Copolymers of methacrylate and styrene, the main components of many solvent-based automotive coating formulations, are produced under higher temperature starved-feed conditions in order to reduce the solvent level while controlling polymer composition. Under these conditions methacrylate depropagation has a significant impact on polymer molecular weights and free monomer concentrations in the reactor. Meanwhile, a strong penultimate effect has been observed for this binary system at lower temperatures, also affecting the polymerization rate. In this work, the combined effect of depropagation and penultimate copolymerization kinetics is investigated. The copolymer-averaged propagation rate coefficient for butyl methacrylate and styrene is determined as a function of monomer composition using pulsed-laser polymerization over a range of temperatures. A clear penultimate effect is seen even at the elevated temperatures at which depropagation is important. Radical and monomer reactivity ratios show a negligible temperature dependency between 50 and 150 °C. The Lowry case 1 representation adequately describes the effect of methacrylate depropagation over the range of conditions examined.

Acrylic copolymers produced via high-temperature solution polymerization are the base resin component for many automotive coatings. These polymers are often manufactured using a semibatch starved-feed reactor policy in order to tightly control copolymer composition and molecular weight. The combination of high temperature and low monomer concentration greatly promotes the importance of secondary reactions, causing observed conversion and molecular weight profiles to deviate significantly from those predicted by classic free radical kinetics. Although the effects of methacrylate depropagation and acrylate branching and scission have been studied during the homopolymerizations of butyl methacrylate and butyl acrylate, there is little knowledge as to how these mechanisms interact during copolymerization. In this work, we experimentally investigate the effect of monomer feed ratio on molecular weight and conversion profiles for high-temperature semibatch solution copolymerization of butyl methacrylate and butyl acrylate. A mechanistic model, constructed and implemented in Predici, provides a good fit to the experimental data set without any tuning of kinetic coefficients or other parameters. IntroductionThe objective of kinetic modeling is to build a description of how polymer architecture and polymerization rate depend on reaction conditions (temperature, pressure) and species concentrations from a defined set of kinetic mechanisms. This kinetic representation is a critical component of larger-scale process models used to predict the influence of operating conditions on reaction rate and polymer properties, guide (along with appropriate experimentation) the selection and optimization of standard operating conditions for existing and new polymer grades, guide process development from laboratory to pilot-plant to full-scale production, help to discriminate between kinetic and physical (e.g., heat and mass transfer) effects, perform design and safety studies, train plant personnel, and understand and optimize transitions and other dynamic behavior (i.e., process control). Harmon Ray pioneered the development of a sound mathematical framework for treatment of polymerization kinetics 1 so that they could be coupled with detailed models of the physical complexities inherent to many polymerization systems. 2 These efforts were instrumental to the developing field of polymer reaction engineering and also provided important motivation for the development of new experimental techniques to accurately measure polymerization rate coefficients, which to that point suffered from order of magnitude uncertainty. 3,4

Gliomas are the most common brain tumors of the center nervous system. And long non-coding RNAs (lncRNAs) are non-protein coding transcripts, which have been considered as one type of gene expression regulator for cancer development. In this study, we investigated the role of lncRNA-TP53TG1 in response to glucose deprivation in human gliomas. The expression levels of TP53TG1 in glioma tissues and cells were analyzed by qRT-PCR. In addition, the influence of TP53TG1 on glucose metabolism related genes at the mRNA level during both high and low glucose treatment was detected by qRT-PCR. MTT, clonogenicity assays, and flow cytometry were performed to detect the cell proliferation and cell apoptosis. Furthermore, the migration of glioma cells was examined by Transwell assays. The expression of TP53TG1 was significantly higher in human glioma tissues or cell lines compared with normal brain tissue or NHA. Moreover, TP53TG1 and some tumor glucose metabolism related genes, such as GRP78, LDHA, and IDH1 were up-regulated significantly in U87 and LN18 cells under glucose deprivation. In addition, knockdown of TP53TG1 decreased cell proliferation and migration and down-regulated GRP78 and IDH1 expression levels and up-regulated PKM2 levels in U87 cells under glucose deprivation. However, over-expression of TP53TG1 showed the opposite tendency. Moreover, the effects of TP53TG1 were more remarkable in low glucose than that in high glucose. Our data showed that TP53TG1 under glucose deprivation may promote cell proliferation and migration by influencing the expression of glucose metabolism related genes in glioma. J. Cell. Biochem. 118: 4897-4904, 2017. © 2017 Wiley Periodicals, Inc.

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