Various researchers and policy analysts have made empirical studies of innovation systems in order to understand their current structure and trace their dynamics. However, policy makers often experience difficulties in extracting practical guidelines from studies of this kind. In this paper, we operationalize our previous work on a functional approach to analyzing innovation system dynamics into a practical scheme of analysis for policy makers. The scheme is based on previous literature and our own experience in developing and applying functional thinking. It can be used by policy makers not only to identify the key policy issues but also to set policy goals.

The rat, mouse and human estrogen receptor (ER) exists as two subtypes, ER alpha and ER beta, which differ in the C-terminal ligand-binding domain and in the N-terminal transactivation domain. In this study, we investigated the estrogenic activity of environmental chemicals and phytoestrogens in competition binding assays with ER alpha or ER beta protein, and in a transient gene expression assay using cells in which an acute estrogenic response is created by cotransfecting cultures with recombinant human ER alpha or ER beta complementary DNA (cDNA) in the presence of an estrogen-dependent reporter plasmid. Saturation ligand-binding analysis of human ER alpha and ER beta protein revealed a single binding component for [3H]-17beta-estradiol (E2) with high affinity [dissociation constant (Kd) = 0.05 - 0.1 nM]. All environmental estrogenic chemicals [polychlorinated hydroxybiphenyls, dichlorodiphenyltrichloroethane (DDT) and derivatives, alkylphenols, bisphenol A, methoxychlor and chlordecone] compete with E2 for binding to both ER subtypes with a similar preference and degree. In most instances the relative binding affinities (RBA) are at least 1000-fold lower than that of E2. Some phytoestrogens such as coumestrol, genistein, apigenin, naringenin, and kaempferol compete stronger with E2 for binding to ER beta than to ER alpha. Estrogenic chemicals, as for instance nonylphenol, bisphenol A, o, p'-DDT and 2',4',6'-trichloro-4-biphenylol stimulate the transcriptional activity of ER alpha and ER beta at concentrations of 100-1000 nM. Phytoestrogens, including genistein, coumestrol and zearalenone stimulate the transcriptional activity of both ER subtypes at concentrations of 1-10 nM. The ranking of the estrogenic potency of phytoestrogens for both ER subtypes in the transactivation assay is different; that is, E2 >> zearalenone = coumestrol > genistein > daidzein > apigenin = phloretin > biochanin A = kaempferol = naringenin > formononetin = ipriflavone = quercetin = chrysin for ER alpha and E2 >> genistein = coumestrol > zearalenone > daidzein > biochanin A = apigenin = kaempferol = naringenin > phloretin = quercetin = ipriflavone = formononetin = chrysin for ER beta. Antiestrogenic activity of the phytoestrogens could not be detected, except for zearalenone which is a full agonist for ER alpha and a mixed agonist-antagonist for ER beta. In summary, while the estrogenic potency of industrial-derived estrogenic chemicals is very limited, the estrogenic potency of phytoestrogens is significant, especially for ER beta, and they may trigger many of the biological responses that are evoked by the physiological estrogens.

The rat estrogen receptor (ER) exists as two subtypes, ER alpha and ER beta, which differ in the C-terminal ligand binding domain and in the N-terminal transactivation domain. In this study we investigated the messenger RNA expression of both ER subtypes in rat tissues by RT-PCR and compared the ligand binding specificity of the ER subtypes. Saturation ligand binding analysis of in vitro synthesized human ER alpha and rat ER beta protein revealed a single binding component for 16 alpha-iodo-17 beta-estradiol with high affinity [dissociation constant (Kd) = 0.1 nM for ER alpha protein and 0.4 nM for ER beta protein]. Most estrogenic substances or estrogenic antagonists compete with 16 alpha-[125I]iodo-17 beta-estradiol for binding to both ER subtypes in a very similar preference and degree; that is, diethylstilbestrol > hexestrol > dienestrol > 4-OH-tamoxifen > 17 beta-estradiol > coumestrol, ICI-164384 > estrone, 17 alpha-estradiol > nafoxidine, moxestrol > clomifene > estriol, 4-OH-estradiol > tamoxifen, 2-OH-estradiol, 5-androstene-3 beta, 17 beta-diol, genistein for the ER alpha protein and dienestrol > 4-OH-tamoxifen > diethylstilbestrol > hexestrol > coumestrol, ICI-164384 > 17 beta-estradiol > estrone, genistein > estriol > nafoxidine, 5-androstene-3 beta, 17 beta-diol > 17 alpha-estradiol, clomifene, 2-OH-estradiol > 4-OH-estradiol, tamoxifen, moxestrol for the ER beta protein. The rat tissue distribution and/or the relative level of ER alpha and ER beta expression seems to be quite different, i.e. moderate to high expression in uterus, testis, pituitary, ovary, kidney, epididymis, and adrenal for ER alpha and prostate, ovary, lung, bladder, brain, uterus, and testis for ER beta. The described differences between the ER subtypes in relative ligand binding affinity and tissue distribution could contribute to the selective action of ER agonists and antagonists in different tissues.

Contemporary theories of entrepreneurship generally focus on the recognition of opportunities and the decision to exploit them. Although the entrepreneurship literature treats opportunities as exogenous, the prevailing theory of economic growth suggests they are endogenous. This paper advances the microeconomic foundations of endogenous growth theory by developing a knowledge spillover theory of entrepreneurship. Knowledge created endogenously results in knowledge spillovers, which allow entrepreneurs to identify and exploit opportunities.

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