Invasion speeds for structured populations in fluctuating environments

We live in a time where climate models predict future increases in environmental variability and biological invasions are becoming increasingly frequent. A key to developing effective responses to biological invasions in increasingly variable environments will be estimates of their rates of spatial spread and the associated uncertainty of these estimates. Using stochastic, stage-structured, integro-difference equation models, we show analytically that invasion speeds are asymptotically normally distributed with a variance that decreases in time. We apply our methods to a simple juvenile-adult model with stochastic variation in reproduction and an illustrative example with published data for the perennial herb, \emph{Calathea ovandensis}. These examples buttressed by additional analysis reveal that increased variability in vital rates simultaneously slow down invasions yet generate greater uncertainty about rates of spatial spread. Moreover, while temporal autocorrelations in vital rates inflate variability in invasion speeds, the effect of these autocorrelations on the average invasion speed can be positive or negative depending on life history traits and how well vital rates ``remember'' the past

Improving Quality And Diffusing Best Practices: The Case Of Schizophrenia

The slow diffusion of empirically supported treatments and the rapid diffusion of treatments lacking empirical support play a significant role in the quality gap in the care of people with severe mental illnesses. Further, the rapid diffusion of treatments of low cost-effectiveness limits the system's ability to provide the full gamut of high-value treatments available to treat this vulnerable population. Using the case of schizophrenia as an illustrative case study, we review the context in which these paradoxical patterns of diffusion have occurred and propose policy solutions

Crude incidence in two-phase designs in the presence of competing risks.

BackgroundIn many studies, some information might not be available for the whole cohort, some covariates, or even the outcome, might be ascertained in selected subsamples. These studies are part of a broad category termed two-phase studies. Common examples include the nested case-control and the case-cohort designs. For two-phase studies, appropriate weighted survival estimates have been derived; however, no estimator of cumulative incidence accounting for competing events has been proposed. This is relevant in the presence of multiple types of events, where estimation of event type specific quantities are needed for evaluating outcome.MethodsWe develop a non parametric estimator of the cumulative incidence function of events accounting for possible competing events. It handles a general sampling design by weights derived from the sampling probabilities. The variance is derived from the influence function of the subdistribution hazard.ResultsThe proposed method shows good performance in simulations. It is applied to estimate the crude incidence of relapse in childhood acute lymphoblastic leukemia in groups defined by a genotype not available for everyone in a cohort of nearly 2000 patients, where death due to toxicity acted as a competing event. In a second example the aim was to estimate engagement in care of a cohort of HIV patients in resource limited setting, where for some patients the outcome itself was missing due to lost to follow-up. A sampling based approach was used to identify outcome in a subsample of lost patients and to obtain a valid estimate of connection to care.ConclusionsA valid estimator for cumulative incidence of events accounting for competing risks under a general sampling design from an infinite target population is derived

Reinforcement learning or active inference?

This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain

Organizational factors and depression management in community-based primary care settings

Abstract Background Evidence-based quality improvement models for depression have not been fully implemented in routine primary care settings. To date, few studies have examined the organizational factors associated with depression management in real-world primary care practice. To successfully implement quality improvement models for depression, there must be a better understanding of the relevant organizational structure and processes of the primary care setting. The objective of this study is to describe these organizational features of routine primary care practice, and the organization of depression care, using survey questions derived from an evidence-based framework. Methods We used this framework to implement a survey of 27 practices comprised of 49 unique offices within a large primary care practice network in western Pennsylvania. Survey questions addressed practice structure (e.g., human resources, leadership, information technology (IT) infrastructure, and external incentives) and process features (e.g., staff performance, degree of integrated depression care, and IT performance). Results The results of our survey demonstrated substantial variation across the practice network of organizational factors pertinent to implementation of evidence-based depression management. Notably, quality improvement capability and IT infrastructure were widespread, but specific application to depression care differed between practices, as did coordination and communication tasks surrounding depression treatment. Conclusions The primary care practices in the network that we surveyed are at differing stages in their organization and implementation of evidence-based depression management. Practical surveys such as this may serve to better direct implementation of these quality improvement strategies for depression by improving understanding of the organizational barriers and facilitators that exist within both practices and practice networks. In addition, survey information can inform efforts of individual primary care practices in customizing intervention strategies to improve depression management.http://deepblue.lib.umich.edu/bitstream/2027.42/78269/1/1748-5908-4-84.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78269/2/1748-5908-4-84-S1.PDFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78269/3/1748-5908-4-84.pdfPeer Reviewe

Insulin-like signalling to the maternal germline controls progeny response to osmotic stress

In 1893 August Weismann proposed that information about the environment could not pass from somatic cells to germ cells, a hypothesis now known as the Weismann barrier. However, recent studies have indicated that parental exposure to environmental stress can modify progeny physiology and that parental stress can contribute to progeny disorders. The mechanisms regulating these phenomena are poorly understood. We report that the nematode Caenorhabditis elegans can protect itself from osmotic stress by entering a state of arrested development and can protect its progeny from osmotic stress by increasing the expression of the glycerol biosynthetic enzyme GPDH-2 in progeny. Both of these protective mechanisms are regulated by insulin-like signalling: insulin-like signalling to the intestine regulates developmental arrest, while insulin-like signalling to the maternal germline regulates glycerol metabolism in progeny. Thus, there is a heritable link between insulin-like signalling to the maternal germline and progeny metabolism and gene expression. We speculate that analogous modulation of insulin-like signalling to the germline is responsible for effects of the maternal environment on human diseases that involve insulin signalling, such as obesity and type-2 diabetes

Dopamine Signaling Is Essential for Precise Rates of Locomotion by C. elegans

Dopamine is an important neuromodulator in both vertebrates and invertebrates. We have found that reduced dopamine signaling can cause a distinct abnormality in the behavior of the nematode C. elegans, which has only eight dopaminergic neurons. Using an automated particle-tracking system for the analysis of C. elegans locomotion, we observed that individual wild-type animals made small adjustments to their speed to maintain constant rates of locomotion. By contrast, individual mutant animals defective in the synthesis of dopamine made larger adjustments to their speeds, resulting in large fluctuations in their rates of locomotion. Mutants defective in dopamine signaling also frequently exhibited both abnormally high and abnormally low average speeds. The ability to make small adjustments to speed was restored to these mutants by treatment with dopamine. These behaviors depended on the D2-like dopamine receptor DOP-3 and the G-protein subunit GOA-1. We suggest that C. elegans and other animals, including humans, might share mechanisms by which dopamine restricts motor activity levels and coordinates movement