A study was conducted to relate the properties of Enterobacter, Pseudomonas, Bacillus, Achromobacter, Flavobacterium, and Arthrobacter strains to their transport with water moving through soil. The bacteria differed markedly in their extent of transport; their hydrophobicity, as measured by adherence to n-octane and by hydrophobic-interaction chromatography; and their net surface electrostatic charge, as determined by electrostatic interaction chromatography and by measurements of the zeta potential. Transport of the 19 strains through Kendaia loam or their retention by this soil was not correlated with hydrophobicities or net surface charges of the cells or the presence of capsules. Among 10 strains tested, the presence of flagella was also not correlated with transport. Retention was statistically related to cell size, with bacteria shorter than 1.0 mum usually showing higher percentages of cells being transported through the soil. We suggest that more than one characteristic of bacterial cells determines whether the organisms are transported through soil with moving water.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC182683 | PMC |
http://dx.doi.org/10.1128/aem.57.1.190-193.1991 | DOI Listing |
The significant absorption and scattering of light during its propagation in water severely degrade the quality of underwater imaging, presenting challenges for developing high-precision 3D imaging techniques based on optical methods. Polarization imaging has demonstrated effectiveness in mitigating the effects of scattering, making it a valuable approach for underwater imaging. Additionally, the polarization state of reflected light can be utilized for surface normal estimation and 3D shape reconstruction.
View Article and Find Full Text PDFInt Dent J
January 2025
Department of Stomatology, Beijing Tongren Hospital, Capital Medical University, Beijing, China. Electronic address:
Introduction And Aim: The assessment of gingival inflammation surface features mainly depends on subjective judgment and lacks quantifiable and reproducible indicators. Therefore, it is a need to acquire objective identification information for accurate monitoring and diagnosis of gingival inflammation. This study aims to develop an automated method combining intraoral scanning (IOS) and deep learning algorithms to identify the surface features of gingival inflammation and evaluate its accuracy and correlation with clinical indicators.
View Article and Find Full Text PDFJ Dent Sci
January 2025
First Clinical Division, Peking University School and Hospital of Stomatology & National Center for Stomatology & National Clinical Research Center for Oral Diseases & National Engineering Research Center of Oral Biomaterials and Digital Medical Devices & Beijing Key Laboratory of Digital Stomatology & NHC Key Laboratory of Digital Stomatology & NMPA Key Laboratory for Dental Materials, Beijing, China.
Background/purpose: Artificial intelligence (AI) can assist in medical diagnosis owing to its high accuracy and efficiency. This study aimed to develop a diagnostic system for automatically determining the degree of tooth wear (TW) using intraoral photographs with deep learning.
Materials And Methods: The study included 388 intraoral photographs.
J Oral Microbiol
January 2025
Periodontal Research Group, Department of Dentistry, School of Health Sciences, College of Medicine and Health, University of Birmingham, Edgbaston, UK.
Background: is a commensal bacterium and an early biofilm coloniser found in the human oral cavity. One of the biofilm matrix constituents is bacterial extracellular DNA (eDNA). Neutrophils are innate immune cells that respond to biofilms, employing antimicrobial mechanisms such as neutrophil extracellular trap (NET) and reactive oxygen species (ROS) release.
View Article and Find Full Text PDFJ Environ Manage
January 2025
Department of Fashion Technology, PSG College of Technology, Coimbatore, 641004, India.
Domestic laundry wastewater is a major contributor to microfiber emissions in the aquatic environment. Among several mitigation measures, the use of external filters to capture microfibers from wastewater is one of the most efficient and commercially viable methods. This study attempted to develop an eco-friendly filtration medium to filter microfibers in laundry wastewater using luffa cylindrica fibers.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!