Biomedical subjects

Sean A McKenna

Publications and source records attributed to Sean A McKenna.

5 recordsLinked to original sources

PubMed2006

Rapid purification of RNAs using fast performance liquid chromatography (FPLC).

We present here an improved RNA purification method using fast performance liquid chromatography (FPLC) size-exclusion chromatography in place of denaturing polyacrylamide gel electrophoresis (PAGE). The method allows preparation of milligram quantities of pure RNA in a single day. As RNA oligonucleotides behave differently from globular proteins in the size-exclusion column, we present standard curves for RNA oligonucleotides of different lengths on both the Superdex 75 column and the Superdex 200 size-exclusion column. Using this approach, we can separate monomer from multimeric RNA species, purify the desired RNA product from hammerhead ribozyme reactions, and isolate refolded RNA that has aggregated after long-term storage. This methodology allows simple and rapid purification of RNA oligonucleotides for structural and biophysical studies.

Chromatography, Gel↗

PubMed2006

Delineating high-density areas in spatial Poisson fields from strip-transect sampling using indicator geostatistics: application to unexploded ordnance removal.

An approach for delineating high anomaly density areas within a mixture of two or more spatial Poisson fields based on limited sample data collected along strip transects was developed. All sampled anomalies were transformed to anomaly count data and indicator kriging was used to estimate the probability of exceeding a threshold value derived from the cdf of the background homogeneous Poisson field. The threshold value was determined so that the delineation of high-density areas was optimized. Additionally, a low-pass filter was applied to the transect data to enhance such segmentation. Example calculations were completed using a controlled military model site, in which accurate delineation of clusters of unexploded ordnance (UXO) was required for site cleanup.

Environmental Monitoring↗

PubMed2006

Uncoupling of RNA binding and PKR kinase activation by viral inhibitor RNAs.

Protein kinase RNA-activated (PKR) is a serine/threonine kinase that contains an N-terminal RNA-binding domain and a C-terminal kinase domain. Upon binding double-stranded RNA (dsRNA), PKR can become activated and phosphorylate cellular targets, such as eukaryotic translation initiation factor 2alpha (eIF-2alpha). Phosphorylation of eIF-2alpha results in attenuation of protein translation by the ribosome in either a general or an mRNA-specific manner. Therefore, the interaction between PKR and dsRNAs represents a crucial host cell defense mechanism against viral infection. Viruses can circumvent PKR function by transcription of virus-encoded dsRNA inhibitors that bind to and inactivate PKR. We present here a biophysical characterization of the interactions between human PKR and two viral inhibitor RNAs, EBER(I) (from Epstein-Barr virus) and VA(I) (from human adenovirus). Autophosphorylation assays confirmed that both EBER(I) and VA(I) are inhibitors of PKR activation, and profiled the kinetics of the inhibition. Binding affinities of dsRNAs to PKR double-stranded RNA-binding domains (dsRBDs) were determined by isothermal titration calorimetry and gel electrophoresis. A single stem-loop domain from each inhibitory RNA mediates the interaction with both dsRBDs of PKR. The binding sites on inhibitor RNAs and the dsRBDs of PKR have been mapped by NMR chemical shift perturbation experiments, which indicate that inhibitors of PKR employ similar surfaces of interaction as activators. Finally, we show that dsRNA binding and inactivation are non-equivalent; regions other than the dsRBD stem-loops of inhibitory RNA are required for inhibition.

Adenoviruses, Human↗

PubMedDate not supplied

Modeling dispersion in three-dimensional heterogeneous fractured media at Yucca Mountain.

Highly resolved numerical simulations are conducted to evaluate the longitudinal and transverse dispersivities proposed for use in the larger-scale Yucca Mountain saturated zone (SZ) site-scale model. Two different stochastic continuum models (SCM) that define the spatial variability of permeability are inferred from the observed fracture characteristics and the measured permeabilities. These models are created with a combination of indicator geostatistics and boolean simulation that allow for modeling different correlation lengths and anisotropy ratios at different permeability thresholds as well as the inclusion of large, high-permeability features. Longitudinal and transverse (horizontal and vertical) dispersion through the permeability realizations is evaluated for both distributed and focused source geometries using groundwater flow and streamline particle tracking. These numerical results are compared to behavior predicted by an analytical solution and to dispersivities estimated by an expert panel. Early time transport results are significantly non-Gaussian due to the strong heterogeneity of the fractured medium. At late times, travel distances of 23 correlation lengths, the longitudinal and transverse horizontal dispersivity results are well approximated by the analytical solution and the expert elicitation estimates. The calculated transverse vertical dispersivity values are smaller than those estimated from the analytical solution. Inclusion of high-permeability features of the same size as the model domain with a distributed planar source creates extreme values of the longitudinal and transverse horizontal dispersivity.

Forecasting↗

PubMedDate not supplied

Local hydraulic gradient estimator analysis of long-term monitoring networks.

Three measurements of head at unique locations form a three-point estimator of the local magnitude and orientation of the hydraulic gradient. The relative head measurement error (RHME) is defined here as the measurement error normalized by the head drop across the three-point estimator. Monte Carlo simulation results show that estimators with base to height ratios between 0.5 and 5.0 and that are large enough to keep the RHME below 0.05 create the most accurate gradient estimates and provide criteria for identifying good estimators. These criteria are applied to an example ground water monitoring network design problem in the Culebra dolomite near the Waste Isolation Pilot Plant repository to both analyze temporal changes and modify and expand the current monitoring network. Limiting the three-point estimators to those that meet the shape and RHME criteria reduces the number of possible estimators by >50% and leads to approximately 1 order of magnitude decrease in the average estimated magnitude of the gradient relative to using all estimators. Application of these criteria also reduces the variability in estimated gradient magnitude and orientation between the two time periods of measurements. Redundant wells in the network are identified by removing each existing well in turn and determining which removals yield the smallest decrease in the number of acceptable estimators. Optimal new well locations are identified by mapping the increase in total number of acceptable estimators for a single new well placed in the study domain.

Computer Simulation↗