Entity

Time filter

Source Type

Santa Ana, CA, United States

Respicio-Kingry L.B.,Centers for Disease Control and Prevention | Byrd L.,Dermatology Clinic | Allison A.,Dermatology Clinic | Brett M.,Centers for Disease Control and Prevention | And 5 more authors.
Journal of Clinical Microbiology | Year: 2013

A 69-year-old patient presented with a tender, thickly crusted skin lesion of 1 week's duration. A bacterial culture swab taken from the underlying granular tissue yielded a pure isolate of a Gram-negative coccobacillus, presumptively identified as a novel Francisella species via 16S rRNA and multilocus gene sequence analysis. Copyright © 2013, American Society for Microbiology. Source


Hellberg R.S.,Chapman University | Li F.,Ibis Biosciences | Sampath R.,Ibis Biosciences | Yasuda I.J.,Ibis Biosciences | And 6 more authors.
Food Microbiology | Year: 2014

The goal of this study was to develop an assay for the detection and differentiation of noroviruses using RT-PCR followed by electrospray ionization mass spectrometry (ESI-MS). Detection of hepatitis A virus was also considered. Thirteen primer pairs were designed for use in this assay and a reference database was created using GenBank sequences and reference norovirus samples. The assay was tested for inclusivity and exclusivity using 160 clinical norovirus samples, 3 samples of hepatitis A virus and 3 other closely related viral strains. Results showed that the assay was able to detect norovirus with a sensitivity of 92% and a specificity of 100%. Norovirus identification at the genogroup level was correct for 98% of samples detected by the assay and for 75% of a subset of samples (n=32) compared at the genotype level. Identification of norovirus genotypes is expected to improve as more reference samples are added to the database. The assay was also capable of detecting and genotyping hepatitis A virus in all 3 samples tested. Overall, the assay developed here allows for detection and differentiation of noroviruses within one working day and may be used as a tool in surveillance efforts or outbreak investigations. © 2014 Elsevier Ltd. Source


Rippy M.A.,University of California at San Diego | Franks P.J.S.,University of California at San Diego | Feddersen F.,University of California at San Diego | Guza R.T.,University of California at San Diego | Moore D.F.,Orange County Public Health Laboratory
Marine Pollution Bulletin | Year: 2013

A suite of physical-biological models was used to explore the importance of mortality and fluid dynamics in controlling concentrations of fecal indicator bacteria (FIB) at Huntington Beach, CA. An advection-diffusion (AD) model provided a baseline to assess improvements in model skill with the inclusion of mortality. Six forms of mortality were modeled. All mortality models performed better than the AD model, especially at offshore sampling stations, where model skill increased from <0.18 to >0.50 (Escherichia coli) or <-0.14 to >0.30 (Enterococcus). Models including cross-shore variable mortality rates reproduced FIB decay accurately (p< 0.05) at more stations than models without. This finding is consistent with analyses that revealed cross-shore variability in Enterococcus species composition and solar dose response. No best model was identified for Enterococcus, as all models including cross-shore variable mortality performed similarly. The best model for E. coli included solar-dependent and cross-shore variable mortality. © 2012 Elsevier Ltd. Source


Rippy M.A.,University of California at San Diego | Franks P.J.S.,University of California at San Diego | Feddersen F.,University of California at San Diego | Guza R.T.,University of California at San Diego | Moore D.F.,Orange County Public Health Laboratory
Marine Pollution Bulletin | Year: 2013

We present results from a 5-h field program (HB06) that took place at California's Huntington State Beach. We assessed the importance of physical dynamics in controlling fecal indicator bacteria (FIB) concentrations during HB06 using an individual based model including alongshore advection and cross-shore variable horizontal diffusion. The model was parameterized with physical (waves and currents) and bacterial (Escherichia coli and Enterococcus) observations made during HB06. The model captured surfzone FIB dynamics well (average surfzone model skill: 0.84 {. E. coli} and 0.52 {. Enterococcus}), but fell short of capturing offshore FIB dynamics. Our analyses support the hypothesis that surfzone FIB variability during HB06 was a consequence of southward advection and diffusion of a patch of FIB originating north of the study area. Offshore FIB may have originated from a different, southern, source. Mortality may account for some of the offshore variability not explained by the physical model. © 2012 Elsevier Ltd. Source

Discover hidden collaborations