Molecular cloning, expression, and characterization of a functional single-chain Fv antibody to the mycotoxin zearalenone

The heavy-chain and kappa light-chain variable region genes of an antizearalenone hybridoma cell line (2G3-6E3-2E2) were isolated by PCR and joined by a DNA linker encoding peptide (Gly4Ser)3 as a single-chain Fv (scFv) DNA fragment. The scFv DNA fragment was cloned into a phagemid (pCANTAB5E) and expressed as a fusion protein with E tag and phage M13 p3 in Escherichia coli TG1. In the presence of helper phage M13K07, the scFv fusion protein was displayed on the surfaces of recombinant phages. High-affinity scFv phages were enriched through affinity selection in microtiter wells coated with zearalenone-ovalbumin conjugate. The selected recombinant phages were used to infect E. coli HB2151 for the production of soluble scFv antibodies. One selected clone (pQY1.5) in HB2151 secreted a soluble scFv antibody (QY1.5) with a high zearalenone-binding affinity (concentration required for 50% inhibition of binding, 14 ng/ml), similar to that of parent monoclonal antibody in a competitive indirect enzyme-linked immunosorbent assay. However, scFv QY1.5 exhibited higher cross-reactivity with zearalenone analogs and had greater sensitivity to methanol destabilization than the parent monoclonal antibody did. Nucleotide sequence analyses revealed that the light-chain portion of scFv QY1.5 had a nucleotide sequence identity of 97% to a mouse germ line gene VK23.32 in mouse kappa light-chain variable region subgroup V, whereas the heavy-chain nucleotide sequence was classified as mouse heavy-chain subgroup III (D) but without any closely related members having highly homologous complementarity-determining region sequences. The potential of soluble scFv QY1.5 for routine screening of zearalenone and its analogs was demonstrated with zearalenone-spiked corn extracts.     

A Numerical Treatment of the rf SQUID: I. General Properties and Noise Energy

We investigate the characteristics and noise performance of rf Superconducting Quantum Interference Devices (SQUIDs) by solving the corresponding Langevin equations numerically and optimizing the model parameters with respect to noise energy. After introducing the basic concepts of the numerical simulations, we give a detailed discussion of the performance of the SQUID as a function of all relevant parameters. The best performance is obtained in the crossover region between the dispersive and dissipative regimes, characterized by an inductance parameter β′ _L ≡2π LI ₀/Φ ₀≈1; L is the loop inductance, I ₀ the critical current of the Josephson junction, and Φ ₀ the flux quantum. In this regime, the lowest (intrinsic) values of noise energy are a factor of about 2 above previous estimates based on analytical approaches. However, several other analytical predictions, such as the inverse proportionality of the noise energy on the tank circuit quality factor and the square of the coupling coefficient between the tank circuit and the SQUID loop, could not be well reproduced. The optimized intrinsic noise energy of the rf SQUID is superior to that of the dc SQUID at all temperatures. Although for technologically achievable parameters this advantage shrinks, particularly at low thermal fluctuation levels, we give examples for realistic parameters that lead to a noise energy comparable to that of the dc SQUID even in this regime.      

STABILITY OF RESINS IN PELLETISED HOPS

The α-acids content and Lead Conductance Value of hop pellets, manufactured from seedless Pride of Ringwood hops grown in Australia and stored at 5°C, 20°C or 30°C, were monitored over a twelve month storage period. No decrease in α-acids content occurred during storage at 5°C, whereas at 20°C the decrease (ca. 7%) was approximately one-third that experienced for baled hops of the same variety. At both 5°C and 20°C the Lead Conductance Value decreased at approximately one-third the rate of that in baled hops. During twelve months storage at 30°C the α-acids content of the hop pellets decreased by approximately 40% and the Lead Conductance Value by 30%. The hop pellets stored at 20°C and 30°C developed rancid odours during the twelve months storage period.     

Mathematical models of the transitions between endocrine therapy responsive and resistant states in breast cancer

Endocrine therapy, targeting the oestrogen receptor pathway, is the most common treatment for oestrogen receptor-positive breast cancers. Unfortunately, these tumours frequently develop resistance to endocrine therapies. Among the strategies to treat resistant tumours are sequential treatment (in which second-line drugs are used to gain additional responses) and intermittent treatment (in which a ‘drug holiday’ is imposed between treatments). To gain a more rigorous understanding of the mechanisms underlying these strategies, we present a mathematical model that captures the transitions among three different, experimentally observed, oestrogen-sensitivity phenotypes in breast cancer (sensitive, hypersensitive and independent). To provide a global view of the transitions between these phenotypes, we compute the potential landscape associated with the model. We show how this oestrogen response landscape can be reshaped by population selection, which is a crucial force in promoting acquired resistance. Techniques from statistical physics are used to create a population-level state-transition model from the cellular-level model. We then illustrate how this population-level model can be used to analyse and optimize sequential and intermittent oestrogen-deprivation protocols for breast cancer. The approach used in this study is general and can also be applied to investigate treatment strategies for other types of cancer.     

The enhancement of spatial microsimulation models using geodemographics

The generation of synthetic population estimates through spatial microsimulation has been a popular technique in recent years, with applications to research and policy problems in many areas of social science. Estimation techniques typically involve cloning or matching households in surveys with small-area census data. When model estimates are benchmarked against real-world data, the models are typically well behaved and very robust, but they can struggle to capture the diversity of spatial variations shown by observed data. We argue in this paper that this is the result of 3 potential problems in spatial microsimulation estimation techniques. The first issue results from the matching process in the estimation techniques, and the second problem relates to the variations of household types in the surveys being reweighted. Third, similar household types may show different behaviours or have different attributes depending on geographical factors not contained in surveys (such as the proximity of service or job locations). The aim of this paper is to demonstrate and measure the loss of accuracy and intensity induced by spatial microsimulation in the context of real individual data. It will be argued in particular that while the first two problems have begun to be addressed in the literature, the third issue is still largely unreported. The paper will thus suggest a solution framework which involves linking spatial microsimulation models with geodemographics and demonstrates the promise of this technique with real numerical experiments.     

Methodology for advanced measurement accuracy of the overall volumetric oxygen transfer coefficient with application to hydrocarbon–aqueous dispersions

Accurate quantification of the overall volumetric oxygen transfer coefficient (K_La) is essential for the success of aerobic bioprocesses. In hydrocarbon‐based bioprocesses where K_La is depressed at higher viscosities, this is particularly critical. In this study an accessible methodology for K_La determination has been developed and validated for alkane‐based systems under a wide range of process conditions. Critical to measurement accuracy in around 90% of the K_La values was the incorporation of the response lag. Neglect of the response lag resulted in errors greater than 5% above K_La = 0.3K_p to K_La = 0.6K_p (where K_p is the inverse response lag or probe constant), at least 1.5‐fold to 3‐fold lower than the analogous K_La in water. Further, K_p varied significantly with both alkane concentration and chain length. A sensitivity analysis confirmed ? 25% to 90% error in K_La with 30% over‐ and under‐estimation of K_p respectively. When incorporating K_p values specific to the process conditions, accurate K_La values were confirmed in 0 to 20% (v/v) C_10–13 and C_14–20 aqueous dispersions over 600 to 1200 rpm agitation. Copyright © 2012 Society of Chemical Industry     

Electronic interaction research 1988 – 2012 through the lens of the Bled eConference

Electronic interaction (EI) depends on technological capabilities that have only become available during the last quarter-century. The Bled eConference has straddled this period. A review of the conference’s successive themes, and of the corpus of over 1,000 papers presented at the 25 events to date, reveals three major Eras, referred to in this paper as the EDI, eCommerce and eInteraction Eras. A trace of the developments in the diverse array of EI technologies and EI-technologies-in-use shows that researchers have focussed very heavily on economic concerns, and until recent years did so almost to the exclusion of social concerns. The paper proposes that EI research needs to seek better balances between organisational and human needs. In addition, because of the instability of bleeding-edge phenomena, empirical research is being published too late to deliver much value to practitioners. The prevailing expectations of journals that rigour be pursued at all costs means that the relevance of research to the real world has become a quite secondary concern to many academics. The EI literature is accordingly at risk of following the IS literature more generally into a closed enclave, in which academics talk to one another and no-one else. Key precepts for an alternative research philosophy are proposed.