bay area
Recently Published Documents


TOTAL DOCUMENTS

3026
(FIVE YEARS 869)

H-INDEX

61
(FIVE YEARS 9)

2022 ◽  
Vol 12 ◽  
Author(s):  
Victor Reyes-Umana ◽  
Jessica Kretschmer ◽  
John D. Coates

Recent reports of dissimilatory iodate-reducing microorganisms (DIRM) have arisen from studies of bacteria in marine environments. These studies described the physiology and distribution of DIRM while also demonstrating their presence in iodine-rich marine environments. We posited that despite lower iodine concentrations, terrestrial and freshwater ecosystems should also harbor DIRM. We established numerous enrichments from coastal and freshwater environments that actively remove amended iodate. We describe the physiology and genome of a new DIRM isolate, Aromatoleum toluclasticum sp. TC-10, emerging from a freshwater creek microcosm. Like other DIRM, A. toluclasticum sp. TC-10 couples acetate oxidation to iodate reduction with a concomitant increase in the OD600. Our results indicate that A. toluclasticum sp. TC-10 performs dissimilatory iodate reduction (DIR) using the recently described iodate reductase (Idr). We provide further evidence of horizontal gene transfer of the idr genes by demonstrating the lack of Idr in the closely related (99.93% 16S rDNA sequence identity) A. toluclasticum sp. MF63 and describe the heterogeneity of the accessory proteins associated with the iodate reduction island (IRI). These observations provide additional evidence that DIR is a horizontally acquired metabolism with broad environmental distribution beyond exclusively marine environments.


Author(s):  
Venice Servellita ◽  
Mary Kate Morris ◽  
Alicia Sotomayor-Gonzalez ◽  
Amelia S. Gliwa ◽  
Erika Torres ◽  
...  

Author(s):  
Zachary Birenbaum ◽  
Hieu Do ◽  
Lauren Horstmeyer ◽  
Hailey Orff ◽  
Krista Ingram ◽  
...  

Methods for long-term monitoring of coastal species such as harbor seals, are often costly, time-consuming, and highly invasive, underscoring the need for improved techniques for data collection and analysis. Here, we propose the use of automated facial recognition technology for identification of individual seals and demonstrate its utility in ecological and population studies. We created a software package, SealNet, that automates photo identification of seals, using a graphical user interface (GUI) software to identify, align and chip seal faces from photographs and a deep convolutional neural network (CNN) suitable for small datasets (e.g., 100 seals with five photos per seal). We piloted the SealNet technology with a population of harbor seals located within Casco Bay on the coast of Maine, USA. Across two-years of sampling, 2019 and 2020, at seven haul-out sites in Middle Bay, we processed 1529 images representing 408 individual seals and achieved 88% (93%) rank-1 accuracy in closed set (open set) seal identification. We identified four seals that were photographed in both years at neighboring haul-out sites, suggesting that some harbor seals exhibit site fidelity within local bays across years, and that there may be evidence of spatial connectivity among haul-out sites. Using capture-mark-recapture (CMR) calculations, we obtained a rough preliminary population estimate of 4386 seals in the Middle Bay area. SealNet software outperformed a similar face recognition method developed for primates, PrimNet, in identifying seals following training on our seal dataset. The ease and wealth of image data that can be processed using SealNet software contributes a vital tool for ecological and behavioral studies of marine mammals in the emerging field of conservation technology.


2022 ◽  
Author(s):  
Wendy K. Tam Cho ◽  
David G. Hwang

BACKGROUND: Higher COVID-19 incidence and morbidity have been amply documented for US Black and Hispanic populations but not as clearly for other racial and ethnic groups. Efforts to elucidate the mechanisms underlying racial health disparities can be confounded by the relationship between race/ethnicity and socioeconomic status. OBJECTIVE: Examine race/ethnicity and social vulnerability effects on COVID-19 outcomes in the San Francisco Bay Area, an ethnically and socioeconomically diverse region. DESIGN: Retrospective cohort study. SETTING: Geocoded patient records from the University of California, San Francisco Health system between January 1, 2020 to December 31, 2020. PATIENTS: Patients who underwent polymerase chain reaction testing for COVID-19. EXPOSURES: Race/ethnicity and Social Vulnerability Index (SVI). MAIN MEASURES: COVID-19 test frequency, positivity, hospitalization rates, and mortality. KEY RESULTS: Higher social vulnerability, but not race/ethnicity, was associated with less frequent testing yet a higher likelihood of testing positive. Asian hospitalization rates (11.5\%) were double that of White patients (5.4\%) and exceeded the rates for Black (9.3\%) and Hispanic (6.9\%) groups. A modest relationship between higher hospitalization rates and increasing social vulnerability was evident only for White individuals. The Hispanic group had the lowest mean age at death and thus highest years of expected life lost due to COVID-19. CONCLUSIONS: COVID-19 outcomes were not consistently explained by greater socioeconomic vulnerability. Asian individuals showed disproportionately high rates of hospitalization regardless of socioeconomic status. Study of the San Francisco Bay Area population not only provides valuable insights into the differential contributions of race/ethnicity and social determinants of health to COVID-19 outcomes but also emphasizes that all racial groups have experienced the toll of the pandemic, albeit in different ways and to varying degrees.


Sign in / Sign up

Export Citation Format

Share Document