Trade regimes and GATT: resource-intensive vs. knowledge intensive growth

Trading blocks can help or hinder the liberalization of world trade. A determining factor is whether trade within the block is organized around traditional comparative advantages, or around economies of scale. Regional free trade agreements such as NAFTA can be a substitutes for global free trade when they are based on traditional comparative advantages; then each regional market develops market power and incentives to impose tariffs on the rest of the word. Alternatively, regional trade agreements can be complementary to global free trade. This occurs when the blocks are organized around the exploitation of economies of scale and based on knowledge-intensive sectors. I establish that external economies of scale produce incentives for expanded trade; they can defeat the standard argument for "optimal tariffs" and mitigate another negative feature of trading blocks: their tendency to divert trade from efficient to inefficient sources. The emergence of regional blocks organized around economies of scale can therefore lead to increasingly open international markets. I discuss policy implications for the EU and for free trade in the Americas

The frequency-dependent Wright-Fisher model: diffusive and non-diffusive approximations

We study a class of processes that are akin to the Wright-Fisher model, with transition probabilities weighted in terms of the frequency-dependent fitness of the population types. By considering an approximate weak formulation of the discrete problem, we are able to derive a corresponding continuous weak formulation for the probability density. Therefore, we obtain a family of partial differential equations (PDE) for the evolution of the probability density, and which will be an approximation of the discrete process in the joint large population, small time-steps and weak selection limit. If the fitness functions are sufficiently regular, we can recast the weak formulation in a more standard formulation, without any boundary conditions, but supplemented by a number of conservation laws. The equations in this family can be purely diffusive, purely hyperbolic or of convection-diffusion type, with frequency dependent convection. The particular outcome will depend on the assumed scalings. The diffusive equations are of the degenerate type; using a duality approach, we also obtain a frequency dependent version of the Kimura equation without any further assumptions. We also show that the convective approximation is related to the replicator dynamics and provide some estimate of how accurate is the convective approximation, with respect to the convective-diffusion approximation. In particular, we show that the mode, but not the expected value, of the probability distribution is modelled by the replicator dynamics. Some numerical simulations that illustrate the results are also presented

Mammary epithelial cell transformation: insights from cell culture and mouse models

Normal human mammary epithelial cells (HMECs) have a finite life span and do not undergo spontaneous immortalization in culture. Critical to oncogenic transformation is the ability of cells to overcome the senescence checkpoints that define their replicative life span and to multiply indefinitely – a phenomenon referred to as immortalization. HMECs can be immortalized by exposing them to chemicals or radiation, or by causing them to overexpress certain cellular genes or viral oncogenes. However, the most efficient and reproducible model of HMEC immortalization remains expression of high-risk human papillomavirus (HPV) oncogenes E6 and E7. Cell culture models have defined the role of tumor suppressor proteins (pRb and p53), inhibitors of cyclin-dependent kinases (p16(INK4a), p21, p27 and p57), p14(ARF), telomerase, and small G proteins Rap, Rho and Ras in immortalization and transformation of HMECs. These cell culture models have also provided evidence that multiple epithelial cell subtypes with distinct patterns of susceptibility to oncogenesis exist in the normal mammary tissue. Coupled with information from distinct molecular portraits of primary breast cancers, these findings suggest that various subtypes of mammary cells may be precursors of different subtypes of breast cancers. Full oncogenic transformation of HMECs in culture requires the expression of multiple gene products, such as SV40 large T and small t, hTERT (catalytic subunit of human telomerase), Raf, phosphatidylinositol 3-kinase, and Ral-GEFs (Ral guanine nucleotide exchange factors). However, when implanted into nude mice these transformed cells typically produce poorly differentiated carcinomas and not adenocarcinomas. On the other hand, transgenic mouse models using ErbB2/neu, Ras, Myc, SV40 T or polyomavirus T develop adenocarcinomas, raising the possibility that the parental normal cell subtype may determine the pathological type of breast tumors. Availability of three-dimensional and mammosphere models has led to the identification of putative stem cells, but more studies are needed to define their biologic role and potential as precursor cells for distinct breast cancers. The combined use of transformation strategies in cell culture and mouse models together with molecular definition of human breast cancer subtypes should help to elucidate the nature of breast cancer diversity and to develop individualized therapies

HER-2 overexpression differentially alters transforming growth factor-β responses in luminal versus mesenchymal human breast cancer cells

INTRODUCTION: Amplification of the HER-2 receptor tyrosine kinase has been implicated in the pathogenesis and aggressive behavior of approximately 25% of invasive human breast cancers. Clinical and experimental evidence suggest that aberrant HER-2 signaling contributes to tumor initiation and disease progression. Transforming growth factor beta (TGF-β) is the dominant factor opposing growth stimulatory factors and early oncogene activation in many tissues, including the mammary gland. Thus, to better understand the mechanisms by which HER-2 overexpression promotes the early stages of breast cancer, we directly assayed the cellular and molecular effects of TGF-β1 on breast cancer cells in the presence or absence of overexpressed HER-2. METHODS: Cell proliferation assays were used to determine the effect of TGF-β on the growth of breast cancer cells with normal or high level expression of HER-2. Affymetrix microarrays combined with Northern and western blot analysis were used to monitor the transcriptional responses to exogenous TGF-β1 in luminal and mesenchymal-like breast cancer cells. The activity of the core TGF-β signaling pathway was assessed using TGF-β1 binding assays, phospho-specific Smad antibodies, immunofluorescent staining of Smad and Smad DNA binding assays. RESULTS: We demonstrate that cells engineered to over-express HER-2 are resistant to the anti-proliferative effect of TGF-β1. HER-2 overexpression profoundly diminishes the transcriptional responses induced by TGF-β in the luminal MCF-7 breast cancer cell line and prevents target gene induction by a novel mechanism that does not involve the abrogation of Smad nuclear accumulation, DNA binding or changes in c-myc repression. Conversely, HER-2 overexpression in the context of the mesenchymal MDA-MB-231 breast cell line potentiated the TGF-β induced pro-invasive and pro-metastatic gene signature. CONCLUSION: HER-2 overexpression promotes the growth and malignancy of mammary epithelial cells, in part, by conferring resistance to the growth inhibitory effects of TGF-β. In contrast, HER-2 and TGF-β signaling pathways can cooperate to promote especially aggressive disease behavior in the context of a highly invasive breast tumor model

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.Comment: 33 pages, 9 figure

The economic effects of illegal migration under the minimum wage policy of a source country

This research note extends Bond and Chen's analysis of illegal migration by assuming that the source country is a developing country in which there is a minimum wage policy. We examine how the minimum wage of the source country and enforcement by the host affect factor prices, migration, unemployment and economic welfare. We find that the enforcement effect is clear and intuitive, but the qualitative effect of the minimum wage depends on the wage elasticity of employment in the source country. Copyright (c) 2007 the author(s). Journal compilation (c) 2007 RSAI.