The goal of this study was to quantify the microbial load (enterococci) contributed by the different animals that frequent a beach site. The highest enterococci concentrations were observed in dog feces with average levels of 3.9 x 10(7) CFU/g; the next highest enterococci levels were observed in birds averaging 3.3 x 10(5)CFU/g. The lowest measured levels of enterococci were observed in material collected from shrimp fecal mounds (2.0 CFU/g). A comparison of the microbial loads showed that 1 dog fecal event was equivalent to 6940 bird fecal events or 3.2 x 10(8) shrimp fecal mounds. Comparing animal contributions to previously published numbers for human bather shedding indicates that one adult human swimmer contributes approximately the same microbial load as one bird fecal event. Given the abundance of animals observed on the beach, this study suggests that dogs are the largest contributing animal source of enterococci to the beach site.
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http://dx.doi.org/10.1016/j.marpolbul.2009.07.003 | DOI Listing |
Front Microbiol
January 2025
Enzyme Technology Laboratory, School of Bioresources and Technology, King Mongkut's University of Technology Thonburi (KMUTT), Bangkok, Thailand.
Maximizing saccharification efficiency of lignocellulose and minimizing the production costs associated with enzyme requirements are crucial for sustainable biofuel production. This study presents a novel semi-fed-batch saccharification method that uses a co-culture of and strain A9 to efficiently break down high solid-loading lignocellulosic biomass without the need for any external enzymes. This method optimizes saccharification efficiency and enhances glucose production from alkaline-treated rice straw, a representative lignocellulosic biomass.
View Article and Find Full Text PDFBiomed Pharmacother
January 2025
Department of Operative Dentistry, Endodontics and Dental Materials, Bauru School of Dentistry, University of São Paulo (FOB - USP), Bauru, São Paulo, Brazil. Electronic address:
Researching disinfection strategies is pivotal because effectively eliminating bacteria and their byproducts during root canal treatment (RCT) remains a challenge. This study investigated the antimicrobial efficacy of natural antimicrobial compounds, propolis (PRO) and copaiba oil-resin (COR), compared to conventional agents in Endodontics. Antimicrobials were tested against endodontic pathogens via macrodilution with standardized inoculums to determine the minimum inhibitory concentration (MIC) and the minimum bactericidal concentration (MBC).
View Article and Find Full Text PDFInt J Food Microbiol
January 2025
Department of Food Science, Cornell University, Ithaca, NY 14853, United States.
Jellified materials were observed in spoiled pasteurized apple juice that contained dimethyl dicarbonate (DMDC). Microbiological analysis showed a high microbial load (4-5 log CFU/mL) in the sample. Acetobacter spp.
View Article and Find Full Text PDFArch Oral Biol
January 2025
Department of Dental Materials and Prosthesis, Ribeirão Preto School of Dentistry, University of São Paulo, Ribeirão Preto, São Paulo, Brazil. Electronic address:
Objective: To evaluate the influence of edentulism, smoking, microbiota, and oral rehabilitation on the cytokine profile in healthy and hypertensive edentulous individuals using complete dentures.
Design: This case-control study was divided into four groups: normotensives (control group - NH), controlled hypertensives (case group 1 - CH), unreported hypertensives (case group 2 - UnrH), and uncontrolled hypertensives (case group 3 - UncH). The participants were characterized by sociodemographic data, clinical and behavioral information, and systolic and diastolic blood pressure.
Water Res
January 2025
School of Civil, Environmental, and Architectural Engineering, Korea University, Seoul 02841, Korea. Electronic address:
Anaerobic digestion (AD), which relies on a complex microbial consortium for efficient biogas generation, is a promising avenue for renewable energy production and organic waste treatment. However, understanding and optimising AD processes are challenging because of the intricate interactions within microbial communities and the impact of volatile fatty acids (VFAs) on biogas production. To address these challenges, this study proposes the application of graph convolutional networks (GCNs) to comprehensively model AD processes.
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