Prophylactic ranitidine treatment in critically ill children - a population pharmacokinetic study

Aims - To characterize the population pharmacokinetics of ranitidine in critically ill children and to determine the influence of various clinical and demographic factors on its disposition. Methods - Data were collected prospectively from 78 paediatric patients (n = 248 plasma samples) who received oral or intravenous ranitidine for prophylaxis against stress ulcers, gastrointestinal bleeding or the treatment of gastro-oesophageal reflux. Plasma samples were analysed using high-performance liquid chromatography, and the data were subjected to population pharmacokinetic analysis using nonlinear mixed-effects modelling. Results - A one-compartment model best described the plasma concentration profile, with an exponential structure for interindividual errors and a proportional structure for intra-individual error. After backward stepwise elimination, the final model showed a significant decrease in objective function value (−12.618; P < 0.001) compared with the weight-corrected base model. Final parameter estimates for the population were 32.1 l h−1 for total clearance and 285 l for volume of distribution, both allometrically modelled for a 70 kg adult. Final estimates for absorption rate constant and bioavailability were 1.31 h−1 and 27.5%, respectively. No significant relationship was found between age and weight-corrected ranitidine pharmacokinetic parameters in the final model, with the covariate for cardiac failure or surgery being shown to reduce clearance significantly by a factor of 0.46. Conclusions - Currently, ranitidine dose recommendations are based on children's weights. However, our findings suggest that a dosing scheme that takes into consideration both weight and cardiac failure/surgery would be more appropriate in order to avoid administration of higher or more frequent doses than necessary.

Hermite Polynomials and the Zero-Distribution of Riemann's Zeta Function

AMS Subject Classification 2010: 11M26, 33C45, 42A38.

Long-range, high bit-rate secure key distribution link utilizing Raman Ultra-long fiber laser (UFL)

The distribution of the secret key is the weakest link of many data encryption systems. Quantum key distribution (QKD) schemes provide attractive solutions [1], however their implementation remains challenging and their range and bit-rate are limited. Moreover, practical QKD systems, employ real-life components and are, therefore, vulnerable to diverse attack schemes [2]. Ultra-Long fiber lasers (UFLs) have been drawing much attention recently because of their fundamentally different properties compared to conventional lasers as well as their unique applications [3]. Here, we demonstrate a 100Bps, practically secure key distribution, over a 500km link, employing Raman gain UFL. Fig. 1(a) depicts a schematic of the UFL system. Each user has an identical set of two wavelength selective mirrors centered at l0 and l 1. In order to exchange a key-bit, each user independently choose one of these mirrors and introduces it as a laser reflector at their end. If both users choose identical mirrors, a clear signal develops and the bits in these cases are discarded. However if they choose complementary mirrors, (1, 0 or 0, 1 states), the UFL remains below lasing threshold and no signal evolves. In these cases, an eavesdropper can only detect noise and is unable to determine the mirror choice of the users, where the choice of mirrors represent a single key bit (e.g. Alice's choice of mirror is the key-bit). These bits are kept and added to the key. The absence of signal in the secure states faxilitates fast measurements to distinguish between the non-secure and the secure states and to determine the key-bit in the later case, Sequentially reapeating the single bit exchange protocol generate the entire keys of any desirable length. © 2013 IEEE.

Characterizations of Exponential Distribution via Conditional Expectations of Record Values

2000 Mathematics Subject Classification: 62G30, 62E10.

Characterizations of Exponential Distribution Based on Sample of Size Three

2010 Mathematics Subject Classification: 62G30, 62E10.

The Application of Fluorescent Nanocrystals to Study the Distribution of Neuropeptides in the Aedes Aegypti Mosquito

Semiconductor nanocrystals, also known as quantum dots (QDs), have been used in studies involving mice and human tissues, but never before in research on insects. We used QDs to study the distribution of two neuropeptides in the Aedes aegypti mosquito, the vector of both dengue and yellow fever. These neuropeptides play a significant role in the production of juvenile hormone, a hormone that controls biting behavior, metamorphosis, and reproduction throughout the life of the mosquito. The two neuropeptides allatostatin-C (AS-C) and allatotropin (AT) function as inhibitory (AS-C) and stimulatory (AT) regulators of juvenile hormone synthesis in the corpus allatum gland. In other insects, they also affect heart rate, gut movement, and nutrient uptake. Conjugating these neuropeptides to quantum dots via a streptavidinlbiotin link, we were able to expose the mosquito corpus allatum and abdomen to allatostatin-C and allatotropin and then to visualize their distribution under UV light using confocal and compound light microscopy. Histological sections of the whole mosquito, incubations of tissues with conjugates (in vitro), and microinjections of conjugates into the mosquito (in vivo) were performed. The results showed that quantum dots can be used to detect neuropeptide distribution in the mosquito. The more we understand about these neuropeptides and juvenile hormone, the more we can contribute to stopping the spread of infectious diseases, such as dengue and yellow fever.

Estimation of Inequality Indices of the Cumulative Distribution Function

Date of Acceptance: 02/03/2015

Cascade failure analysis of power grid using new load distribution law and node removal rule

The work is supported in part by NSFC (Grant no. 61172070), IRT of Shaanxi Province (2013KCT-04), EPSRC (Grant no.Ep/1032606/1).

The Effect of Selective Heart Rate Slowing in Heart Failure with Preserved Ejection Fraction

Acknowledgments Dr Ashrafian acknowledges support from the BHF Center of Research Excellence, Oxford, UK. The research was also supported by the National Institute for Health Research Oxford Biomedical Research Center Program and by the National Institute for Health Research Rare Diseases Translational Research Collaboration (NIHR RD-TRC)

Estimation of Inequality Indices of the Cumulative Distribution Function

Date of Acceptance: 02/03/2015

Cascade failure analysis of power grid using new load distribution law and node removal rule

The work is supported in part by NSFC (Grant no. 61172070), IRT of Shaanxi Province (2013KCT-04), EPSRC (Grant no.Ep/1032606/1).

The Effect of Selective Heart Rate Slowing in Heart Failure with Preserved Ejection Fraction

Acknowledgments Dr Ashrafian acknowledges support from the BHF Center of Research Excellence, Oxford, UK. The research was also supported by the National Institute for Health Research Oxford Biomedical Research Center Program and by the National Institute for Health Research Rare Diseases Translational Research Collaboration (NIHR RD-TRC)

An assessment of the influence of the industry distribution chain on the oxygen levels in commercial modified atmosphere packaged cheddar cheese using non-destructive oxygen sensor technology

The establishment and control of oxygen levels in packs of oxygen-sensitive food products such as cheese is imperative in order to maintain product quality over a determined shelf life. Oxygen sensors quantify oxygen concentrations within packaging using a reversible optical measurement process, and this non-destructive nature ensures the entire supply chain can be monitored and can assist in pinpointing negative issues pertaining to product packaging. This study was carried out in a commercial cheese packaging plant and involved the insertion of 768 sensors into 384 flow-wrapped cheese packs (two sensors per pack) that were flushed with 100% carbon dioxide prior to sealing. The cheese blocks were randomly assigned to two different storage groups to assess the effects of package quality, packaging process efficiency, and handling and distribution on package containment. Results demonstrated that oxygen levels increased in both experimental groups examined over the 30-day assessment period. The group subjected to a simulated industrial distribution route and handling procedures of commercial retailed cheese exhibited the highest level of oxygen detected on every day examined and experienced the highest rate of package failure. The study concluded that fluctuating storage conditions, product movement associated with distribution activities, and the possible presence of cheese-derived contaminants such as calcium lactate crystals were chief contributors to package failure.

Does the Pareto Distribution of Hurricane Damage Inherit its Fat Tail from a Zipf Distribution of Assets at Hazard?

Tropical Cyclones are a continuing threat to life and property. Willoughby (2012) found that a Pareto (power-law) cumulative distribution fitted to the most damaging 10% of US hurricane seasons fit their impacts well. Here, we find that damage follows a Pareto distribution because the assets at hazard follow a Zipf distribution, which can be thought of as a Pareto distribution with exponent 1. The Z-CAT model is an idealized hurricane catastrophe model that represents a coastline where populated places with Zipf- distributed assets are randomly scattered and damaged by virtual hurricanes with sizes and intensities generated through a Monte-Carlo process. Results produce realistic Pareto exponents. The ability of the Z-CAT model to simulate different climate scenarios allowed testing of sensitivities to Maximum Potential Intensity, landfall rates and building structure vulnerability. The Z-CAT model results demonstrate that a statistical significant difference in damage is found when only changes in the parameters create a doubling of damage.

THE DISTRIBUTION AND FUNCTION OF DENITRIFICATION GENES: EXPLORING AGRICULTURAL MANAGEMENT AND SOIL CHEMICAL IMPLICATIONS

Denitrification is a microbially-mediated process that converts nitrate (NO3-) to dinitrogen (N2) gas and has implications for soil fertility, climate change, and water quality. Using PCR, qPCR, and T-RFLP, the effects of environmental drivers and land management on the abundance and composition of functional genes were investigated. Environmental variables affecting gene abundance were soil type, soil depth, nitrogen concentrations, soil moisture, and pH, although each gene was unique in its spatial distribution and controlling factors. The inclusion of microbial variables, specifically genotype and gene abundance, improved denitrification models and highlights the benefit of including microbial data in modeling denitrification. Along with some evidence of niche selection, I show that nirS is a good predictor of denitrification enzyme activity (DEA) and N2O:N2 ratio, especially in alkaline and wetland soils. nirK was correlated to N2O production and became a stronger predictor of DEA in acidic soils, indicating that nirK and nirS are not ecologically redundant.