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1.
FEMS Microbes ; 3: 1-12, 2022 Jan 29.
Artigo em Inglês | MEDLINE | ID: mdl-37228897

RESUMO

Wastewater surveillance has been widely used as a supplemental method to track the community infection levels of severe acute respiratory syndrome coronavirus 2. A gap exists in standardized reporting for fecal indicator concentrations, which can be used to calibrate the primary outcome concentrations from wastewater monitoring for use in epidemiological models. To address this, measurements of fecal indicator concentration among wastewater samples collected from sewers and treatment centers in four counties of Kentucky (N = 650) were examined. Results from the untransformed wastewater data over 4 months of sampling indicated that the fecal indicator concentration of human ribonuclease P (RNase P) ranged from 5.1 × 101 to 1.15 × 106 copies/ml, pepper mild mottle virus (PMMoV) ranged from 7.23 × 103 to 3.53 × 107 copies/ml, and cross-assembly phage (CrAssphage) ranged from 9.69 × 103 to 1.85 × 108 copies/ml. The results showed both regional and temporal variability. If fecal indicators are used as normalization factors, knowing the daily sewer system flow of the sample location may matter more than rainfall. RNase P, while it may be suitable as an internal amplification and sample adequacy control, has less utility than PMMoV and CrAssphage as a fecal indicator in wastewater samples when working at different sizes of catchment area. The choice of fecal indicator will impact the results of surveillance studies using this indicator to represent fecal load. Our results contribute broadly to an applicable standard normalization factor and assist in interpreting wastewater data in epidemiological modeling and monitoring.

2.
Sci Total Environ ; 816: 151534, 2022 Apr 10.
Artigo em Inglês | MEDLINE | ID: mdl-34780821

RESUMO

Wastewater monitoring of SARS-CoV-2 presents a means of tracking COVID-19 community infection dynamics on a broader geographic scale. However, accounting for environmental and sample-processing losses may be necessary for wastewater measurements to readily inform our understanding of infection prevalence. Here, we present measurements of the SARS-CoV-2 N1 and N2 gene targets from weekly wastewater samples at three sites in Hamilton County, Ohio, during an increase and subsequent decline of COVID-19 infections. The concentration of N1 or N2 RNA in wastewater, measured over the course of six months, ranged from below the detection limit to over 104 gene copies/l, and correlated with case data at two wastewater treatment plants, but not at a sub-sewershed-level sampling site. We also evaluated the utility of a broader range of variables than has been reported consistently in previous work, in improving correlations of SARS-CoV-2 concentrations with case data. These include a spiked matrix recovery control (OC43), flow-normalization, and assessment of fecal loading using endogenous fecal markers (HF183, PMMoV, crAssphage). We found that adjusting for recovery, flow, and fecal indicators increased these correlations for samples from a larger sewershed (serving ~488,000 people) with greater industrial and stormwater inputs, but raw N1/N2 concentrations corresponded better with case data at a smaller, residential-oriented sewershed. Our results indicate that the optimal adjustment factors for correlating wastewater and clinical case data moving forward may not be generalizable to all sewersheds.


Assuntos
COVID-19 , SARS-CoV-2 , Humanos , Prevalência , RNA , Águas Residuárias
3.
J Appl Microbiol ; 131(5): 2178-2192, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-33905584

RESUMO

Greywater, the wastewater from sinks, showers and laundry, is an understudied environment for bacterial communities. Most greywater studies focus on quantifying pathogens, often via proxies used in other wastewater, like faecal indicator bacteria; there is a need to identify more greywater-appropriate surrogates, like Staphylococcus sp. Sequencing-based studies have revealed distinct communities in different types of greywater as well as in different parts of greywater infrastructure, including biofilms on pipes, holding tanks and filtration systems. The use of metagenomic sequencing provides high resolution on both the taxa and genes present, which may be of interest in cases like identifying pathogens and surrogates relevant to different matrices, monitoring antibiotic resistance genes and understanding metabolic processes occurring in the system. Here, we review what is known about bacterial communities in different types of greywater and its infrastructure. We suggest that wider adoption of environmental sequencing in greywater research is important because it can describe the entire bacterial community along with its metabolic capabilities, including pathways for removal of nutrients and organic materials. We briefly describe a metagenomic dataset comparing different types of greywater samples in a college dormitory building to highlight the type of questions these methods can address. Metagenomic sequencing can help further the understanding of greywater treatment for reuse because it allows for identification of new pathogens or genes of concern.


Assuntos
Eliminação de Resíduos Líquidos , Águas Residuárias , Bactérias/genética , Filtração , Humanos , Staphylococcus
5.
Appl Opt ; 36(18): 4099-101, 1997 Jun 20.
Artigo em Inglês | MEDLINE | ID: mdl-18253433

RESUMO

We propose and demonstrate a technique for obtaining a symmetric power tuning curve for a single-mode continuous-wave CO(2) laser regardless of the operating power level.

6.
Appl Opt ; 36(36): 9515-7, 1997 Dec 20.
Artigo em Inglês | MEDLINE | ID: mdl-18264513

RESUMO

We report a new method for the measurement of the absorption coefficient of CO(2) laser windows. The method exploits the hysteresis in the power-tuning curve of a single-mode continuous-wave CO(2) laser and allows measurements of absorption coefficients of the order of approximately 10(-3) cm(-1) in CO(2) laser windows a few millimeters thick.

7.
J Indian Med Assoc ; 69(10): 236-7, 1977 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-615919
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