Insulin Glargine in the Intensive Care Unit: A Model-Based Clinical Trial Design

Online 4 Oct 2012Introduction: Current succesful AGC (Accurate Glycemic Control) protocols require extra clinical effort and are impractical in less acute wards where patients are still susceptible to stress-induced hyperglycemia. Long-acting insulin Glargine has the potential to be used in a low effort controller. However, potential variability in efficacy and length of action, prevent direct in-hospital use in an AGC framework for less acute wards. Method: Clinically validated virtual trials based on data from stable ICU patients from the SPRINT cohort who would be transferred to such an approach are used to develop a 24-hour AGC protocol robust to different Glargine potencies (1.0x, 1.5x and 2.0x regular insulin) and initial dose sizes (dose = total insulin over prior 12, 18 and 24 hours). Glycemic control in this period is provided only by varying nutritional inputs. Performance is assessed as %BG in the 4.0-8.0mmol/L band and safety by %BG<4.0mmol/L. Results: The final protocol consisted of Glargine bolus size equal to insulin over the previous 18 hours. Compared to SPRINT there was a 6.9% - 9.5% absolute decrease in mild hypoglycemia (%BG<4.0mmol/L) and up to a 6.2% increase in %BG between 4.0 and 8.0mmol/L. When the efficacy is known (1.5x assumed) there were reductions of: 27% BG measurements, 59% insulin boluses, 67% nutrition changes, and 6.3% absolute in mild hypoglycemia. Conclusion: A robust 24-48 clinical trial has been designed to safely investigate the efficacy and kinetics of Glargine as a first step towards developing a Glargine-based protocol for less acute wards. Ensuring robustness to variability in Glargine efficacy significantly affects the performance and safety that can be obtained

Ambient-aware continuous care through semantic context dissemination

Background: The ultimate ambient-intelligent care room contains numerous sensors and devices to monitor the patient, sense and adjust the environment and support the staff. This sensor-based approach results in a large amount of data, which can be processed by current and future applications, e. g., task management and alerting systems. Today, nurses are responsible for coordinating all these applications and supplied information, which reduces the added value and slows down the adoption rate. The aim of the presented research is the design of a pervasive and scalable framework that is able to optimize continuous care processes by intelligently reasoning on the large amount of heterogeneous care data. Methods: The developed Ontology-based Care Platform (OCarePlatform) consists of modular components that perform a specific reasoning task. Consequently, they can easily be replicated and distributed. Complex reasoning is achieved by combining the results of different components. To ensure that the components only receive information, which is of interest to them at that time, they are able to dynamically generate and register filter rules with a Semantic Communication Bus (SCB). This SCB semantically filters all the heterogeneous care data according to the registered rules by using a continuous care ontology. The SCB can be distributed and a cache can be employed to ensure scalability. Results: A prototype implementation is presented consisting of a new-generation nurse call system supported by a localization and a home automation component. The amount of data that is filtered and the performance of the SCB are evaluated by testing the prototype in a living lab. The delay introduced by processing the filter rules is negligible when 10 or fewer rules are registered. Conclusions: The OCarePlatform allows disseminating relevant care data for the different applications and additionally supports composing complex applications from a set of smaller independent components. This way, the platform significantly reduces the amount of information that needs to be processed by the nurses. The delay resulting from processing the filter rules is linear in the amount of rules. Distributed deployment of the SCB and using a cache allows further improvement of these performance results

Promoter regions of Plasmodium vivax are poorly or not recognized by Plasmodium falciparum

BACKGROUND: Heterologous promoter analysis in Plasmodium has revealed the existence of conserved cis regulatory elements as promoters from different species can drive expression of reporter genes in heterologous transfection assays. Here, the functional characterization of different Plasmodium vivax promoters in Plasmodium falciparum using luciferase as the reporter gene is presented. METHODS: Luciferase reporter plasmids harboring the upstream regions of the msp1, dhfr, and vir3 genes as well as the full-length intergenic regions of the vir23/24 and ef-1α genes of P. vivax were constructed and transiently transfected in P. falciparum. RESULTS: Only the constructs with the full-length intergenic regions of the vir23/24 and ef-1α genes were recognized by the P. falciparum transcription machinery albeit to values approximately two orders of magnitude lower than those reported by luc plasmids harbouring promoter regions from P. falciparum and Plasmodium berghei. A bioinformatics approach allowed the identification of a motif (GCATAT) in the ef-1α intergenic region that is conserved in five Plasmodium species but is degenerate (GCANAN) in P. vivax. Mutations of this motif in the P. berghei ef-1α promoter region decreased reporter expression indicating it is active in gene expression in Plasmodium. CONCLUSION: Together, this data indicates that promoter regions of P. vivax are poorly or not recognized by the P. falciparum transcription machinery suggesting the existence of P. vivax-specific transcription regulatory elements

Probing the effect of ß-triketonates in visible and NIR emitting lanthanoid complexes

An isomorphous series of lanthanoid complexes containing tribenzoylmethanide (tbm) and 1,10-phenanthroline (phen) ligands has been synthesised and structurally characterised. These complexes, formulated as [Ln(phen)(tbm)3] (Ln = Eu3+, Er3+ and Yb3+), were compared with analogous dibenzoylmethanide (dbm) [Ln(phen)(dbm)3] complexes to investigate the effect of changing ß-diketonate to ß-triketonate ligands on the photophysical properties of the complex. The photophysical properties for the Eu3+ complexes were similar for both systems, whereas a modest enhancement was observed for Yb3+ and Er3+ moving from the dbm to the tbm complexes. A detailed study of the NIR photophysical properties was achieved by adapting the integrating sphere method for the calculation of overall quantum yields in the solid state

The Chemical Information Ontology: Provenance and Disambiguation for Chemical Data on the Biological Semantic Web

Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project. More details, together with a downloadable OWL file, are available at http://code.google.com/p/semanticchemistry/ (license: CC-BY-SA)

Identification and Genome-Wide Prediction of DNA Binding Specificities for the ApiAP2 Family of Regulators from the Malaria Parasite

The molecular mechanisms underlying transcriptional regulation in apicomplexan parasites remain poorly understood. Recently, the Apicomplexan AP2 (ApiAP2) family of DNA binding proteins was identified as a major class of transcriptional regulators that are found across all Apicomplexa. To gain insight into the regulatory role of these proteins in the malaria parasite, we have comprehensively surveyed the DNA-binding specificities of all 27 members of the ApiAP2 protein family from Plasmodium falciparum revealing unique binding preferences for the majority of these DNA binding proteins. In addition to high affinity primary motif interactions, we also observe interactions with secondary motifs. The ability of a number of ApiAP2 proteins to bind multiple, distinct motifs significantly increases the potential complexity of the transcriptional regulatory networks governed by the ApiAP2 family. Using these newly identified sequence motifs, we infer the trans-factors associated with previously reported plasmodial cis-elements and provide evidence that ApiAP2 proteins modulate key regulatory decisions at all stages of parasite development. Our results offer a detailed view of ApiAP2 DNA binding specificity and take the first step toward inferring comprehensive gene regulatory networks for P. falciparum