Evaluation of learning and memory is crucial in juvenile animal toxicity studies (JAS) during the development of CNS active drugs, but there are no currently recommended test methods. We compared the ability of the Morris water maze (MWM) and the Biel water maze (BWM) to detect learning and memory disorder (LMD) using rats inhaled isoflurane (IFN). Rats were treated with 1% IFN using inhalation on postnatal day (PND) 7 for 6 h. All rats were subjected to the MWM on PND 33 and the BWM on PND 55/57 (Experiment 1), or the BWM on PND 32/33 and the MWM on PND 54/55 (Experiment 2). On PND 70, the brain was weighed and then neurohistopathology was conducted. There were no IFN-related changes in clinical signs and body weight. In the tests beginning on PND 32/33, the MWM clearly detected IFN-related LMD in both sexes whereas the BWM detected LMD only in males. With an additional benefit of a simpler procedure, the MWM was considered superior to the BMW for JAS. LMD was not detected in both mazes tested from PND 54/55/57, which was considered due to weak effect and/or recovery of brain function with growth. Single IFN inhalation on PND 7 was considered useful as positive control to induce LMD caused by postnatal exposure in rats, but stronger treatment regimens was recommended.
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BMC Pharmacol Toxicol
January 2025
Yanzhou District People's Hospital, Jining, Shandong, China.
Background: Osteoporosis (OP), often termed the "silent epidemic," poses a substantial public health burden. Emerging insights into the molecular functions of FBXW4 have spurred interest in its potential roles across various diseases.
Methods: This study explored FBXW4 by integrating DEGs from GEO datasets GSE2208, GSE7158, GSE56815, and GSE35956 with immune-related gene compilations from the ImmPort repository.
Mol Neurodegener
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The Picower Institute for Learning and Memory, Cambridge, MA, USA.
Many diseases and disorders of the nervous system suffer from a lack of adequate therapeutics to halt or slow disease progression, and to this day, no cure exists for any of the fatal neurodegenerative diseases. In part this is due to the incredible diversity of cell types that comprise the brain, knowledge gaps in understanding basic mechanisms of disease, as well as a lack of reliable strategies for delivering new therapeutic modalities to affected areas. With the advent of single cell genomics, it is now possible to interrogate the molecular characteristics of diverse cell populations and their alterations in diseased states.
View Article and Find Full Text PDFSci Rep
January 2025
School of Architecture and Urban Planning, Beijing University of Civil Engineering and Architecture, Beijing, 100055, China.
Air pollution is a critical global environmental issue, further exacerbated by rapid industrialization and urbanization. Accurate prediction of air pollutant concentrations is essential for effective pollution prevention and control measures. The complex nature of pollutant data is influenced by fluctuating meteorological conditions, diverse pollution sources, and propagation processes, underscores the crucial importance of the spatial and temporal feature extraction for accurately predicting air pollutant concentrations.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Science and Technology, Suan Sunandha Rajabhat University, Bangkok, 10300, Thailand.
Attention mechanisms such as the Convolutional Block Attention Module (CBAM) can help emphasize and refine the most relevant feature maps such as color, texture, spots, and wrinkle variations for the avocado ripeness classification. However, the CBAM lacks global context awareness, which may prevent it from capturing long-range dependencies or global patterns such as relationships between distant regions in the image. Further, more complex neural networks can improve model performance but at the cost of increasing the number of layers and train parameters, which may not be suitable for resource constrained devices.
View Article and Find Full Text PDFNat Commun
January 2025
Institute of Theoretical Computer Science, Graz University of Technology, Graz, Austria.
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