Perioperative medication management: expanding the role of the preadmission clinic pharmacist in a single centre, randomised controlled trial of collaborative prescribing

Objectives Current evidence to support non-medical prescribing is predominantly qualitative, with little evaluation of accuracy, safety and appropriateness. Our aim was to evaluate a new model of service for the Australia healthcare system, of inpatient medication prescribing by a pharmacist in an elective surgery preadmission clinic (PAC) against usual care, using an endorsed performance framework. Design Single centre, randomised controlled, two-arm trial. Setting Elective surgery PAC in a Brisbane-based tertiary hospital. Participants 400 adults scheduled for elective surgery were randomised to intervention or control. Intervention A pharmacist generated the inpatient medication chart to reflect the patient's regular medication, made a plan for medication perioperatively and prescribed venous thromboembolism (VTE) prophylaxis. In the control arm, the medication chart was generated by the Resident Medical Officers. Outcome measures Primary outcome was frequency of omissions and prescribing errors when compared against the medication history. The clinical significance of omissions was also analysed. Secondary outcome was appropriateness of VTE prophylaxis prescribing. Results There were significantly less unintended omissions of medications: 11 of 887 (1.2%) intervention orders compared with 383 of 1217 (31.5%) control (p<0.001). There were significantly less prescribing errors involving selection of drug, dose or frequency: 2 in 857 (0.2%) intervention orders compared with 51 in 807 (6.3%) control (p<0.001). Orders with at least one component of the prescription missing, incorrect or unclear occurred in 208 of 904 (23%) intervention orders and 445 of 1034 (43%) controls (p<0.001). VTE prophylaxis on admission to the ward was appropriate in 93% of intervention patients and 90% controls (p=0.29). Conclusions Medication charts in the intervention arm contained fewer clinically significant omissions, and prescribing errors, when compared with controls. There was no difference in appropriateness of VTE prophylaxis on admission between the two groups.

Modelling for the electricity distribution network

Global awareness for cleaner and renewable energy is transforming the electricity sector at many levels. New technologies are being increasingly integrated into the electricity grid at high, medium and low voltage levels, new taxes on carbon emissions are being introduced and individuals can now produce electricity, mainly through rooftop photovoltaic (PV) systems. While leading to improvements, these changes also introduce challenges, and a question that often rises is ‘how can we manage this constantly evolving grid?’ The Queensland Government and Ergon Energy, one of the two Queensland distribution companies, have partnered with some Australian and German universities on a project to answer this question in a holistic manner. The project investigates the impact the integration of renewables and other new technologies has on the physical structure of the grid, and how this evolving system can be managed in a sustainable and economical manner. To aid understanding of what the future might bring, a software platform has been developed that integrates two modelling techniques: agent-based modelling (ABM) to capture the characteristics of the different system units accurately and dynamically, and particle swarm optimization (PSO) to find the most economical mix of network extension and integration of distributed generation over long periods of time. Using data from Ergon Energy, two types of networks (3 phase, and Single Wired Earth Return or SWER) have been modelled; three-phase networks are usually used in dense networks such as urban areas, while SWER networks are widely used in rural Queensland. Simulations can be performed on these networks to identify the required upgrades, following a three-step process: a) what is already in place and how it performs under current and future loads, b) what can be done to manage it and plan the future grid and c) how these upgrades/new installations will perform over time. The number of small-scale distributed generators, e.g. PV and battery, is now sufficient (and expected to increase) to impact the operation of the grid, which in turn needs to be considered by the distribution network manager when planning for upgrades and/or installations to stay within regulatory limits. Different scenarios can be simulated, with different levels of distributed generation, in-place as well as expected, so that a large number of options can be assessed (Step a). Once the location, sizing and timing of assets upgrade and/or installation are found using optimisation techniques (Step b), it is possible to assess the adequacy of their daily performance using agent-based modelling (Step c). One distinguishing feature of this software is that it is possible to analyse a whole area at once, while still having a tailored solution for each of the sub-areas. To illustrate this, using the impact of battery and PV can have on the two types of networks mentioned above, three design conditions can be identified (amongst others): · Urban conditions o Feeders that have a low take-up of solar generators, may benefit from adding solar panels o Feeders that need voltage support at specific times, may be assisted by installing batteries · Rural conditions - SWER network o Feeders that need voltage support as well as peak lopping may benefit from both battery and solar panel installations. This small example demonstrates that no single solution can be applied across all three areas, and there is a need to be selective in which one is applied to each branch of the network. This is currently the function of the engineer who can define various scenarios against a configuration, test them and iterate towards an appropriate solution. Future work will focus on increasing the level of automation in identifying areas where particular solutions are applicable.

Alcohol ingestion impairs maximal post-exercise rates of myofibrillar protein synthesis following a single bout of concurrent training

Introduction The culture in many team sports involves consumption of large amounts of alcohol after training/competition. The effect of such a practice on recovery processes underlying protein turnover in human skeletal muscle are unknown. We determined the effect of alcohol intake on rates of myofibrillar protein synthesis (MPS) following strenuous exercise with carbohydrate (CHO) or protein ingestion. Methods In a randomized cross-over design, 8 physically active males completed three experimental trials comprising resistance exercise (8×5 reps leg extension, 80% 1 repetition maximum) followed by continuous (30 min, 63% peak power output (PPO)) and high intensity interval (10×30 s, 110% PPO) cycling. Immediately, and 4 h post-exercise, subjects consumed either 500 mL of whey protein (25 g; PRO), alcohol (1.5 g·kg body mass−1, 12±2 standard drinks) co-ingested with protein (ALC-PRO), or an energy-matched quantity of carbohydrate also with alcohol (25 g maltodextrin; ALC-CHO). Subjects also consumed a CHO meal (1.5 g CHO·kg body mass−1) 2 h post-exercise. Muscle biopsies were taken at rest, 2 and 8 h post-exercise. Results Blood alcohol concentration was elevated above baseline with ALC-CHO and ALC-PRO throughout recovery (P<0.05). Phosphorylation of mTORSer2448 2 h after exercise was higher with PRO compared to ALC-PRO and ALC-CHO (P<0.05), while p70S6K phosphorylation was higher 2 h post-exercise with ALC-PRO and PRO compared to ALC-CHO (P<0.05). Rates of MPS increased above rest for all conditions (~29–109%, P<0.05). However, compared to PRO, there was a hierarchical reduction in MPS with ALC-PRO (24%, P<0.05) and with ALC-CHO (37%, P<0.05). Conclusion We provide novel data demonstrating that alcohol consumption reduces rates of MPS following a bout of concurrent exercise, even when co-ingested with protein. We conclude that alcohol ingestion suppresses the anabolic response in skeletal muscle and may therefore impair recovery and adaptation to training and/or subsequent performance.

From single crystal surfaces to single atoms : investigating active sites in electrocatalysis

Electrocatalytic processes will undoubtedly be at the heart of energising future transportation and technology with the added importance of being able to create the necessary fuels required to do so in an environmentally friendly and cost effective manner. For this to be successful two almost mutually exclusive surface properties need to be reconciled, namely producing highly active/reactive surface sites that exhibit long term stability. This article reviews the various approaches which have been undertaken to study the elusive nature of these active sites on metal surfaces which are considered as adatoms or clusters of adatoms with low coordination number. This includes the pioneering studies at extended well defined stepped single crystal surfaces using cyclic voltammetry up to the highly sophisticated in situ electrochemical imaging techniques used to study chemically synthesised nanomaterials. By combining the information attained from single crystal surfaces, individual nanoparticles of defined size and shape, density functional theory calculations and new concepts such as mesoporous multimetallic thin films and single atom electrocatalysts new insights into the design and fabrication of materials with highly active but stable active sites can be achieved. The area of electrocatalysis is therefore not only a fascinating and exciting field in terms of realistic technological and economical benefits but also from the fundamental understanding that can be acquired by studying such an array of interesting materials.

Maximum loadability achievement in SWER networks using optimal sizing and locating of batteries

This paper presents an optimisation algorithm to maximize the loadability of single wire earth return (SWER) by minimizing the cost of batteries and regulators considering the voltage constraints and thermal limits. This algorithm, that finds the optimum location of batteries and regulators, uses hybrid discrete particle swarm optimization and mutation (DPSO + Mutation). The simulation results on realistic highly loaded SWER network show the effectiveness of using battery to improve the loadability of SWER network in a cost-effective way. In this case, while only 61% of peak load can be supplied without violating the constraints by existing network, the loadability of the network is increased to peak load by utilizing two battery sites which are located optimally. That is, in a SWER system like the studied one, each installed kVA of batteries, optimally located, supports a loadability increase as 2 kVA.

A modified particle swarm optimization for correlated phenomena

The wide applicability of correlation analysis inspired the development of this paper. In this paper, a new correlated modified particle swarm optimization (COM-PSO) is developed. The Correlation Adjustment algorithm is proposed to recover the correlation between the considered variables of all particles at each of iterations. It is shown that the best solution, the mean and standard deviation of the solutions over the multiple runs as well as the convergence speed were improved when the correlation between the variables was increased. However, for some rotated benchmark function, the contrary results are obtained. Moreover, the best solution, the mean and standard deviation of the solutions are improved when the number of correlated variables of the benchmark functions is increased. The results of simulations and convergence performance are compared with the original PSO. The improvement of results, the convergence speed, and the ability to simulate the correlated phenomena by the proposed COM-PSO are discussed by the experimental results.

Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO)

This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

Raising Children in Single-Parent Families

Children from single-parent families fare more poorly on multiple outcomes than those in two-parent families. Most explanations for these differences assume that compromised parenting and parent mental health play a central role. This chapter explores the contribution of a range of factors to the parenting and mental health of single mothers using data from approximately 1000 Australian single mothers with a child aged 4–5 or 8–9 years. The findings show that single mothers are more likely than couple mothers to experience parenting and mental health difficulties; however, they also face heightened adversity in their home and extra-familial environments. Importantly, this comparison of single and couple mothers facing similar levels of adversity shows no difference in poor parenting practices, although single mothers remain more vulnerable to psychological distress. These findings have policy implications since they challenge the prevailing view that single-parent families inherently provide sub-optimal environments for raising children.

Direct lipid profiling of single cells from inkjet printed microarrays

The on-demand printing of living cells using inkjet technologies has recently been demonstrated and allows for the controlled deposition of cells in microarrays. Here, we show that such arrays can be interrogated directly by robot-controlled liquid microextraction coupled with chip-based nanoelectospray mass spectrometry. Such automated analyses generate a profile of abundant membrane lipids that are characteristic of cell type. Significantly, the spatial control in both deposition and extraction steps combined with the sensitivity of the mass spectrometric detection allows for robust molecular profiling of individual cells. © 2012 American Chemical Society.

Analysis of strain-rate dependent mechanical behavior of single chondrocyte : a finite element study

Various studies have been conducted to investigate the effects of impact loading on cartilage damage and chondrocyte death. These have shown that the rate and magnitude of the applied strain significantly influence chondrocyte death, and that cell death occurred mostly in the superficial zone of cartilage suggesting the need to further understand the fundamental mechanisms underlying the chondrocytes death induced at certain levels of strain-rate. To date there is no comprehensive study providing insight on this phenomenon. The aim of this study is to examine the strain-rate dependent behavior of a single chondrocyte using a computational approach based on Finite Element Method (FEM). An FEM model was developed using various mechanical models, which were Standard Neo-Hookean Solid (SnHS), porohyperelastic (PHE) and poroviscohyperelastic (PVHE) to simulate Atomic Force Microscopy (AFM) experiments of chondrocyte. The PVHE showed, it can capture both relaxation and loading rate dependent behaviors of chondrocytes, accurately compared to other models.

Encapsulation of nanoparticles into single-crystal ZnO nanorods and microrods

One-dimensional single crystal incorporating functional nanoparticles of other materials could be an interesting platform for various applications. We studied the encapsulation of nanoparticles into single-crystal ZnO nanorods by exploiting the crystal growth of ZnO in aqueous solution. Two types of nanodiamonds with mean diameters of 10 nm and 40 nm, respectively, and polymer nanobeads with size of 200 nm have been used to study the encapsulation process. It was found that by regrowing these ZnO nanorods with nanoparticles attached to their surfaces, a full encapsulation of nanoparticles into nanorods can be achieved. We demonstrate that our low-temperature aqueous solution growth of ZnO nanorods do not affect or cause degradation of the nanoparticles of either inorganic or organic materials. This new growth method opens the way to a plethora of applications combining the properties of single crystal host and encapsulated nanoparticles. We perform micro-photoluminescence measurement on a single ZnO nanorod containing luminescent nanodiamonds and the spectrum has a different shape from that of naked nanodiamonds, revealing the cavity effect of ZnO nanorod.

A multi-genome analysis approach enables tracking of the invasion of a single Russian wheat aphid (Diuraphis noxia) clone throughout the New World

This study investigated the population genetics, demographic history and pathway of invasion of the Russian wheat aphid (RWA) from its native range in Central Asia, the Middle East and Europe to South Africa and the Americas. We screened microsatellite markers, mitochondrial DNA and endosymbiont genes in 504 RWA clones from nineteen populations worldwide. Following pathway analyses of microsatellite and endosymbiont data, we postulate that Turkey and Syria were the most likely sources of invasion to Kenya and South Africa, respectively. Furthermore, we found that one clone transferred between South Africa and the Americas was most likely responsible for the New World invasion. Finally, endosymbiont DNA was found to be a high resolution population genetic marker, extremely useful for studies of invasion over a relatively short evolutionary history time frame. This study has provided valuable insights into the factors that may have facilitated the recent global invasion by this damaging pest.

Second-order elastic finite element analysis of structures using a single element per member

Finite element frame analysis programs targeted for design office application necessitate algorithms which can deliver reliable numerical convergence in a practical timeframe with comparable degrees of accuracy, and a highly desirable attribute is the use of a single element per member to reduce computational storage, as well as data preparation and the interpretation of the results. To this end, a higher-order finite element method including geometric non-linearity is addressed in the paper for the analysis of elastic frames for which a single element is used to model each member. The geometric non-linearity in the structure is handled using an updated Lagrangian formulation, which takes the effects of the large translations and rotations that occur at the joints into consideration by accumulating their nodal coordinates. Rigid body movements are eliminated from the local member load-displacement relationship for which the total secant stiffness is formulated for evaluating the large member deformations of an element. The influences of the axial force on the member stiffness and the changes in the member chord length are taken into account using a modified bowing function which is formulated in the total secant stiffness relationship, for which the coupling of the axial strain and flexural bowing is included.

Simulation of plant cell shrinkage during drying : A SPH–DEM approach

Plant based dried food products are popular commodities in global market where much research is focused to improve the products and processing techniques. In this regard, numerical modelling is highly applicable and in this work, a coupled meshfree particle-based two-dimensional (2-D) model was developed to simulate micro-scale deformations of plant cells during drying. Smoothed Particle Hydrodynamics (SPH) was used to model the viscous cell protoplasm (cell fluid) by approximating it to an incompressible Newtonian fluid. The visco-elastic characteristic of the cell wall was approximated to a Neo-Hookean solid material augmented with a viscous term and modelled with a Discrete Element Method (DEM). Compared to a previous work [H. C. P. Karunasena, W. Senadeera, Y. T. Gu and R. J. Brown, Appl. Math. Model., 2014], this study proposes three model improvements: linearly decreasing positive cell turgor pressure during drying, cell wall contraction forces and cell wall drying. The improvements made the model more comparable with experimental findings on dried cell morphology and geometric properties such as cell area, diameter, perimeter, roundness, elongation and compactness. This single cell model could be used as a building block for advanced tissue models which are highly applicable for product and process optimizations in Food Engineering.