Expert consensus regarding drivers of antimicrobial stewardship in companion animal veterinary practice: a Delphi study

Antimicrobial resistance (AMR) is a global challenge facing both human and animal healthcare professionals; an effective response to this threat requires a ‘One-Health’ approach to antimicrobial stewardship (AMS) to preserve important antibiotics for urgent clinical need. However, understanding of barriers and enablers to effective AMS behaviour in companion animal veterinary practice is currently limited. We conducted a Delphi study of 16 nationally recognised experts from UK-based veterinary policymakers, university academics and leaders of professional bodies. This Delphi study sought to identify veterinary behaviours which experts believe contribute to AMR and form vital aspects of AMS. Analysis of Delphi findings indicated a perceived hierarchy of behaviours, the most influential being antibiotic prescribing behaviours and interactions with clients. Other veterinary behaviours perceived as being important related to interactions with veterinary colleagues; infection control practices; and the use of diagnostic tests to confirm infection. Key barriers and enablers to AMS within each of these behavioural domains were identified. Specific interventions to address important barriers and enablers are recommended. To the authors’ knowledge, this is the first study to establish expert consensus at a national level about which ‘behaviours’ (aspects of veterinarian practice) should be targeted in relation to AMR and AMS in companion animal veterinary practice

An on-line training radial basis function neural network for optimum operation of the UPFC

The concept of Flexible A.C. Transmission Systems (FACTS) technology was developed to enhance the performance of electric power networks (both in steady-state and transient-state) and to make better utilization of existing power transmission facilities. The continuous improvement in power ratings and switching performance of power electronic devices together with advances in circuit design and control techniques are making this concept and devices employed in FACTS more commercially attractive. The Unified Power Flow Controller (UPFC) is one of the main FACTS devices that have a wide implication on the power transmission systems and distribution. The purpose of this paper is to explore the use of Radial Basis Function Neural Network (RBFNN) to control the operation of the UPFC in order to improve its dynamic performance. The performance of the proposed controller compares favourably with the conventional PI and the off-line trained controller. The simple structure of the proposed controller reduces the computational requirements and emphasizes its appropriateness for on-line operation. Real-time implementation of the controller is achieved through using dSPACE ds1103 control and data acquisition board. Simulation and experimental results are presented to demonstrate the robustness of the proposed controller against changes in the transmission system operating conditions

The social construction of the software operation: Reinforcing effects in metrics programs

In a large software company in Denmark, much effort was expended capturing metrics about the company’s software operation. The purpose of the metrics program was to change and improve the software operation. Writing software can be understood as a socially constructed practice, which can be analyzed using structuration theory. This structurational analysis showed that the company’s software operation followed an easily recognizable and widely understood pattern. The software operation was organized in terms of development projects leading to applications that then needed maintenance, and displayed a heavy focus on project development work and hitting the project deadline. Study of the metrics program (and the computer software underpinning it) revealed that the familiar pattern was also inscribed into the metrics software, heavily influencing the company’s metrics practice. Rather than challenge the underlying social practice of the software operation, the metrics program reinforced it by adopting the same underlying values. Our conclusion is that, under these circumstances, metrics programs are unlikely to result in radical changes to the software operation, and are best suited to small, incremental improvements

Pharmacodynamic modelling of in vitro activity of tetracycline against a representative, naturally occurring population of porcine Escherichia coli

Background The complex relationship between drug concentrations and bacterial growth rates require not only the minimum inhibitory concentration but also other parameters to capture the dynamic nature of the relationship. To analyse this relationship between tetracycline concentration and growth of Escherichia coli representative of those found in the Danish pig population, we compared the growth of 50 randomly selected strains. The observed net growth rates were used to describe the in vitro pharmacodynamic relationship between drug concentration and net growth rate based on E max model with three parameters: maximum net growth rate (α max ); concentration for a half-maximal response (E max ); and the Hill coefficient (γ). Results The net growth rate in the absence of antibiotic did not differ between susceptible and resistant isolates (P = 0.97). The net growth rate decreased with increasing tetracycline concentrations, and this decline was greater in susceptible strains than resistant strains. The lag phase, defined as the time needed for the strain to reach an OD 600 value of 0.01, increased exponentially with increasing tetracycline concentration. The pharmacodynamic parameters confirmed that the αmax between susceptible and resistant strains in the absence of a drug was not different. EC 50 increased linearly with MIC on a log–log scale, and γ was different between susceptible and resistant strains. Conclusions The in vitro model parameters described the inhibition effect of tetracycline on E. coli when strains were exposed to a wide range of tetracycline concentrations. These parameters, along with in vivo pharmacokinetic data, may be useful in mathematical models to predict in vivo competitive growth of many different strains and for development of optimal dosing regimens for preventing selection of resistance