Prediction of many new exons and introns in Plasmodium falciparum chromosome 2

The current prediction or genes in the Plasmodium falciparum genome database relies upon a limited number of specially developed computer algorithms. We have re-annotated the sequence of chromosome 2 of P. falciparum by a computer-assisted manual analysis. which is described here. Of 161 newly predicted introns, we have experimentally confirmed 98. We regard 110 introns from the previously published analyses as probable, we delete 3, change 26 and add 135. We recognise 214 genes in chromosome 2. We have predicted introns in 121 genes. The increased complexity or gene structure on chromosome 2 is likely to be mirrored by the entire genome. (C) 2001 Elsevier Science B.V. All rights reserved.

Body mass index and the prediction of percentage body fat in Australian Chinese women

Background Body mass index (BMI) is frequently related to percentage body fat. Nevertheless, the relationship between BMI and fat mass/height(2) (FM/H-2), theoretically, should be more appropriate. Aim: This study seeks to evaluate the relationship between BMI and both percentage body fat and FM/H-2 in a group of Chinese Australian females. Subjects and methods: Forty subjects took part in the study and all were Chinese females resident in Brisbane, Australia. Body mass index was calculated from height and weight. Percentage body fat and fat mass were calculated from measurements of total body water. Results: The use of BMI to predict FM/H-2 accounted for double the variance of that found when BMI was used to predict percentage body fat. Conclusions: As a consequence, it is possible that the use of BMI to predict FM/H-2 and not percentage body fat in the first instance may prove to be more useful in a number of adult populations. Nevertheless, with a relatively small sample size it is difficult, if not impossible, to test the developed equations on a validation group and further investigation into the findings described in this paper needs to be undertaken.

Mechanical effects on the skeleton: Are there clinical implications?

The basic morphology of the skeleton is determined genetically, but its final mass and architecture are modulated by adaptive mechanisms sensitive to mechanical factors. When subjected to loading, the ability of bones to resist fracture depends on their mass, material properties, geometry and tissue quality. The contribution of altered bone geometry to fracture risk is unappreciated by clinical assessment using absorptiometry because it fails to distinguish geometry and density. For example, for the same bone area and density, small increases in the diaphyseal radius effect a disproportionate influence on torsional strength of bone. Mechanical factors are clinically relevant because of their ability to influence growth, modeling and remodeling activities that can maximize, or maintain, the determinants of fracture resistance. Mechanical loads, greater than those habitually encountered by the skeleton, effect adaptations in cortical and cancellous bone, reduce the rate of bone turnover, and activate new bone formation on cortical and trabecular surfaces. In doing so, they increase bone strength by beneficial adaptations in the geometric dimensions and material properties of the tissue. There is no direct evidence to demonstrate anti-fracture efficacy for mechanical loading, but the geometric alterations engendered undoubtedly increase the structural properties of bone as an organ, increasing the resistance to fracture. Like all interventions, issues of safety also arise. Physical activities involving high strain rates, heavy lifting or impact loading may be detrimental to the joints, leading to osteoarthritis; may stimulate fatigue damage leading with some to stress fractures; or may interact pharmaceutical interventions to increase the rate of microdamage within cortical or trabecular bone.

Growth hormone is permissive for skeletal adaptation to mechanical loading

The Lewis dwarf (DW) rat was used as a model to test the hypothesis that growth hormone (GH) is permissive for new bone formation induced by mechanical loading in vivo. Adult female Lewis DW rats aged 6.2 +/- 0.1 months (187 +/- 18 g) were allocated to four vehicle groups (DW), four GH treatment groups at 32.5 mug/100 g body mass (DWGH1), and four GH treatment groups at 65 mug/100 g (DWGH2). Saline vehicle or GH was injected intraperitoneally (ip) at 6:30 p.m. and 6:30 a.m. before mechanical loading of tibias at 7:30 a.m. A single period of 300 cycles of four-point bending was applied to right tibias at 2.0 Hz, and magnitudes of 24, 29, 38, or 48N were applied. Separate strain gauge analyses in 5 DW rats validated the selection of loading magnitudes. After loading, double-label histomorphometry was used to assess bone formation at the periosteal surface (Ps.S) and endocortical surface (Ec.S) of tibias. Comparing left (unloaded) tibias among groups, GH treatment had no effect on bone formation. Bone formation in tibias in DW rats was insensitive to mechanical loading. At the Ec.S, mechanically induced lamellar bone formation increased in the DWGH2 group loaded at 48N (p < 0.05), and no significant increases in bone formation were observed among other groups. The percentage of tibias expressing woven bone formation (Wo.B) at the Ps.S was significantly greater in the DWGH groups compared with controls (p < 0.05). We concluded that GH influences loading-related bone formation in a permissive manner and modulates the responsiveness of bone tissue to mechanical stimuli by changing thresholds for bone formation.

Techniques to determine ignition, flame stability and burnout of blended coals in p.f. power station boilers

The blending of coals has become popular to improve the performance of coals, to meet specifications of power plants and, to reduce the cost of coals, This article reviews the results and provides new information on ignition, flame stability, and carbon burnout studies of blended coals. The reviewed studies were conducted in laboratory-, pilot-, and full-scale facilities. The new information was taken in pilot-scale studies. The results generally show that blending a high-volatile coal with a low-volatile coal or anthracite can improve the ignition, flame stability and burnout of the blends. This paper discusses two general methods to predict the performance of blended coals: (1) experiment; and (2) indices. Laboratory- and pilot-scale tests, at least, provide a relative ranking of the combustion performance of coal/blends in power station boilers. Several indices, volatile matter content, heating value and a maceral index, can be used to predict the relative ranking of ignitability and flame stability of coals and blends. The maceral index, fuel ratio, and vitrinite reflectance can also be used to predict the absolute carbon burnout of coal and blends within limits. (C) 2000 Elsevier Science Ltd. All rights reserved.

The mechanisms of combustion and continuous reactions during mechanical alloying

Some materials exhibit a combustion event during mechanical alloying, which results in the rapid transformation of reactants into products, while others show a slow transformation of reactants into products, In this paper, the continuous W + C --> WC reaction is compared to the Ti + C --> TiC combustion reaction. Rietveld refinement of X-ray diffraction patterns is used to show that these particular reactions proceed through different pathways, determined by crystallographic factors of the reactants. When a crystallographic relationship exists between the reactants and the products, such as that between W and WC, the product forms slowly over a period of time. In contrast, insertion of C into the Ti structure is associated with atomic rearrangements within the crowded lattice planes and the subsequent catastrophic failure of the reactant lattices results in combustion to form TiC. (C) 2001 Academic Press.

The Alcohol Helplessness Scale and its prediction of depression among problem drinkers

Event-specific scales commonly have greater power than generalized scales in prediction of specific disorders and in testing mediator models for predicting such disorders. Therefore, in a preliminary study, a 6-item Alcohol Helplessness Scale was constructed and found to be reliable for a sample of 98 problem drinkers. Hierarchical multiple regression and its derivative path analysis were used to test whether helplessness and self-efficacy moderate or mediate the link between alcohol dependence and depression, A test of a moderation model was not supported, whereas a test of a mediation model was supported. Helplessness and self-efficacy both significantly and independently mediated between alcohol dependence and depression. Nevertheless, a significant direct effect of alcohol dependence on depression also remained, (C) 2001 John Wiley & Sons, Inc.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

Computation of the linear elastic properties of random porous materials with a wide variety of microstructure

A finite-element method is used to study the elastic properties of random three-dimensional porous materials with highly interconnected pores. We show that Young's modulus, E, is practically independent of Poisson's ratio of the solid phase, nu(s), over the entire solid fraction range, and Poisson's ratio, nu, becomes independent of nu(s) as the percolation threshold is approached. We represent this behaviour of nu in a flow diagram. This interesting but approximate behaviour is very similar to the exactly known behaviour in two-dimensional porous materials. In addition, the behaviour of nu versus nu(s) appears to imply that information in the dilute porosity limit can affect behaviour in the percolation threshold limit. We summarize the finite-element results in terms of simple structure-property relations, instead of tables of data, to make it easier to apply the computational results. Without using accurate numerical computations, one is limited to various effective medium theories and rigorous approximations like bounds and expansions. The accuracy of these equations is unknown for general porous media. To verify a particular theory it is important to check that it predicts both isotropic elastic moduli, i.e. prediction of Young's modulus alone is necessary but not sufficient. The subtleties of Poisson's ratio behaviour actually provide a very effective method for showing differences between the theories and demonstrating their ranges of validity. We find that for moderate- to high-porosity materials, none of the analytical theories is accurate and, at present, numerical techniques must be relied upon.