Balancing Selection at the Tomato RCR3 Guardee Gene Family Maintains Variation in Strength of Pathogen Defense

Coevolution between hosts and pathogens is thought to occur between interacting molecules of both species. This results in the maintenance of genetic diversity at pathogen antigens (or so-called effectors) and host resistance genes such as the major histocompatibility complex (MHC) in mammals or resistance (R) genes in plants. In plant–pathogen interactions, the current paradigm posits that a specific defense response is activated upon recognition of pathogen effectors via interaction with their corresponding R proteins. According to the ‘‘Guard-Hypothesis,’ ’ R proteins (the ‘‘guards’’) can sense modification of target molecules in the host (the ‘‘guardees’’) by pathogen effectors and subsequently trigger the defense response. Multiple studies have reported high genetic diversity at R genes maintained by balancing selection. In contrast, little is known about the evolutionary mechanisms shaping the guardee, which may be subject to contrasting evolutionary forces. Here we show that the evolution of the guardee RCR3 is characterized by gene duplication, frequent gene conversion, and balancing selection in the wild tomato species Solanum peruvianum. Investigating the functional characteristics of 54 natural variants through in vitro and in planta assays, we detected differences in recognition of the pathogen effector through interaction with the guardee, as well as substantial variation in the strength of the defense response. This variation is maintained by balancing selection at each copy of the RCR3 gene. Our analyses pinpoint three amino acid polymorphisms with key functional consequences for the coevolution between the guardee (RCR3) and its guard (Cf-2). We conclude that, i

Tractable POMDP-planning for robots with complex non-linear dynamics

Planning under partial observability is an essential capability of autonomous robots. While robots operate in the real world, they are inherently subject to various uncertainties such a control and sensing errors, and limited information regarding the operating environment.Conceptually these type of planning problems can be solved in a principled manner when framed as a Partially Observable Markov Decision Process (POMDP). POMDPs model the aforementioned uncertainties as conditional probability functions and estimate the state of the system as probability functions over the state space, called beliefs. Instead of computing the best strategy with respect to single states, POMDP solvers compute the best strategy with respect to beliefs. Solving a POMDP exactly is computationally intractable in general.However, in the past two decades we have seen tremendous progress in the development of approximately optimal solvers that trade optimality for computational tractability. Despite this progress, approximately solving POMDPs for systems with complex non-linear dynamics remains challenging. Most state-of-the-art solvers rely on a large number of expensive forward simulations of the system to find an approximate-optimal strategy. For systems with complex non-linear dynamics that admit no closed-form solution, this strategy can become prohibitively expensive. Another difficulty in applying POMDPs to physical robots with complex transition dynamics is the fact that almost all implementations of state-of-the-art on-line POMDP solvers restrict the user to specific data structures for the POMDP model, and the model has to be hard-coded within the solver implementation. This, in turn, severely hinders the process of applying POMDPs to physical robots.In this thesis we aim to make POMDPs more practical for realistic robotic motion planning tasks under partial observability. We show that systematic approximations of complex, non-linear transition dynamics can be used to design on-line POMDP solvers that are more efficient than current solvers. Furthermore, we propose a new software-framework that supports the user in modeling complex planning problems under uncertainty with minimal implementation effort

A study of BiFeO₃ and the Hall effect in BiFeO₃ and CdS

Pure samples of BiFeO₃ were heat treated in oxygen and nitrogen atmospheres in an attempt to reduce the conductivity of the samples. Dielectric constant and dissipation factor measurements, as a function of frequency, were made to determine whether the samples had been altered. A special high temperature Hall effect apparatus was constructed. Using this apparatus an upper limit for the Hall mobility in BiFeO₃ was established. The apparatus was also used for room temperature measurements of Ga-doped CdS samples. Resistivity measurements to be used with the Hall effect results were made on both the BiFeO₃ and the CdS samples. Hot-Point Probe (thermoelectric) measurements on BiFeO₃ indicated p-type conduction, and the Hall effect results established n-type conduction for the CdS samples --Abstract, page i

Forward and backward digit span difficulties in children with specific learning disorder

This study examined performance in the forward and backward digit span task of the Wechsler Intelligence Scale for Children–Fourth Edition (WISC–IV) in a large group of children with specific learning disorder (SLD) as compared with a group of typically developing children matched for age and sex. Our results further support the hypothesis that the intellectual difficulties of children with SLD involve working memory in the forward digit span task to a greater extent than in the backward digit span task. The correlation of the two spans with a General Ability Index (GAI) was similar in SLD, and smaller in magnitude than in typically developing children. Despite a GAI within normal range, children with SLD had difficulty with both digit span tasks, but more so for forward span. This pattern was similar for different SLD profiles with clinical diagnoses of dyslexia and mixed disorder, but the impairments were more severe in the latter. Age differences were also investigated, demonstrating larger span impairment in older children with SLD than in younger

Methods Used in Economic Evaluations of Chronic Kidney Disease Testing — A Systematic Review

Background: The prevalence of chronic kidney disease (CKD) is high in general populations around the world. Targeted testing and screening for CKD are often conducted to help identify individuals that may benefit from treatment to ameliorate or prevent their disease progression. Aims: This systematic review examines the methods used in economic evaluations of testing and screening in CKD, with a particular focus on whether test accuracy has been considered, and how analysis has incorporated issues that may be important to the patient, such as the impact of testing on quality of life and the costs they incur. Methods: Articles that described model-based economic evaluations of patient testing interventions focused on CKD were identified through the searching of electronic databases and the hand searching of the bibliographies of the included studies. Results: The initial electronic searches identified 2,671 papers of which 21 were included in the final review. Eighteen studies focused on proteinuria, three evaluated glomerular filtration rate testing and one included both tests. The full impact of inaccurate test results was frequently not considered in economic evaluations in this setting as a societal perspective was rarely adopted. The impact of false positive tests on patients in terms of the costs incurred in re-attending for repeat testing, and the anxiety associated with a positive test was almost always overlooked. In one study where the impact of a false positive test on patient quality of life was examined in sensitivity analysis, it had a significant impact on the conclusions drawn from the model. Conclusion: Future economic evaluations of kidney function testing should examine testing and monitoring pathways from the perspective of patients, to ensure that issues that are important to patients, such as the possibility of inaccurate test results, are properly considered in the analysis