Publications by authors named "M R Gyetko"

Background: The role of airway microbiota in COPD is highly debated. Symptomology assessment is vital for the management of clinically stable COPD patients; however, the link between symp toms and the airway microbiome is currently unknown.

Purpose: The present study aimed to evaluate the relationship among stable COPD patients.

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The St. George's Respiratory Questionnaire (SGRQ) is a standardized questionnaire for measuring impaired health and perceived well-being in chronic airway disease, but it is not available in the Nepali language. We translated the original SGRQ into Nepali and validated its use in 150 individuals aged 40 to 80 years with and without COPD.

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Background: In academia, women remain underrepresented. The authors' sought to examine differences in faculty position and professional satisfaction among academic physicians by gender.

Methods: From 2008 to 2012, academic faculty members at a single institution were surveyed (2008, n = 737; 2010, n = 1151; and 2012, n = 971) regarding current position, choice of position, professional satisfaction, and desire for leaving.

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Objective: To optimize the method of isolating a small amount of metagenomic DNA efficiently from bronchoalveolar lavage fluids (BALF) of patients with stable chronic obstructive pulmonary diseases (COPD) , which will facilitate subsequent PCR and DNA sequencing.

Methods: BALF (5mL) of stable COPD patients was spun down to collect the cells. To extract genomic DNA from Gram-positive bacteria more efficiently, QIAGEN's DNA extraction protocol was optimized as follows: Added Buffer ATL to the pellets and used bead tubes and tissue homogenizers to break cell walls; then added proteinase K and incubated; after adding Buffer AL and ethanol, pipetted the mixture into a DNeasy spin column then centrifuged; washed the column with Buffer AW1 and Buffer AW2, finally added 50 microL Buffer AE to elute DNA.

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This study investigated the use of direct gradient analysis of bacterial 16S pyrosequencing surveys to identify relevant bacterial community signals in the midst of a "noisy" background, and to facilitate hypothesis-testing both within and beyond the realm of ecological surveys. The results, utilizing 3 different real world data sets, demonstrate the utility of adding direct gradient analysis to any analysis that draws conclusions from indirect methods such as Principal Component Analysis (PCA) and Principal Coordinates Analysis (PCoA). Direct gradient analysis produces testable models, and can identify significant patterns in the midst of noisy data.

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