Integral-based filtering of continuous glucose sensor measurements for glycaemic control in critical care

Hyperglycaemia is prevalent in critical illness and increases the risk of further complications and mortality, while tight control can reduce mortality up to 43%. Adaptive control methods are capable of highly accurate, targeted blood glucose regulation using limited numbers of manual measurements due to patient discomfort and labour intensity. Therefore, the option to obtain greater data density using emerging continuous glucose sensing devices is attractive. However, the few such systems currently available can have errors in excess of 20-30%. In contrast, typical bedside testing kits have errors of approximately 7-10%. Despite greater measurement frequency larger errors significantly impact the resulting glucose and patient specific parameter estimates, and thus the control actions determined creating an important safety and performance issue. This paper models the impact of the continuous glucose monitoring system (CGMS, Medtronic, Northridge, CA) on model-based parameter identification and glucose prediction. An integral-based fitting and filtering method is developed to reduce the effect of these errors. A noise model is developed based on CGMS data reported in the literature, and is slightly conservative with a mean Clarke Error Grid (CEG) correlation of R=0.81 (range: 0.68-0.88) as compared to a reported value of R=0.82 in a critical care study. Using 17 virtual patient profiles developed from retrospective clinical data, this noise model was used to test the methods developed. Monte-Carlo simulation for each patient resulted in an average absolute 1-h glucose prediction error of 6.20% (range: 4.97-8.06%) with an average standard deviation per patient of 5.22% (range: 3.26-8.55%). Note that all the methods and results are generalizable to similar applications outside of critical care, such as less acute wards and eventually ambulatory individuals. Clinically, the results show one possible computational method for managing the larger errors encountered in emerging continuous blood glucose sensors, thus enabling their more effective use in clinical glucose regulation studies.     

Sterol and steryl ester regulation of phospholipase A2 from the mosquito parasiteLagenidium giganteum

Lagenidium giganteum, a facultative parasite of mosquito larvae, cannot synthesize sterols, and requires an exogenous source of these lipids in order to enter its reproductive cycle. This parasite grows vegetatively in the absence of sterols, but requires cholesterol or structurally related compounds to produce motile zoospores, which are the only stage capable of infecting mosquitoes. Sterols structurally related to cholesterol and some steryl esters inhibited the activity ofL. giganteum phospholipase A₂ (PLA₂), an enzyme that hydrolyzes fatty acids from thesn-2 position of glycerophospholipids. Sterols that induce reproduction inhibitedL. giganteum PLA₂ activity, while sterols and steroids that do not support sporulation had minimal effect. Most steryl esters had no effect on enzyme activity, but cholesteryl arachidonate (CA) was a potent inhibitor of parasite PLA₂. Not all enzymes partly purified using a DEAE-Sephacel column were affected by these lipids, demonstrating selective inhibition of specific enzymes. Potency was enhanced by up to several orders of magnitude if epoxy fatty acids were esterified to the cholesterol nucleus. The steryl ester pool was dynamic during morphogenesis, and the fatty acid composition of the steryl esters did not mimic total cell or membrane (glycerophospholipid) fatty acid composition asL. giganteum proceeded through its growth cycle. Synthesis of CA and monoepoxy CA by the parasite was confirmed using electrospray mass spectrometry and collision-induced dissociation. Steryl derivatives selectively inhibited PLA₂ enzymes from bovine pancreas, snake venom, and human cytoplasmic 85-kDa PLA₂.     

Mentoring, Modeling, and Money: The 3 Ms of Producing Academics.

The program at Lehigh University has been very successful in producing a high percentage of students (42% of all graduates) who have entered academic careers as trainers of school psychologists. This article presents a conceptual model for the three variables that are considered as critical components of why students select an academic career--mentoring, modeling, and money. Results of a survey of the program alumni at Lehigh University are presented. Outcomes of the survey showed significant and substantial differences in the perceptions of the mentoring and modeling process by students who are in academic versus nonacademic careers. Implications for doctoral training programs interested in training students to enter academic careers are discussed. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Effectiveness of traffic light vs. boom barrier controls at road–rail level crossings: A simulator study

Although collisions at level crossings are relatively uncommon occurrences, the potential severity of their consequences make them a top priority among safety authorities. Twenty-five fully-licensed drivers aged between 20 and 50 years participated in a driving simulator study that compared the efficacy, and drivers’ subjective perception, of two active level crossing traffic control devices: flashing lights with boom barriers and standard traffic lights. Because of its common usage in most states in Australia, a stop sign-controlled level crossing served as the passive referent. Although crossing violations were less likely at the level crossings controlled by active devices than at those controlled by stop signs, both kinds of active control were associated with a similar number of violations. Further, the majority (72%) of drivers reported preferring flashing lights to traffic lights. Collectively, results indicate that the installation of traffic lights at real-world level crossings would not be likely to offer safety benefits over and above those provided already by flashing lights with boom barriers. Furthermore, the high rate of violations at passively controlled crossings strongly supports the continued practice of upgrading level crossings with active traffic control devices.     

Extraction of Algal Lipids and Their Analysis by HPLC and Mass Spectrometry

Algae are a promising source of biofuel but claims about their lipid content can be ambiguous because extraction methods vary and lipid quantitation often does not distinguish between particular lipid classes. Here we compared methods for the extraction of algal lipids and showed that 2-ethoxyethanol (2-EE) provides superior lipid recovery (>150–200 %) compared to other common extraction solvents such as chloroform:methanol or hexane. Extractions of wet and dry algal biomass showed that 2-EE was more effective at extracting lipids from wet rather than dried algal pellets. To analyze lipid content we used normal-phase HPLC with parallel quantitation by an evaporative light scattering detector and a mass spectrometer. Analysis of crude lipid extracts showed that all major lipid classes could be identified and quantified and revealed a surprisingly large amount of saturated hydrocarbons (HC). This HC fraction was isolated from extracts of bioreactor-grown algae and further analyzed by HPLC/MS, NMR, and GC/MS. The results showed that the sample consisted of a mixture of saturated, straight- and branched-chain HC of different chain lengths. These algal HC could represent an alternative biofuel to triacylglycerols (TAG) that could feed directly into the current petroleum infrastructure.     

Changes in bioactive compounds and antioxidant activity during convective drying of murta (Ugni molinae T.) berries

Murta (Ugni molinae T.) berries were air‐dried at five temperatures (40, 50, 60, 70 and 80 °C), and the changes in β‐carotene, phenolic acids, total phenolic and flavonoid contents and antioxidant capacities (DPPH and ORAC) were investigated. The berries showed a high content of β‐carotene, which decreased during drying temperature between 40 °C and 80 °C. Free and bound phenolic acids were also determined, showing gallic acid to be the prevalent phenolic acid. Total phenolic and flavonoid contents in the dried berries showed a higher decrease at lower temperature due to longer drying time. The radical‐scavenging activity also showed higher antioxidant activity at higher drying temperatures (70–80 °C) than at lower drying temperatures (40–50 °C). Total phenolic content (TPC) and flavonoids showed good correlation with antioxidant capacity. Murta berries proved to be an excellent source of antioxidants and bioactive compounds and are therefore a potential ingredient for new functional food products.