High threshold of β1 integrin inhibition required to block collagen I-induced membrane type-1 matrix metalloproteinase (MT1-MMP) activation of matrix metalloproteinase 2 (MMP-2)

Background Matrix metalloproteinase-2 (MMP-2) is an endopeptidase that facilitates extracellular matrix remodeling and molecular regulation, and is implicated in tumor metastasis. Type I collagen (Col I) regulates the activation of MMP-2 through both transcriptional and post-transcriptional means; however gaps remain in our understanding of the involvement of collagen-binding ?1 integrins in collagen-stimulated MMP-2 activation. Methods Three ?1 integrin siRNAs were used to elucidate the involvement of ?1 integrins in the Col I-induced MMP-2 activation mechanism. ?1 integrin knockdown was analyzed by quantitative RT-PCR, Western Blot and FACS analysis. Adhesion assay and collagen gel contraction were used to test the biological effects of ?1 integrin abrogation. MMP-2 activation levels were monitored by gelatin zymography. Results All three ?1 integrin siRNAs were efficient at ?1 integrin knockdown and FACS analysis revealed commensurate reductions of integrins ?2 and ?3, which are heterodimeric partners of ?1, but not ?V, which is not. All three ?1 integrin siRNAs inhibited adhesion and collagen gel contraction, however only the siRNA showing the greatest magnitude of ?1 knockdown inhibited Col I-induced MMP-2 activation and reduced the accompanying upregulation of MT1-MMP, suggesting a dose response threshold effect. Re-transfection with codon-swapped ?1 integrin overcame the reduction in MMP-2 activation induced by Col-1, confirming the ?1 integrin target specificity. MMP-2 activation induced by TPA or Concanavalin A (Con A) was not inhibited by ?1 integrin siRNA knockdown. Conclusion Together, the data reveals that strong abrogation of ?1 integrin is required to block MMP-2 activation induced by Col I, which may have implications for the therapeutic targeting of ?1 integrin.

Simulation of pesticide behavior in a paddy block by a pesticide fate and transport model

A simulation model (PCPF-B) was developed based on the PCPF-1 model to predict the runoff of pesticides from paddy plots to a drainage canal in a paddy block. The block-scale model now comprises three modules: (1) a module for pesticide application, (2) a module for pesticide behavior in paddy fields, and (3) a module for pesticide concentration in the drainage canal. The PCPF-B model was first evaluated by published data in a single plot and then was applied to predict the concentration of bensulfuron-methyl in one paddy block in the Sakura river basin, Ibaraki, Japan, where a detailed field survey was conducted. The PCPF-B model simulated well the behavior of bensulfuron-methyl in individual paddy plots. It also reflected the runoff pattern of bensulfuron-methyl at the block outlet, although overestimation of bensulfuronmethyl concentrations occurred due to uncertainty in water balance estimation. Application of water management practice such as water-holding period and seepage control also affected the performance of the model. A probabilistic approach may be necessary for a comprehensive risk assessment in large-scale paddy areas.

A pilot study in different unstable designs on the biomechanical effect of gait characteristics

The purpose of this study was to compare kinematics and kinetics during walking for healthy subjects using unstable shoes with different designs. Ten subjects participated in this study, and foot biomechanical data during walking were quantified using motion analysis system and a force plate. Data were collected for unstable shoes condition after accommodation period of one week. With soft material added in the heel region, the peak impact force was effectively reduced when compared among similar shapes. In addition, the soft material added in the rocker bottom showed more to be in dorsiflexed position during the initial stance. The shoe with three rocker curves design reduced the contact area in the heel strike, which may result in increasing human body forward speed. Further studies shall be carried out after adapting to long periods of wearing unstable shoes.

Efficient designs for sampling and subsampling in fisheries research based on ranked sets

Sampling strategies are developed based on the idea of ranked set sampling (RSS) to increase efficiency and therefore to reduce the cost of sampling in fishery research. The RSS incorporates information on concomitant variables that are correlated with the variable of interest in the selection of samples. For example, estimating a monitoring survey abundance index would be more efficient if the sampling sites were selected based on the information from previous surveys or catch rates of the fishery. We use two practical fishery examples to demonstrate the approach: site selection for a fishery-independent monitoring survey in the Australian northern prawn fishery (NPF) and fish age prediction by simple linear regression modelling a short-lived tropical clupeoid. The relative efficiencies of the new designs were derived analytically and compared with the traditional simple random sampling (SRS). Optimal sampling schemes were measured by different optimality criteria. For the NPF monitoring survey, the efficiency in terms of variance or mean squared errors of the estimated mean abundance index ranged from 114 to 199% compared with the SRS. In the case of a fish ageing study for Tenualosa ilisha in Bangladesh, the efficiency of age prediction from fish body weight reached 140%.

Bayesian designs with frequentist and Bayesian error rate considerations

So far, most Phase II trials have been designed and analysed under a frequentist framework. Under this framework, a trial is designed so that the overall Type I and Type II errors of the trial are controlled at some desired levels. Recently, a number of articles have advocated the use of Bavesian designs in practice. Under a Bayesian framework, a trial is designed so that the trial stops when the posterior probability of treatment is within certain prespecified thresholds. In this article, we argue that trials under a Bayesian framework can also be designed to control frequentist error rates. We introduce a Bayesian version of Simon's well-known two-stage design to achieve this goal. We also consider two other errors, which are called Bayesian errors in this article because of their similarities to posterior probabilities. We show that our method can also control these Bayesian-type errors. We compare our method with other recent Bayesian designs in a numerical study and discuss implications of different designs on error rates. An example of a clinical trial for patients with nasopharyngeal carcinoma is used to illustrate differences of the different designs.

Designs for phase I clinical trials with multiple courses of subjects at different doses

The goal of this article is to provide a new design framework and its corresponding estimation for phase I trials. Existing phase I designs assign each subject to one dose level based on responses from previous subjects. Yet it is possible that subjects with neither toxicity nor efficacy responses can be treated at higher dose levels, and their subsequent responses to higher doses will provide more information. In addition, for some trials, it might be possible to obtain multiple responses (repeated measures) from a subject at different dose levels. In this article, a nonparametric estimation method is developed for such studies. We also explore how the designs of multiple doses per subject can be implemented to improve design efficiency. The gain of efficiency from "single dose per subject" to "multiple doses per subject" is evaluated for several scenarios. Our numerical study shows that using "multiple doses per subject" and the proposed estimation method together increases the efficiency substantially.

Decision-theoretic designs for dose-finding clinical trials with multiple outcomes

A decision-theoretic framework is proposed for designing sequential dose-finding trials with multiple outcomes. The optimal strategy is solvable theoretically via backward induction. However, for dose-finding studies involving k doses, the computational complexity is the same as the bandit problem with k-dependent arms, which is computationally prohibitive. We therefore provide two computationally compromised strategies, which is of practical interest as the computational complexity is greatly reduced: one is closely related to the continual reassessment method (CRM), and the other improves CRM and approximates to the optimal strategy better. In particular, we present the framework for phase I/II trials with multiple outcomes. Applications to a pediatric HIV trial and a cancer chemotherapy trial are given to illustrate the proposed approach. Simulation results for the two trials show that the computationally compromised strategy can perform well and appear to be ethical for allocating patients. The proposed framework can provide better approximation to the optimal strategy if more extensive computing is available.

Optimal designs for evaluating a series of treatments

Several articles in this journal have studied optimal designs for testing a series of treatments to identify promising ones for further study. These designs formulate testing as an ongoing process until a promising treatment is identified. This formulation is considered to be more realistic but substantially increases the computational complexity. In this article, we show that these new designs, which control the error rates for a series of treatments, can be reformulated as conventional designs that control the error rates for each individual treatment. This reformulation leads to a more meaningful interpretation of the error rates and hence easier specification of the error rates in practice. The reformulation also allows us to use conventional designs from published tables or standard computer programs to design trials for a series of treatments. We illustrate these using a study in soft tissue sarcoma.

Isotonic designs for phase I trials

The purpose of a phase I trial in cancer is to determine the level (dose) of the treatment under study that has an acceptable level of adverse effects. Although substantial progress has recently been made in this area using parametric approaches, the method that is widely used is based on treating small cohorts of patients at escalating doses until the frequency of toxicities seen at a dose exceeds a predefined tolerable toxicity rate. This method is popular because of its simplicity and freedom from parametric assumptions. In this payer, we consider cases in which it is undesirable to assume a parametric dose-toxicity relationship. We propose a simple model-free approach by modifying the method that is in common use. The approach assumes toxicity is nondecreasing with dose and fits an isotonic regression to accumulated data. At any point in a trial, the dose given is that with estimated toxicity deemed closest to the maximum tolerable toxicity. Simulations indicate that this approach performs substantially better than the commonly used method and it compares favorably with other phase I designs.

Block works

A retail precinct along James Street in Brisbane is made more permeable by Richards and Spence.

A comparison of DNA pools constructed following whole genome amplification for two-stage SNP genotyping designs

Genotyping in DNA pools reduces the cost and the time required to complete large genotyping projects. The aim of the present study was to evaluate pooling as part of a strategy for fine mapping in regions of significant linkage. Thirty-nine single nucleotide polymorphisms (SNPs) were analyzed in two genomic DNA pools of 384 individuals each and results compared with data after typing all individuals used in the pools. There were no significant differences using data from either 2 or 8 heterozygous individuals to correct frequency estimates for unequal allelic amplification. After correction, the mean difference between estimates from the genomic pool and individual allele frequencies was .033. A major limitation of the use of DNA pools is the time and effort required to carefully adjust the concentration of each individual DNA sample before mixing aliquots. Pools were also constructed by combining DNA after Multiple Displacement Amplification (MDA). The MDA pools gave similar results to pools constructed after careful DNA quantitation (mean difference from individual genotyping .040) and MDA provides a rapid method to generate pools suitable for some applications. Pools provide a rapid and cost-effective screen to eliminate SNPs that are not polymorphic in a test population and can detect minor allele frequencies as low as 1% in the pooled samples. With current levels of accuracy, pooling is best suited to an initial screen in the SNP validation process that can provide high-throughput comparisons between cases and controls to prioritize SNPs for subsequent individual genotyping.

Open-pit block sequencing optimization: A mathematical model and solution technique

This study presents a comprehensive mathematical formulation model for a short-term open-pit mine block sequencing problem, which considers nearly all relevant technical aspects in open-pit mining. The proposed model aims to obtain the optimum extraction sequences of the original-size (smallest) blocks over short time intervals and in the presence of real-life constraints, including precedence relationship, machine capacity, grade requirements, processing demands and stockpile management. A hybrid branch-and-bound and simulated annealing algorithm is developed to solve the problem. Computational experiments show that the proposed methodology is a promising way to provide quantitative recommendations for mine planning and scheduling engineers.

The creative suburb: Building and urban designs for suburban innovators

Influential creative industries and creative place thinkers Richard Florida and Charles Landry agree that creativity is necessary for a prospering liveable and, therefore, sustainable city. Following Florida’s work, the ‘creative class’ has become central to what has turned out to be city-centre-centric growth policies. However, until the Queensland University of Technology’s Australian Research Council sponsored research into “creative suburbia”, few researchers had demonstrated – let alone challenged – the notion that a substantial cohort of creative industries workers might prefer to live and work at home in the suburbs rather than in city centres. The “creative suburb” work builds on the creative suburbia research. In a practice-led and property development industry embedded inquiry, the creative suburb draws on significant primary research with suburban, home-based, creative industries workers, vernacular architecture, and town planning in the Toowoomba region, in the state of Queensland, Australia, as inspiration for a series of new building and urban designs available for innovators operating in new suburban greenfield situations and suburban areas undergoing a refit in Queensland and possibly further afield. This paper focuses on one building design informed by this inquiry, with the intention of its construction as a ’showcasestudy’ ‘homeworkhouse’, suitable for creative industries workers in the Toowoomba region.

Translating emotional insights into digital channel designs: Opportunities to enhance the airport experience

Purpose The purpose of this study is to identify and understand the emotions behind a passenger’s airport experience and how this can inform digital channel engagements. Design/methodology/approach This study investigates the emotional experience of two hundred (200) passengers’ journeys at an Australian domestic airport. A survey was conducted which implemented the use of Emocards and an interview approach of laddering. The responses were then analysed into attributes, consequences and values. Findings The results indicate that across key stages of the airport (parking, retail, gates and arrivals) passengers had different emotional experiences (positive, negative and neutral). The attributes, consequences and values behind these emotions were then used to propose digital channel content and purpose of various future digital channel engagements. Research limitations/implications By gaining emotional insights airports are able to generate digital channel engagements, which align with passengers’ needs and values rather than internal operational motivations. Theoretical contributions include the development of the Technology Acceptance Model to include emotional drivers as influences in the use of digital channels. Originality/value This research provides a unique method to understand the passengers’ emotional journey across the airport infrastructure and suggest how to better design digital channel engagements to address passenger latent needs.