16 research outputs found

    Characterizing and Improving the Data Reduction Pipeline for the Keck OSIRIS Integral Field Spectrograph

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    OSIRIS is a near-infrared (1.0--2.4 μ\mum) integral field spectrograph operating behind the adaptive optics system at Keck Observatory, and is one of the first lenslet-based integral field spectrographs. Since its commissioning in 2005, it has been a productive instrument, producing nearly half the laser guide star adaptive optics (LGS AO) papers on Keck. The complexity of its raw data format necessitated a custom data reduction pipeline (DRP) delivered with the instrument in order to iteratively assign flux in overlapping spectra to the proper spatial and spectral locations in a data cube. Other than bug fixes and updates required for hardware upgrades, the bulk of the DRP has not been updated since initial instrument commissioning. We report on the first major comprehensive characterization of the DRP using on-sky and calibration data. We also detail improvements to the DRP including characterization of the flux assignment algorithm; exploration of spatial rippling in the reduced data cubes; and improvements to several calibration files, including the rectification matrix, the bad pixel mask, and the wavelength solution. We present lessons learned from over a decade of OSIRIS data reduction that are relevant to the next generation of integral field spectrograph hardware and data reduction software design.Comment: 18 pages, 16 figures; accepted for publication in A

    Malaria endemicity and co-infection with tissue-dwelling parasites in Sub-Saharan Africa: a review

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    Acceptability of Electronic Visits for Return of Research Results in the Mayo Clinic Biobank

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    Objective: To understand patient characteristics related to acceptability of returning individual research results via various modalities, focusing on electronic visits (e-visits). Patients and Methods: Twelve hundred participants from the Mayo Clinic Biobank were selected using a stratified random sampling approach based on sex, age, and education level. Mailed surveys ascertained return of results preferences for 2 disease vignettes (cystic fibrosis and hereditary breast cancer) and a pharmacogenomics vignette. The study was conducted from October 1, 2013, through March 31, 2014. Results: In all, 685 patients (57%) responded, and 60% reported liking e-visits, although the option of receiving results in an office visit was liked most frequently. Multivariable logistic models showed that the odds of liking the use of e-visits for returning results for cystic fibrosis and hereditary breast cancer were higher among those with higher education and better genetic knowledge and among those not living in proximity to the Mayo Clinic (Rochester, Minnesota). Level of genetic knowledge was not considerably associated with accepting e-visits, whereas education level remained important. For all vignettes, those who are divorced were less likely to accept e-visits. Conclusion: Researchers are faced with a difficult challenge of returning results with a method that is both acceptable to recipients and logistically feasible. This study implies that the use of e-visits may be a viable option for return of results to stratify the chasm between in-person genetic counseling and online portal receipt of results

    Distinct microbes, metabolites, and ecologies define the microbiome in deficient and proficient mismatch repair colorectal cancers

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    Abstract Background Links between colorectal cancer (CRC) and the gut microbiome have been established, but the specific microbial species and their role in carcinogenesis remain an active area of inquiry. Our understanding would be enhanced by better accounting for tumor subtype, microbial community interactions, metabolism, and ecology. Methods We collected paired colon tumor and normal-adjacent tissue and mucosa samples from 83 individuals who underwent partial or total colectomies for CRC. Mismatch repair (MMR) status was determined in each tumor sample and classified as either deficient MMR (dMMR) or proficient MMR (pMMR) tumor subtypes. Samples underwent 16S rRNA gene sequencing and a subset of samples from 50 individuals were submitted for targeted metabolomic analysis to quantify amino acids and short-chain fatty acids. A PERMANOVA was used to identify the biological variables that explained variance within the microbial communities. dMMR and pMMR microbial communities were then analyzed separately using a generalized linear mixed effects model that accounted for MMR status, sample location, intra-subject variability, and read depth. Genome-scale metabolic models were then used to generate microbial interaction networks for dMMR and pMMR microbial communities. We assessed global network properties as well as the metabolic influence of each microbe within the dMMR and pMMR networks. Results We demonstrate distinct roles for microbes in dMMR and pMMR CRC. Bacteroides fragilis and sulfidogenic Fusobacterium nucleatum were significantly enriched in dMMR CRC, but not pMMR CRC. These findings were further supported by metabolic modeling and metabolomics indicating suppression of B. fragilis in pMMR CRC and increased production of amino acid proxies for hydrogen sulfide in dMMR CRC. Conclusions Integrating tumor biology and microbial ecology highlighted distinct microbial, metabolic, and ecological properties unique to dMMR and pMMR CRC. This approach could critically improve our ability to define, predict, prevent, and treat colorectal cancers
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