Potassium canrenoate treatment in paediatric patients:a population pharmacokinetic study using novel dried blood spot sampling

Objective: To characterize the population pharmacokinetics of canrenone following administration of potassium canrenoate (K-canrenoate) in paediatric patients. Methods: Data were collected prospectively from 37 paediatric patients (median weight 2.9 kg, age range 2 days–0.85 years) who received intravenous K-canrenoate for management of retained fluids, for example in heart failure and chronic lung disease. Dried blood spot (DBS) samples (n = 213) from these were analysed for canrenone content and the data subjected to pharmacokinetic analysis using nonlinear mixed-effects modelling. Another group of patients (n = 16) who had 71 matching plasma and DBS samples was analysed separately to compare canrenone pharmacokinetic parameters obtained using the two different matrices. Results: A one-compartment model best described the DBS data. Significant covariates were weight, postmenstrual age (PMA) and gestational age. The final population models for canrenone clearance (CL/F) and volume of distribution (V/F) in DBS were CL/F (l/h) = 12.86 ×  (WT/70.0)0.75 × e [0.066 ×  (PMA - 40]) and V/F (l) = 603.30 ×  (WT/70) × (GA/40)1.89 where weight is in kilograms. The corresponding values of CL/F and V/F in a patient with a median weight of 2.9 kg are 1.11 l/h and 20.48 l, respectively. Estimated half-life of canrenone based on DBS concentrations was similar to that based on matched plasma concentrations (19.99 and 19.37 h, respectively, in 70 kg patient). Conclusion: The range of estimated CL/F in DBS for the study population was 0.12–9.62 l/h; hence, bodyweight-based dosage adjustment of K-canrenoate appears necessary. However, a dosing scheme that takes into consideration both weight and age (PMA/gestational age) of paediatric patients seems more appropriate.

Immunoblotting and tear sampling techniques for the study of contact lens-induced variations in tear protein profiles

More information on the biochemical interactions taking place between the tear film and the contact lens is required to further our understanding of the causative mechanisms behind the symptoms of dryness and grittiness often experienced by contact lens wearers. These symptoms can often lead to an intolerance to contact lens wear.

Incremental tensor biased discriminant analysis:a new color-based visual tracking method

Most existing color-based tracking algorithms utilize the statistical color information of the object as the tracking clues, without maintaining the spatial structure within a single chromatic image. Recently, the researches on the multilinear algebra provide the possibility to hold the spatial structural relationship in a representation of the image ensembles. In this paper, a third-order color tensor is constructed to represent the object to be tracked. Considering the influence of the environment changing on the tracking, the biased discriminant analysis (BDA) is extended to the tensor biased discriminant analysis (TBDA) for distinguishing the object from the background. At the same time, an incremental scheme for the TBDA is developed for the tensor biased discriminant subspace online learning, which can be used to adapt to the appearance variant of both the object and background. The experimental results show that the proposed method can track objects precisely undergoing large pose, scale and lighting changes, as well as partial occlusion. © 2009 Elsevier B.V.

How good are citizen weather stations? Addressing a biased opinion

The UK is home to a dense network of Citizen Weather Stations (CWS) primarily set up by members of the public. The majority of these stations record air temperature, relative humidity and precipitation, amongst other variables, at sub-hourly intervals. This high resolution network could have benefits in many applications, but only if the data quality is well characterised. Here we present results from an intercomparison field study, in which popular CWS models were tested against Met Office standard equipment. The study identifies some common instrumental biases and their dependencies, which will help us to quantify and correct such biases from the CWS network.

Consumers’ biased perceptions of the environmental impact of products, and their influence on advertising efficiency

This paper investigates the main perceptual biases developed by consumers regarding the environmental impact of products. It shows that these biases make consumers unable to distinguish between advertisements for highly versus less sustainable products, but that the inclusion of relevant information can increase the efficiency of arguments for true sustainability.

Accuracy and optimal sampling in Monte Carlo solution of population balance equations

Implementation of a Monte Carlo simulation for the solution of population balance equations (PBEs) requires choice of initial sample number (N0), number of replicates (M), and number of bins for probability distribution reconstruction (n). It is found that Squared Hellinger Distance, H2, is a useful measurement of the accuracy of Monte Carlo (MC) simulation, and can be related directly to N0, M, and n. Asymptotic approximations of H2 are deduced and tested for both one-dimensional (1-D) and 2-D PBEs with coalescence. The central processing unit (CPU) cost, C, is found in a power-law relationship, C= aMNb0, with the CPU cost index, b, indicating the weighting of N0 in the total CPU cost. n must be chosen to balance accuracy and resolution. For fixed n, M × N0 determines the accuracy of MC prediction; if b > 1, then the optimal solution strategy uses multiple replications and small sample size. Conversely, if 0 < b < 1, one replicate and a large initial sample size is preferred. © 2015 American Institute of Chemical Engineers AIChE J, 61: 2394–2402, 2015

A hydrogen-bonded polar network in the core of the glucagon-like peptide-1 receptor is a fulcrum for biased agonism:lessons from class B crystal structuress

The glucagon-like peptide 1 (GLP-1) receptor is a class B G protein-coupled receptor (GPCR) that is a key target for treatments for type II diabetes and obesity. This receptor, like other class B GPCRs, displays biased agonism, though the physiologic significance of this is yet to be elucidated. Previous work has implicated R2.60190 , N3.43240 , Q7.49394 , and H6.52363 as key residues involved in peptide-mediated biased agonism, with R2.60190 , N3.43240 , and Q7.49394 predicted to form a polar interaction network. In this study, we used novel insight gained from recent crystal structures of the transmembrane domains of the glucagon and corticotropin releasing factor 1 (CRF1) receptors to develop improved models of the GLP-1 receptor that predict additional key molecular interactions with these amino acids. We have introduced E6.53364 A, N3.43240 Q, Q7.49493N, and N3.43240 Q/Q7.49 Q/Q7.49493N mutations to probe the role of predicted H-bonding and charge-charge interactions in driving cAMP, calcium, or extracellular signal-regulated kinase (ERK) signaling. A polar interaction between E6.53364 and R2.60190 was predicted to be important for GLP-1- and exendin-4-, but not oxyntomodulin-mediated cAMP formation and also ERK1/2 phosphorylation. In contrast, Q7.49394 , but not R2.60190 /E6.53364 was critical for calcium mobilization for all three peptides. Mutation of N3.43240 and Q7.49394 had differential effects on individual peptides, providing evidence for molecular differences in activation transition. Collectively, this work expands our understanding of peptide-mediated signaling from the GLP-1 receptor and the key role that the central polar network plays in these events.

The extracellular surface of the GLP-1 receptor is a molecular trigger for biased agonism

Ligand-directed signal bias offers opportunities for sculpting molecular events, with the promise of better, safer therapeutics. Critical to the exploitation of signal bias is an understanding of the molecular events coupling ligand binding to intracellular signaling. Activation of class B G protein-coupled receptors is driven by interaction of the peptide N terminus with the receptor core. To understand how this drives signaling, we have used advanced analytical methods that enable separation of effects on pathway-specific signaling from those that modify agonist affinity and mapped the functional consequence of receptor modification onto three-dimensional models of a receptor-ligand complex. This yields molecular insights into the initiation of receptor activation and the mechanistic basis for biased agonism. Our data reveal that peptide agonists can engage different elements of the receptor extracellular face to achieve effector coupling and biased signaling providing a foundation for rational design of biased agonists.

Hybrid sampling on mutual information entropy-based clustering ensembles for optimizations

In this paper, we focus on the design of bivariate EDAs for discrete optimization problems and propose a new approach named HSMIEC. While the current EDAs require much time in the statistical learning process as the relationships among the variables are too complicated, we employ the Selfish gene theory (SG) in this approach, as well as a Mutual Information and Entropy based Cluster (MIEC) model is also set to optimize the probability distribution of the virtual population. This model uses a hybrid sampling method by considering both the clustering accuracy and clustering diversity and an incremental learning and resample scheme is also set to optimize the parameters of the correlations of the variables. Compared with several benchmark problems, our experimental results demonstrate that HSMIEC often performs better than some other EDAs, such as BMDA, COMIT, MIMIC and ECGA. © 2009 Elsevier B.V. All rights reserved.

The development of an automated nano sampling handling system for nanometre protein crystallography experiments

As the world's synchrotrons and X-FELs endeavour to meet the need to analyse ever-smaller protein crystals, there grows a requirement for a new technique to present nano-dimensional samples to the beam for X-ray diffraction experiments.The work presented here details developmental work to reconfigure the nano tweezer technology developed by Optofluidics (PA, USA) for the trapping of nano dimensional protein crystals for X-ray crystallography experiments. The system in its standard configuration is used to trap nano particles for optical microscopy. It uses silicon nitride laser waveguides that bridge a micro fluidic channel. These waveguides contain 180 nm apertures of enabling the system to use biologically compatible 1.6 micron wavelength laser light to trap nano dimensional biological samples. Using conventional laser tweezers, the wavelength required to trap such nano dimensional samples would destroy them. The system in its optical configuration has trapped protein molecules as small as 10 nanometres.

The development of an automated nano sampling handling system for nanometne protein crystallography experiments

As the world's synchrotrons and X-FELs endeavour to meet the need to analyse ever-smaller protein crystals, there grows a requirement for a new technique to present nano-dimensional samples to the beam for X-ray diffraction experiments.The work presented here details developmental work to reconfigure the nano tweezer technology developed by Optofluidics (PA, USA) for the trapping of nano dimensional protein crystals for X-ray crystallography experiments. The system in its standard configuration is used to trap nano particles for optical microscopy. It uses silicon nitride laser waveguides that bridge a micro fluidic channel. These waveguides contain 180 nm apertures of enabling the system to use biologically compatible 1.6 micron wavelength laser light to trap nano dimensional biological samples. Using conventional laser tweezers, the wavelength required to trap such nano dimensional samples would destroy them. The system in its optical configuration has trapped protein molecules as small as 10 nanometres.