2007 Annual progress report synopsis of the Center for Structures of Membrane Proteins

A synopsis of the 2007 annual progress report for the Center for Structures of Membrane Proteins, a specialized center of the Protein Structure Initiative

p3d – Python module for structural bioinformatics

<p>Abstract</p> <p>Background</p> <p>High-throughput bioinformatic analysis tools are needed to mine the large amount of structural data via knowledge based approaches. The development of such tools requires a robust interface to access the structural data in an easy way. For this the Python scripting language is the optimal choice since its philosophy is to write an understandable source code.</p> <p>Results</p> <p>p3d is an object oriented Python module that adds a simple yet powerful interface to the Python interpreter to process and analyse three dimensional protein structure files (PDB files). p3d's strength arises from the combination of a) very fast spatial access to the structural data due to the implementation of a binary space partitioning (BSP) tree, b) set theory and c) functions that allow to combine a and b and that use human readable language in the search queries rather than complex computer language. All these factors combined facilitate the rapid development of bioinformatic tools that can perform quick and complex analyses of protein structures.</p> <p>Conclusion</p> <p>p3d is the perfect tool to quickly develop tools for structural bioinformatics using the Python scripting language.</p

Designing an automated clinical decision support system to match clinical practice guidelines for opioid therapy for chronic pain

Abstract Background Opioid prescribing for chronic pain is common and controversial, but recommended clinical practices are followed inconsistently in many clinical settings. Strategies for increasing adherence to clinical practice guideline recommendations are needed to increase effectiveness and reduce negative consequences of opioid prescribing in chronic pain patients. Methods Here we describe the process and outcomes of a project to operationalize the 2003 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Non-Cancer Pain into a computerized decision support system (DSS) to encourage good opioid prescribing practices during primary care visits. We based the DSS on the existing ATHENA-DSS. We used an iterative process of design, testing, and revision of the DSS by a diverse team including guideline authors, medical informatics experts, clinical content experts, and end-users to convert the written clinical practice guideline into a computable algorithm to generate patient-specific recommendations for care based upon existing information in the electronic medical record (EMR), and a set of clinical tools. Results The iterative revision process identified numerous and varied problems with the initially designed system despite diverse expert participation in the design process. The process of operationalizing the guideline identified areas in which the guideline was vague, left decisions to clinical judgment, or required clarification of detail to insure safe clinical implementation. The revisions led to workable solutions to problems, defined the limits of the DSS and its utility in clinical practice, improved integration into clinical workflow, and improved the clarity and accuracy of system recommendations and tools. Conclusions Use of this iterative process led to development of a multifunctional DSS that met the approval of the clinical practice guideline authors, content experts, and clinicians involved in testing. The process and experiences described provide a model for development of other DSSs that translate written guidelines into actionable, real-time clinical recommendations.http://deepblue.lib.umich.edu/bitstream/2027.42/78267/1/1748-5908-5-26.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/2/1748-5908-5-26.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/3/1748-5908-5-26-S3.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/4/1748-5908-5-26-S2.TIFFhttp://deepblue.lib.umich.edu/bitstream/2027.42/78267/5/1748-5908-5-26-S1.TIFFPeer Reviewe

Validation study of a web-based assessment of functional recovery after radical prostatectomy

<p>Abstract</p> <p>Background</p> <p>Good clinical care of prostate cancer patients after radical prostatectomy depends on careful assessment of post-operative morbidities, yet physicians do not always judge patient symptoms accurately. Logistical problems associated with using paper questionnaire limit their use in the clinic. We have implemented a web-interface ("STAR") for patient-reported outcomes after radical prostatectomy.</p> <p>Methods</p> <p>We analyzed data on the first 9 months of clinical implementation to evaluate the validity of the STAR questionnaire to assess functional outcomes following radical prostatectomy. We assessed response rate, internal consistency within domains, and the association between survey responses and known predictors of sexual and urinary function, including age, time from surgery, nerve sparing status and co-morbidities.</p> <p>Results</p> <p>Of 1581 men sent an invitation to complete the instrument online, 1235 responded for a response rate of 78%. Cronbach's alpha was 0.84, 0.86 and 0.97 for bowel, urinary and sexual function respectively. All known predictors of sexual and urinary function were significantly associated with survey responses in the hypothesized direction.</p> <p>Conclusions</p> <p>We have found that web-based assessment of functional recovery after radical prostatectomy is practical and feasible. The instrument demonstrated excellent psychometric properties, suggested that validity is maintained when questions are transferred from paper to electronic format and when patients give responses that they know will be seen by their doctor and added to their clinic record. As such, our system allows ready implementation of patient-reported outcomes into routine clinical practice.</p

A compendium and functional characterization of mammalian genes involved in adaptation to Arctic or Antarctic environments

Many mammals are well adapted to surviving in extremely cold environments. These species have likely accumulated genetic changes that help them efficiently cope with low temperatures. It is not known whether the same genes related to cold adaptation in one species would be under selection in another species. The aims of this study therefore were: to create a compendium of mammalian genes related to adaptations to a low temperature environment; to identify genes related to cold tolerance that have been subjected to independent positive selection in several species; to determine promising candidate genes/pathways/organs for further empirical research on cold adaptation in mammals

Inhibition of the aquaporin 3 water channel increases the sensitivity of prostate cancer cells to cryotherapy

Aquaporins (AQPs) are intrinsic membrane proteins that facilitate selective water and small solute movement across the plasma membrane. In this study, we investigate the role of inhibiting AQPs in sensitising prostate cancer cells to cryotherapy. PC-3 and DU145 prostate cancer cells were cooled to 0, −5 and −10°C. The expression of AQP3 in response to freezing was determined using real-time quantitative polymerase chain reaction (RT–qPCR) and western blot analysis. Aquaporins were inhibited using mercuric chloride (HgCl2) and small interfering RNA (siRNA) duplex, and cell survival was assessed using a colorimetric assay. There was a significant increase in AQP3 expression in response to freezing. Cells treated with AQP3 siRNA were more sensitive to cryoinjury compared with control cells (P<0.001). Inhibition of the AQPs by HgCl2 also increased the sensitivity of both cell lines to cryoinjury and there was a complete loss of cell viability at −10°C (P<0.01). In conclusion, we have shown that AQP3 is involved directly in cryoinjury. Inhibition of AQP3 increases the sensitivity of prostate cancer cells to freezing. This strategy may be exploited in the clinic to improve the efficacy of prostate cryotherapy

Water channel pore size determines exclusion properties but not solute selectivity

Aquaporins (AQPs) are a ubiquitous family of transmembrane water channel proteins. A subgroup of AQP water channels also facilitates transmembrane diffusion of small, polar solutes. A constriction within the pore, the aromatic/arginine (ar/R) selectivity filter, is thought to control solute permeability: previous studies on single representative water channel proteins suggest narrow channels conduct water, whilst wider channels permit passage of solutes. To assess this model of selectivity, we used mutagenesis, permeability measurements and in silico comparisons of water-specific as well as glycerol-permeable human AQPs. Our studies show that single amino acid substitutions in the selectivity filters of AQP1, AQP4 and AQP3 differentially affect glycerol and urea permeability in an AQP-specific manner. Comparison between in silico-calculated channel cross-sectional areas and in vitro permeability measurements suggests that selectivity filter cross-sectional area predicts urea but not glycerol permeability. Our data show that substrate discrimination in water channels depends on a complex interplay between the solute, pore size, and polarity, and that using single water channel proteins as representative models has led to an underestimation of this complexity

The SunPy Project: Open Source Development and Status of the Version 1.0 Core Package

The goal of the SunPy project is to facilitate and promote the use and development of community-led, free, and open source data analysis software for solar physics based on the scientific Python environment. The project achieves this goal by developing and maintaining the sunpy core package and supporting an ecosystem of affiliated packages. This paper describes the first official stable release (version 1.0) of the core package, as well as the project organization and infrastructure. This paper concludes with a discussion of the future of the SunPy project

Water dynamics in Shewanella oneidensis at ambient and high pressure using quasi-elastic neutron scattering

Quasielastic neutron scattering (QENS) is an ideal technique for studying water transport and relaxation dynamics at pico- to nanosecond timescales and at length scales relevant to cellular dimensions. Studies of high pressure dynamic effects in live organisms are needed to understand Earth’s deep biosphere and biotechnology applications. Here we applied QENS to study water transport in Shewanella oneidensis at ambient (0.1 MPa) and high (200 MPa) pressure using H/D isotopic contrast experiments for normal and perdeuterated bacteria and buffer solutions to distinguish intracellular and transmembrane processes. The results indicate that intracellular water dynamics are comparable with bulk diffusion rates in aqueous fluids at ambient conditions but a significant reduction occurs in high pressure mobility. We interpret this as due to enhanced interactions with macromolecules in the nanoconfined environment. Overall diffusion rates across the cell envelope also occur at similar rates but unexpected narrowing of the QENS signal appears between momentum transfer values Q = 0.7–1.1 Å−1 corresponding to real space dimensions of 6–9 Å. The relaxation time increase can be explained by correlated dynamics of molecules passing through Aquaporin water transport complexes located within the inner or outer membrane structures

A model for improving microbial biofuel production using a synthetic feedback loop

Cells use feedback to implement a diverse range of regulatory functions. Building synthetic feedback control systems may yield insight into the roles that feedback can play in regulation since it can be introduced independently of native regulation, and alternative control architectures can be compared. We propose a model for microbial biofuel production where a synthetic control system is used to increase cell viability and biofuel yields. Although microbes can be engineered to produce biofuels, the fuels are often toxic to cell growth, creating a negative feedback loop that limits biofuel production. These toxic effects may be mitigated by expressing efflux pumps that export biofuel from the cell. We developed a model for cell growth and biofuel production and used it to compare several genetic control strategies for their ability to improve biofuel yields. We show that controlling efflux pump expression directly with a biofuel-responsive promoter is a straightforward way of improving biofuel production. In addition, a feed forward loop controller is shown to be versatile at dealing with uncertainty in biofuel production rates