Submission of Microarray Data to Public Repositories

The Microarray Gene Expression Data Society believe that the time is right for journals to require that microarray data be deposited in public repositories, as a condition for publicatio

Effect of a Mass Casualty Incident: Clinical Outcomes and Hospital Charges for Casualty Patients Versus Concurrent Inpatients

Objectives:  A mass casualty incident (MCI) may strain a health care system beyond surge capacity, affecting patterns of care for casualties and other patients. Prior studies of MCIs have assessed clinical care for casualty patients, but have not examined outcomes or expenditures for noncasualty inpatients in the same time period. Methods:  This was a retrospective analysis of administrative hospital claims in a state where an MCI with over 200 casualties occurred; two hospitals that admitted casualties of >5% of their inpatient capacity were studied. The “surge period” was defined as 7 days after the MCI. Using diagnostic codes, patients admitted on the MCI day with diagnoses of burns or inhalation injury were included in the “MCI surge cohort.” Patients admitted within a time frame of 7 days prior to 7 days after the MCI who were inpatients during the surge period were included in the “non‐MCI surge cohort.” The authors compared the MCI and non‐MCI surge cohorts to a mutually exclusive reference cohort (all inpatients during 6 weeks prior to the MCI), regarding key outcomes of hospital length of stay (LOS) and hospital charges adjusted for age, sex, race/ethnicity, and severity of illness. Results:  Fifty‐five patients met criteria for the MCI surge cohort, 1,369 for the non‐MCI surge cohort, and 5,980 for the reference group. Compared with the reference group and adjusted for covariates, the mean (±SD) hospital LOS was 4.90 (±1.85) days longer for the MCI surge cohort (95% confidence interval [CI] = 1.67 to 8.84) and 1.34 (±0.16) days longer for the non‐MCI surge cohort (95% CI = 1.00 to 1.65). The MCI cohort also had significantly longer mean hospital LOS than the non‐MCI surge cohort (difference = 3.56 days; 95% CI = 0.36 to 7.36). Also adjusted for covariates, mean (±SD) total hospital charges for the MCI surge cohort were $22,349 (±$8,342) greater than for the reference group (95% CI = $8,182 to$39,485). Mean (±SD) charges for the non‐MCI surge cohort were $4,028 (±$633) greater than for the reference group (95% CI = $2,792 to$5,196). The MCI cohort also had higher mean total charges than the non‐MCI surge cohort (difference = $18,321; 95$4,488 to $34,980). Conclusions:  When adjusted for severity of illness, casualty patients and noncasualty patients receiving concurrent hospital care have significantly longer LOS and higher charges than typical hospital patients at times unaffected by MCIs. Spillover effects from MCIs for noncasualty patients have not been previously described and have implications for clinical and hospital management in MCI and other high‐surge circumstances.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90586/1/j.1553-2712.2011.01278.x.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/90586/2/ACEM_1278_sm_DataSupplementS1.pd

NCBI GEO: archive for high-throughput functional genomic data

The Gene Expression Omnibus (GEO) at the National Center for Biotechnology Information (NCBI) is the largest public repository for high-throughput gene expression data. Additionally, GEO hosts other categories of high-throughput functional genomic data, including those that examine genome copy number variations, chromatin structure, methylation status and transcription factor binding. These data are generated by the research community using high-throughput technologies like microarrays and, more recently, next-generation sequencing. The database has a flexible infrastructure that can capture fully annotated raw and processed data, enabling compliance with major community-derived scientific reporting standards such as ‘Minimum Information About a Microarray Experiment’ (MIAME). In addition to serving as a centralized data storage hub, GEO offers many tools and features that allow users to effectively explore, analyze and download expression data from both gene-centric and experiment-centric perspectives. This article summarizes the GEO repository structure, content and operating procedures, as well as recently introduced data mining features. GEO is freely accessible at http://www.ncbi.nlm.nih.gov/geo/

Incorporation by coordination and release of the iron chelator drug deferiprone from zinc-based metal–organic frameworks

A series of new zinc-based metal–organic framework materials has been prepared in which deferiprone is incorporated as a chelating ligand on infinite or tri-zinc secondary building units following deprotonation. Deferiprone is immediately released from the MOFs on treatments with 1 N hydrochloric acid or buffer, but slow release is observed in ethanoic acid

Navigating Public Microarray Databases

With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources

Identification of gene expression logical invariants in Arabidopsis.

Numerous gene expression datasets from diverse tissue samples from the plant variety Arabidopsis thaliana have been already deposited in the public domain. There have been several attempts to do large scale meta-analyses of all of these datasets. Most of these analyses summarize pairwise gene expression relationships using correlation, or identify differentially expressed genes in two conditions. We propose here a new large scale meta-analysis of the publicly available Arabidopsis datasets to identify Boolean logical relationships between genes. Boolean logic is a branch of mathematics that deals with two possible values. In the context of gene expression datasets we use qualitative high and low expression values. A strong logical relationship between genes emerges if at least one of the quadrants is sparsely populated. We pointed out serious issues in the data normalization steps widely accepted and published recently in this context. We put together a web resource where gene expression relationships can be explored online which helps visualize the logical relationships between genes. We believe that this website will be useful in identifying important genes in different biological context. The web link is http://hegemon.ucsd.edu/plant/

Phenological shifts in hoverflies (Diptera: Syrphidae): linking measurement and mechanism

An understanding of ecological and evolutionary responses to global environmental change requires both a robust measurement of the change that is occurring and a mechanistic framework for understanding the drivers of that change. Such a requirement provides a challenge because biological monitoring is often ad hoc, and mechanistic experiments are often performed under highly simplified conditions. This study integrates multiple datasets to evaluate our current knowledge of the measurement and mechanism of phenological shifts in a key pollinator taxon: the hoverflies (Diptera: Syrphidae). First, two large, complementary and independent monitoring datasets are used to test for trends in phenology: an ad hoc national recording scheme containing >620,000 records, and standardised monitoring with consistent methods over 30 years. Results show that ad hoc and standardised recording data give quantitatively the same value for phenological advance in hoverflies (ca. 12 days°C-1 on average at the beginning of the flight period), supporting the value of biological recording for the measurement of global ecological change. While the end of the flight period appears static in ad hoc recording, the standardised dataset suggests a similar advance as in the beginning of the flight period. Second, an extensive traits dataset and a novel database of laboratory-derived developmental data on Syrphidae (153 published studies) are used to test for mechanistic patterns in phenological shifts. The only species trait that influenced phenology was voltinism, where species with more generations per year exhibit stronger phenological advances. We demonstrate considerable variation in the laboratory-derived sensitivity to temperature but this does not match field-derived measures of phenology. The results demonstrate that, as for many taxa, we have a strong understanding of the patterns of global ecological change but that we currently lack a detailed mechanistic understanding of those processes despite extensive research into 45 the fundamental biology of some taxonomic groups

Crystallographic and Biochemical Analysis of the Ran-Binding Zinc Finger Domain

The nuclear pore complex (NPC) resides in circular openings within the nuclear envelope and serves as the sole conduit to facilitate nucleocytoplasmic transport in eukaryotes. The asymmetric distribution of the small G protein Ran across the nuclear envelope regulates directionality of protein transport. Ran interacts with the NPC of metazoa via two asymmetrically localized components, Nup153 at the nuclear face and Nup358 at the cytoplasmic face. Both nucleoporins contain a stretch of distinct, Ran-binding zinc finger domains. Here, we present six crystal structures of Nup153-zinc fingers in complex with Ran and a 1.48 Å crystal structure of RanGDP. Crystal engineering allowed us to obtain well diffracting crystals so that all ZnF–Ran complex structures are refined to high resolution. Each of the four zinc finger modules of Nup153 binds one Ran molecule in apparently non-allosteric fashion. The affinity is measurably higher for RanGDP than for RanGTP and varies modestly between the individual zinc fingers. By microcalorimetric and mutational analysis, we determined that one specific hydrogen bond accounts for most of the differences in the binding affinity of individual zinc fingers. Genomic analysis reveals that only in animals do NPCs contain Ran-binding zinc fingers. We speculate that these organisms evolved a mechanism to maintain a high local concentration of Ran at the vicinity of the NPC, using this zinc finger domain as a sink