It has been well-established that mycotoxins are poisonous chemical metabolites secreted by certain molds. Some of them significantly affect the health of humans and livestock. Increasing attention is now being paid to uncovering and identifying mycotoxins' presence in the building's environment. However, the main challenge remains in suitable and reliable analytical methods for their identification and detection in infected structures. GC-MS and LC-MS/MS techniques have been used extensively for mycotoxin analysis, and advancement in these techniques enabled a more comprehensive range of mycotoxins to be detected. As such, this study aimed to address a brief overview of various phenomena of existing sample collection, preparation, and analysis to detect mycotoxins in the building's environment. This scoping review includes articles from 2010 to 2020 available from PubMed, Scopus, Cochrane, Wiley, Google Scholar, and ScienceDirect. Duplicate articles were removed, and exclusion criteria were applied to eliminate unrelated studies, resulting in 14 eligible articles. The present study provides an overview of mycotoxin analysis by GC-MS and LC-MS/MS in buildings. Many techniques are available for analyzing and detecting multiple mycotoxins using these methods. Future efforts would focus on rapid assays and tools enabling measuring a broader range of mycotoxins in a single matrix and lower detection limits. In addition, it would assist future findings on new techniques and mycotoxins that existed in the building's environment.
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http://dx.doi.org/10.1155/2024/8581029 | DOI Listing |
Sensors (Basel)
January 2025
Key Laboratory of Automotive Power Train and Electronics, Hubei University of Automotive Technology, Shiyan 442002, China.
Autonomous driving has demonstrated impressive driving capabilities, with behavior decision-making playing a crucial role as a bridge between perception and control. Imitation Learning (IL) and Reinforcement Learning (RL) have introduced innovative approaches to behavior decision-making in autonomous driving, but challenges remain. On one hand, RL's policy networks often lack sufficient reasoning ability to make optimal decisions in highly complex and stochastic environments.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Engineering, RMIT University, 124 La Trobe Street, Melbourne, VIC 3000, Australia.
Civil infrastructure assets' contribution to countries' economic growth is significantly increasing due to the rapid population growth and demands for public services. These civil infrastructures, including roads, bridges, railways, tunnels, dams, residential complexes, and commercial buildings, experience significant deterioration from the surrounding harsh environment. Traditional methods of visual inspection and non-destructive tests are generally undertaken to monitor and evaluate the structural health of the infrastructure.
View Article and Find Full Text PDFSensors (Basel)
December 2024
2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, 12462 Athens, Greece.
The widespread propagation of wireless communication devices, from smartphones and tablets to Internet of Things (IoT) systems, has become an integral part of modern life. However, the expansion of wireless technology has also raised public concern about the potential health risks associated with prolonged exposure to electromagnetic fields. Our objective is to determine the optimal machine learning model for constructing electric field strength maps across urban areas, enhancing the field of environmental monitoring with the aid of sensor-based data collection.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Physics and Astronomy, University of Glasgow, Glasgow G12 8QQ, UK.
Accurate depth estimation is crucial for many fields, including robotics, navigation, and medical imaging. However, conventional depth sensors often produce low-resolution (LR) depth maps, making detailed scene perception challenging. To address this, enhancing LR depth maps to high-resolution (HR) ones has become essential, guided by HR-structured inputs like RGB or grayscale images.
View Article and Find Full Text PDFNutrients
December 2024
Lipids and Atherosclerosis Unit, Department of Internal Medicine, Reina Sofia University Hospital, 14004 Cordoba, Spain.
Background/objectives: Gut microbiota interacts with nutrients, which may be relevant to assigning a microbial signature to colorectal cancer (CRC). We aim to evaluate the potential of gut microbiota combined with dietary habits in the early detection of pathological findings related to CRC in the course of a screening program.
Methodology: The colonoscopy performed on 152 subjects positive for fecal occult blood test showed that 6 subjects had adenocarcinoma, 123 had polyps, and 23 subjects had no pathological findings.
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