To investigate risk factors for sporadic salmonellosis, for each notified case four randomly selected population controls matched for age, sex and geographical region were interviewed via self-administered questionnaire. Conditional logistic regression analysis of 285 matched pairs revealed significant associations for raw ground pork consumption [odds ratio (OR) 6·0, 95% confidence interval (CI) 1·8-20·1], taking antacids (OR 5·8, 95% CI 1·4-24·5), eating meat outside the home (OR 5·7, 95% CI 2·2-14·6) and daily changing or cleaning of dishcloth (OR 2·1, 95% CI 1·2-3·9). Animal contact and ice cream consumption were negatively associated with salmonellosis (OR 0·5, 95% CI 0·2-1 and OR 0·3, 95% CI 0·1-0·6, respectively). S. Typhimurium infections were significantly associated with raw ground pork consumption (OR 16·7, 95% CI 1·4-194·4) and S. Enteritidis infections with having travelled abroad (OR 9·7, 95% CI 2·0-47·3). Raw egg consumption was not a risk factor, substantiating the success of recently implemented national control programmes in the poultry industry. Unexpectedly, hygienic behaviour was more frequently reported by cases, probably because they overestimated their hygiene precautions retrospectively. Although animal contact might enhance human immunocompetence, underreporting of salmonellosis by pet owners could have occurred. Eating raw pork products is the major risk factor for sporadic human S. Typhimurium infections in Lower Saxony.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9151068 | PMC |
http://dx.doi.org/10.1017/S0950268814003768 | DOI Listing |
Plants (Basel)
January 2025
Departamento de Química, Universidade Federal de Viçosa, Campus Universitário, Avenida Peter Henry Rolfs, s/n, Viçosa 36570-900, MG, Brazil.
Soxhlet extraction is a method recommended by the Association of Official Analytical Chemists (AOAC) to determine the lipid content in plant samples. Generally, n-hexane (toxicity grade 5) is used as the solvent (≈300 mL; ≈30 g sample) at boiling temperatures (69 °C) for long times (≤16 h) under a chilled water reflux (≈90 L/h), proportionally aggravated by the number of repetitions and samples determined. In this sense, the technique is neither safe nor sustainable for the analyst or the environment.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Engineering Design, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden.
Topography estimation is essential for autonomous off-road navigation. Common methods rely on point cloud data from, e.g.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Civil Engineering and Engineering Management, National Quemoy University, Kinmen 89250, Taiwan.
Ground-based LiDAR technology has been widely applied in various fields for acquiring 3D point cloud data, including spatial coordinates, digital color information, and laser reflectance intensities (I-values). These datasets preserve the digital information of scanned objects, supporting value-added applications. However, raw point cloud data visually represent spatial features but lack attribute information, posing challenges for automated object classification and effective management.
View Article and Find Full Text PDFMaterials (Basel)
January 2025
Guizhou Provincial Architectural Design & Research Institute Co., Ltd., Guiyang 550025, China.
Electrolytic manganese residue (EMR) is a solid waste generated during the production of electrolytic manganese metal through wet metallurgy, accumulating in large quantities and causing significant environment pollution. Due to its high sulfate content, EMR can be utilized to prepare supersulfate cement when combined with Ground Granulated Blast furnace Slag (GGBS). In this process, GGBS serves as the primary raw material, EMR acts as the sulfate activator, and CaO powder, along with trace amounts of cement, functions as the alkali activator.
View Article and Find Full Text PDFSci Rep
January 2025
Institute of Agricultural Information Technology, Henan Academy of Agricultural Sciences, Zhengzhou, 450002, China.
Identification and diagnosis of tobacco diseases are prerequisites for the scientific prevention and control of these ailments. To address the limitations of traditional methods, such as weak generalization and sensitivity to noise in segmenting tobacco leaf lesions, this study focused on four tobacco diseases: angular leaf spot, brown spot, wildfire disease, and frog eye disease. Building upon the Unet architecture, we developed the Multi-scale Residual Dilated Segmentation Model (MD-Unet) by enhancing the feature extraction module and integrating attention mechanisms.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!