New approaches to gene discovery with animal models of obesity and diabetes

DNA-based approaches to the discovery of genes contributing to the development of type 2 diabetes have not been very successful despite substantial investments of time and money. The multiple gene-gene and gene-environment interactions that influence the development of type 2 diabetes mean that DNA approaches are not the ideal tool for defining the etiology of this complex disease. Gene expression-based technologies may prove to be a more rewarding strategy to identify diabetes candidate genes. There are a number of RNA-based technologies available to identify genes that are differentially expressed in various tissues in type 2 diabetes. These include differential display polymerase chain reaction (ddPCR), suppression subtractive hybridization (SSH), and cDNA microarrays. The power of new technologies to detect differential gene expression is ideally suited to studies utilizing appropriate animal models of human disease. We have shown that the gene expression approach, in combination with an excellent animal model such as the Israeli sand rat (Psammomys obesus), can provide novel genes and pathways that may be important in the disease process and provide novel therapeutic approaches. This paper will describe a new gene discovery, beacon, a novel gene linked with energy intake. As the functional characterization of novel genes discovered in our laboratory using this approach continues, it is anticipated that we will soon be able to compile a definitive list of genes that are important in the development of obesity and type 2 diabetes.

Intelligent animal fiber classification with artificial neural networks

Artificial neural networks (ANN) are increasingly used to solve many problems related to pattern recognition and object classification. In this paper, we report on a study using artificial neural networks to classify two kinds of animal fibers: merino and mohair. We have developed two different models, one extracting nine scale parameters with image processing, and the other using an unsupervised artificial neural network to extract features automatically, which are determined in accordance with the complexity of the scale structure and the accuracy of the model. Although the first model can achieve higher accuracy, it requires more effort for image processing and more prior knowledge, since the accuracy of the ANN largely depends on the parameters selected. The second model is more robust than the first, since only raw images are used. Because only ordinary optical images taken with a microscope are employed, we can use the approach for many textile applications without expensive equipment such as scanning electron microscopy.

Evaluating the softness of animal fibers

Softness is an important property of textile fibers, and animal fibers in particular. At present, there is no reliable method for objectively evaluating fiber softness. This paper examines a simple technique of such evaluations by pulling a bundle of parallel fibers through a series of pins. Softer fibers with lower bending rigidities and smoother surfaces should have lower pulling forces. Alpaca and wool fibers are used in this study to validate this technique, and the results suggest that pulling force measurements can reflect differences in fiber softness.

Methodological and conceptual issues in the search for a relationship between animal body-size distributions and benthic habitat architecture

Benthic ecologists have studied the distribution of animal body sizes because it is a form of ‘taxon-free’ classification that may be a useful metric for describing variation within and between ecological communities. In particular, the idea that the allometry of physiological and life-history traits may control species composition and relative abundances implies a functional link between body-size distributions and communities. The physical structure of aquatic habitats has often been cited as the mechanism by which habitat may determine body-size distributions in communities. However, further progress is hindered by a lack of theoretical clarity regarding the mechanisms that connect body size to the characteristics of ecological communities, leading to methods that may obscure interesting trends in body-size data. This review examines the methodological and conceptual issues hindering progress in the search for a relationship between animal body size and habitat architecture and suggests ways to resolve these issues. Problems are identified with current methods for the measurement of animal body size, the data and measures used to quantify body-size distributions and the methods used to identify patterns therein. Fundamentally, renewed emphasis on the mechanisms by which animal body sizes are influenced by habitat architecture is required to refine methodology and synthesise results from pattern-seeking and mechanistic studies.

Population dynamics and animal welfare issues raised by the culling of kangaroos in Puckapunyal

The culling of kangaroos at the Puckapunyal Army base (Australia) raises some intriguing ethical issues around animal welfare. After discussing the costs and benefits of the cull, this paper addresses the more general animal welfare issues related to population dynamics. Natural selection favours the maximization of the number of surviving offspring. This need not result in the maximization of the welfare of individuals in the species. The contrast between growth maximization and welfare maximization is first illustrated for a single population and then discussed in terms of competing populations. In the Lotka-Volterra model of competing species and its generalizations, the choice of different birthrates does not affect the population sizes at equilibrium. Welfare could be much higher at lower birthrates without even reducing numbers (at equilibrium)

FTIR and thermal analysis of cashmere and other animal fibres

In this paper, sereval varieties of animal fibres including cashmere and Australian fine Merino wool have been analysed by Fourier transform infrared microscope and differential scanning calorimeter. The results showed that both Chinese and Australian cashmere fibres started absorbing heat at a relatively higher temperature but were thermally degraded quicker than other animal fibres tested. However, the mass changes (within the temperature range of 200oC to 350oC) and associated onset temperatures varied among fibre varieties. From the attenuated total reflectance spectra, the Chinese cashmere was clearly different from Australian cashmere and wool in a peak near 1040 cm-1 wavelength for S-O stretching of cysteic acid residues. The Chinese cashmere presented a stronger absorption at 1019 cm-1 wavelength, while Australian cashmere and wool peaked at 1079 cm-1 wavelength and had a weaker absorption. Combined with thermal analysis, the normalised R-SO3 - content of cysteic acid residues to the amide II peak of the protein backbone may have potential use in identifying Australian fine Merino wool from Chinese cashmere.

A comparative study on the felting propensity of animal fibers

The felting propensity of different animal fibers, particularly alpaca and wool, has been examined. The Aachen felting test method was employed. 1 g of each type of fiber was soaked in 50 ml of wetting solution and agitated in a dyeing machine to make felt balls. The diameter of each ball was measured in nine directions and the ball density was calculated in g/cm3; the higher the density value of the ball, the higher the feltability of the fibers. The effects of fiber diameter and fiber length on the felting propensity of these fibers were investigated. The results show that the alpaca fibers felt to a higher degree than wool fibers, and short and fine cashmere fibers have lower felting propensity than wool fibers at a similar diameter range. There is a higher tendency of felting for bleached and dyed alpaca fibers than for untreated fibers. Fiber length has a remarkable influence on the propensity of fiber felting. Cotton and nylon fibers were also tested for felting propensity to verify the mechanism responsible for the different fiber felting behavior.

Profile of dyslipodemia in psammomys obesus, an animal model of the metabolic syndrome

Objective. To investigate lipid profiles in Psammomys obesus and relationships between lipid profile and other components of the Metabolic Syndrome.

Methods. A total number of 49 adults with a wide range of body weight and glucose tolerance were studied in a cross-sectional analysis. Plasma cholesterol distribution profiles were measured by size exclusion lipid chromatography. Blood glucose was measured using an enzymatic glucose analyser, and plasma insulin was determined by radioimmunossay.

Results. Obese diabetic Psammomys obesus had elevated plasma cholesterol (P=0.003) and triglyceride levels (p>0.001) compared to their lean littermates. The hypercholesterolemia was mainly due to increased circulating levels of VLDL-cholesterol (P=0.003) and LDL-cholesterol (P=0.003) in these animals. Multiple linear regression analyses revealed that body weight was independently associated with plasma cholesterol (P=0.011) and LDL concentration (P=0.009), while plasma insulin was associated with VLDL-cholesterol concentration (P=0.005). All of the variables measured exhibited continuous distributions across a wide range of phenotypes, from a normal rodent lipid profile to profound dyslipidemia.

Conclusions. These data suggest that the dyslipidemia in obese, diabetic Psammomys obesus is closely associated with other components of the Metabolic Syndrome, including obesity and insulin resistance.