dynamic-contrast-enhanced-magnetic-resonance-imaging-an-orthotopic

Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has been limitedly used for orthotopic pancreatic tumor xenografts due to severe ...

University of Alabama at Birmingham

Body size is a major component of fitness. However, the relative contributions of different factors to optimal size, and the determinants of spatial and temporal variation in size, have not been fully established empirically. Here, we use a mesocosm of a Drosophilidae assemblage inhabiting decaying nectarines to investigate the influence of spatial variation in temperature on adult body size in Drosophila simulans Sturtevant. Two treatments were established; one in the sun where developing larvae were exposed to high temperatures and the other in the shade where temperature conditions were milder. The simple developmental effects of temperature differences (i.e. larger flies are likely to emerge from cooler environments), or the simple effects of stressful temperatures (i.e. high temperatures yield wing abnormalities and smaller flies), were overridden by interactive effects between temperature and larval density. Emergences were lower in the sun than shade, probably as a result of temperature-induced mortality. However, flies attained the same final sizes in the shade and sun. In addition, abnormally winged flies were clustered in the shaded treatments. In the shade treatments, where emergences were higher than in the sun, stressful conditions as a result of high larval density likely resulted in wing abnormalities and small size. Consequently, there was little spatial variation in size across the mesocosm, but substantial spatial variation in abundance. Under natural conditions both mortality and non-lethal effects of temperature and/or crowding are likely to play a role in the evolution of body size.

Body size patterns in Drosophila inhabiting a mesocosm: interactive effects of spatial variation in temperature and abundance.

1. Understanding and predicting the form of species distributions, or occupancy patterns, is fundamental to macroecology and is dependent on the identification of scaling relationships that underlie the patterns observed. 2. Occupancy-abundance models based on the negative binomial distribution and Taylor's power law are spatially implicit, rather than explicit, as they include no information on the relative positions of individuals. Here we present a spatially explicit model, the spatial scaling occupancy (SSO) model, to estimate species occupancy and spatial correlation, based on join-count statistics, or a pair approximation, approach. This model provides a spatially explicit description of species range size and aspects of range structure. 3. Occupancy data from Drosophilidae species inhabiting a decaying fruit mesocosm were used to test the SSO model. Predictions from the spatially implicit and explicit models were largely equally accurate. The SSO model is thus more efficient as it is less data demanding, and more informative as it provides an estimation of spatial correlation. 4. The results also showed that species distribution patterns differ when examined with spatially implicit vs. explicit approaches; the scaling relationship between occupancy and local density identifies a focal grain for studying the scale-dependent nature of ecological relationships; and the longer the length of the sample edge, the higher the occupancy observed under conditions of spatial aggregation. 5. The SSO model presents a step towards a general scaling model for occupancy, and demonstrates that the inclusion of spatially explicit information in macroecological models warrants further attention.

Marie Warren

Radiology

University of Alabama at Birmingham

Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model

Marie Warren

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University of Alabama at Birmingham

Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model

Radiology