ASU Scholarship Showcase

Although previous research has studied power in mediation models, the extent to which the inclusion of a mediator will increase power has not been investigated. To address this deficit, in a first study we compared the analytical power values of the mediated effect and the total effect in a single-mediator model, to identify the situations in which the inclusion of one mediator increased statistical power. The results from this first study indicated that including a mediator increased statistical power in small samples with large coefficients and in large samples with small coefficients, and when coefficients were nonzero and equal across models. Next, we identified conditions under which power was greater for the test of the total mediated effect than for the test of the total effect in the parallel two-mediator model. These results indicated that including two mediators increased power in small samples with large coefficients and in large samples with small coefficients, the same pattern of results that had been found in the first study. Finally, we assessed the analytical power for a sequential (three-path) two-mediator model and compared the power to detect the three-path mediated effect to the power to detect both the test of the total effect and the test of the mediated effect for the single-mediator model. The results indicated that the three-path mediated effect had more power than the mediated effect from the single-mediator model and the test of the total effect. Practical implications of these results for researchers are then discussed.

Climate change will result in increased precipitation variability with more extreme events reflected in more frequent droughts as well as more frequent extremely wet conditions. The increase in precipitation variability will occur at different temporal scales from intra to inter-annual and even longer scales. At the intra-annual scale, extreme precipitation events will be interspersed with prolonged periods in between events. At the inter-annual scale, dry years or multi-year droughts will be combined with wet years or multi-year wet conditions. Consequences of this aspect of climate change for the functioning ecosystems and their ability to provide ecosystem services have been underexplored. We used a process-based ecosystem model to simulate water losses and soil-water availability at 35 grassland locations in the central US under 4 levels of precipitation variability (control, +25, +50 + 75 %) and six temporal scales ranging from intra- to multi-annual variability.

We show that the scale of temporal variability had a larger effect on soil-water availability than the magnitude of variability, and that inter- and multi-annual variability had much larger effects than intra-annual variability. Further, the effect of precipitation variability was modulated by mean annual precipitation. Arid-semiarid locations receiving less than about 380 mm yr^-1 mean annual precipitation showed increases in water availability as a result of enhanced precipitation variability while more mesic locations (>380 mm yr^-1) showed a decrease in soil water availability. The beneficial effects of enhanced variability in arid-semiarid regions resulted from a deepening of the soil-water availability profile and a reduction in bare soil evaporation. The deepening of the soil-water availability profile resulting from increase precipitation variability may promote future shifts in species composition and dominance to deeper-rooted woody plants for ecosystems that are susceptible to state changes. The break point, which has a mean of 380-mm with a range between 440 and 350 mm, is remarkably similar to the 370-mm threshold of the inverse texture hypothesis, below which coarse-texture soils had higher productivity than fine-textured soils.

To achieve improved sensitivity in cardiac biomarker detection, a batch incubation magnetic microbead immunoassay was developed and tested on three separate human protein targets: myoglobin, heart-type fatty acid binding protein, and cardiac troponin I. A sandwich immunoassay was performed in a simple micro-centrifuge tube allowing full dispersal of the solid capture surface during incubations. Following magnetic bead capture and wash steps, samples were analyzed in the presence of a manipulated magnetic field utilizing a modified microscope slide and fluorescent inverted microscope to collect video data files. Analysis of the video data allowed for the quantitation of myoglobin, heart-type fatty acid binding protein and cardiac troponin I to levels of 360 aM, 67 fM, and 42 fM, respectively. Compared to the previous detection limit of 50 pM for myoglobin, this offers a five-fold improvement in sensitivity. This improvement in sensitivity and incorporation of additional markers, along with the small sample volumes required, suggest the potential of this platform for incorporation as a detection method in a total sample analysis device enabling multiplexed detection for the analysis of clinical samples.

Electrophoretic and dielectrophoretic approaches to separations can provide unique capabilities. In the past, capillary and microchip-based approaches to electrophoresis have demonstrated extremely high-resolution separations. More recently, dielectrophoretic systems have shown excellent results for the separation of bioparticles. Here we demonstrate resolution of a difficult pair of targets: gentamicin resistant and susceptible strains of Staphylococcus epidermidis. This separation has significant potential implications for healthcare. This establishes a foundation for biophysical separations as a direct diagnostic tool, potentially improving nearly every figure of merit for diagnostics and antibiotic stewardship. The separations are performed on a modified gradient insulator-based dielectrophoresis (g-iDEP) system and demonstrate that the presence of antibiotic resistance enzymes (or secondary effects) produces a sufficient degree of electrophysical difference to allow separation. The differentiating factor is the ratio of electrophoretic to dielectrophoretic mobilities. This factor is 4.6 ± 0.6 × 109 V m−2 for the resistant strain, versus 9.2 ± 0.4 × 109 V m−2 for the susceptible strain. Using g-iDEP separation, this difference produces clear and easily discerned differentiation of the two strains.