The extant literature highlights that environmental conditions, during the creation phase, imprint on a startup's survival and growth. However, there are few studies that explore the composite nature of a founding team's capabilities and networks, developed within this phase, and the contribution made to future performance. This paper uses the distinctive context of university spin-offs, where early stage ventures are fostered by institutional interventions, to analyse the influence that the capabilities and networks of a founding team, at incorporation, have upon the future performance of the spin-off. Based on data from 181 university spin-offs, this paper empirically demonstrates that the entrepreneurial capabilities of a founding team, augmented during the 'creation' phase, have a positive influence on the performance of a spin-off during the 'growth' phase, and that the networks of a founding team indirectly affect a spin-off's performance through the enhancement of a team's entrepreneurial capabilities.

University spin-offs have increasingly received attention from academia, governments and policy-makers. However, there are only a limited number of studies within the university spin-off context which fully understand the contribution made by the founding team to fundraising, specifically how they use their social networks and capabilities. Employing resource-based theory and social networks approach, this paper examines whether a founding team exploits its social networks and capabilities to signal the value of a university spinoff. Capabilities are analysed through a set of constructs -technology, strategy, human capital, organizational viability and commercial resource -that have been derived from previous literature. The contribution made by social networks is evaluated using three dimensions -structure, governance and content -which form the construct of relationships within a network. Based on data from 181 university spin-offs in Spain, this paper empirically demonstrates that by exploiting social networks a founding team can improve its capabilities which, in turn, enhance its fundraising ability.

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Gold nanoparticles (AuNPs) of 15-20 nm size range have attracted attention for producing smart sensing devices as diagnostic tools in biomedical sciences. Citrate capped AuNPs are negatively charged, which can be exploited for electrostatic interactions with some positively charged biomolecules like antibodies. In this paper we describe a method for the low cost synthesis of gold nanoparticles using sodium citrate (Na 3 Ct) reduction in chloroauric acid (HAuCl 4 .3H 2 O) by microwave heating (diameter about 13-15 nm). Gold nanoparticles were functionalized with surface activation by 3-mercaptopropionic acid for attaching antibody. These nanoparticles were then reacted with anti-E. coli O157:H7, using N-hydroxy succinimide (NHS) and carbondimide hydrochloride (EDC) coupling chemistry. The product was characterized with UV-visible spectroscopy, Fourier transform infrared (FTIR) spectroscopy and zeta potential. In addition, the binding of antibody-gold nanoparticles conjugates to E. coli O157:H7 was demonstrated using transmission electron microscopy (TEM).

Although Escherichia coli (E. coli) is a commensalism organism in the intestine of humans and warm-blooded animals, it can be toxic at higher density and causes diseases, especially the highly toxic E. coli O157:H7. In this paper a quartz crystal microbalance (QCM) biosensor was developed for the detection of E. coli O157:H7 bacteria. The anti-E. coli O157:H7 antibodies were immobilized on a self-assembly monolayer (SAM) modified 5 MHz AT-cut quartz crystal resonator. The SAMs were activated with 16-mercaptopropanoic acid, in the presence of 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) and ester N-hydroxysuccinimide (NHS). The result of changing frequency due to the adsorption of E. coli O157:H7 was measured by the QCM biosensor system designed and fabricated by ICDREC-VNUHCM. This system gave good results in the range of 102–107 CFU mL−1 E. coli O157:H7. The time of bacteria E. coli O157:H7 detection in the sample was about 50 m. Besides, QCM biosensor from SAM method was comparable to protein A method-based piezoelectric immunosensor in terms of the amount of immobilized antibodies and detection sensitivity.