Evolved polygenic herbicide resistance in Lolium rigidum by low-dose herbicide selection within standing genetic variation

The interaction between environment and genetic traits under selection is the basis of evolution. In this study, we have investigated the genetic basis of herbicide resistance in a highly characterized initially herbicide-susceptible Lolium rigidum population recurrently selected with low (below recommended label) doses of the herbicide diclofop-methyl. We report the variability in herbicide resistance levels observed in F1 families and the segregation of resistance observed in F2 and back-cross (BC) families. The selected herbicide resistance phenotypic trait(s) appear to be under complex polygenic control. The estimation of the effective minimum number of genes (NE), depending on the herbicide dose used, reveals at least three resistance genes had been enriched. A joint scaling test indicates that an additive-dominance model best explains gene interactions in parental, F1, F2 and BC families. The Mendelian study of six F2 and two BC segregating families confirmed involvement of more than one resistance gene. Cross-pollinated L. rigidum under selection at low herbicide dose can rapidly evolve polygenic broad-spectrum herbicide resistance by quantitative accumulation of additive genes of small effect. This can be minimized by using herbicides at the recommended dose which causes high mortality acting outside the normal range of phenotypic variation for herbicide susceptibility

Collaborative Lawyers' Duties to Screen the Appropriateness of Collaborative Law and Obtain Clients' Informed Consent to Use Collaborative Law

Published in cooperation with the American Bar Association Section of Dispute Resolutio

The Uniform Collaborative Law Act\u27s Contribution to Informed Client Decision Making in Choosing a Dispute Resolution Process

This Article describes how lawyers can implement the requirements of the Uniform Collaborative Law Act to obtain clients’ informed consent. The Act requires lawyers to obtain clients’ informed consent before undertaking a Collaborative representation but does not specify the information that lawyers must discuss with prospective Collaborative parties. To flesh out the Act’s requirements, this Article describes how lawyers should analyze the facts and parties’ interests, screen the appropriateness of dispute resolution processes, analyze the reasonably available dispute resolution options, and discuss the Collaborative process with clients. It specifically addresses privacy issues including privilege, confidentiality, and full disclosure requirements. This Article also suggests ways that lawyers may educate clients generally to make good decisions about dispute resolution options generally, and the Collaborative process in particular

3D statistical shape analysis of the face in Apert syndrome

Timely diagnosis of craniofacial syndromes as well as adequate timing and choice of surgical technique are essential for proper care management. Statistical shape models and machine learning approaches are playing an increasing role in Medicine and have proven its usefulness. Frameworks that automate processes have become more popular. The use of 2D photographs for automated syndromic identification has shown its potential with the Face2Gene application. Yet, using 3D shape information without texture has not been studied in such depth. Moreover, the use of these models to understand shape change during growth and its applicability for surgical outcome measurements have not been analysed at length. This thesis presents a framework using state-of-the-art machine learning and computer vision algorithms to explore possibilities for automated syndrome identification based on shape information only. The purpose of this was to enhance understanding of the natural development of the Apert syndromic face and its abnormality as compared to a normative group. An additional method was used to objectify changes as result of facial bipartition distraction, a common surgical correction technique, providing information on the successfulness and on inadequacies in terms of facial normalisation. Growth curves were constructed to further quantify facial abnormalities in Apert syndrome over time along with 3D shape models for intuitive visualisation of the shape variations. Post-operative models were built and compared with age-matched normative data to understand where normalisation is coming short. The findings in this thesis provide markers for future translational research and may accelerate the adoption of the next generation diagnostics and surgical planning tools to further supplement the clinical decision-making process and ultimately to improve patients’ quality of life