Bayesian survival analysis using a MARS model

A Bayesian multivariate adaptive regression spline fitting approach is used to model univariate and multivariate survival data with censoring. The possible models contain the proportional hazards model as a subclass and automatically detect departures from this. A reversible jump Markov chain Monte Carlo algorithm is described to obtain the estimate of the hazard function as well as the survival curve.     

Copper-induced oxidative stress in the chlorophycean microalga Chlorella vulgaris: response of the antioxidant system

A concentration dependent increase in lipid peroxidation, carotenoid content and activity of superoxide dismutase was observed in the green microalga Chlorella vulgaris following copper exposure. In contrast, activities of catalase, ascorbate peroxidase and glutathione reductase, and the cellular GSH, ascorbate and K+ pool depicted a reverse trend. However, a significant rise in intracellular proline content was also evident in copper supplemented cultures. Though this study depicted the malfunction of the major antioxidant system of C. vulgaris under copper stress the test organism was found to survive and grow even at 3.0 microg mL(-1) of Cu treatment (32% growth). Further study is needed to establish the role of proline in metal toxicity regulation.     

Automatic particle selection: results of a comparative study

Manual selection of single particles in images acquired using cryo-electron microscopy (cryoEM) will become a significant bottleneck when datasets of a hundred thousand or even a million particles are required for structure determination at near atomic resolution. Algorithm development of fully automated particle selection is thus an important research objective in the cryoEM field. A number of research groups are making promising new advances in this area. Evaluation of algorithms using a standard set of cryoEM images is an essential aspect of this algorithm development. With this goal in mind, a particle selection "bakeoff" was included in the program of the Multidisciplinary Workshop on Automatic Particle Selection for cryoEM. Twelve groups participated by submitting the results of testing their own algorithms on a common dataset. The dataset consisted of 82 defocus pairs of high-magnification micrographs, containing keyhole limpet hemocyanin particles, acquired using cryoEM. The results of the bakeoff are presented in this paper along with a summary of the discussion from the workshop. It was agreed that establishing benchmark particles and using bakeoffs to evaluate algorithms are useful in promoting algorithm development for fully automated particle selection, and that the infrastructure set up to support the bakeoff should be maintained and extended to include larger and more varied datasets, and more criteria for future evaluations.     

GXXXG and AXXXA: common alpha-helical interaction motifs in proteins, particularly in extremophiles

The GXXXG motif is a frequently occurring sequence of residues that is known to favor helix-helix interactions in membrane proteins. Here we show that the GXXXG motif is also prevalent in soluble proteins whose structures have been determined. Some 152 proteins from a non-redundant PDB set contain at least one alpha-helix with the GXXXG motif, 41 +/- 9% more than expected if glycine residues were uniformly distributed in those alpha-helices. More than 50% of the GXXXG-containing alpha-helices participate in helix-helix interactions. In fact, 26 of those helix-helix interactions are structurally similar to the helix-helix interaction of the glycophorin A dimer, where two transmembrane helices associate to form a dimer stabilized by the GXXXG motif. As for the glycophorin A structure, we find backbone-to-backbone atomic contacts of the C alpha-H...O type in each of these 26 helix-helix interactions that display the stereochemical hallmarks of hydrogen bond formation. These glycophorin A-like helix-helix interactions are enriched in the general set of helix-helix interactions containing the GXXXG motif, suggesting that the inferred C alpha-H...O hydrogen bonds stabilize the helix-helix interactions. In addition to the GXXXG motif, some 808 proteins from the non-redundant PDB set contain at least one alpha-helix with the AXXXA motif (30 +/- 3% greater than expected). Both the GXXXG and AXXXA motifs occur frequently in predicted alpha-helices from 24 fully sequenced genomes. Occurrence of the AXXXA motif is enhanced to a greater extent in thermophiles than in mesophiles, suggesting that helical interaction based on the AXXXA motif may be a common mechanism of thermostability in protein structures. We conclude that the GXXXG sequence motif stabilizes helix-helix interactions in proteins, and that the AXXXA sequence motif also stabilizes the folded state of proteins.     

Semiparametric regression modeling with mixtures of Berkson and classical error, with application to fallout from the Nevada test site

We construct Bayesian methods for semiparametric modeling of a monotonic regression function when the predictors are measured with classical error. Berkson error, or a mixture of the two. Such methods require a distribution for the unobserved (latent) predictor, a distribution we also model semiparametrically. Such combinations of semiparametric methods for the dose response as well as the latent variable distribution have not been considered in the measurement error literature for any form of measurement error. In addition, our methods represent a new approach to those problems where the measurement error combines Berkson and classical components. While the methods are general, we develop them around a specific application, namely, the study of thyroid disease in relation to radiation fallout from the Nevada test site. We use this data to illustrate our methods, which suggest a point estimate (posterior mean) of relative risk at high doses nearly double that of previous analyses but that also suggest much greater uncertainty in the relative risk.     

Fundamentals and Application Potential of Arsenic-Resistant Bacteria for Bioremediation in Rhizosphere: A Review

As a hazardous environmental metalloid toxicant, arsenic (As)—at elevated levels in water and soil—has created a major public health concern through its entry into the food chain by accumulation in crops. Among the various methods reported thus far for reclamation of As-contaminated crop fields, bioremediation using bacteria with plant-growth-promoting traits has been found to be a most promising solution. There is every possibility that bacterial isolates with the ability to remove or immobilize As could be used for successful bioremediation. However, bioremediation needs to define its boundaries between promise and field application, as most studies have been restricted to laboratory results only. Rhizosphere interactions play a critical role in monitoring As bioavailability to crop plants, thus a better understanding of it might improve rhizoremediation technologies. The challenges rely on the application of these novel approaches under field conditions. Despite some limitations, the prospect for successful stimulation and exploitation of microbial metabolism for As rhizoremediation appears to be very promising.     

The UT-A1 urea transporter interacts with snapin, a SNARE-associated protein

The UT-A1 urea transporter mediates rapid transepithelial urea transport across the inner medullary collecting duct and plays a major role in the urinary concentrating mechanism. To transport urea, UT-A1 must be present in the plasma membrane. The purpose of this study was to screen for UT-A1-interacting proteins and to study the interactions of one of the identified potential binding partners with UT-A1. Using a yeast two-hybrid screen of a human kidney cDNA library with the UT-A1 intracellular loop (residues 409-594) as bait, we identified snapin, a ubiquitously expressed SNARE-associated protein, as a novel UT-A1 binding partner. Deletion analysis indicated that the C-terminal coiled-coil domain (H2) of snapin is required for UT-A1 interaction. Snapin binds to the intracellular loop of UT-A1 but not to the N- or C-terminal fragments. Glutathione S-transferase pulldown experiments and co-immunoprecipitation studies verified that snapin interacts with native UT-A1, SNAP23, and syntaxin-4 (t-SNARE partners), indicating that UT-A1 participates with the SNARE machinery in rat kidney inner medulla. Confocal microscopic analysis of immunofluorescent UT-A1 and snapin showed co-localization in both the cytoplasm and in the plasma membrane. When we co-injected UT-A1 with snapin cRNA in Xenopus oocytes, urea influx was significantly increased. In the absence of snapin, the influx was decreased when UT-A1 was combined with t-SNARE components syntaxin-4 and SNAP23. We conclude that UT-A1 may be linked to the SNARE machinery via snapin and that this interaction may be functionally and physiologically important for urea transport.