ASU Regents' Professors Open Access Works
The title “Regents’ Professor” is the highest faculty honor awarded at Arizona State University. It is conferred on ASU faculty who have made pioneering contributions in their areas of expertise, who have achieved a sustained level of distinction, and who enjoy national and international recognition for these accomplishments. This collection contains primarily open access works by ASU Regents' Professors.
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- Creators: School of Earth and Space Exploration
- Creators: Ji, Shuiwang
Nutrient availability and ratios can play an important role in shaping microbial communities of freshwater ecosystems. The Cuatro Ciénegas Basin (CCB) in Mexico is a desert oasis where, perhaps paradoxically, high microbial diversity coincides with extreme oligotrophy. To better understand the effects of nutrients on microbial communities in CCB, a mesocosm experiment was implemented in a stoichiometrically imbalanced pond, Lagunita, which has an average TN:TP ratio of 122 (atomic). The experiment had four treatments, each with five spatial replicates – unamended controls and three fertilization treatments with different nitrogen:phosphorus (N:P) regimes (P only, N:P = 16 and N:P = 75 by atoms). In the water column, quantitative PCR of the 16S rRNA gene indicated that P enrichment alone favored proliferation of bacterial taxa with high rRNA gene copy number, consistent with a previously hypothesized but untested connection between rRNA gene copy number and P requirement. Bacterial and microbial eukaryotic community structure was investigated by pyrosequencing of 16S and 18S rRNA genes from the planktonic and surficial sediment samples. Nutrient enrichment shifted the composition of the planktonic community in a treatment-specific manner and promoted the growth of previously rare bacterial taxa at the expense of the more abundant, potentially endemic, taxa. The eukaryotic community was highly enriched with phototrophic populations in the fertilized treatment. The sediment microbial community exhibited high beta diversity among replicates within treatments, which obscured any changes due to fertilization. Overall, these results showed that nutrient stoichiometry can be an important factor in shaping microbial community structure.
Cell-sediment separation methods can potentially enable determination of the elemental composition of microbial communities by removing the sediment elemental contribution from bulk samples. We demonstrate that a separation method can be applied to determine the composition of prokaryotic cells. The method uses chemical and physical means to extract cells from benthic sediments and mats. Recovery yields were between 5% and 40%, as determined from cell counts. The method conserves cellular element contents to within 30% or better, as assessed by comparing C, N, P, Mg, Al, Ca, Ti, Mn, Fe, Ni, Cu, Zn, and Mo contents in Escherichia coli. Contamination by C, N, and P from chemicals used during the procedure was negligible. Na and K were not conserved, being likely exchanged through the cell membrane as cations during separation. V, Cr, and Co abundances could not be determined due to large (>100%) measurement uncertainties. We applied this method to measure elemental contents in extremophilic communities of Yellowstone National Park hot springs. The method was generally successful at separating cells from sediment, but does not discriminate between cells and detrital biological or noncellular material of similar density. This resulted in Al, Ti, Mn, and Fe contamination, which can be tracked using proxies such as metal:Al ratios. With these caveats, we present the first measurements, to our knowledge, of the elemental abundances of a chemosynthetic community. The communities have C:N ratios typical of aquatic microorganisms, are low in P, and their metal abundances vary between hot springs by orders of magnitude.
Cataclysmic Variables (CVs) are close binary star systems with one component a white dwarf (WD) and the other a larger cooler star that fills its Roche Lobe. The cooler star is losing mass through the inner Lagrangian point of the binary and some unknown fraction of this material is accreted by the WD. One consequence of the WDs accreting material, is the possibility that they are growing in mass and will eventually reach the Chandrasekhar Limit. This evolution could result in a Supernova Ia (SN Ia) explosion and is designated the Single Degenerate Progenitor (SD) scenario. This paper is concerned with the SD scenario for SN Ia progenitors. One problem with the single degenerate scenario is that it is generally assumed that the accreting material mixes with WD core material at some time during the accretion phase of evolution and, since the typical WD has a carbon-oxygen CO core, the mixing results in large amounts of carbon and oxygen being brought up into the accreted layers. The presence of enriched carbon causes enhanced nuclear fusion and a Classical Nova explosion.
Both observations and theoretical studies of these explosions imply that more mass is ejected than is accreted. Thus, the WD in a Classical Nova system is losing mass and cannot be a SN Ia progenitor. However, the composition in the nuclear burning region is important and, in new calculations reported here, the consequences to the WD of no mixing of accreted material with core material have been investigated so that the material involved in the explosion has only a Solar composition. WDs with a large range in initial masses and mass accretion rates have been evolved. I find that once sufficient material has been accreted, nuclear burning occurs in all evolutionary sequences and continues until a thermonuclear runaway (TNR) occurs and the WD either ejects a small amount of material or its radius grows to about 10[superscript 12] cm and the evolution is ended. In all cases where mass ejection occurs, the mass of the ejecta is far less than the mass of the accreted material. Therefore, all the WDs are growing in mass. It is also found that the accretion time to explosion can be sufficiently short for a 1.0M[subscript ⊙] WD that recurrent novae can occur on a low mass WD. This mass is lower than typically assumed for the WDs in recurrent nova systems. Finally, the predicted surface temperatures when the WD is near the peak of the explosion imply that only the most massive WDs will be significant X-ray emitters at this time.
The occurrence of nonliquid and liquid physical states of submicron atmospheric particulate matter (PM) downwind of an urban region in central Amazonia was investigated. Measurements were conducted during two intensive operating periods (IOP1 and IOP2) that took place during the wet and dry seasons of the GoAmazon2014/5 campaign. Air masses representing variable influences of background conditions, urban pollution, and regional- and continental-scale biomass burning passed over the research site. As the air masses varied, particle rebound fraction, an indicator of physical state, was measured in real time at ground level using an impactor apparatus. Micrographs collected by transmission electron microscopy confirmed that liquid particles adhered, while nonliquid particles rebounded. Relative humidity (RH) was scanned to collect rebound curves.
When the apparatus RH matched ambient RH, 95 % of the particles adhered as a campaign average. Secondary organic material, produced for the most part by the oxidation of volatile organic compounds emitted from the forest, produces liquid PM over this tropical forest. During periods of anthropogenic influence, by comparison, the rebound fraction dropped to as low as 60 % at 95 % RH. Analyses of the mass spectra of the atmospheric PM by positive-matrix factorization (PMF) and of concentrations of carbon monoxide, total particle number, and oxides of nitrogen were used to identify time periods affected by anthropogenic influences, including both urban pollution and biomass burning. The occurrence of nonliquid PM at high RH correlated with these indicators of anthropogenic influence. A linear model having as output the rebound fraction and as input the PMF factor loadings explained up to 70 % of the variance in the observed rebound fractions. Anthropogenic influences can contribute to the presence of nonliquid PM in the atmospheric particle population through the combined effects of molecular species that increase viscosity when internally mixed with background PM and increased concentrations of nonliquid anthropogenic particles in external mixtures of anthropogenic and biogenic PM.
Background:
Drosophila gene expression pattern images document the spatiotemporal dynamics of gene expression during embryogenesis. A comparative analysis of these images could provide a fundamentally important way for studying the regulatory networks governing development. To facilitate pattern comparison and searching, groups of images in the Berkeley Drosophila Genome Project (BDGP) high-throughput study were annotated with a variable number of anatomical terms manually using a controlled vocabulary. Considering that the number of available images is rapidly increasing, it is imperative to design computational methods to automate this task.
Results:
We present a computational method to annotate gene expression pattern images automatically. The proposed method uses the bag-of-words scheme to utilize the existing information on pattern annotation and annotates images using a model that exploits correlations among terms. The proposed method can annotate images individually or in groups (e.g., according to the developmental stage). In addition, the proposed method can integrate information from different two-dimensional views of embryos. Results on embryonic patterns from BDGP data demonstrate that our method significantly outperforms other methods.
Conclusion:
The proposed bag-of-words scheme is effective in representing a set of annotations assigned to a group of images, and the model employed to annotate images successfully captures the correlations among different controlled vocabulary terms. The integration of existing annotation information from multiple embryonic views improves annotation performance.
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.