Co-Carriage of Metal and Antibiotic Resistance Genes in Sewage Associated Staphylococci.

Controlling spread of resistance genes from wastewater to aquatic systems requires more knowledge on how resistance genes are acquired and transmitted. Whole genomic sequences from sewage-associated staphylococcus isolates (20 , 2 , and 2 ) were analyzed for the presence of antibiotic resistance genes (ARGs) and metal resistance genes (MRGs). Plasmid sequences were identified in each isolate to investigate co-carriage of ARGs and MRGs within.

Solar disinfection of turbid hygiene waters in Lexington, KY, USA.

Solar disinfection (SODIS) could be a key to providing a clean, hygiene water for birthing uses, but the recommended climate zone is limited, the microbial indicators are related to gastrointestinal illness and not wound infections. SODIS feasibility was investigated to remove Escherichia coli from turbid water at temperatures less than 50 °C in Lexington, KY. Increasing turbidity from 0 to 200 NTU decreased E.

Thiol-Affinity Immobilization of Casein-Coated Silver Nanoparticles on Polymeric Membranes for Biofouling Control.

Silver nanoparticles (AgNPs) have been widely studied for the control of biofouling on polymeric membranes due to their antimicrobial properties. However, nanoparticle leaching has posed a significant impediment against their widespread use. In this study, a one-step method of chemically embedding AgNPs on cellulose acetate (CA) membranes via their affinity to thiol group chemistry was investigated.

Prevalence and characterization of Staphylococcus aureus in wastewater treatment plants by whole genomic sequencing.

Infections with Staphylococcus aureus are being spread through contact with the community environment, but the role of wastewater treatment plants in the transmission routes is not defined. This study investigated the prevalence, types, genetic elements, and potential for transmission of S. aureus by these engineered systems.

Use of acetaminophen and sucralose as co-analytes to differentiate sources of human excreta in surface waters.

Reducing pathogenic risks in surface waters impacted by leaking or overflowing sewage requires the ability to detect human excreta in raw sewage, discriminate human excreta from other types of animal excreta, and differentiate between treated wastewater and raw sewage. We used the relative concentrations of a degradable, human-specific pharmaceutical and a persistent artificial sweetener to indicate the presence of human excreta, its degree of environmental degradation, and the amount of dilution by freshwater sources. Samples were collected and analyzed for acetaminophen and sucralose between 2016 and 2018 from wastewater treatment plants (WWTPs) and streams in metropolitan Lexington, Kentucky (USA).

Use of Nitrogen-15-Enriched Escherichia coli as a Bacterial Tracer in Karst Aquifers.

Karst aquifers are susceptible to contamination by microorganisms, but relatively few studies have used bacteria as tracers. We demonstrate the utility of Escherichia coli enriched in the stable isotope nitrogen-15 ( N) as a novel bacterial tracer. Nonpathogenic E.

Prevalence of and Relationship between Two Human-Associated DNA Biomarkers for Bacteroidales in an Urban Watershed.

Human-associated fecal biomarkers offer potent tools for the detection and control of human fecal pollution in watersheds. In some cases, the probability of false-negative findings may call for using a less specific biomarker that is present in higher quantities as long as it can be related to the more specific indicator. The objective of this study is to investigate the relationship between two previously published human-associated biomarkers for Bacteroidales bacteria in an urban watershed influenced by human fecal pollution and to determine if the less specific marker may be used to identify the locations of broken or leaking sewer lines.

Peracetic acid as an alternative disinfection technology for wet weather flows.

Rain-induced wet weather flows (WWFs) consist of combined sewer overflows, sanitary sewer overflows, and stormwater, all of which introduce pathogens to surface waters when discharged. When people come into contact with the contaminated surface water, these pathogens can be transmitted resulting in severe health problems. As such, WWFs should be disinfected.

Occupational exposure to trichloroethylene and cancer risk for workers at the Paducah Gaseous Diffusion Plant.

Objective: The Paducah Gaseous Diffusion Plant (PGDP) became operational in 1952; it is located in the western part of Kentucky. We conducted a mortality study for adverse health effects that workers may have suffered while working at the plant, including exposures to chemicals.

Materials And Methods: We studied a cohort of 6820 workers at the PGDP for the period 1953 to 2003; there were a total of 1672 deaths to cohort members.

Time-period mortality patterns in a Gaseous Diffusion Plant workforce.

Background: We sub-divided a cohort of 6820 workers at the Paducah (KY) Gaseous Diffusion Plant (PGDP) which was traced from 1953 to 2003. The subdivisions were made to assess the mortality risks in a sub-group of workers employed solely during the plant's refit period, a time of suspected higher exposure to metal dusts (nickel, arsenic, chromium and uranium) and trichloroethylene.

Methods: This article describes a comparison of exposures and causes of death for 754 workers employed exclusively during the period of 1975-1979, with 1554 workers who worked in this period as well as other years.

Mortality patterns among Paducah Gaseous Diffusion Plant workers.

Objective: To determine whether Paducah Gaseous Diffusion Plant workers had mortality patterns that differed from the general US population and to investigate whether mortality patterns were associated with job title or workplace exposures.

Methods: A retrospective occupational cohort mortality study was conducted on 6759 workers. Standardized mortality ratio analyses compared the cohort with the referent US population.

Backfilling missing microbial concentrations in a riverine database using artificial neural networks.

Predicting peak pathogen loadings can provide a basis for watershed and water treatment plant management decisions that can minimize microbial risk to the public from contact or ingestion. Artificial neural network models (ANN) have been successfully applied to the complex problem of predicting peak pathogen loadings in surface waters. However, these data-driven models require substantial, multiparameter databases upon which to train, and missing input values for pathogen indicators must often be estimated.

Artificial neural network prediction of viruses in shellfish.

A database was probed with artificial neural network (ANN) and multivariate logistic regression (MLR) models to investigate the efficacy of predicting PCR-identified human adenovirus (ADV), Norwalk-like virus (NLV), and enterovirus (EV) presence or absence in shellfish harvested from diverse countries in Europe (Spain, Sweden, Greece, and the United Kingdom). The relative importance of numerical and heuristic input variables to the ANN model for each country and for the combined data was analyzed with a newly defined relative strength effect, which illuminated the importance of bacteriophages as potential viral indicators. The results of this analysis showed that ANN models predicted all types of viral presence and absence in shellfish with better precision than MLR models for a multicountry database.

Comparison of bacteriophages for use in iodine inactivation: batch and continuous flow studies.

Inactivation rates in batch studies for four commonly used surrogate bacteriophages were measured in stable aqueous iodine solutions for the purpose of determining which was the most suited to evaluate iodine disinfection efficacy in batch and continuous flow conditions. Two types of group Leviviridae bacteriophages were used, Type I (MS2) and Type II (GA), along with group Microviridae, Phi-X174, and group Tectiviridae, PRD1. Inactivation was compared at iodine doses of 1.

A neural-network-based classification scheme for sorting sources and ages of fecal contamination in water.

Artificial neural networks (ANNs) were successfully applied to data observations from a small watershed consisting of commonly measured indicator bacteria, weather conditions, and turbidity to distinguish between human sewage and animal-impacted runoff, fresh runoff from aged, and agricultural land-use-associated fresh runoff from that of suburban land-use-associated-fresh runoff. The ANNs were applied in a cascading, or hierarchical scheme. ANN performance was measured in two ways: (1) training and (2) testing.