A continuum model of the growth of engineered epidermal skin substitutes

We present a porous medium model of the growth and deterioration of the viable sublayers of an epidermal skin substitute. It consists of five species: cells, intracellular and extracellular calcium, tight junctions, and a hypothesised signal chemical emanating from the stratum corneum. The model is solved numerically in Matlab using a finite difference scheme. Steady state calcium distributions are predicted that agree well with the experimental data. Our model also demonstrates epidermal skin substitute deterioration if the calcium diffusion coefficient is reduced compared to reported values in the literature.

Solution methods for advection-diffusion-reaction equations on growing domains and subdomains, with application to modelling skin substitutes

Problems involving the solution of advection-diffusion-reaction equations on domains and subdomains whose growth affects and is affected by these equations, commonly arise in developmental biology. Here, a mathematical framework for these situations, together with methods for obtaining spatio-temporal solutions and steady states of models built from this framework, is presented. The framework and methods are applied to a recently published model of epidermal skin substitutes. Despite the use of Eulerian schemes, excellent agreement is obtained between the numerical spatio-temporal, numerical steady state, and analytical solutions of the model.

Dietary intake in Australian children aged 4–24 months: Consumption of meat and meat alternatives

Meat/meat alternatives (M/MA) are key sources of Fe, Zn and protein, but intake tends to be low in young children. Australian recommendations state that Fe-rich foods, including M/MA, should be the first complementary foods offered to infants. The present paper reports M/MA consumption of Australian infants and toddlers, compares intake with guidelines, and suggests strategies to enhance adherence to those guidelines. Mother–infant dyads recruited as part of the NOURISH and South Australian Infants Dietary Intake studies provided 3 d of intake data at three time points: Time 1 (T1) (n 482, mean age 5·5 (SD 1·1) months), Time 2 (T2) (n 600, mean age 14·0 (SD 1·2) months) and Time 3 (T3) (n 533, mean age 24 (SD 0·7) months). Of 170 infants consuming solids and aged greater than 6 months at T1, 50 (29 %) consumed beef, lamb, veal (BLV) or pork on at least one of 3 d. Commercial infant foods containing BLV or poultry were the most common form of M/MA consumed at T1, whilst by T2 BLV mixed dishes (including pasta bolognaise) became more popular and remained so at T3. The processed M/MA increased in popularity over time, led by pork (including ham). The present study shows that M/MA are not being eaten by Australian infants or toddlers regularly enough; or in adequate quantities to meet recommendations; and that the form in which these foods are eaten can lead to smaller M/MA serve sizes and greater Na intake. Parents should be encouraged to offer M/MA in a recognisable form, as one of the first complementary foods, in order to increase acceptance at a later age.

Owning omega-3: Monsanto and the invention of meat

In August of 2010, Anna Salleh of the Science Unit of the Australian Broadcasting Corporation broke a story about Monsanto seeking to patent the enhancement of meat, including omega-3 fatty acids: ‘Enhanced port is sparking debate over the ethics of placing patents on food. Patent applications covering the enhancement of meat, including pork with omega-3 fatty acids, are stimulating debate over the ethics and legalities of claiming intellectual property over food. Monsanto has filed patents that cover the feeding of animals soybeans, which have been genetically modified by the company to contain stearidonic acid (SDA), a plant-derived omega-3 fatty acid... Omega-3s have been linked to improved cardiovascular health and there are many companies engineering them into foodstuffs. But the new patent applications have touched a raw nerve among those who see them as an attempt by the company to exert control over the food chain.’ This article providers a critical evaluation of the controversy of Monsanto’s patent applications, and the larger issues over patenting food. It first considers the patent portfolio of Monsanto; the nature of the patent claims; and the examination of the claims by patent examiners. Second, it examines the withdrawal and revision of the patent claims by Monsanto in the wake of criticism by patent authorities and the public disquiet over the controversial application. Third, this article considers the larger policy issues raised by Monsanto’s patent applications – including the patenting of plants, animals, and foodstuffs. There is also a consideration of the impact of patents upon the administration of health-care, competition, and research.

Modeling meat yield based on measurements of body traits in genetically improved giant freshwater prawn (GFP) Macrobrachium rosenbergii

A single-generation dataset consisting of 1,730 records from a selection program for high growth rate in giant freshwater prawn (GFP, Macrobrachium rosenbergii) was used to derive prediction equations for meat weight and meat yield. Models were based on body traits [body weight, total length and abdominal width (AW)] and carcass measurements (tail weight and exoskeleton-off weight). Lengths and width were adjusted for the systematic effects of selection line, male morphotypes and female reproductive status, and for the covariables of age at slaughter within sex and body weight. Body and meat weights adjusted for the same effects (except body weight) were used to calculate meat yield (expressed as percentage of tail weight/body weight and exoskeleton-off weight/body weight). The edible meat weight and yield in this GFP population ranged from 12 to 15 g and 37 to 45 %, respectively. The simple (Pearson) correlation coefficients between body traits (body weight, total length and AW) and meat weight were moderate to very high and positive (0.75–0.94), but the correlations between body traits and meat yield were negative (−0.47 to −0.74). There were strong linear positive relationships between measurements of body traits and meat weight, whereas relationships of body traits with meat yield were moderate and negative. Step-wise multiple regression analysis showed that the best model to predict meat weight included all body traits, with a coefficient of determination (R 2) of 0.99 and a correlation between observed and predicted values of meat weight of 0.99. The corresponding figures for meat yield were 0.91 and 0.95, respectively. Body weight or length was the best predictor of meat weight, explaining 91–94 % of observed variance when it was fitted alone in the model. By contrast, tail width explained a lower proportion (69–82 %) of total variance in the single trait models. It is concluded that in practical breeding programs, improvement of meat weight can be easily made through indirect selection for body trait combinations. The improvement of meat yield, albeit being more difficult, is possible by genetic means, with 91 % of the variation in the trait explained by the body and carcass traits examined in this study.

Drivers of technology substitution : successive generations of high tech products

Principal Topic High technology consumer products such as notebooks, digital cameras and DVD players are not introduced into a vacuum. Consumer experience with related earlier generation technologies, such as PCs, film cameras and VCRs, and the installed base of these products strongly impacts the market diffusion of the new generation products. Yet technology substitution has received only sparse attention in the diffusion of innovation literature. Research for consumer durables has been dominated by studies of (first purchase) adoption (c.f. Bass 1969) which do not explicitly consider the presence of an existing product/technology. More recently, considerable attention has also been given to replacement purchases (c.f. Kamakura and Balasubramanian 1987). Only a handful of papers explicitly deal with the diffusion of technology/product substitutes (e.g. Norton and Bass, 1987: Bass and Bass, 2004). They propose diffusion-type aggregate-level sales models that are used to forecast the overall sales for successive generations. Lacking household data, these aggregate models are unable to give insights into the decisions by individual households - whether to adopt generation II, and if so, when and why. This paper makes two contributions. It is the first large-scale empirical study that collects household data for successive generations of technologies in an effort to understand the drivers of adoption. Second, in comparision to traditional analysis that evaluates technology substitution as an ''adoption of innovation'' type process, we propose that from a consumer's perspective, technology substitution combines elements of both adoption (adopting the new generation technology) and replacement (replacing the generation I product with generation II). Based on this proposition, we develop and test a number of hypotheses. Methodology/Key Propositions In some cases, successive generations are clear ''substitutes'' for the earlier generation, in that they have almost identical functionality. For example, successive generations of PCs Pentium I to II to III or flat screen TV substituting for colour TV. More commonly, however, the new technology (generation II) is a ''partial substitute'' for existing technology (generation I). For example, digital cameras substitute for film-based cameras in the sense that they perform the same core function of taking photographs. They have some additional attributes of easier copying and sharing of images. However, the attribute of image quality is inferior. In cases of partial substitution, some consumers will purchase generation II products as substitutes for their generation I product, while other consumers will purchase generation II products as additional products to be used as well as their generation I product. We propose that substitute generation II purchases combine elements of both adoption and replacement, but additional generation II purchases are solely adoption-driven process. Extensive research on innovation adoption has consistently shown consumer innovativeness is the most important consumer characteristic that drives adoption timing (Goldsmith et al. 1995; Gielens and Steenkamp 2007). Hence, we expect consumer innovativeness also to influence both additional and substitute generation II purchases. Hypothesis 1a) More innovative households will make additional generation II purchases earlier. 1 b) More innovative households will make substitute generation II purchases earlier. 1 c) Consumer innovativeness will have a stronger impact on additional generation II purchases than on substitute generation II purchases. As outlined above, substitute generation II purchases act, in part like a replacement purchase for the generation I product. Prior research (Bayus 1991; Grewal et al 2004) identified product age as the most dominant factor influencing replacements. Hence, we hypothesise that: Hypothesis 2: Households with older generation I products will make substitute generation II purchases earlier. Our survey of 8,077 households investigates their adoption of two new generation products: notebooks as a technology change to PCs, and DVD players as a technology shift from VCRs. We employ Cox hazard modelling to study factors influencing the timing of a household's adoption of generation II products. We determine whether this is an additional or substitute purchase by asking whether the generation I product is still used. A separate hazard model is conducted for additional and substitute purchases. Consumer Innovativeness is measured as domain innovativeness adapted from the scales of Goldsmith and Hofacker (1991) and Flynn et al. (1996). The age of the generation I product is calculated based on the most recent household purchase of that product. Control variables include age, size and income of household, and age and education of primary decision-maker. Results and Implications Our preliminary results confirm both our hypotheses. Consumer innovativeness has a strong influence on both additional purchases (exp = 1.11) and substitute purchases (exp = 1.09). Exp is interpreted as the increased probability of purchase for an increase of 1.0 on a 7-point innovativeness scale. Also consistent with our hypotheses, the age of the generation I product has a dramatic influence for substitute purchases of VCR/DVD (exp = 2.92) and a strong influence for PCs/notebooks (exp = 1.30). Exp is interpreted as the increased probability of purchase for an increase of 10 years in the age of the generation I product. Yet, also as hypothesised, there was no influence on additional purchases. The results lead to two key implications. First, there is a clear distinction between additional and substitute purchases of generation II products, each with different drivers. Treating these as a single process will mask the true drivers of adoption. For substitute purchases, product age is a key driver. Hence, implications for marketers of high technology products can utilise data on generation I product age (e.g. from warranty or loyalty programs) to target customers who are more likely to make a purchase.

Biological performance of a polycaprolactone-based scaffold used as fusion cage device in a large animal model of spinal reconstructive surgery

A bioactive and bioresorbable scaffold fabricated from medical grade poly (epsilon-caprolactone) and incorporating 20% beta-tricalcium phosphate (mPCL–TCP) was recently developed for bone regeneration at load bearing sites. In the present study, we aimed to evaluate bone ingrowth into mPCL–TCP in a large animal model of lumbar interbody fusion. Six pigs underwent a 2-level (L3/4; L5/6) anterior lumbar interbody fusion (ALIF) implanted with mPCL–TCP þ 0.6 mg rhBMP-2 as treatment group while four other pigs implanted with autogenous bone graft served as control. Computed tomographic scanning and histology revealed complete defect bridging in all (100%) specimen from the treatment group as early as 3 months. Histological evidence of continuing bone remodeling and maturation was observed at 6 months. In the control group, only partial bridging was observed at 3 months and only 50% of segments in this group showed complete defect bridging at 6 months. Furthermore, 25% of segments in the control group showed evidence of graft fracture, resorption and pseudoarthrosis. In contrast, no evidence of graft fractures, pseudoarthrosis or foreign body reaction was observed in the treatment group. These results reveal that mPCL–TCP scaffolds could act as bone graft substitutes by providing a suitable environment for bone regeneration in a dynamic load bearing setting such as in a porcine model of interbody spine fusion.

Drivers of adoption for successive generation of high-tech products

To understand the diffusion of high technology products such as PCs, digital cameras and DVD players it is necessary to consider the dynamics of successive generations of technology. From the consumer’s perspective, these technology changes may manifest themselves as either a new generation product substituting for the old (for instance digital cameras) or as multiple generations of a single product (for example PCs). To date, research has been confined to aggregate level sales models. These models consider the demand relationship between one generation of a product and a successor generation. However, they do not give insights into the disaggregate-level decisions by individual households – whether to adopt the newer generation, and if so, when. This paper makes two contributions. It is the first large scale empirical study to collect household data for successive generations of technologies in an effort to understand the drivers of adoption. Second, in contrast to traditional analysis in diffusion research that conceptualizes technology substitution as an “adoption of innovation” type process, we propose that from a consumer’s perspective, technology substitution combines elements of both adoption (adopting the new generation technology) and replacement (replacing generation I product with generation II). Key Propositions In some cases, successive generations are clear “substitutes” for the earlier generation (e.g. PCs Pentium I to II to III ). More commonly the new generation II technology is a “partial substitute” for existing generation I technology (e.g. DVD players and VCRs). Some consumers will purchase generation II products as substitutes for their generation I product, while other consumers will purchase generation II products as additional products to be used as well as their generation I product. We propose that substitute generation II purchases combine elements of both adoption and replacement, but additional generation II purchases are solely adoption-driven process. Moreover, drawing on adoption theory consumer innovativeness is the most important consumer characteristic for adoption timing of new products. Hence, we hypothesize consumer innovativeness to influence the timing of both additional and substitute generation II purchases but to have a stronger impact on additional generation II purchases. We further propose that substitute generation II purchases act partially as a replacement purchase for the generation I product. Thus, we hypothesize that households with older generation I products will make substitute generation II purchases earlier. Methods We employ Cox hazard modeling to study factors influencing the timing of a household’s adoption of generation II products. A separate hazard model is conducted for additional and substitute purchases. The age of the generation I product is calculated based on the most recent household purchase of that product. Control variables include size and income of household, age and education of decision-maker. Results and Implications Our preliminary results confirm both our hypotheses. Consumer innovativeness has a strong influence on both additional purchases and substitute purchases. Also consistent with our hypotheses, the age of the generation I product has a dramatic influence for substitute purchases of VCR/DVD players and a strong influence for PCs/notebooks. Yet, also as hypothesized, there was no influence on additional purchases. This implies that there is a clear distinction between additional and substitute purchases of generation II products, each with different drivers. For substitute purchases, product age is a key driver. Therefore marketers of high technology products can utilize data on generation I product age (e.g. from warranty or loyalty programs) to target customers who are more likely to make a purchase.