Using logic models in research and evaluation of Health EDRM interventions

This chapter outlines how logic models can be used to conceptualize how interventions are intended to work, and their relationship with the broader context in which they take place – focusing on Health EDRM settings. Logic models are tools used to outline assumptions about the chains of processes, activities or events expected to occur during the implementation of an intervention, and the way in which these lead to changes in outcomes. They provide an initial set of assumptions about how different components of an intervention are expected to change outcomes, and can be used to develop further sub-research questions to investigate the validity of these assumptions. Logic models can also be used to communicate findings from research and evaluation activities, and can serve as useful tools in planning an intervention, including for the identification of relevant outcomes and monitoring of its delivery. However, this chapter will focus primarily on the use of logic models for research and evaluation purposes

Nonheritable Cellular Variability Accelerates the Evolutionary Processes of Cancer

Heritable genetic or epigenetic changes in cells are thought to drive tumor development, metastasis, and drug resistance. This essay discusses the possibility that nonheritable phenotypic variability contributes to the evolution of cancer, suggesting new approaches to treatment

Mathematics and biology: a Kantian view on the history of pattern formation theory

Driesch’s statement, made around 1900, that the physics and chemistry of his day were unable to explain self-regulation during embryogenesis was correct and could be extended until the year 1972. The emergence of theories of self-organisation required progress in several areas including chemistry, physics, computing and cybernetics. Two parallel lines of development can be distinguished which both culminated in the early 1970s. Firstly, physicochemical theories of self-organisation arose from theoretical (Lotka 1910–1920) and experimental work (Bray 1920; Belousov 1951) on chemical oscillations. However, this research area gained broader acceptance only after thermodynamics was extended to systems far from equilibrium (1922–1967) and the mechanism of the prime example for a chemical oscillator, the Belousov–Zhabotinski reaction, was deciphered in the early 1970s. Secondly, biological theories of self-organisation were rooted in the intellectual environment of artificial intelligence and cybernetics. Turing wrote his The chemical basis of morphogenesis (1952) after working on the construction of one of the first electronic computers. Likewise, Gierer and Meinhardt’s theory of local activation and lateral inhibition (1972) was influenced by ideas from cybernetics. The Gierer–Meinhardt theory provided an explanation for the first time of both spontaneous formation of spatial order and of self-regulation that proved to be extremely successful in elucidating a wide range of patterning processes. With the advent of developmental genetics in the 1980s, detailed molecular and functional data became available for complex developmental processes, allowing a new generation of data-driven theoretical approaches. Three examples of such approaches will be discussed. The successes and limitations of mathematical pattern formation theory throughout its history suggest a picture of the organism, which has structural similarity to views of the organic world held by the philosopher Immanuel Kant at the end of the eighteenth century

Development of novel adenoviral vectors to overcome challenges observed with HAdV-5 based constructs

Recombinant vectors based on human adenovirus serotype 5 (HAdV-5) have been extensively studied in pre-clinical models and clinical trials over the last two decades. However, the thorough understanding of the HAdV-5 interaction with human subjects has uncovered major concerns about its product applicability. High vector-associated toxicity and widespread pre-existing immunity have been shown to significantly impede the effectiveness of HAdV-5 mediated gene transfer. It is therefore that the in depth knowledge attained working on HAdV-5 is currently being used to develop alternative vectors. Here, we provide a comprehensive overview of data obtained in recent years disqualifying the HAdV-5 vector for systemic gene delivery as well as novel strategies being pursued to overcome the limitations observed with particular emphasis on the ongoing vectorization efforts to obtain vectors based on alternative serotypes

Rewriting DNA Methylation Signatures at Will:The Curable Genome Within Reach?

DNA methyltransferases are important enzymes in a broad range of organisms. Dysfunction of DNA methyltransferases in humans leads to many severe diseases, including cancer. This book focuses on the biochemical properties of these enzymes, describing their structures and mechanisms in bacteria, humans and other species, including plants, and also explains the biological processes of reading of DNA methylation and DNA demethylation. It covers many emerging aspects of the biological roles of DNA methylation functioning as an essential epigenetic mark and describes the role of DNA methylation in diseases. Moreover, the book explains modern technologies, like targeted rewriting of DNA methylation by designed DNA methyltransferases, as well as technological applications of DNA methyltransferases in DNA labelling. Finally, the book summarizes recent methods for the analysis of DNA methylation in human DNA. Overall, this book represents a comprehensive state-of-the-art- work and is a must-have for advanced researchers in the field of DNA methylation and epigenetics

The Effectiveness of Contract Farming for Raising Income of Smallholder Farmers in Low- and Middle-Income Countries: a Systematic Review

Contract farming is used by an increasing number of firms as a preferred modality to source products from smallholder farmers in low and middle-income countries. Quality requirements of consumers, economies of scale in production or land ownership rights are common incentives for firms to offer contractual arrangements to farmers. Prices and access to key technology, key inputs or support services are the main incentives for farmers to enter into these contracts. There is great heterogeneity in contract farming, with differences in contracts, farmers, products, buyers, and institutional environments. The last decade shows a rapid increase in studies that use quasi-experimental research designs to assess the effects of specific empirical instances of contract farming on smallholders. The objective of this systematic review was to distill generalised inferences from this rapidly growing body of evidence. The review synthesised the studies in order to answer two questions: 1: What is known about the effect size of contract farming on income and food security of smallholder farmers in low- and middle-income countries? 2: Under which enabling or limiting conditions are contract farming arrangements effective for improving income and food security of smallholders

Mapping the Environmental Fitness Landscape of a Synthetic Gene Circuit

Gene expression actualizes the organismal phenotypes encoded within the genome in an environment-dependent manner. Among all encoded phenotypes, cell population growth rate (fitness) is perhaps the most important, since it determines how well-adapted a genotype is in various environments. Traditional biological measurement techniques have revealed the connection between the environment and fitness based on the gene expression mean. Yet, recently it became clear that cells with identical genomes exposed to the same environment can differ dramatically from the population average in their gene expression and division rate (individual fitness). For cell populations with bimodal gene expression, this difference is particularly pronounced, and may involve stochastic transitions between two cellular states that form distinct sub-populations. Currently it remains unclear how a cell population's growth rate and its subpopulation fractions emerge from the molecular-level kinetics of gene networks and the division rates of single cells. To address this question we developed and quantitatively characterized an inducible, bistable synthetic gene circuit controlling the expression of a bifunctional antibiotic resistance gene in Saccharomyces cerevisiae. Following fitness and fluorescence measurements in two distinct environments (inducer alone and antibiotic alone), we applied a computational approach to predict cell population fitness and subpopulation fractions in the combination of these environments based on stochastic cellular movement in gene expression space and fitness space. We found that knowing the fitness and nongenetic (cellular) memory associated with specific gene expression states were necessary for predicting the overall fitness of cell populations in combined environments. We validated these predictions experimentally and identified environmental conditions that defined a “sweet spot” of drug resistance. These findings may provide a roadmap for connecting the molecular-level kinetics of gene networks to cell population fitness in well-defined environments, and may have important implications for phenotypic variability of drug resistance in natural settings

Using viral vectors as gene transfer tools (Cell Biology and Toxicology Special Issue: ETCS-UK 1 day meeting on genetic manipulation of cells)

In recent years, the development of powerful viral gene transfer techniques has greatly facilitated the study of gene function. This review summarises some of the viral delivery systems routinely used to mediate gene transfer into cell lines, primary cell cultures and in whole animal models. The systems described were originally discussed at a 1-day European Tissue Culture Society (ETCS-UK) workshop that was held at University College London on 1st April 2009. Recombinant-deficient viral vectors (viruses that are no longer able to replicate) are used to transduce dividing and post-mitotic cells, and they have been optimised to mediate regulatable, powerful, long-term and cell-specific expression. Hence, viral systems have become very widely used, especially in the field of neurobiology. This review introduces the main categories of viral vectors, focusing on their initial development and highlighting modifications and improvements made since their introduction. In particular, the use of specific promoters to restrict expression, translational enhancers and regulatory elements to boost expression from a single virion and the development of regulatable systems is described

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders