Null Models of Economic Networks: The Case of the World Trade Web

In all empirical-network studies, the observed properties of economic networks are informative only if compared with a well-defined null model that can quantitatively predict the behavior of such properties in constrained graphs. However, predictions of the available null-model methods can be derived analytically only under assumptions (e.g., sparseness of the network) that are unrealistic for most economic networks like the World Trade Web (WTW). In this paper we study the evolution of the WTW using a recently-proposed family of null network models. The method allows to analytically obtain the expected value of any network statistic across the ensemble of networks that preserve on average some local properties, and are otherwise fully random. We compare expected and observed properties of the WTW in the period 1950-2000, when either the expected number of trade partners or total country trade is kept fixed and equal to observed quantities. We show that, in the binary WTW, node-degree sequences are sufficient to explain higher-order network properties such as disassortativity and clustering-degree correlation, especially in the last part of the sample. Conversely, in the weighted WTW, the observed sequence of total country imports and exports are not sufficient to predict higher-order patterns of the WTW. We discuss some important implications of these findings for international-trade models.Comment: 39 pages, 46 figures, 2 table

Heterogeneity and the dynamics of technology adoption

We estimate the demand for a videocalling technology in the presence of both network effects and heterogeneity. Using a unique dataset from a large multinational firm, we pose and estimate a fully dynamic model of technology adoption. We propose a novel identification strategy based on post-adoption technology usage to disentangle equilibrium beliefs concerning the evolution of the network from observed and unobserved heterogeneity in technology adoption costs and use benefits. We find that employees have significant heterogeneity in both adoption costs and network benefits, and have preferences for diverse networks. Using our estimates, we evaluate a number of counterfactual adoption policies, and find that a policy of strategically targeting the right subtype for initial adoption can lead to a faster-growing and larger network than a policy of uncoordinated or diffuse adoption

Peer influence in network markets: a theoretical and empirical analysis

Network externalities spur the growth of networks and the adoption of network goods in two ways. First, they make it more attractive to join a network the larger its installed base. Second, they create incentives for network members to actively recruit new members. Despite indications that the latter "peer effect" can be more important for network growth than the installed-base effect, it has so far been largely ignored in the literature. We address this gap using game-theoretical models. When all early adopters can band together to exert peer influence-an assumption that fits, e.g., the case of firms supporting a technical standard-we find that the peer effect induces additional growth of the network by a factor. When, in contrast, individuals exert peer influence in small groups of size n, the increase in network size is by an additive constant-which, for small networks, can amount to a large relative increase. The difference between small, local, personal networks and large, global, anonymous networks arises endogenously from our analysis. Fundamentally, the first type of networks is "tie-reinforcing," the other, "tie-creating". We use survey data from users of the Internet services, Skype and eBay, to illustrate the main logic of our theoretical results. As predicted by the model, we find that the peer effect matters strongly for the network of Skype users-which effectively consists of numerous small sub-networks-but not for that of eBay users. Since many network goods give rise to small, local networks

Probing the action of a novel anti-leukaemic drug therapy at the single cell level using modern vibrational spectroscopy techniques

Acute myeloid leukaemia (AML) is a life threatening cancer for which there is an urgent clinical need for novel therapeutic approaches. A redeployed drug combination of bezafibrate and medroxyprogesterone acetate (BaP) has shown anti-leukaemic activity in vitro and in vivo. Elucidation of the BaP mechanism of action is required in order to understand how to maximise the clinical benefit. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, Synchrotron radiation FTIR (S-FTIR) and Raman microspectroscopy are powerful complementary techniques which were employed to probe the biochemical composition of two AML cell lines in the presence and absence of BaP. Analysis was performed on single living cells along with dehydrated and fixed cells to provide a large and detailed data set. A consideration of the main spectral differences in conjunction with multivariate statistical analysis reveals a significant change to the cellular lipid composition with drug treatment; furthermore, this response is not caused by cell apoptosis. No change to the DNA of either cell line was observed suggesting this combination therapy primarily targets lipid biosynthesis or effects bioactive lipids that activate specific signalling pathways

Metabolic Regulation of Invadopodia and Invasion by Acetyl-CoA Carboxylase 1 and De novo Lipogenesis

Invadopodia are membrane protrusions that facilitate matrix degradation and cellular invasion. Although lipids have been implicated in several aspects of invadopodia formation, the contributions of de novo fatty acid synthesis and lipogenesis have not been defined. Inhibition of acetyl-CoA carboxylase 1 (ACC1), the committed step of fatty acid synthesis, reduced invadopodia formation in Src-transformed 3T3 (3T3-Src) cells, and also decreased the ability to degrade gelatin. Inhibition of fatty acid synthesis through AMP-activated kinase (AMPK) activation and ACC phosphorylation also decreased invadopodia incidence. The addition of exogenous 16∶0 and 18∶1 fatty acid, products of de novo fatty acid synthesis, restored invadopodia and gelatin degradation to cells with decreased ACC1 activity. Pharmacological inhibition of ACC also altered the phospholipid profile of 3T3-Src cells, with the majority of changes occurring in the phosphatidylcholine (PC) species. Exogenous supplementation with the most abundant PC species, 34∶1 PC, restored invadopodia incidence, the ability to degrade gelatin and the ability to invade through matrigel to cells deficient in ACC1 activity. On the other hand, 30∶0 PC did not restore invadopodia and 36∶2 PC only restored invadopodia incidence and gelatin degradation, but not cellular invasion through matrigel. Pharmacological inhibition of ACC also reduced the ability of MDA-MB-231 breast, Snb19 glioblastoma, and PC-3 prostate cancer cells to invade through matrigel. Invasion of PC-3 cells through matrigel was also restored by 34∶1 PC supplementation. Collectively, the data elucidate the novel metabolic regulation of invadopodia and the invasive process by de novo fatty acid synthesis and lipogenesis