Development and Evaluation of an Open Source Software Tool for Deidentification of Pathology Reports

Background: Electronic medical records, including pathology reports, are often used for research purposes. Currently, there are few programs freely available to remove identifiers while leaving the remainder of the pathology report text intact. Our goal was to produce an open source, Health Insurance Portability and Accountability Act (HIPAA) compliant, deidentification tool tailored for pathology reports. We designed a three-step process for removing potential identifiers. The first step is to look for identifiers known to be associated with the patient, such as name, medical record number, pathology accession number, etc. Next, a series of pattern matches look for predictable patterns likely to represent identifying data; such as dates, accession numbers and addresses as well as patient, institution and physician names. Finally, individual words are compared with a database of proper names and geographic locations. Pathology reports from three institutions were used to design and test the algorithms. The software was improved iteratively on training sets until it exhibited good performance. 1800 new pathology reports were then processed. Each report was reviewed manually before and after deidentification to catalog all identifiers and note those that were not removed. Results: 1254 (69.7 %) of 1800 pathology reports contained identifiers in the body of the report. 3439 (98.3%) of 3499 unique identifiers in the test set were removed. Only 19 HIPAA-specified identifiers (mainly consult accession numbers and misspelled names) were missed. Of 41 non-HIPAA identifiers missed, the majority were partial institutional addresses and ages. Outside consultation case reports typically contain numerous identifiers and were the most challenging to deidentify comprehensively. There was variation in performance among reports from the three institutions, highlighting the need for site-specific customization, which is easily accomplished with our tool. Conclusion: We have demonstrated that it is possible to create an open-source deidentification program which performs well on free-text pathology reports

Experimental Design for the Gemini Planet Imager

The Gemini Planet Imager (GPI) is a high performance adaptive optics system being designed and built for the Gemini Observatory. GPI is optimized for high contrast imaging, combining precise and accurate wavefront control, diffraction suppression, and a speckle-suppressing science camera with integral field and polarimetry capabilities. The primary science goal for GPI is the direct detection and characterization of young, Jovian-mass exoplanets. For plausible assumptions about the distribution of gas giant properties at large semi-major axes, GPI will be capable of detecting more than 10% of gas giants more massive than 0.5 M_J around stars younger than 100 Myr and nearer than 75 parsecs. For systems younger than 1 Gyr, gas giants more massive than 8 M_J and with semi-major axes greater than 15 AU are detected with completeness greater than 50%. A survey targeting young stars in the solar neighborhood will help determine the formation mechanism of gas giant planets by studying them at ages where planet brightness depends upon formation mechanism. Such a survey will also be sensitive to planets at semi-major axes comparable to the gas giants in our own solar system. In the simple, and idealized, situation in which planets formed by either the "hot-start" model of Burrows et al. (2003) or the core accretion model of Marley et al. (2007), a few tens of detected planets are sufficient to distinguish how planets form.Comment: 15 pages, 9 figures, revised after referee's comments and resubmitted to PAS

Optical/IR from ground

Optical/infrared (O/IR) astronomy in the 1990's is reviewed. The following subject areas are included: research environment; science opportunities; technical development of the 1980's and opportunities for the 1990's; and ground-based O/IR astronomy outside the U.S. Recommendations are presented for: (1) large scale programs (Priority 1: a coordinated program for large O/IR telescopes); (2) medium scale programs (Priority 1: a coordinated program for high angular resolution; Priority 2: a new generation of 4-m class telescopes); (3) small scale programs (Priority 1: near-IR and optical all-sky surveys; Priority 2: a National Astrometric Facility); and (4) infrastructure issues (develop, purchase, and distribute optical CCDs and infrared arrays; a program to support large optics technology; a new generation of large filled aperture telescopes; a program to archive and disseminate astronomical databases; and a program for training new instrumentalists

Development and evaluation of an open source software tool for deidentification of pathology reports

BACKGROUND: Electronic medical records, including pathology reports, are often used for research purposes. Currently, there are few programs freely available to remove identifiers while leaving the remainder of the pathology report text intact. Our goal was to produce an open source, Health Insurance Portability and Accountability Act (HIPAA) compliant, deidentification tool tailored for pathology reports. We designed a three-step process for removing potential identifiers. The first step is to look for identifiers known to be associated with the patient, such as name, medical record number, pathology accession number, etc. Next, a series of pattern matches look for predictable patterns likely to represent identifying data; such as dates, accession numbers and addresses as well as patient, institution and physician names. Finally, individual words are compared with a database of proper names and geographic locations. Pathology reports from three institutions were used to design and test the algorithms. The software was improved iteratively on training sets until it exhibited good performance. 1800 new pathology reports were then processed. Each report was reviewed manually before and after deidentification to catalog all identifiers and note those that were not removed. RESULTS: 1254 (69.7 %) of 1800 pathology reports contained identifiers in the body of the report. 3439 (98.3%) of 3499 unique identifiers in the test set were removed. Only 19 HIPAA-specified identifiers (mainly consult accession numbers and misspelled names) were missed. Of 41 non-HIPAA identifiers missed, the majority were partial institutional addresses and ages. Outside consultation case reports typically contain numerous identifiers and were the most challenging to deidentify comprehensively. There was variation in performance among reports from the three institutions, highlighting the need for site-specific customization, which is easily accomplished with our tool. CONCLUSION: We have demonstrated that it is possible to create an open-source deidentification program which performs well on free-text pathology reports

The Hubble Space Telescope Wide Field Camera 3 Early Release Science data: Panchromatic Faint Object Counts for 0.2-2 microns wavelength

We describe the Hubble Space Telescope (HST) Wide Field Camera 3 (WFC3) Early Release Science (ERS) observations in the Great Observatories Origins Deep Survey (GOODS) South field. The new WFC3 ERS data provide calibrated, drizzled mosaics in the UV filters F225W, F275W, and F336W, as well as in the near-IR filters F098M (Ys), F125W (J), and F160W (H) with 1-2 HST orbits per filter. Together with the existing HST Advanced Camera for Surveys (ACS) GOODS-South mosaics in the BViz filters, these panchromatic 10-band ERS data cover 40-50 square arcmin at 0.2-1.7 {\mu}m in wavelength at 0.07-0.15" FWHM resolution and 0.090" Multidrizzled pixels to depths of AB\simeq 26.0-27.0 mag (5-{\sigma}) for point sources, and AB\simeq 25.5-26.5 mag for compact galaxies. In this paper, we describe: a) the scientific rationale, and the data taking plus reduction procedures of the panchromatic 10-band ERS mosaics; b) the procedure of generating object catalogs across the 10 different ERS filters, and the specific star-galaxy separation techniques used; and c) the reliability and completeness of the object catalogs from the WFC3 ERS mosaics. The excellent 0.07-0.15" FWHM resolution of HST/WFC3 and ACS makes star- galaxy separation straightforward over a factor of 10 in wavelength to AB\simeq 25-26 mag from the UV to the near-IR, respectively.Comment: 51 pages, 71 figures Accepted to ApJS 2011.01.2

Resistance of Bovine Spongiform Encephalopathy (BSE) Prions to Inactivation

Distinct prion strains often exhibit different incubation periods and patterns of neuropathological lesions. Strain characteristics are generally retained upon intraspecies transmission, but may change on transmission to another species. We investigated the inactivation of two related prions strains: BSE prions from cattle and mouse-passaged BSE prions, termed 301V. Inactivation was manipulated by exposure to sodium dodecyl sulfate (SDS), variations in pH, and different temperatures. Infectivity was measured using transgenic mouse lines that are highly susceptible to either BSE or 301V prions. Bioassays demonstrated that BSE prions are up to 1,000-fold more resistant to inactivation than 301V prions while Western immunoblotting showed that short acidic SDS treatments reduced protease-resistant PrPSc from BSE prions and 301V prions at similar rates. Our findings argue that despite being derived from BSE prions, mouse 301V prions are not necessarily a reliable model for cattle BSE prions. Extending these comparisons to human sporadic Creutzfeldt-Jakob disease and hamster Sc237 prions, we found that BSE prions were 10- and 106-fold more resistant to inactivation, respectively. Our studies contend that any prion inactivation procedures must be validated by bioassay against the prion strain for which they are intended to be used

Identification of Candidate Genes for Dyslexia Susceptibility on Chromosome 18

Background: Six independent studies have identified linkage to chromosome 18 for developmental dyslexia or general reading ability. Until now, no candidate genes have been identified to explain this linkage. Here, we set out to identify the gene(s) conferring susceptibility by a two stage strategy of linkage and association analysis. Methodology/Principal Findings: Linkage analysis: 264 UK families and 155 US families each containing at least one child diagnosed with dyslexia were genotyped with a dense set of microsatellite markers on chromosome 18. Association analysis: Using a discovery sample of 187 UK families, nearly 3000 SNPs were genotyped across the chromosome 18 dyslexia susceptibility candidate region. Following association analysis, the top ranking SNPs were then genotyped in the remaining samples. The linkage analysis revealed a broad signal that spans approximately 40 Mb from 18p11.2 to 18q12.2. Following the association analysis and subsequent replication attempts, we observed consistent association with the same SNPs in three genes; melanocortin 5 receptor (MC5R), dymeclin (DYM) and neural precursor cell expressed, developmentally down-regulated 4-like (NEDD4L). Conclusions: Along with already published biological evidence, MC5R, DYM and NEDD4L make attractive candidates for dyslexia susceptibility genes. However, further replication and functional studies are still required.Publisher PDFPeer reviewe

Family Firms and Firm Performance: Evidence from Japan

Corrigendum: Nature Structural and Molecular Biology 16 (12), 1331 (2009) doi:10.1038/nsmb1209-1331bInternational audienceThioredoxins (Trxs) are oxidoreductase enzymes, present in all organisms, that catalyze the reduction of disulfide bonds in proteins. By applying a calibrated force to a substrate disulfide, the chemical mechanisms of Trx catalysis can be examined in detail at the single-molecule level. Here we use single-molecule force-clamp spectroscopy to explore the chemical evolution of Trx catalysis by probing the chemistry of eight different Trx enzymes. All Trxs show a characteristic Michaelis-Menten mechanism that is detected when the disulfide bond is stretched at low forces, but at high forces, two different chemical behaviors distinguish bacterial-origin from eukaryotic-origin Trxs. Eukaryotic-origin Trxs reduce disulfide bonds through a single-electron transfer reaction (SET), whereas bacterial-origin Trxs show both nucleophilic substitution (SN2) and SET reactions. A computational analysis of Trx structures identifies the evolution of the binding groove as an important factor controlling the chemistry of Trx catalysis