Estrogen induces estrogen receptor alpha-dependent cAMP response element-binding protein phosphorylation via mitogen activated protein kinase pathway in basal forebrain cholinergic neurons in vivo

In addition to classical genomic mechanisms, estrogen also exerts nonclassical effects via a signal transduction system on neurons. To study whether estrogen has a nonclassical effect on basal forebrain cholinergic system, we measured the intensity of cAMP response element-binding protein (CREB) phosphorylation (pCREB) in cholinergic neurons after administration of 17 beta-estradiol to ovariectomized (OVX) mice. A significant time-dependent increase in the number of pCREB-positive cholinergic cells was detected after estrogen administration in the medial septum-diagonal band (MS-DB) and the substantia innominata ( SI). The increase was first observed 15 min after estrogen administration. The role of classical estrogen receptors (ERs) was evaluated using ER knock-out mice in vivo. The estrogen-induced CREB phosphorylation in cholinergic neurons was present in ER beta knock-out mice but completely absent in ER beta knock-out mice in MS-DB and SI. A series of in vitro studies demonstrated that estrogen acted directly on cholinergic neurons. Selective blockade of the mitogen activated protein kinase (MAPK) pathway in vivo completely prevented estrogen-induced CREB phosphorylation in cholinergic neurons in MS-DB and SI. In contrast, blockade of protein kinase A (PKA) was effective only in SI. Finally, studies in intact female mice revealed levels of CREB phosphorylation within cholinergic neurons that were similar to those of estrogen-treated OVX mice. These observations demonstrate an ER alpha-mediated nonclassical effect of estrogen on the cholinergic neurons and that these actions are present under physiological conditions. They also reveal the role of MAPK and PKA-MAPK pathway activation in nonclassical estrogen signaling in the basal forebrain cholinergic neurons in vivo

Estrogen Up-regulates Apolipoprotein E (ApoE) Gene Expression by Increasing ApoE mRNA in the Translating Pool via the Estrogen Receptor α-Mediated Pathway

The antiatherogenic property of estrogens is mediated via at least two mechanisms: first by affecting plasma lipoprotein profiles, and second by affecting the components of the vessel wall. Raising plasma apolipoprotein E (apoE) in mice protects them against diet-induced atherosclerosis (Shimano, H., Yamada, N., Katsuki, M., Gotoda, T., Harada, K., Murase, T., Fukuzawa, C., Takaku, F., and Yazaka, Y. (1992) Proc. Natl. Acad. Sci. U. S. A. 89, 1750-1754). It is possible that estrogen may be antiatherogenic at least in part by increasing plasma apoE levels. Therefore, we studied the regulation of apoE by estrogen. A survey of 15 inbred strains of mice showed that some mouse strains responded to injections or subcutaneously implanted pellets of estradiol by raising their apoB and apoE levels and some did not. We performed detailed studies in two "responder" strains, C57L and C57BL, and two "non-responder" strains, C3H and BALBc. Responders increased their plasma apoE levels 2.5-fold. Non-responders' levels were altered +/-10%. In the responders the distribution of apoE among the plasma lipoproteins shifted from high density lipoprotein toward the apoB-containing lipoprotein fractions. In nonresponders the shift was toward high density lipoprotein. Hepatic apoE mRNA levels and relative rates of apoE mRNA transcription were unchanged in all strains, suggesting that apoE regulation occurred at posttranscriptional loci. Therefore, we measured apoE synthesis in fresh liver slices and on isolated hepatic polysomes. Two-fold increases were noted but only in responders accompanied by selective 1.5-fold increases in polysomal apoE mRNA levels. Similar increases in apoE synthesis were also observed in castrated C57BL mice given either physiological or pharmacological replacement doses of estradiol, but not testosterone, suggesting that the effect of estradiol was specific on the distribution of apoE mRNA in the translationally active polysomal pool. Next, we examined whether the effects of estrogen on apoE translation were mediated by estrogen receptors (ER). ER-alpha knock-out mice and their wild-type littermates were administered estradiol. As expected, apoE levels and hepatic apoE synthesis increased more than 2-fold in the wild-type littermates, but only 20% increases in the plasma apoE and hepatic synthesis were observed in the ER knock-out mice. Hepatic apoE mRNA levels did not change in either the wild-type or the ER knock-out mice. Thus, estradiol up-regulates apoE gene expression by increasing levels of apoE mRNA in the polysomal translating pool. Furthermore, the increased polysomal recruitment of apoE mRNA is largely mediated by estrogen receptors

Modelling and optimal control of blood glucose levels in the human body

Regulating the blood glucose level is a challenging control problem for the human body. Abnormal blood glucose levels can cause serious health problems over time, including diabetes. Although several mathematical models have been proposed to describe the dynamics of glucose-insulin interaction, none of them have been universally adopted by the research community. In this paper, we consider a dynamic model of the blood glucose regulatory system originally proposed by Liu and Tang in 2008. This model consists of eight state variables naturally divided into three subsystems: the glucagon and insulin transition subsystem, the receptor binding subsystem and the glucosesubsystem. The model contains 36 model parameters, many of which are unknown and difficult to determine accurately. We formulate an optimal parameter selection problem in which optimal values for the model parameters must be selected so that the resulting model best its given experimental data.We demonstrate that this optimal parameter selection problem can be solved readily using the optimal control software MISER 3.3. Using this approach, significant improvements can be made in matching the model to the experimental data. We also investigate the sensitivity of the resulting optimizedmodel with respect to the insulin release rate. Finally, we use MISER 3.3 to determine optimal open loop controls for the optimized model