Responding to Requests for Assisted Reproductive Technology Intervention Involving Women Who Cannot Give Consent

One of the plots of the Canadian science fiction thriller Orphan Black involves a scheme to create dozens of siblings by harvesting the eggs of one woman, fertilizing them with the sperm of a single man, and implanting them for gestation in dozens of apparently willing surrogates. The casualness of the procedure speaks to how comfortable we have all become with reproduction by technology. Yet there are still aspects of this process that remain outside the normative boundaries of most of our worldviews. This article considers recent advances in assisted reproductive technology (ART) that can result in a viable, fertilized embryo even when the mother is herself either permanently unconscious from a severe injury or has actually lost all brain function and therefore meets the legal criteria for brain death. It reviews these advances and applies them to four scenarios, or vignettes, that represent different concerns about the prospective mother’s intent to reproduce before losing her ability to give consent

Responding to Requests for Assisted Reproductive Technology Intervention Involving Women Who Cannot Give Consent

One of the plots of the Canadian science fiction thriller Orphan Black involves a scheme to create dozens of siblings by harvesting the eggs of one woman, fertilizing them with the sperm of a single man, and implanting them for gestation in dozens of apparently willing surrogates. The casualness of the procedure speaks to how comfortable we have all become with reproduction by technology. Yet there are still aspects of this process that remain outside the normative boundaries of most of our worldviews. This article considers recent advances in assisted reproductive technology (ART) that can result in a viable, fertilized embryo even when the mother is herself either permanently unconscious from a severe injury or has actually lost all brain function and therefore meets the legal criteria for brain death. It reviews these advances and applies them to four scenarios, or vignettes, that represent different concerns about the prospective mother’s intent to reproduce before losing her ability to give consent

Boltzmann-Shannon Entropy: Generalization and Application

The paper deals with the generalization of both Boltzmann entropy and distribution in the light of most-probable interpretation of statistical equilibrium. The statistical analysis of the generalized entropy and distribution leads to some new interesting results of significant physical importance.Comment: 5 pages, Accepted in Mod.Phys.Lett.

Resistance in Triticum aestivum to infection by Gaeumannomyces graminis var Tritici / by L. Penrose

Bibliography: leaves 141-145vii, 145 leaves, [4] leaves of plates : ill. (4 col.) ; 30 cm.Thesis (Ph.D.)--University of Adelaide, Depts. of Plant Pathology and Agronomy, 198

Applications of Hierarchical Statistical Models to Interpret Biological Data

This thesis looks at two biological applications of hierarchical models. The first application considers the non-linear decay of a contaminant in beef cattle, while the other quite different application considers the transmission probability of genetic markers in the mouse. In the first application, a contaminant was measured over time on 11 animals. Each animal was then a random effect in a small data set. Application of a non-linear random effects model was the only way to analyse these data. This required integrating over animal effects to obtain the marginal model for the small animal population. Lack of a closed form solution for the integration, necessitated use of LaPlace's approximation. A better analysis was demonstrated using MCMC, which provided confidence intervals for parameter estimates, and was not limited by the number of parameters in the model. The second application was seemingly very different. The data consisted of counts of genetic markers in mouse progeny, and so was binary with many elements in common to a time series. Of interest was change in transmission probability of markers from parents, as a function of marker location down each chromosome. An empirical (unconstrained) regression was found to potentially confound transmission effects with local error effects, and constrained the models sensitivity to very local effects. A better approach was to constrain transmission probabilities to specific states, which allowed nearby markers to have either abrupt changes in state, or no change. Hidden Markov Models confer this structure to data, having some similarity to step functions. The best method of fitting these models to data was shown to be the Baum-Welch algorithm, which allows model flexibility and expansion. It was shown that Hidden Markov Models provided a good fit to the mouse data. The ability to pool information within states provided a better estimate of transmission means and standard error, than is incurred by treating each locus in isolation and attaching a global error. In common to both hierarchical models, was the bringing of some sort of pre-existing information to models. For the random effects model, this was the constraint that random effects were normally distributed, and for the mouse data, that nearby markers may have the same transmission probability. This had the effect of adding to the information in the data, and so improved parameter estimation, and gave models stability. This latter benefit is particularly beneficial to small data sets. The bringing of pre-existing information to a model is implicitly a Bayesian approach to analysis

Responding to Requests for Assisted Reproductive Technology Intervention Involving Women Who Cannot Give Consent

One of the plots of the Canadian science fiction thriller Orphan Black involves a scheme to create dozens of siblings by harvesting the eggs of one woman, fertilizing them with the sperm of a single man, and implanting them for gestation in dozens of apparently willing surrogates. The casualness of the procedure speaks to how comfortable we have all become with reproduction by technology. Yet there are still aspects of this process that remain outside the normative boundaries of most of our worldviews. This article considers recent advances in assisted reproductive technology (ART) that can result in a viable, fertilized embryo even when the mother is herself either permanently unconscious from a severe injury or has actually lost all brain function and therefore meets the legal criteria for brain death. It reviews these advances and applies them to four scenarios, or vignettes, that represent different concerns about the prospective mother’s intent to reproduce before losing her ability to give consent

Dispersal in a hurry: Bayesian learning from surveillance to establish area freedom from plant pests with early dispersal

Declaration of area freedom from plant pests is crucial for the agricultural sector, since it promotes continuing domestic and international trade of crops at risk from exotic pests. Freedom from plant pests may also enhance environmental health, with indirect effects on agricultural productivity. Every year, several new exotic plant pest species are reported for the first time. In the face of this continual pressure and growing globalization, resources to undertake surveillance are limited. Design of surveillance is critical for determining how to allocate these limited resources. Designs for surveillance that help assess area freedom have focused on the colonization process, captured by a prevalence model that does not accommodate dispersal. In this paper, we extend these designs to accommodate early dispersal from a few colonization points. This provides a basis for evaluating the effectiveness of surveillance over multiple sampling occasions. To achieve this we harness a Bayesian statistical framework. Although there are some computational overheads, this provides several benefits: (i) an intuitive hierarchical structure that helps separate then link modelling components; (ii) the facility to incorporate expert knowledge; and (iii) inference that directly addresses the questions of farmers and biosecurity managers, in a way that the range of plausible outcomes is provided together with point estimates. Finally the Bayesian framework facilitates a natural cycle of learrning, that readily incorporates new information – from surveillance snapshots – as it becomes available. Firstly, we harness the natural hierarchical structure of the Bayesian statistical framework to separate the model—for the spatio-temporal dynamics of dispersal underlying prevalence—from the model for detection, which depends on prevalence. Secondly, expert knowledge on both point estimates and variability can be explicitly incorporated as Bayesian prior distributions, and in each phase, these priors are updated into new posteriors as more surveillance data becomes available. This is important since much of the data informing design of surveillance for exotic plant pests relies heavily on expert judgment, especially during the early phases of plant biosecurity—when establishing area freedom. Thirdly, the Bayesian posterior approach used here automatically answers the question of If we detect nothing, how many infested plants could we have missed? This approach provides a ready mechanism for including information about dispersal on the infested plants (both missed and detected). Finally, the Bayesian framework facilitates an adaptive cycle of learning. We can apply Bayesian inference to analyze the first surveillance snapshot and learn about prevalence and detectability parameters. Then Bayesian predictions can be used to progress the pest status before analysis of the next snapshot. This flexibly provides a basis for incorporating new knowledge as it is obtained. We utilized freely available software, that enjoy high utilization among non-statisticians and statisticians, for: exploratory data analysis, statistical modelling and visualization.Full Tex

Use of Oral Agents and/or Insulin in the Treatment of Diabetes during Pregnancy: An Examination of Outcomes in Pregestational versus Gestational Diabetics

Abstract The management of diabetes in pregnancy varies depending on whether the condition was first diagnosed during pregnancy (gestational diabetes) or was diagnosed before pregnancy (pregestational diabetes). Little has been published comparing the relative efficacy of various oral agents for the treatment of gestational diabetes and the reported experience with the insulin pump in pregnancy for pregestational diabetes remains meager. We conducted a retrospective chart review of women managed in a specialized diabetic clinic to compare the results of treatment of gestational diabetes with oral agents, glyburide and acarbose, to those treated with split-mixed insulin and treatment of pregestational diabetes with either the insulin pump or conventional splitmixed insulin. Gestational diabetics treated with split-mixed insulin were hospitalized significantly more often (p < 0.001) than those treated with oral agents only. The incidence of several important pregnancy complications (growth restriction, preterm labor, preeclampsia, oligohydramnios) did not differ between groups. Pregestational diabetics managed with an insulin pump had comparable glycemic control, as measured by hemoglobin A1c, to those managed with split-mixed insulin. Infant birth weights and Apgar scores were similar in each group. There were no perinatal deaths in either group. Acarbose and glyburide showed comparable efficacy in treating gestational diabetics. In addition, our experience adds to the small number of pregnant women with pregestational diabetes who were managed with an insulin pump that have been reported in the literature