Entrepreneurial capital, social values and Islamic traditions: exploring the growth of women-owned enterprises in Pakistan

Main ArticleThis study seeks to explore the variables contributing to the growth of women-owned enterprises in the Islamic Republic of Pakistan. Based on a previously established multivariate model, it uses two econometric approaches: first classifying variables into predetermined blocks; and second, using the general to specific approach. Statistical analyses and in-depth interviews confirm that women entrepreneurs’ personal resources and social capital have a significant role in their business growth. Further, it reveals that the moral support of immediate family, independent mobility and being allowed to meet with men play a decisive role in the sales and employment growth of women-owned enterprises in an Islamic country such as Pakistan

Initial/boundary-value problems of tumor growth within a host tissue

This paper concerns multiphase models of tumor growth in interaction with a surrounding tissue, taking into account also the interplay with diffusible nutrients feeding the cells. Models specialize in nonlinear systems of possibly degenerate parabolic equations, which include phenomenological terms related to specific cell functions. The paper discusses general modeling guidelines for such terms, as well as for initial and boundary conditions, aiming at both biological consistency and mathematical robustness of the resulting problems. Particularly, it addresses some qualitative properties such as a priori nonnegativity, boundedness, and uniqueness of the solutions. Existence of the solutions is studied in the one-dimensional time-independent case.Comment: 30 pages, 5 figure

Evaluation of rate law approximations in bottom-up kinetic models of metabolism.

BackgroundThe mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws with reduced numbers of parameters. Whether such simplified models can reproduce dynamic characteristics of the full system is an important question.ResultsIn this work, we compared the local transient response properties of dynamic models constructed using rate laws with varying levels of approximation. These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law with measured enzyme parameters yields an excellent approximation of the full system dynamics, while other assumptions cause greater discrepancies in system dynamic behavior. However, iteratively replacing mechanistic rate laws with approximations resulted in a model that retains a high correlation with the true model behavior. Investigating this consistency, we determined that the order of magnitude differences among fluxes and concentrations in the network were greatly influential on the network dynamics. We further identified reaction features such as thermodynamic reversibility, high substrate concentration, and lack of allosteric regulation, which make certain reactions more suitable for rate law approximations.ConclusionsOverall, our work generally supports the use of approximate rate laws when building large scale kinetic models, due to the key role that physiologically meaningful flux and concentration ranges play in determining network dynamics. However, we also showed that detailed mechanistic models show a clear benefit in prediction accuracy when data is available. The work here should help to provide guidance to future kinetic modeling efforts on the choice of rate law and parameterization approaches

Entrepreneurial growth and ownership under market socialism in China: a longitudinal case study of small business growth

How firms grow is still a mystery and a definitive explanation remains elusive. This is especially the case for emerging economies, where the development of research into business growth has been notably slow whilst emerging business ventures are developing at hyper speed. Since most empirical studies have focused on the quantitative differences in growth across firms, this paper adopts a longitudinal case study approach to explore the qualitative differences in terms of how various types of firm achieve their growth outcomes in the organisational development process over a prolonged period of time. Through a theoretical lens which focuses on growth process approaches, this study not only demonstrates that entrepreneurial processes take different forms and dimensions in different contexts, but it also provides insights into the interactions of various organisational factors underpinning the strategies and changes that lead to contrasting growth outcomes. Case study findings assert that the ownership factor is a key contingent factor that shapes management structure and resources which, in turn, affect particular entrepreneurial outcomes. Furthermore, a combination of leadership style and the approach to knowledge management also play critical roles in the learning process which, tends to determine the strategy choice of either high or low value added product strategy. The findings of this research are that small firms with a low value product strategy can improve their survival chances and growth through the vertical broadening of a product portfolio in synchrony with increasing production and technology advancement. The case study companies show a tendency to reinforce their industry position by adopting contrasting choices for growth. The paper addresses the challenges and managerial implications for Western company managers in different growth contexts

The ineffectiveness of entrepreneurship policy:Is policy formulation to blame?

Entrepreneurship policy has been criticised for its lack of effectiveness. Some scholars, such as Scott Shane in this journal, have argued that it is ‘bad’ public policy. But this simply begs the question why the legislative process should generate bad policy? To answer this question this study examines the UK’s enterprise policy process in the 2009–2010 period. It suggests that a key factor for the ineffectiveness of policy is how it is formulated. This stage in the policy process is seldom visible to those outside of government departments and has been largely ignored by prior research. The application of institutional theory provides a detailed theoretical understanding of the actors and the process by which enterprise policy is formulated. We find that by opening up the ‘black box’ of enterprise policy formulation, the process is dominated by powerful actors who govern the process with their interests

Transketolase-Like 1 Expression Is Modulated during Colorectal Cancer Progression and Metastasis Formation

Background Transketolase-like 1 (TKTL1) induces glucose degradation through anaerobic pathways, even in presence of oxygen, favoring the malignant aerobic glycolytic phenotype characteristic of tumor cells. As TKTL1 appears to be a valid biomarker for cancer prognosis, the aim of the current study was to correlate its expression with tumor stage, probability of tumor recurrence and survival, in a series of colorectal cancer patients. Methodolody/Principal Findings Tumor tissues from 63 patients diagnosed with colorectal cancer at different stages of progression were analyzed for TKTL1 by immunohistochemistry. Staining was quantified by computational image analysis, and correlations between enzyme expression, local growth, lymph-node involvement and metastasis were assessed. The highest values for TKTL1 expression were detected in the group of stage III tumors, which showed significant differences from the other groups (Kruskal-Wallis test, P = 0.000008). Deeper analyses of T, N and M classifications revealed a weak correlation between local tumor growth and enzyme expression (Mann-Whitney test, P = 0.029), a significant association of the enzyme expression with lymph-node involvement (Mann-Whitney test, P = 0.0014) and a significant decrease in TKTL1 expression associated with metastasis (Mann-Whitney test, P = 0.0004). Conclusions/Significance To our knowledge, few studies have explored the association between variations in TKTL1 expression in the primary tumor and metastasis formation. Here we report downregulation of enzyme expression when metastasis appears, and a correlation between enzyme expression and regional lymph-node involvement in colon cancer. This finding may improve our understanding of metastasis and lead to new and more efficient therapies against cancer

Design Constraints on a Synthetic Metabolism

A metabolism is a complex network of chemical reactions that converts sources of energy and chemical elements into biomass and other molecules. To design a metabolism from scratch and to implement it in a synthetic genome is almost within technological reach. Ideally, a synthetic metabolism should be able to synthesize a desired spectrum of molecules at a high rate, from multiple different nutrients, while using few chemical reactions, and producing little or no waste. Not all of these properties are achievable simultaneously. We here use a recently developed technique to create random metabolic networks with pre-specified properties to quantify trade-offs between these and other properties. We find that for every additional molecule to be synthesized a network needs on average three additional reactions. For every additional carbon source to be utilized, it needs on average two additional reactions. Networks able to synthesize 20 biomass molecules from each of 20 alternative sole carbon sources need to have at least 260 reactions. This number increases to 518 reactions for networks that can synthesize more than 60 molecules from each of 80 carbon sources. The maximally achievable rate of biosynthesis decreases by approximately 5 percent for every additional molecule to be synthesized. Biochemically related molecules can be synthesized at higher rates, because their synthesis produces less waste. Overall, the variables we study can explain 87 percent of variation in network size and 84 percent of the variation in synthesis rate. The constraints we identify prescribe broad boundary conditions that can help to guide synthetic metabolism design

Role of monocarboxylate transporters in human cancers : state of the art

Monocarboxylate transporters (MCTs) belong to the SLC16 gene family, presently composed by 14 members. MCT1-MCT4 are proton symporters, which mediate the transmembrane transport of pyruvate, lactate and ketone bodies. The role of MCTs in cell homeostasis has been characterized in detail in normal tissues, however, their role in cancer is still far from understood. Most solid tumors are known to rely on glycolysis for energy production and this activity leads to production of important amounts of lactate, which are exported into the extracellular milieu, contributing to the acidic microenvironment. In this context, MCTs will play a dual role in the maintenance of the hyper-glycolytic acidresistant phenotype of cancer, allowing the maintenance of the high glycolytic rates by performing lactate efflux, and pH regulation by the co-transport of protons. Thus, they constitute attractive targets for cancer therapy, which have been little explored. Here we review the literature on the role of MCTs in solid tumors in different locations, such as colon, central nervous system, breast, lung, gynecologic tract, prostate, stomach, however, there are many conflicting results and in most cases there are no functional studies showing the dependence of the tumors on MCT expression and activity. Additional studies on MCT expression in other tumor types, confirmation of the results already published as well as additional functional studies are needed to deeply understand the role of MCTs in cancer maintenance and aggressiveness

Nutritional Systems Biology Modeling: From Molecular Mechanisms to Physiology

The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a “middle-out” strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from “-omics” signatures are identified as key elements of a successful systems biology modeling approach in nutrition research—one that integrates physiological mechanisms and data at multiple space and time scales