Time to pregnancy : a computational method for using the duration of non-conception for predicting conception

An important problem in reproductive medicine is deciding when people who have failed to become pregnant without medical assistance should begin investigation and treatment. This study describes a computational approach to determining what can be deduced about a couple's future chances of pregnancy from the number of menstrual cycles over which they have been trying to conceive. The starting point is that a couple's fertility is inherently uncertain. This uncertainty is modelled as a probability distribution for the chance of conceiving in each menstrual cycle. We have developed a general numerical computational method, which uses Bayes' theorem to generate a posterior distribution for a couple's chance of conceiving in each cycle, conditional on the number of previous cycles of attempted conception. When various metrics of a couple's expected chances of pregnancy were computed as a function of the number of cycles over which they had been trying to conceive, we found good fits to observed data on time to pregnancy for different populations. The commonly-used standard of 12 cycles of non-conception as an indicator of subfertility was found to be reasonably robust, though a larger or smaller number of cycles may be more appropriate depending on the population from which a couple is drawn and the precise subfertility metric which is most relevant, for example the probability of conception in the next cycle or the next 12 cycles. We have also applied our computational method to model the impact of female reproductive ageing. Results indicate that, for women over the age of 35, it may be appropriate to start investigation and treatment more quickly than for younger women. Ignoring reproductive decline during the period of attempted conception added up to two cycles to the computed number of cycles before reaching a metric of subfertility

Consent agreements for cryopreserved embryos : the case for choice

Under current UK law, an embryo cannot be transferred to a woman’s uterus without the consent of both of its genetic parents, that is both of the people from whose gametes the embryo was created. This consent can be withdrawn at any time before the embryo transfer procedure. Withdrawal of consent by one genetic parent can result in the other genetic parent losing the opportunity to have their own genetic children. We argue that offering couples only one type of consent agreement, as happens at present, is too restrictive. An alternative form of agreement, in which one genetic parent agrees to forego the right to future withdrawal of consent, should be available alongside the current form of agreement. Giving couples such a choice will better enable them to store embryos under a consent agreement that is appropriate for their circumstances. Allowing such a choice, with robust procedures in place to ensure the validity of consent, is the best way to respect patient autonomy

Consent agreements for cryopreserved embryos : the case for choice

Under current UK law, an embryo cannot be transferred to a woman’s uterus without the consent of both of its genetic parents, that is both of the people from whose gametes the embryo was created. This consent can be withdrawn at any time before the embryo transfer procedure. Withdrawal of consent by one genetic parent can result in the other genetic parent losing the opportunity to have their own genetic children. We argue that offering couples only one type of consent agreement, as happens at present, is too restrictive. An alternative form of agreement, in which one genetic parent agrees to forego the right to future withdrawal of consent, should be available alongside the current form of agreement. Giving couples such a choice will better enable them to store embryos under a consent agreement that is appropriate for their circumstances. Allowing such a choice, with robust procedures in place to ensure the validity of consent, is the best way to respect patient autonomy

Evolving process-based models from psychological datausing genetic programming

The development of computational models to provide explanations of psychological data can be achieved using semi-automated search techniques, such as genetic programming. One challenge with these techniques is to control the type of model that is evolved to be cognitively plausible – a typical problem is that of “bloating”, where continued evolution generates models of increasing size without improving overall fitness. In this paper we describe a system for representing psychological data, a class of process-based models, and algorithms for evolving models. We apply this system to the delayed match-to-sample task. We show how the challenge of bloating may be addressed by extending the fitness function to include measures of cognitive performance

Simple Models of Competition between Two Hospitals

In the NHS internal market, hospital trusts compete with each other to sell patient care to health purchasers. We are interested in modelling the patterns of health provision resulting from the competition process; these can be compared with the optimal patterns of provision under a centrally planned system. As a starting point it is instructive to model simplified aspects of the competition process To this end, I consider a system in which there are just two trusts T1 and T2 competing for patients. In the most general form of this model, the trusts have a fnite capacities, limiting the number of patients they can treat, and the patients live in a range of locations, some closer to T1 and others closer to T2. Each trust has overheads, and also faces a marginal cost for treating each patient. Under the centrally planned system, it will be optimal to run a hospital at just one site if overheads are relatively high and patients travel costs are low, subject to the chosen hospital having su�cient capacity. Otherwise it will be optimal to run hospitals on both sites. In the internal market, each hospital will be assumed to make a charge per-patient for treatment. The purchaser(s), acting on the patients' behalf, allocate(s) each patient to one or other of the trusts: the choice is determined by the charge for treatment at each trust and the distance of the patient to each trust. Each trust sets its own treatment price. If it raises its price it will make more money from each patient, but at the cost of losing market share to the other trust. Two alternative game-theoretical scenarios may be considered: Scenario 1: Each trust seeks to maximise its profit. Scenario 2: Each trust seeks a fixed profit, corresponding to fixed return on its assets, as specified by the Department of Health [1]. Where more than one price will achieve this return, it will be assumed that the trust will set the lower or lowest price. Whichever scenario operates, the price one trust should set will in general depend on the price charged by the other. More generally, the pricing strategy of one trust will depend on the strategy of the other. Under rational bargaining, each trust's strategy will be an optimal response to the strategy of the other, and in this sense any resulting solution can be described as a Nash equilibrium. The form of the solution will depend on the bargaining dynamics of the interaction between the trusts. A resulting solution may be grossly defined by a configuration which specifies which hospital(s) are operational. The possible configurations may be denoted by S1 (T1 only), S2 (T2 only), and S12 (both hospitals). Within configuration S12, different patterns of patient allocation between the trusts may be possible. It is of interest to characterise the properties (uniqueness, stability) of the solutions.

Duration of courtship effort as a costly signal

We consider a male and a female in a courtship encounter over continuous time. Both parties pay participation costs per unit time. The game ends when either one or other of the parties quits or the female accepts the male as a mate. We assume that there is a binary variable which determines whether the mate is a "good" or "bad" type from the female's point of view, according to either his condition or his willingness to care for the young after mating. This variable is not directly observable by the female, but has fitness consequences for her: she gets a positive fitness payoff from mating with a "good" male but a negative fitness payoff from mating with a "bad" male. We assume also that a "good" male has a higher ratio of fitness benefit from mating to fitness cost per unit time of courtship than a "bad" male. We show that, under suitable assumptions, there are evolutionarily stable equilibrium behaviours in which time-extended courtship takes place. A "good" male is willing to court for longer than a "bad" male; in this way the duration of a male's courtship signals his type, and acts as a costly handicap. By not being willing to mate immediately the female achieves a degree of screening because the posterior probability that the male is "good", conditional on his not having quit the game, increases with the duration of courtship. (C) 2008 Elsevier Ltd. All rights reserved

Individual and social discounting in a viscous population

Social discounting in economics involves applying a diminishing weight to community-wide benefits or costs into the future. It impacts on public policy decisions involving future positive or negative effects, but there is no consensus on the correct basis for determining the social discount rate. This study presents an evolutionary biological framework for social discounting. How an organism should value future benefits to its local community is governed by the extent to which members of the community in the future are likely to be its kin. Trade-offs between immediate and delayed benefits to an individual or to its community are analysed for a modelled patch-structured iteroparous population with limited dispersal. It is shown that the social discount rate is generally lower than the individual (private) discount rate. The difference in the two rates is most pronounced, in ratio terms, when the dispersal level is low and the hazard rate for patch destruction is much smaller than the individual mortality rate. When decisions involve enforced collective action rather than individuals acting independently, social investment increases but the social discount rate remains the same

To age or not to age.

According to the antagonistic pleiotropy theory of ageing, natural selection has favoured genes conferring short-term benefits to the organism at the cost of deterioration in later life. The 'disposable soma' theory expresses this as a life-history strategy in which somatic maintenance is below the level required to prevent ageing, thus enabling higher immediate fertility. It has been argued that a non-ageing strategy will always be bettered by a low but non-zero rate of ageing, because the costs of such ageing will be felt only in the distant future when they are of negligible importance. Here, we examine this argument critically. We find that a non-ageing strategy will be locally optimal if, in the presence of ageing, the onset of deterioration is sufficiently rapid or early. Conversely, ageing will be optimal if deterioration is sufficiently slow or late. As the temporal profile of ageing changes from one of steady deterioration to one involving a sudden loss of vitality after a period of little or no decline, the conditions for a non-ageing strategy to be locally optimal become progressively more stringent. But for all forms of profile considered, conditions can be found for which a strategy involving no ageing is locally optimal