The mouse bioassay for diarrhetic shellfish poisoning (DSP) toxins had been used as the official method in Japan and also used in the world. In this study, hypothermia, one of the symptoms observed in mice after inoculation with DSP toxins, were characterized. Lethal and sublethal doses of okadaic acid (OA), a representative component of DSP toxins, were inoculated intraperitoneally into mice. Body-temperature changes over time were measured by an electronic thermometer or monitored by an infrared camera. Drastic hypothermia (<30°C in some mice) was observed in a few hours after administration of a lethal dose of OA. Dose-dependency was clearly seen between doses of OA inoculated and body-temperature decrease. Drastic hypothermia was also detected by using an infrared camera. These results suggest that hypothermia could be used as an index for the humane endpoint in experimental animal toxicological studies.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8390301 | PMC |
http://dx.doi.org/10.1538/expanim.21-0048 | DOI Listing |
eNeuro
January 2025
Solomon H. Snyder Department of Neuroscience, The Johns Hopkins University School of Medicine, Baltimore, Maryland 21205
It is widely believed that axons in the central nervous system of adult mammals do not regrow following injury. This failure is thought, at least in part, to underlie the limited recovery of function following injury to the brain or spinal cord. Some studies of fixed tissue have suggested that, counter to dogma, norepinephrine (NE) axons regrow following brain injury.
View Article and Find Full Text PDFHarmful Algae
January 2025
School of Marine and Atmospheric Sciences, Stony Brook University, Southampton, NY, United States. Electronic address:
Mar Drugs
November 2024
Key Laboratory of Aquatic Eutrophication and Control of Harmful Algal Blooms of Guangdong Higher Education Institute, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Harmful Algae
November 2024
National Institute of Biology, Marine Biology Station Piran, Slovenia.
In this study, explainable machine learning techniques are applied to predict the toxicity of mussels in the Gulf of Trieste (Adriatic Sea) caused by harmful algal blooms. By analysing a newly created 28-year dataset containing records of toxic phytoplankton in mussel farming areas and diarrhetic shellfish toxins in mussels (Mytilus galloprovincialis), we train and evaluate the performance of machine learning (ML) models to accurately predict diarrhetic shellfish poisoning (DSP) events. Based on the F1 score, the random forest model provided the best prediction of toxicity results at which the harvesting of mussels is stopped according to EU regulations.
View Article and Find Full Text PDFChemosphere
October 2024
Departamento de Farmacología, Facultad de Veterinaria, Universidad de Santiago de Compostela, Lugo, Spain.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!