The indole diterpenoid toxin lolitrem B is a tremorgenic agent found in the common grass species, perennial ryegrass (Lolium perenne). The toxin is produced by a symbiotic fungus Epichloë festucae (var. lolii) and ingestion of infested grass with sufficient toxin levels causes a movement disorder in grazing herbivores known as 'ryegrass staggers'. Beside ataxia, lolitrem B intoxicated animals frequently show indicators of cognitive dysfunction or exhibition of erratic and unpredictable behaviours during handling. Evidence from field cases in livestock and controlled feeding studies in horses have indicated that intoxication with lolitrem B may affect higher cortical or subcortical functioning. In order to define the role of lolitrem B in voluntary motor control, spatial learning and memory under controlled conditions, mice were exposed to a known dose of purified lolitrem B toxin and tremor, coordination, voluntary motor activity and spatial learning and memory assessed. Motor activity, coordination and spatial memory were compared to tremor intensity using a novel quantitative piezo-electronic tremor analysis. Peak tremor was observed as frequencies between 15 and 25Hz compared to normal movement at approximately 1.4-10Hz. A single exposure to a known tremorgenic dose of lolitrem B (2 mg/kg IP) induced measureable tremor for up to 72 h in some animals. Initially, intoxication with lolitrem B significantly decreased voluntary movement. By 25 h post exposure a return to normal voluntary movement was observed in this group, despite continuing evidence of tremor. This effect was not observed in animals exposed to the short-acting tremorgenic toxin paxilline. Lolitrem B intoxicated mice demonstrated a random search pattern and delayed latency to escape a 3 h post intoxication, however by 27 h post exposure latency to escape matched controls and mice had returned to normal searching behavior indicating normal spatial learning and memory. Together these data indicate that the tremor exhibited by lolitrem B intoxicated mice does not directly impair spatial learning and memory but that exposure does reduce voluntary motor activity in intoxicated animals. Management of acutely affected livestock suffering toxicosis should be considered in the context of their ability to spatially orientate with severe toxicity.
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http://dx.doi.org/10.1016/j.toxicon.2019.06.228 | DOI Listing |
PLoS One
January 2025
Department of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi Arabia.
Modernizing power systems into smart grids has introduced numerous benefits, including enhanced efficiency, reliability, and integration of renewable energy sources. However, this advancement has also increased vulnerability to cyber threats, particularly False Data Injection Attacks (FDIAs). Traditional Intrusion Detection Systems (IDS) often fall short in identifying sophisticated FDIAs due to their reliance on predefined rules and signatures.
View Article and Find Full Text PDFNeurochem Res
January 2025
Neurosciences Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder characterized by cognitive decline. Despite extensive research, therapeutic options remain limited. Varenicline, an αβ nicotinic acetylcholine receptor agonist, shows promise in enhancing cognitive function.
View Article and Find Full Text PDFSingle-omics approaches often provide a limited view of complex biological systems, whereas multiomics integration offers a more comprehensive understanding by combining diverse data views. However, integrating heterogeneous data types and interpreting the intricate relationships between biological features-both within and across different data views-remains a bottleneck. To address these challenges, we introduce COSIME (Cooperative Multi-view Integration and Scalable Interpretable Model Explainer).
View Article and Find Full Text PDFISME Commun
January 2024
School of Chemistry and Molecular Biosciences, Australian Centre for Ecogenomics, The University of Queensland, QLD 4072, Australia.
Anthropogenic influences have drastically increased nutrient concentrations in many estuaries globally, and microbial communities have adapted to the resulting hypereutrophic ecosystems. However, our knowledge of the dominant microbial taxa and their potential functions in these ecosystems has remained sparse. Here, we study prokaryotic community dynamics in a temporal-spatial dataset, from a subtropical hypereutrophic estuary.
View Article and Find Full Text PDFFront Plant Sci
January 2025
School of Computer Science and Technology, Henan Institute of Science and Technology, Xinxiang, China.
Introduction: With the advent of technologies such as deep learning in agriculture, a novel approach to classifying wheat seed varieties has emerged. However, some existing deep learning models encounter challenges, including long processing times, high computational demands, and low classification accuracy when analyzing wheat seed images, which can hinder their ability to meet real-time requirements.
Methods: To address these challenges, we propose a lightweight wheat seed classification model called LWheatNet.
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