HENNOVATION: Learnings from Promoting Practice-Led Multi-Actor Innovation Networks to Address Complex Animal Welfare Challenges within the Laying Hen Industry

The Hennovation project, an EU H2020 funded thematic network, aimed to explore the potential value of practice-led multi-actor innovation networks within the laying hen industry. The project proposed that husbandry solutions can be practice-led and effectively supported to achieve durable gains in sustainability and animal welfare. It encouraged a move away from the traditional model of science providing solutions for practice, towards a collaborative approach where expertise from science and practice were equally valued. During the 32-month project, the team facilitated 19 multi-actor networks in five countries through six critical steps in the innovation process: problem identification, generation of ideas, planning, small scale trials, implementation and sharing with others. The networks included farmers, processors, veterinarians, technical advisors, market representatives and scientists. The interaction between the farmers and the other network actors, including scientists, was essential for farmer innovation. New relationships emerged between the scientists and farmers, based on experimental learning and the co-production of knowledge for improving laying hen welfare. The project demonstrated that a practice-led approach can be a major stimulus for innovation with several networks generating novel ideas and testing them in their commercial context. The Hennovation innovation networks not only contributed to bridging the science-practice gap by application of existing scientific solutions in practice but more so by jointly finding new solutions. Successful multi-actor, practice-led innovation networks appeared to depend upon the following key factors: active participation from relevant actors, professional facilitation, moderate resource support and access to relevant expertise. Farmers and processors involved in the project were often very enthusiastic about the approach, committing significant time to the network’s activities. It is suggested that the agricultural research community and funding agencies should place greater value on practice-led multi-actor innovation networks alongside technology and advisor focused initiatives to improve animal welfare and embed best practices

Foreword

In 2014, four of Emeritus Prof. Peter (fondly known as PB) Beighton’s past PhD students decided that they would like to honour him for his leadership and the influence that he had on their professional lives, and collaborated on a project to compile a Festschrift in his honour. They are Prof. Michael Hayden, now living in Canada, the first PhD graduate that PB supervised in 1979, together with Profs Jacquie Greenberg from the University of Cape Town (UCT), Alan Bryer from UCT and Groote Schuur Hospital (GSH), and Lawrence Stephen from the University of the Western Cape (UWC). Prof. Lawrence Stephen was the last PhD graduate that Prof. Beighton supervised before he officially retired in 1999.Many colleagues who have worked over the past 5 decades and who continue to work with him were invited to contribute to this supplement to the SAMJ. The Festschrift includes the history behind Peter Beighton, who was born, grew up and trained in the UK and came to UCT in 1972. His legacy includes the impact that he made on those who trained under him in SA, as well as throughout the world. The Festschrift includes the history of genetics and current genetic practice in South Africa, as well as the influence that he has had on medical genetics in general, dental genetics and now genomics going into the new millennium. Tributes have been received from people all over the world, attesting to his outstanding leadership and mentorship, and highlight how he influenced the climate, growth and development of genetics at UCT, and scientific and technological fields in genetics and genomics over the past few decades.This Foreword includes a message from Emeritus Prof. Stuart Saunders – former Head of Department (HoD) of Medicine at GSH in the 1970s when PB arrived at UCT – followed by some words from Emeritus Prof. J P van Niekerk, former Dean of the UCT Faculty of Health Sciences in the 1980s. Profs Greenberg, Bryer and Stephen conclude the Foreword, while Prof. Hayden introduces the legacy that Prof. Beighton has passed on

GA-based multi-objective optimization of active nonlinear quarter car suspension system—PID and fuzzy logic control

Background The primary function of a suspension system is to isolate the vehicle body from road irregularities thus providing the ride comfort and to support the vehicle and provide stability. The suspension system has to perform conflicting requirements; hence, a passive suspension system is replaced by the active suspension system which can supply force to the system. Active suspension supplies energy to respond dynamically and achieve relative motion between body and wheel and thus improves the performance of suspension system. Methods This study presents modelling and control optimization of a nonlinear quarter car suspension system. A mathematical model of nonlinear quarter car is developed and simulated for control and optimization in Matlab/Simulink® environment. Class C road is selected as input road condition with the vehicle traveling at 80 kmph. Active control of the suspension system is achieved using FLC and PID control actions. Instead of guessing and or trial and error method, genetic algorithm (GA)-based optimization algorithm is implemented to tune PID parameters and FLC membership functions’ range and scaling factors. The optimization function is modeled as a multi-objective problem comprising of frequency weighted RMS seat acceleration, Vibration dose value (VDV), RMS suspension space, and RMS tyre deflection. ISO 2631-1 standard is adopted to assess the ride and health criterion. Results The nonlinear quarter model along with the controller is modeled and simulated and optimized in a Matlab/Simulink environment. It is observed that GA-optimized FLC gives better control as compared to PID and passive suspension system. Further simulations are validated on suspension system with seat and human model. Parameters under observation are frequency-weighted RMS head acceleration, VDV at the head, crest factor, and amplitude ratios at the head and upper torso (AR_h and AR_ut). Simulation results are presented in time and frequency domain. Conclusion Simulation results show that GA-based FLC and PID controller gives better ride comfort and health criterion by reducing RMS head acceleration, VDV at the head, CF, and AR_h and AR_ut over passive suspension system

Entanglement Entropy from a Holographic Viewpoint

The entanglement entropy has been historically studied by many authors in order to obtain quantum mechanical interpretations of the gravitational entropy. The discovery of AdS/CFT correspondence leads to the idea of holographic entanglement entropy, which is a clear solution to this important problem in gravity. In this article, we would like to give a quick survey of recent progresses on the holographic entanglement entropy. We focus on its gravitational aspects, so that it is comprehensible to those who are familiar with general relativity and basics of quantum field theory.Comment: Latex, 30 pages, invited review for Classical and Quantum Gravity, minor correction

Targeting pathogen metabolism without collateral damage to the host

The development of drugs that can inactivate disease-causing cells (e.g. cancer cells or parasites) without causing collateral damage to healthy or to host cells is complicated by the fact that many proteins are very similar between organisms. Nevertheless, due to subtle, quantitative differences between the biochemical reaction networks of target cell and host, a drug can limit the flux of the same essential process in one organism more than in another. We identified precise criteria for this â €network-based' drug selectivity, which can serve as an alternative or additive to structural differences. We combined computational and experimental approaches to compare energy metabolism in the causative agent of sleeping sickness, Trypanosoma brucei, with that of human erythrocytes, and identified glucose transport and glyceraldehyde-3-phosphate dehydrogenase as the most selective antiparasitic targets. Computational predictions were validated experimentally in a novel parasite-erythrocytes co-culture system. Glucose-transport inhibitors killed trypanosomes without killing erythrocytes, neurons or liver cells

Differential Analysis of Ovarian and Endometrial Cancers Identifies a Methylator Phenotype

Despite improved outcomes in the past 30 years, less than half of all women diagnosed with epithelial ovarian cancer live five years beyond their diagnosis. Although typically treated as a single disease, epithelial ovarian cancer includes several distinct histological subtypes, such as papillary serous and endometrioid carcinomas. To address whether the morphological differences seen in these carcinomas represent distinct characteristics at the molecular level we analyzed DNA methylation patterns in 11 papillary serous tumors, 9 endometrioid ovarian tumors, 4 normal fallopian tube samples and 6 normal endometrial tissues, plus 8 normal fallopian tube and 4 serous samples from TCGA. For comparison within the endometrioid subtype we added 6 primary uterine endometrioid tumors and 5 endometrioid metastases from uterus to ovary. Data was obtained from 27,578 CpG dinucleotides occurring in or near promoter regions of 14,495 genes. We identified 36 locations with significant increases or decreases in methylation in comparisons of serous tumors and normal fallopian tube samples. Moreover, unsupervised clustering techniques applied to all samples showed three major profiles comprising mostly normal samples, serous tumors, and endometrioid tumors including ovarian, uterine and metastatic origins. The clustering analysis identified 60 differentially methylated sites between the serous group and the normal group. An unrelated set of 25 serous tumors validated the reproducibility of the methylation patterns. In contrast, >1,000 genes were differentially methylated between endometrioid tumors and normal samples. This finding is consistent with a generalized regulatory disruption caused by a methylator phenotype. Through DNA methylation analyses we have identified genes with known roles in ovarian carcinoma etiology, whereas pathway analyses provided biological insight to the role of novel genes. Our finding of differences between serous and endometrioid ovarian tumors indicates that intervention strategies could be developed to specifically address subtypes of epithelial ovarian cancer

Osteosarcoma microenvironment: whole-slide imaging and optimized antigen detection overcome major limitations in immunohistochemical quantification.

BACKGROUND: In osteosarcoma survival rates could not be improved over the last 30 years. Novel biomarkers are warranted to allow risk stratification of patients for more individual treatment following initial diagnosis. Although previous studies of the tumor microenvironment have identified promising candidates, novel biomarkers have not been translated into routine histopathology. Substantial difficulties regarding immunohistochemical detection and quantification of antigens in decalcified and heterogeneous osteosarcoma might largely explain this translational short-coming. Furthermore, we hypothesized that conventional hot spot analysis is often not representative for the whole section when applied to heterogeneous tissues like osteosarcoma. We aimed to overcome these difficulties for major biomarkers of the immunovascular microenvironment. METHODS: Immunohistochemistry was systematically optimized for cell surface (CD31, CD8) and intracellular antigens (FOXP3) including evaluation of 200 different antigen retrieval conditions. Distribution patterns of these antigens were analyzed in formalin-fixed and paraffin-embedded samples from 120 high-grade central osteosarcoma biopsies and computer-assisted whole-slide analysis was compared with conventional quantification methods including hot spot analysis. RESULTS: More than 96% of osteosarcoma samples were positive for all antigens after optimization of immunohistochemistry. In contrast, standard immunohistochemistry retrieved false negative results in 35-65% of decalcified osteosarcoma specimens. Standard hot spot analysis was applicable for homogeneous distributed FOXP3+ and CD8+ cells. However, heterogeneous distribution of vascular CD31 did not allow reliable quantification with hot spot analysis in 85% of all samples. Computer-assisted whole-slide analysis of total CD31- immunoreactive area proved as the most appropriate quantification method. CONCLUSION: Standard staining and quantification procedures are not applicable in decalcified formalin-fixed and paraffin-embedded samples for major parameters of the immunovascular microenvironment in osteosarcoma. Whole-slide imaging and optimized antigen retrieval overcome these limitations

Gender differences in the use of cardiovascular interventions in HIV-positive persons; the D:A:D Study

Peer reviewe