Background: Helicobacter pylori is present in surface water and wastewater, and biofilms in drinking water systems have been reported as possible reservoirs of H. pylori. However, its ability to survive in an infectious state in the environment is hindered because it rapidly loses its cultivability. The aim of this study was to determine the presence of cultivable and therefore viable H. pylori in wastewater treatment plants to understand the role of wastewater in the pathogen's transmission.
Materials And Methods: A modified filter technique was used to obtain a positive H. pylori culture, and specific detection of this pathogen was achieved with FISH and PCR techniques.
Results: A total of six positive H. pylori cultures were obtained from the water samples, and molecular techniques positively identified H. pylori in 21 culture-negative samples.
Conclusions: The combination of a culturing procedure after sample filtration followed by the application of a molecular method, such as PCR or FISH, provides a specific tool for the detection, identification, and direct visualization of cultivable and therefore viable H. pylori cells from complex mixed communities such as water samples.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/j.1523-5378.2012.00961.x | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Machine Learning for the Early Prediction of Delayed Cerebral Ischemia in Patients With Subarachnoid Hemorrhage: Systematic Review and Meta-Analysis.
J Med Internet Res
January 2025
Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Background: Delayed cerebral ischemia (DCI) is a primary contributor to death after subarachnoid hemorrhage (SAH), with significant incidence. Therefore, early determination of the risk of DCI is an urgent need. Machine learning (ML) has received much attention in clinical practice.
View Article and Find Full Text PDFApplication of the 6-SNP elevated LDL-cholesterol polygenic risk score in individuals with familial hypercholesterolemia phenotype from an Argentine population.
Gac Med Mex
January 2025
Universidad de Buenos Aires, Facultad de Farmacia y Bioquímica, Departamento de Bioquímica Clínica, Laboratorio de Lípidos y Aterosclerosis, Ciudad Autónoma de Buenos Aires.
Introduction: LDL-cholesterol greater than 190 mg/dL indicates severe hypercholesterolemia (HS) of monogenic and/or polygenic origin. Genetic risk scores (GRS) evaluate potential polygenic causes.
Objective: we applied a GRS of 6-SNP (GRS-6) in HS individuals.
Enhancing panoramic dental imaging with AI-driven arch surface fitting: Achieving improved clarity and accuracy through an optimal reconstruction zone.
Dentomaxillofac Radiol
January 2025
Department of Oral and Maxillofacial Radiology, School of Dentistry, Pusan National University, Yangsan, 50612, Korea.
Objectives: This study aimed to develop an automated method for generating clearer, well-aligned panoramic views by creating an optimized three-dimensional (3D) reconstruction zone centered on the teeth. The approach focused on achieving high contrast and clarity in key dental features, including tooth roots, morphology, and periapical lesions, by applying a 3D U-Net deep learning model to generate an arch surface and align the panoramic view.
Methods: This retrospective study analyzed anonymized cone-beam CT (CBCT) scans from 312 patients (mean age 40 years; range 10-78; 41.
Detection of multidrug-resistant methicillin-resistant Staphylococcus aureus from healthy black Bengal goat in Bangladesh.
J Infect Dev Ctries
December 2024
Department of Microbiology & Hygiene, Bangladesh Agricultural University, Mymensingh-2202, Bangladesh.
Introduction: The emergence of livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) is a growing public health concern. The objective of this study was to determine the prevalence and multi-drug resistant (MDR) profiles of MRSA in goats in Bangladesh.
Methodology: A total of 150 samples from goats comprised of rectal swab (n = 50), nasal swab (n = 50), and milk (n = 50) were collected.
Multispectral imaging-based detection of apple bruises using segmentation network and classification model.
J Food Sci
January 2025
College of Electronics and Engineering, Heilongjiang University, Harbin, China.
Bruises can affect the appearance and nutritional value of apples and cause economic losses. Therefore, the accurate detection of bruise levels and bruise time of apples is crucial. In this paper, we proposed a method that combines a self-designed multispectral imaging system with deep learning to accurately detect the level and time of bruising on apples.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!