The emergence threshold in our model was defined as the number of resistant lesions at the start of a growing season giving a specified low probability of extinction in the absence of new mutations. In experiments, it would not be possible to use this threshold as the generation of new mutations by the sensitive pathogen population cannot be stopped. However, it may be possible to design experiments that determine the time that it takes for a resistant strain to arise in a completely sensitive pathogen population and subsequently invade this population until it constitutes a specified very small threshold frequency in the pathogen population. It is important to note that the emergence threshold is a number of resistant lesions, which applies irrespective of the size of the sensitive pathogen population. For PKM2 inhibitor small pathogen populations, the emergence threshold corresponds to a higher frequency of the resistant strain in the pathogen population than for a large pathogen population and the required sample size to detect the resistant strain early may be less. However, for smaller populations, the time until a resistant mutant arises will be longer than for a large pathogen population. In this study, we formulated a model structure to describe the emergence of resistance in a sensitive pathogen population. The resistance simulated was representative of observed cases where a mutation affecting the target protein results in a large shift in sensitivity. We subsequently showed how the model could be used to evaluate the usefulness of treatment strategies for delaying the emergence of such resistance. There are important conclusions from the model output which have implications for practical resistance management. In the absence of previous exposure to high-risk fungicides with the same mode of action, the model output suggests that resistance to high-risk fungicides is likely to emerge after their introduction on the market, making it important that anti-resistance strategies implemented at introduction are effective against both emergence and selection. Our analysis suggests that the dose and mixture treatment strategies which have been shown previously to reduce selection for resistance in the selection phase, may also be effective in prolonging the emergence phase in the evolution of resistance to fungicides. Liver plays an essential role in ethanol metabolism. Chronic consumption of alcohol can lead to fatty liver, alcoholic hepatitis and development of cirrhosis. The pathogenesis of ethanolinduced liver injury is complex and involves, among other factors, gut-derived lipopolysaccharide, cytokines, the innate immune system, oxidative stress, Fadrozole as well as the interactions of these factors with intracellular signaling pathways. A major molecular mechanism is the lipid peroxidation and oxidative stress induced by alcohol, which is a focus of considerable research. Despite much research, the mechanisms by which alcohol causes cell injury are still not fully understand. Alcohol is metabolized in hepatocytes through oxidation to acetaldehyde and subsequently from acetaldehyde to acetate as catalyzed by various enzymes or enzymatic systems, including the alcohol dehydrogenase and aldehyde dehydrogenase pathways, cytochrome P450 2E1 system and catalase. CYP2E1, which is up-regulated with chronic alcoholic ingestion, is an important source of reactive oxygen species generation and contributor to oxidative stress in the liver.