Dynamics of Gray Matter Loss in Alzheimer's Disease

We detected and mapped a dynamically spreading wave of gray matter loss in the brains of patients with Alzheimer's disease (AD). The loss pattern was visualized in four dimensions as it spread over time from temporal and limbic cortices into frontal and occipital brain regions, sparing sensorimotor cortices. The shifting deficits were asymmetric (left hemisphere >right hemisphere) and correlated with progressively declining cognitive status ( p 15% loss). The maps distinguished different phases of AD and differentiated AD from normal aging. Local gray matter loss rates (5.3 +/- 2.3% per year in AD v 0.9 +/- 0.9% per year in controls) were faster in the left hemisphere ( p < 0.029) than the right. Transient barriers to disease progression appeared at limbic/frontal boundaries. This degenerative sequence, observed in vivo as it developed, provides the first quantitative, dynamic visualization of cortical atrophic rates in normal elderly populations and in those with dementia.

Nitrogen cycling in degraded Leucaena leucocephala-Brachiaria decumbens pastures on an acid infertile soil in south-east Queensland, Australia

A grazing trial was conducted to quantify N cycling in degraded Leucaena leucocephala (leucaena)-Brachiaria decumbens (signal grass) pastures grown on an acid, infertile, podzolic soil in south-east Queensland. Nitrogen accumulation and cycling in leucaena-signal grass pastures were evaluated for 9 weeks until all of the leucaena on offer (mean 600 kg edible dry matter (EDM)/ha, 28% of total pasture EDM) was consumed. Nitrogen pools in the grass, leucaena, soil, cattle liveweight, faeces and urine were estimated. The podzolic soil (pH 4.8-5.9) was found to be deficient in P, Ca and K. Leucaena leaf tissues contained deficient levels of N, P and Ca. Grass tissues were deficient in N and P. Grazing was found to cycle 65% of N on offer in pasture herbage. However, due to the effect of the plant nutrient imbalances described above, biological N fixation by leucaena contributed only 15 kg/ha N to the pasture system over the 9-month regrowth period, of which 13 kg/ha N was cycled. Cattle retained 1.8 kg/ha N (8% of total N consumed) in body tissue and the remainder was excreted in dung and urine in approximately equal proportions. Mineral soil N concentrations did not change significantly (-3.5 kg/ha N) over the trial period. The ramifications of grazing and fertiliser management strategies, and implications for pasture rundown and sustainability are discussed.

Evaluating plant breeding strategies by simulating gene action and dryland environment effects

Functional genomics is the systematic study of genome-wide effects of gene expression on organism growth and development with the ultimate aim of understanding how networks of genes influence traits. Here, we use a dynamic biophysical cropping systems model (APSIM-Sorg) to generate a state space of genotype performance based on 15 genes controlling four adaptive traits and then search this spice using a quantitative genetics model of a plant breeding program (QU-GENE) to simulate recurrent selection. Complex epistatic and gene X environment effects were generated for yield even though gene action at the trait level had been defined as simple additive effects. Given alternative breeding strategies that restricted either the cultivar maturity type or the drought environment type, the positive (+) alleles for 15 genes associated with the four adaptive traits were accumulated at different rates over cycles of selection. While early maturing genotypes were favored in the Severe-Terminal drought environment type, late genotypes were favored in the Mild-Terminal and Midseason drought environment types. In the Severe-Terminal environment, there was an interaction of the stay-green (SG) trait with other traits: Selection for + alleles of the SG genes was delayed until + alleles for genes associated with the transpiration efficiency and osmotic adjustment traits had been fixed. Given limitations in our current understanding of trait interaction and genetic control, the results are not conclusive. However, they demonstrate how the per se complexity of gene X gene X environment interactions will challenge the application of genomics and marker-assisted selection in crop improvement for dryland adaptation.

SPAnDX: a process-based population dynamics model to explore management and climate change impacts on an invasive alien plant, Acacia nilotica

This paper describes a process-based metapopulation dynamics and phenology model of prickly acacia, Acacia nilotica, an invasive alien species in Australia. The model, SPAnDX, describes the interactions between riparian and upland sub-populations of A. nilotica within livestock paddocks, including the effects of extrinsic factors such as temperature, soil moisture availability and atmospheric concentrations of carbon dioxide. The model includes the effects of management events such as changing the livestock species or stocking rate, applying fire, and herbicide application. The predicted population behaviour of A. nilotica was sensitive to climate. Using 35 years daily weather datasets for five representative sites spanning the range of conditions that A. nilotica is found in Australia, the model predicted biomass levels that closely accord with expected values at each site. SPAnDX can be used as a decision-support tool in integrated weed management, and to explore the sensitivity of cultural management practices to climate change throughout the range of A. nilotica. The cohort-based DYMEX modelling package used to build and run SPAnDX provided several advantages over more traditional population modelling approaches (e.g. an appropriate specific formalism (discrete time, cohort-based, process-oriented), user-friendly graphical environment, extensible library of reusable components, and useful and flexible input/output support framework). (C) 2003 Published by Elsevier Science B.V.