation. Afterwards, these four archetypes were validated by domain experts in a team review. The review was a formalised process, organised in the Clinical Knowledge Manager. Both, development and review process turned out to be time- consuming tasks, mostly due to difficult selection processes between alternative modelling approaches. The archetype review was a straightforward team process with the goal to validate archetypes pragmatically. Conclusions The quality of medical information models is crucial to guarantee standardised semantic representation in order to improve interoperability. The validation process is a practical way to better harmonise models that diverge due to necessary flexibility left open by the underlying formal reference model definitions. This case study provides evidence that both community- and tool- enabled review processes, structured in the Clinical Knowledge Manager, ensure archetype quality. It offers a pragmatic but feasible way to reduce variation in the representation of clinical information models towards a more unified and interoperable model

Validating archetypes for the Multiple Sclerosis Functional Composite

Background Numerous information models for electronic health records, such as openEHR archetypes are available. The quality of such clinical models is important to guarantee standardised semantics and to facilitate their interoperability. However, validation aspects are not regarded sufficiently yet. The objective of this report is to investigate the feasibility of archetype development and its community-based validation process, presuming that this review process is a practical way to ensure high-quality information models amending the formal reference model definitions. Methods A standard archetype development approach was applied on a case set of three clinical tests for multiple sclerosis assessment: After an analysis of the tests, the obtained data elements were organised and structured. The appropriate archetype class was selected and the data elements were implemented in an iterative refinement process. Clinical and information modelling experts validated the models in a structured review process. Results Four new archetypes were developed and publicly deployed in the openEHR Clinical Knowledge Manager, an online platform provided by the openEHR Foundation. Afterwards, these four archetypes were validated by domain experts in a team review. The review was a formalised process, organised in the Clinical Knowledge Manager. Both, development and review process turned out to be time- consuming tasks, mostly due to difficult selection processes between alternative modelling approaches. The archetype review was a straightforward team process with the goal to validate archetypes pragmatically. Conclusions The quality of medical information models is crucial to guarantee standardised semantic representation in order to improve interoperability. The validation process is a practical way to better harmonise models that diverge due to necessary flexibility left open by the underlying formal reference model definitions. This case study provides evidence that both community- and tool- enabled review processes, structured in the Clinical Knowledge Manager, ensure archetype quality. It offers a pragmatic but feasible way to reduce variation in the representation of clinical information models towards a more unified and interoperable model

The State of the Art in Language Workbenches. Conclusions from the Language Workbench Challenge

Language workbenches are tools that provide high-level mechanisms for the implementation of (domain-specific) languages. Language workbenches are an active area of research that also receives many contributions from industry. To compare and discuss existing language workbenches, the annual Language Workbench Challenge was launched in 2011. Each year, participants are challenged to realize a given domain-specific language with their workbenches as a basis for discussion and comparison. In this paper, we describe the state of the art of language workbenches as observed in the previous editions of the Language Workbench Challenge. In particular, we capture the design space of language workbenches in a feature model and show where in this design space the participants of the 2013 Language Workbench Challenge reside. We compare these workbenches based on a DSL for questionnaires that was realized in all workbenches

Membership and behavior of ultra-low-diversity pathogen communities present in the gut of humans during prolonged critical illness.

UnlabelledWe analyzed the 16S rRNA amplicon composition in fecal samples of selected patients during their prolonged stay in an intensive care unit (ICU) and observed the emergence of ultra-low-diversity communities (1 to 4 bacterial taxa) in 30% of the patients. Bacteria associated with the genera Enterococcus and Staphylococcus and the family Enterobacteriaceae comprised the majority of these communities. The composition of cultured species from stool samples correlated to the 16S rRNA analysis and additionally revealed the emergence of Candida albicans and Candida glabrata in ~75% of cases. Four of 14 ICU patients harbored 2-member pathogen communities consisting of one Candida taxon and one bacterial taxon. Bacterial members displayed a high degree of resistance to multiple antibiotics. The virulence potential of the 2-member communities was examined in C. elegans during nutrient deprivation and exposure to opioids in order to mimic local conditions in the gut during critical illness. Under conditions of nutrient deprivation, the bacterial members attenuated the virulence of fungal members, leading to a "commensal lifestyle." However, exposure to opioids led to a breakdown in this commensalism in 2 of the ultra-low-diversity communities. Application of a novel antivirulence agent (phosphate-polyethylene glycol [Pi-PEG]) that creates local phosphate abundance prevented opioid-induced virulence among these pathogen communities, thus rescuing the commensal lifestyle. To conclude, the gut microflora in critically ill patients can consist of ultra-low-diversity communities of multidrug-resistant pathogenic microbes. Local environmental conditions in gut may direct pathogen communities to adapt to either a commensal style or a pathogenic style.ImportanceDuring critical illness, the normal gut microbiota becomes disrupted in response to host physiologic stress and antibiotic treatment. Here we demonstrate that the community structure of the gut microbiota during prolonged critical illness is dramatically changed such that in many cases only two-member pathogen communities remain. Most of these ultra-low-membership communities display low virulence when grouped together (i.e., a commensal lifestyle); individually, however, they can express highly harmful behaviors (i.e., a pathogenic lifestyle). The commensal lifestyle of the whole community can be shifted to a pathogenic one in response to host factors such as opioids that are released during physiologic stress and critical illness. This shift can be prevented by using compounds such as Pi-PEG15-20 that interrupt bacterial virulence expression. Taking the data together, this report characterizes the plasticity seen with respect to the choice between a commensal lifestyle and a pathogenic lifestyle among ultra-low-diversity pathogen communities that predominate in the gut during critical illness and offers novel strategies for prevention of sepsis

Combining physical constraints with geometric constraint-based modeling for virtual assembly

The research presented in this dissertation aims to create a virtual assembly environment capable of simulating the constant and subtle interactions (hand-part, part-part) that occur during manual assembly, and providing appropriate feedback to the user in real-time. A virtual assembly system called SHARP System for Haptic Assembly and Realistic Prototyping is created, which utilizes simulated physical constraints for part placement during assembly.;The first approach taken in this research attempt utilized Voxmap Point Shell (VPS) software for implementing collision detection and physics-based modeling in SHARP. A volumetric approach, where complex CAD models were represented by numerous small cubic-voxel elements was used to obtain fast physics update rates (500--1000 Hz). A novel dual-handed haptic interface was developed and integrated into the system allowing the user to simultaneously manipulate parts with both hands. However, coarse model approximations used for collision detection and physics-based modeling only allowed assembly when minimum clearance was limited to ∼8-10%.;To provide a solution to the low clearance assembly problem, the second effort focused on importing accurate parametric CAD data (B-Rep) models into SHARP. These accurate B-Rep representations are used for collision detection as well as for simulating physical contacts more accurately. A new hybrid approach is presented, which combines the simulated physical constraints with geometric constraints which can be defined at runtime. Different case studies are used to identify the suitable combination of methods (collision detection, physical constraints, geometric constraints) capable of best simulating intricate interactions and environment behavior during manual assembly. An innovative automatic constraint recognition algorithm is created and integrated into SHARP. The feature-based approach utilized for the algorithm design, facilitates faster identification of potential geometric constraints that need to be defined. This approach results in optimized system performance while providing a more natural user experience for assembly