Risk homeostasis theory in simulated environments

This thesis has two aims. First, it sets out to develop an alternative methodology for the investigation of risk homeostasis theory (RHT). It is argued that the current methodologies of the pseudo-experimental design and post hoc analysis of road-traffic accident data both have their limitations, and that the newer 'game' type simulation exercises are also, but for different reasons, incapable of testing RHT predictions. The alternative methodology described here is based on the simulation of physical risk with intrinsic reward rather than a 'points pay-off'. The second aim of the thesis is to examine a number of predictions made by RHT through the use of this alternative methodology. Since the pseudo-experimental design and post hoc analysis of road-traffic data are both ill-suited to the investigation of that part of RHT which deals with the role of utility in determining risk-taking behaviour in response to a change in environmental risk, and since the concept of utility is critical to RHT, the methodology reported here is applied to the specific investigation of utility. Attention too is given to the question of which behavioural pathways carry the homeostasis effect, and whether those pathways are 'local' to the nature of the change in environmental risk. It is suggested that investigating RHT through this new methodology holds a number of advantages and should be developed further in an attempt to answer the RHT question. It is suggested too that the methodology allows RHT to be seen in a psychological context, rather than the statistical context that has so far characterised its investigation. The experimental findings reported here are in support of hypotheses derived from RHT and would therefore seem to argue for the importance of the individual and collective target level of risk, as opposed to the level of environmental risk, as the major determinant of accident loss

Risk homeostasis theory - A study of intrinsic compensation

Risk homeostasis theory (RHT) suggests that changes made to the intrinsic risk of environments are negated in one of three ways: behavioural adjustments within the environment, mode migration, and avoidance of the physical risk. To date, this three-way model of RHT has little empirical support, whilst research findings on RHT have at times been diametrically opposed. A reconciliation of apparently opposing findings might be possible by suggesting that extrinsic compensation fails to restore previously existing levels of actual risk in cases where behavioural adjustments within the environment are incapable of negating intrinsic risk changes. This paper reports a study in which behavioural adjustments within the physical risk-taking environment are capable of reconciling target with actual risk. The results provide positive support for RHT in the form of overcompensation for the intrinsic risk change on specific driver behaviours

Identification of a novel NAMPT inhibitor by CRISPR/Cas9 chemogenomic profiling in mammalian cells

Chemogenomic profiling is a powerful and unbiased approach to elucidate targets and mechanism of bioactive compounds. Until recently, high-quality experiments of this nature have been limited to fungal systems due to lack of mammalian genome-wide deletion collections. Here we show that the CRISPR/Cas9 system enables the generation of such libraries and allows for the identification of targets and pathways mediating hypersensitivity and resistance relevant to the compound mechanism of action, using a novel NAMPT inhibitor as an example

CRISPR-UMI : single-cell lineage tracing of pooled CRISPR-Cas9 screens

Pooled CRISPR screens are a powerful tool for assessments of gene function. However, conventional analysis is based exclusively on the relative abundance of integrated single guide RNAs (sgRNAs) between populations, which does not discern distinct phenotypes and editing outcomes generated by identical sgRNAs. Here we present CRISPR-UMI, a single-cell lineage-tracing methodology for pooled screening to account for cell heterogeneity. We generated complex sgRNA libraries with unique molecular identifiers (UMIs) that allowed for screening of clonally expanded, individually tagged cells. A proof-of-principle CRISPR-UMI negative-selection screen provided increased sensitivity and robustness compared with conventional analysis by accounting for underlying cellular and editing-outcome heterogeneity and detection of outlier clones. Furthermore, a CRISPR-UMI positive-selection screen uncovered new roadblocks in reprogramming mouse embryonic fibroblasts as pluripotent stem cells, distinguishing reprogramming frequency and speed (i.e., effect size and probability). CRISPR-UMI boosts the predictive power, sensitivity, and information content of pooled CRISPR screens