Biomedical subjects

Andrew P Robinson

Publications and source records attributed to Andrew P Robinson.

5 recordsLinked to original sources

PubMed2005

Human stem/progenitor cells from bone marrow promote neurogenesis of endogenous neural stem cells in the hippocampus of mice.

Stem/progenitor cells from bone marrow and other sources have been shown to repair injured tissues by differentiating into tissue-specific phenotypes, by secreting chemokines, and, in part, by cell fusion. Here we prepared the stem/progenitor cells from human bone marrow (MSCs) and implanted athem into the dentate gyrus of the hippocampus of immunodeficient mice. The implanted human MSCs markedly increased the proliferation of endogenous neural stem cells that expressed the stem cell marker Sox2. Labeling of the mice with BrdUrd demonstrated that, 7 days after implantation of the human MSCs, BrdUrd-labeled endogenous cells migrated throughout the dorsal hippocampus (positive for doublecortin) and expressed markers for astrocytes and for neural or oligodendrocyte progenitors. Subpopulations of BrdUrd-labeled cells exhibited short cytoplasmic processes immunoreactive for nerve growth factor and VEGF. By 30 days after implantation, the newly generated cells expressed markers for more mature neurons and astrocytes. Also, subpopulations of BrdUrd-labeled cells exhibited elaborate processes immunoreactive for ciliary neurotrophic factor, neurotrophin-4/5, nerve growth factor, or VEGF. Therefore, implantation of human MSCs stimulated proliferation, migration, and differentiation of the endogenous neural stem cells that survived as differentiated neural cells. The results provide a paradigm to explain recent observations in which MSCs or related stem/progenitor cells were found to produce improvements in disease models even though a limited number of the cells engrafted.

Alu Elements↗

PubMed2005

Estimating leaf-level parameters for ecosystem process models: a study in mixed conifer canopies on complex terrain.

Ecosystem process models are often used to predict carbon flux on a landscape or on a global scale. Such models must be aggregate and canopies are often treated as a uniform unit of foliage. Parameters that are known to vary within the canopy, e.g., nitrogen content and leaf mass per area, are often estimated by a mean value for the canopy. Estimating appropriate means is complicated, especially in mixed-species stands and in complex terrain. We analyzed sources of variation in specific parameters with the goal of testing various simplifying assumptions. The measurements came from mixed-species forests in the northern Rocky Mountains. We found that, for three important parameters (nitrogen concentration and content, and leaf mass per area), a sample taken near the vertical center of the crown provided a good estimate of the mean values for the crown. Altitude (700-1700 m), solar insolation (4200-5400 MJ m(-2) year(-1)) and leaf area index (1-11) had negligible effects on the parameters; only species differences were consistently detected. The correlation between mass-based photosynthetic rates and mass-based nitrogen concentrations was much weaker than the correlation between area-based photosynthetic rates and area-based nitrogen concentration. Comparison of photosynthesis-nitrogen relationships for a wide variety of conifer species and sites revealed a broad general trend that can be used in models. These results suggest important potential simplifications in model parameterization, most notably that canopy means can be estimated with ease, that complex terrain is a minor source of variation in these parameters and that use of one photosynthesis-nitrogen relationship for conifer species does not result in large errors. Species-to-species variation, however, was large and needs to be accounted for when parameterizing process models.

Altitude↗

PubMed2005

On the validation of models of forest CO2 exchange using eddy covariance data: some perils and pitfalls.

With the widespread application of eddy covariance technology, long-term records of hourly ecosystem mass and energy exchange are becoming available for forests around the world. These data sets hold great promise for testing and validation of models of forest function. However, model validation is not a straightforward task. The goals of this paper were to: (1) review some of the problems inherent in model validation; and (2) survey the tools available to modelers to improve validation procedures, with particular reference to eddy covariance data. A simple set of models applied to a data set of ecosystem CO2 exchange is used to illustrate our points. The major problems discussed are equifinality, insensitivity and uncertainty. Equifinality is the problem that different models, or different parameterizations of the same model, may yield similar results, making it difficult to distinguish which is correct. Insensitivity arises because the major sources of variation in eddy covariance data are the annual and diurnal cycles, which are represented by even the most basic models, and the size of the response to these cycles can mask effects of other driving variables. Uncertainty arises from three main sources: parameters, model structure and data, each of which is discussed in turn. Uncertainty is a particular issue with eddy covariance data because of the lack of replicated measurements and the potential for unquantified systematic errors such as flux loss due to advection. We surveyed several tools that improve model validation, including sensitivity analysis, uncertainty analysis, residual analysis and model comparison. Illustrative examples are used to demonstrate the use of each tool. We show that simplistic comparisons of model outputs with eddy covariance data are problematic, but use of these tools can greatly improve our confidence in model predictions.

Carbon Dioxide↗

PubMed2005

A regression-based equivalence test for model validation: shifting the burden of proof.

Model validation is often realized as a test of how well model predictions match a set of independent observations. One would think that the burden of proof should rest with the model, to force it to show that it can make accurate predictions. Further, one would think that increasing the sample size ought to increase the model's ability to demonstrate its utility. Traditional statistical tools are inappropriate for this because they default to the case that the model and the data are no different, and their ability to detect differences increases with the sample size. These traditional tools are optimized to detect differences, rather than similarities. We present an alternative strategy for model validation that is based on regression and statistical tests of equivalence. Equivalence tests reverse the usual null hypothesis: they posit that the populations being compared are different and use the data to prove otherwise. In this sense, equivalence tests are lumping tests, whereas the traditional statistical tests are splitting tests. To date, model validation with equivalence tests has focused on comparisons of means. Our proposed test checks not only for similarity of means, but also for similarity between individual predictions and observations. The strategy is demonstrated using three case studies that differ in their modeling objectives, and for varied sample sizes. The proposed strategy provides a formal means of model validation that is superior to traditional statistical tests in each case.

Forestry↗

PubMed2003

Effects of a simple plant morphological mutation on the arthropod community and the impacts of predators on a principal insect herbivore.

Plant features that enhance predator effectiveness can be considered extrinsic-resistance factors because they result in reduced insect herbivory. In this paper we test the hypothesis that reduced epicuticular wax (EW) in Pisum sativum L. is an extrinsic-resistance factor contributing to field resistance to Acyrthosiphon pisum (Harris). We monitored pea aphid populations in the field on reduced EW and normal EW near isolines of peas for two seasons and confirmed that aphid populations are lower on reduced EW peas than on normal EW peas. We also monitored predators within the canopies of the two pea lines to discover community level patterns in response to differences in EW. We found that while predator numbers were similar between the two lines, there were more syrphids on the normal EW peas, and a trend towards more coccinellids on reduced EW peas. We tested the impact of predators on pea aphids on the two EW lines by monitoring their population levels in cages that excluded predators, and in cages that allowed predators to enter. We found that pea aphid populations were similar on the two EW lines when predators were excluded. When predators were allowed access to the plants, pea aphid populations were reduced more on reduced EW peas than on normal EW peas. We also examined the intrinsic resistance to aphids in reduced EW peas with laboratory dual-choice tests comparing aphid response to reduced EW and normal EW peas, and found that walking, apterous aphids displayed no preference for one pea line over the other. Bioassays to measure growth and fecundity of the pea aphid on the two EW types in the greenhouse and in the field showed that intrinsic rate of increase, and other life table parameters, were not different for aphids on the two lines. Together these results support the hypothesis that reduced EW in peas is a predator-dependent extrinsic resistance factor. Genetically reducing EW bloom in peas and other waxy crop plants might improve the effectiveness of arthropod natural enemies of insect pests. More generally, the results show that a subtle change in plant morphology can substantially influence the impact of predators on insect herbivore populations. The benefit of extrinsic resistance to herbivory conferred by reduced EW may balance any benefits of a prominent EW bloom, thereby sustaining EW polymorphisms in some natural plant populations.

Adaptation, Physiological↗