With the prevalence of hepatitis C virus expected to decline, the proportion of hepatocellular carcinoma (HCC) related to non-alcoholic steatohepatitis (NASH) is anticipated to increase exponentially due to the growing epidemic of obesity and diabetes. The annual incidence rate of developing HCC in patients with NASH-related cirrhosis is not clearly understood with rates ranging from 2.6%-12.8%. While multiple new mechanisms have been implicated in the development of HCC in NASH; further prospective long-term studies are needed to validate these findings. Recent evidence has shown a significant proportion of patients with non-alcoholic fatty liver disease and NASH progress to HCC in the absence of cirrhosis. Liver resection and transplantation represent curative therapeutic options in select NASH-related HCC patients but have placed a significant burden to our healthcare resources and utilization. Currently NASH-related HCC is the fastest growing indication for liver transplant in HCC candidates. Increased efforts to implement effective screening and preventative strategies, particularly in non-cirrhotic NASH patients, are needed to reduce the future impact imposed by NASH-related HCC.

An analysis of available methods of dealing with polymer crystallization for process modeling is presented. Problems encountered in using isothermal data to predict nonisothermal results are discussed and illustrated using experimental data for nylon 6. A half‐time analysis is used to evaluate and extrapolate the isothermal crystallization rates. It is concluded that none of the available models are entirely satisfactory for computing nonisothermal crystallization from isothermal data, though the Nakamura model is shown to be more satisfactory for process modeling than other models discussed in the literature. A nonlinear regression method is presented for directly fitting nonisothermal crystallinity data using the Nakamura model to obtain crystallization rate equation parameters. Two empirical methods for including amorphous orientation effects are also considered and evaluated by comparing predicted results to online experimental data for melt spinning of nylon 6.

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