Chemical composition of essential oil of exudates of Dryobalanops aromatica

Purpose: To identify the chemical composition of essential oil from the exudates of Dryobalanops aromatica from Malaysia.Methods: Exudate was collected from D. aromatica and subjected to fractional  distillation to obtain essential oil. Gas chromatography-mass spectrometry  (GC-MS) was used to characterize the composition of the isolated essential oil.Results: The yield of essential oil was 7.58 %, with the highest yield (3.24 %) within the first 2 h of fractional distillation. Thirty compounds which accounted for 97.56 % of essential oil composition were identified. These include sesquiterpenes (46.87 %), monoterpenes (31.05 %), oxygenated monoterpenes (16.76 %) and oxygenated  sesquiterpenes (2.13 %). Borneol accounted for 0.74 % of the essential oil.Conclusion: Essential oil from the exudates of D. aromatica contains terpenoid  compounds and borneol.Keywords: Dryobalanops aromatica, exudate, fractional distillation, essential oil, GS-MS, borneo

Determination of borneol and other chemical compounds of essential oil of Dryobalanops aromatica exudate from Malaysia

Purpose: To determine borneol and other chemical compounds of essential oil derived from the exudate of Dryobalanops aromatica in Malaysia.Methods: Exudate was collected from D. aromatica and subjected to fractional distillation to obtain essential oil. Gas chromatography-mass spectrometry (GC-MS) was performed to characterize the composition of the isolated essential oil.Results: Essential oil (7.58 %) was obtained with the highest yield (3.24 %) in the first 2 h of fractional distillation. Thirty compounds which accounted for 97.56 % of total essential oil composition were identified by GC-MS, and they include sesquiterpenes (46.87 %), monoterpenes (31.05 %), oxygenated monoterpenes (16.76 %) and oxygenated sesquiterpenes (2.13 %). Borneol (0.74 %) was also detected in the essential oil.Conclusion: Borneol and other terpenoid compounds are present in the essential oil of the exudate of D. aromatica.Keywords: Exudate, Dryobalanops Aromatica, Fractional distillation, Essential oil, Gaschromatography-mass spectrometry, Borneo

Pilot proof of concept clinical trials of Stochastic Targeted (STAR) glycemic control

ABSTRACT: INTRODUCTION: Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. STAR (Stochastic TARgeted) is a flexible, model-based TGC approach directly accounting for intra- and inter- patient variability with a stochastically derived maximum 5% risk of blood glucose (BG) /=3 days. Written informed consent was obtained for all patients, and approval was granted by the NZ Upper South A Regional Ethics Committee. RESULTS: A total of 402 measurements were taken over 660 hours (~14/day), because nurses showed a preference for 2-hourly measurements. Median [interquartile range, (IQR)] cohort BG was 5.9 mmol/L [5.2-6.8]. Overall, 63.2%, 75.9%, and 89.8% of measurements were in the 4.0-6.5, 4.0-7.0, and 4.0-8.0 mmol/L bands. There were no hypoglycemic events (BG < 2.2 mmol/L), and the minimum BG was 3.5 mmol/L with 4.5% < 4.4 mmol/L. Per patient, the median [IQR] hours of TGC was 92 h [29-113] using 53 [19-62] measurements (median, ~13/day). Median [IQR] results: BG, 5.9 mmol/L [5.8-6.3]; carbohydrate nutrition, 6.8 g/h [5.5-8.7] (~70% goal feed median); insulin, 2.5 U/h [0.1-5.1]. All patients achieved BG < 6.1 mmol/L. These results match or exceed SPRINT and clinical workload is reduced more than 20%. CONCLUSIONS: STAR TGC modulating insulin and nutrition inputs provided very tight control with minimal variability by managing intra- and inter- patient variability. Performance and safety exceed that of SPRINT, which reduced mortality and cost in the Christchurch ICU. The use of glucometers did not appear to impact the quality of TGC. Finally, clinical workload was self-managed and reduced 20% compared with SPRINT

Genome-Wide Association Study Identifies Novel Restless Legs Syndrome Susceptibility Loci on 2p14 and 16q12.1

Peer reviewe

Black holes, gravitational waves and fundamental physics: a roadmap

The grand challenges of contemporary fundamental physics—dark matter, dark energy, vacuum energy, inflation and early universe cosmology, singularities and the hierarchy problem—all involve gravity as a key component. And of all gravitational phenomena, black holes stand out in their elegant simplicity, while harbouring some of the most remarkable predictions of General Relativity: event horizons, singularities and ergoregions. The hitherto invisible landscape of the gravitational Universe is being unveiled before our eyes: the historical direct detection of gravitational waves by the LIGO-Virgo collaboration marks the dawn of a new era of scientific exploration. Gravitational-wave astronomy will allow us to test models of black hole formation, growth and evolution, as well as models of gravitational-wave generation and propagation. It will provide evidence for event horizons and ergoregions, test the theory of General Relativity itself, and may reveal the existence of new fundamental fields. The synthesis of these results has the potential to radically reshape our understanding of the cosmos and of the laws of Nature. The purpose of this work is to present a concise, yet comprehensive overview of the state of the art in the relevant fields of research, summarize important open problems, and lay out a roadmap for future progress. This write-up is an initiative taken within the framework of the European Action on 'Black holes, Gravitational waves and Fundamental Physics'

Interface Design and Human Factors Consideration for Model-Based Tight Glycemic Control in Critical Care

Introduction: Tight glycemic control (TGC) has shown benefits but has been difficult to implement. Model-based methods and computerized protocols offer the opportunity to improve TGC quality and compliance. This research presents an interface design to maximize compliance, minimize real and perceived clinical effort, and minimize error based on simple human factors and end user input. Method: The graphical user interface (GUI) design is presented by construction based on a series of simple, short design criteria based on fundamental human factors engineering and includes the use of user feedback and focus groups comprising nursing staff at Christchurch Hospital. The overall design maximizes ease of use and minimizes (unnecessary) interaction and use. It is coupled to a protocol that allows nurse staff to select measurement intervals and thus self-manage workload. Results: The overall GUI design is presented and requires only one data entry point per intervention cycle. The design and main interface are heavily focused on the nurse end users who are the predominant users, while additional detailed and longitudinal data, which are of interest to doctors guiding overall patient care, are available via tabs. This dichotomy of needs and interests based on the end user’s immediate focus and goals shows how interfaces must adapt to offer different information to multiple types of users. Conclusions: The interface is designed to minimize real and perceived clinical effort, and ongoing pilot trials have reported high levels of acceptance. The overall design principles, approach, and testing methods are based on fundamental human factors principles designed to reduce user effort and error and are readily generalizable

Data Entry Errors and Design for Model-Based Tight Glycemic Control in Critical Care

Introduction: Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. Model-based methods and computerized protocols offer the opportunity to improve TGC quality but require human data entry, particularly of blood glucose (BG) values, which can be significantly prone to error. This study presents the design and optimization of data entry methods to minimize error for a computerized and model-based TGC method prior to pilot clinical trials. Method: To minimize data entry error, two tests were carried out to optimize a method with errors less than the 5%-plus reported in other studies. Four initial methods were tested on 40 subjects in random order, and the best two were tested more rigorously on 34 subjects. The tests measured entry speed and accuracy. Errors were reported as corrected and uncorrected errors, with the sum comprising a total error rate. The first set of tests used randomly selected values, while the second set used the same values for all subjects to allow comparisons across users and direct assessment of the magnitude of errors. These research tests were approved by the University of Canterbury Ethics Committee. Results: The final data entry method tested reduced errors to less than 1–2%, a 60–80% reduction from reported values. The magnitude of errors was clinically significant and was typically by 10.0 mmol/liter or an order of magnitude but only for extreme values of BG 15.0–20.0 mmol/liter, both of which could be easily corrected with automated checking of extreme values for safety. Conclusions: The data entry method selected significantly reduced data entry errors in the limited design tests presented, and is in use on a clinical pilot TGC study. The overall approach and testing methods are easily performed and generalizable to other applications and protocols

Stochastic Targeted (STAR) Glycemic Control - Design, Safety and Performance

INTRODUCTION: Tight glycemic control (TGC) has shown benefits but has been difficult to achieve consistently. STAR (Stochastic TARgeted) is a flexible, model-based TGC approach that directly accounts for intra- and interpatient variability with a stochastically derived maximum 5% risk of blood glucose (BG) below 72 mg/dl. This research assesses the safety, efficacy, and clinical burden of a STAR TGC controller modulating both insulin and nutrition inputs in virtual and clinical pilot trials. METHODS: Clinically validated virtual trials using data from 370 patients in the SPRINT (Specialized Relative Insulin and Nutrition Titration) study were used to design the STAR protocol and test its safety, performance, and required clinical effort prior to clinical pilot trials. Insulin and nutrition interventions were given every 1–3 h as chosen by the nurse to allow them to manage workload. Interventions were designed to maximize the overlap of the model-predicted (5–95(th) percentile) range of BG outcomes with the 72–117 mg/dl band and thus provide a maximum 5% risk of BG <72 mg/dl. Interventions were calculated using clinically validated computer models of human metabolism and its variability in critical illness. Carbohydrate intake (all sources) was selected to maximize intake up to 100% of the American College of Chest Physicians/Society of Critical Care Medicine (ACCP/SCCM) goal (25 kg/kcal/h). Insulin doses were limited (8 U/h maximum), with limited increases based on current rate (0.5–2.0 U/h). Initial clinical pilot trials involved 3 patients covering ∼450 h. Approval was granted by the Upper South A Regional Ethics Committee. RESULTS: Virtual trials indicate that STAR provides similar glycemic control performance to SPRINT with 2–3 h (maximum) measurement intervals. Time in the 72–126 mg/dl and 72–145 mg/dl bands was equivalent for all controllers, indicating that glycemic outcome differences between protocols were only shifted in this range. Safety from hypoglycemia was improved. Importantly, STAR using 2–3 h (maximum) intervention intervals reduced clinical burden up to 30%, which is clinically very significant. Initial clinical trials showed glycemic performance, safety, and management of inter- and intrapatient variability that matched or exceeded the virtual trial results. CONCLUSIONS: In virtual trials, STAR TGC provided tight control that maximized the likelihood of BG in a clinically specified glycemic band and reduced hypoglycemia with a maximum 5% (or lower) expected risk of light hypoglycemia (BG <72 mg/dl) via model-based management of intra- and interpatient variability. Clinical workload was self-managed and reduced up to 30% compared with SPRINT. Initial pilot clinical trials matched or exceeded these virtual results