Informed consent in veterinary medicine: ethical implications for the profession and the animal 'patient'

Informed consent processes are a vital component of both human and veterinary medicine. Current practice encourages veterinarians to learn from insights in the human medical field about how best to achieve valid consent. However, drawing on published literature in veterinary and medical ethics, this paper identifies considerable differences between the purposes of veterinary and human medical consent. Crucially, it is argued that the legal status of animal patients as ‘property’ has implications for the ethical role of veterinary informed consent and the protection of the animal ‘patient’. It is suggested that veterinary informed consent should be viewed as an ethical pivot point where the multiple responsibilities of a veterinary professional converge. In practice, balancing these responsibilities creates considerable ethical challenges. As an example, the paper discusses the renewed call for UK veterinarians to make animal welfare their first priority; we predict that this imperative may increasingly cause veterinary informed consent to become an ethical pressure point due to tensions caused by the often conflicting interests of animals, owners and the veterinary profession. In conclusion, the paper argues that whilst gaining informed consent can often be presented as a robust ethical justification in human medicine, the same cannot be said in veterinary medicine. If the veterinary profession wish to prioritise animal welfare, there is an urgent need to re-evaluate the nature of authority gained through owner informed consent and to consider whether animal patients might need to be better protected outside the consent process in certain circumstances

Data analysis issues for allele-specific expression using Illumina's GoldenGate assay.

BACKGROUND: High-throughput measurement of allele-specific expression (ASE) is a relatively new and exciting application area for array-based technologies. In this paper, we explore several data sets which make use of Illumina's GoldenGate BeadArray technology to measure ASE. This platform exploits coding SNPs to obtain relative expression measurements for alleles at approximately 1500 positions in the genome. RESULTS: We analyze data from a mixture experiment where genomic DNA samples from pairs of individuals of known genotypes are pooled to create allelic imbalances at varying levels for the majority of SNPs on the array. We observe that GoldenGate has less sensitivity at detecting subtle allelic imbalances (around 1.3 fold) compared to extreme imbalances, and note the benefit of applying local background correction to the data. Analysis of data from a dye-swap control experiment allowed us to quantify dye-bias, which can be reduced considerably by careful normalization. The need to filter the data before carrying out further downstream analysis to remove non-responding probes, which show either weak, or non-specific signal for each allele, was also demonstrated. Throughout this paper, we find that a linear model analysis of the data from each SNP is a flexible modelling strategy that allows for testing of allelic imbalances in each sample when replicate hybridizations are available. CONCLUSIONS: Our analysis shows that local background correction carried out by Illumina's software, together with quantile normalization of the red and green channels within each array, provides optimal performance in terms of false positive rates. In addition, we strongly encourage intensity-based filtering to remove SNPs which only measure non-specific signal. We anticipate that a similar analysis strategy will prove useful when quantifying ASE on Illumina's higher density Infinium BeadChips.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Environmental and genetic influences on early attachment

Attachment theory predicts and subsequent empirical research has amply demonstrated that individual variations in patterns of early attachment behaviour are primarily influenced by differences in sensitive responsiveness of caregivers. However, meta-analyses have shown that parenting behaviour accounts for about one third of the variance in attachment security or disorganisation. The exclusively environmental explanation has been challenged by results demonstrating some, albeit inconclusive, evidence of the effect of infant temperament. In this paper, after reviewing briefly the well-demonstrated familial and wider environmental influences, the evidence is reviewed for genetic and gene-environment interaction effects on developing early attachment relationships. Studies investigating the interaction of genes of monoamine neurotransmission with parenting environment in the course of early relationship development suggest that children's differential susceptibility to the rearing environment depends partly on genetic differences. In addition to the overview of environmental and genetic contributions to infant attachment, and especially to disorganised attachment relevant to mental health issues, the few existing studies of gene-attachment interaction effects on development of childhood behavioural problems are also reviewed. A short account of the most important methodological problems to be overcome in molecular genetic studies of psychological and psychiatric phenotypes is also given. Finally, animal research focusing on brain-structural aspects related to early care and the new, conceptually important direction of studying environmental programming of early development through epigenetic modification of gene functioning is examined in brief

Uterine Dysfunction in Biglycan and Decorin Deficient Mice Leads to Dystocia during Parturition

Cesarean birth rates are rising. Uterine dysfunction, the exact mechanism of which is unknown, is a common indication for Cesarean delivery. Biglycan and decorin are two small leucine-rich proteoglycans expressed in the extracellular matrix of reproductive tissues and muscle. Mice deficient in biglycan display a mild muscular dystrophy, and, along with mice deficient in decorin, are models of Ehlers-Danlos Syndrome, a connective tissue anomaly associated with uterine rupture. As a variant of Ehlers-Danlos Syndrome is caused by a genetic mutation resulting in abnormal biglycan and decorin secretion, we hypothesized that biglycan and decorin play a role in uterine function. Thus, we assessed wild-type, biglycan, decorin and double knockout pregnancies for timing of birth and uterine function. Uteri were harvested at embryonic days 12, 15 and 18. Nonpregnant uterine samples of the same genotypes were assessed for tissue failure rate and spontaneous and oxytocin-induced contractility. We discovered that biglycan/decorin mixed double-knockout dams displayed dystocia, were at increased risk of delayed labor onset, and showed increased tissue failure in a predominantly decorin-dependent manner. In vitro spontaneous uterine contractile amplitude and oxytocin-induced contractile force were decreased in all biglycan and decorin knockout genotypes compared to wild-type. Notably, we found no significant compensation between biglycan and decorin using quantitative real time PCR or immunohistochemistry. We conclude that the biglycan/decorin mixed double knockout mouse is a model of dystocia and delayed labor onset. Moreover, decorin is necessary for uterine function in a dose-dependent manner, while biglycan exhibits partial compensatory mechanisms in vivo. Thus, this model is poised for use as a model for testing novel targets for preventive or therapeutic manipulation of uterine dysfunction

Bank performance and executive pay: tournament or teamwork

We investigate the relationship between the dispersion of executive pay and bank performance/valuation by examining two competing theories, the tournament theory (hierarchical wage structure) and the equity fairness theory (compressed wage structure). The key variable of executive pay dispersion is measured using a hand-collected dataset composed of 63 banks from OECD countries and 29 banks from developing countries. The dataset covers the period 2004 to 2012. By combining and modifying a translog profit function and a pay-dispersion model, we are able to address the potential problems of relying on reduced-form estimation. In our subsample of developed and civil law countries, where bank performance is measured by either Tobin’s Q or by the price-to-book ratio, the overall impact of executive pay dispersion is mostly negative, and we find supporting evidence for the equity fairness theory, except for very high levels of dispersion. There is a non-linear effect, as banks perform best when there is either very low or very high executive pay dispersion. For developing country sample banks, greater executive pay dispersion has a negative impact on bank profit. In our subsample of common law countries, however, we find no evidence of a significant impact of executive pay dispersion on bank performance. We conclude that lower executive pay dispersion, a proxy for teamwork, is mostly effective in enhancing bank performance in a significant section of sample banks, i.e., civil law and developing countries

A Two-Locus Model of the Evolution of Insecticide Resistance to Inform and Optimise Public Health Insecticide Deployment Strategies

We develop a flexible, two-locus model for the spread of insecticide resistance applicable to mosquito species that transmit human diseases such as malaria. The model allows differential exposure of males and females, allows them to encounter high or low concentrations of insecticide, and allows selection pressures and dominance values to differ depending on the concentration of insecticide encountered. We demonstrate its application by investigating the relative merits of sequential use of insecticides versus their deployment as a mixture to minimise the spread of resistance. We recover previously published results as subsets of this model and conduct a sensitivity analysis over an extensive parameter space to identify what circumstances favour mixtures over sequences. Both strategies lasted more than 500 mosquito generations (or about 40 years) in 24% of runs, while in those runs where resistance had spread to high levels by 500 generations, 56% favoured sequential use and 44% favoured mixtures. Mixtures are favoured when insecticide effectiveness (their ability to kill homozygous susceptible mosquitoes) is high and exposure (the proportion of mosquitoes that encounter the insecticide) is low. If insecticides do not reliably kill homozygous sensitive genotypes, it is likely that sequential deployment will be a more robust strategy. Resistance to an insecticide always spreads slower if that insecticide is used in a mixture although this may be insufficient to outperform sequential use: for example, a mixture may last 5 years while the two insecticides deployed individually may last 3 and 4 years giving an overall ‘lifespan’ of 7 years for sequential use. We emphasise that this paper is primarily about designing and implementing a flexible modelling strategy to investigate the spread of insecticide resistance in vector populations and demonstrate how our model can identify vector control strategies most likely to minimise the spread of insecticide resistance