Progressive loss of dopaminergic neurons in substantia nigra is a key pathogenesis of Parkinson's disease. In the present study, we investigated the effects of treadmill exercise on short-term memory, apoptotic dopaminergic neuronal cell death and fiber loss in the nigrostriatum, and cell proliferation in the hippocampal dentate gyrus of Parkinson's rats. Parkinson's rats were made by injection of 6-hydroxydopamine (6-OHDA) into the striatum using stereotaxic instrument. Four weeks after 6-OHDA injection, the rats in the 6-OHDA-injection group exhibited significant rotational asymmetry following apomorphine challenge. The rats in the exercise groups were put on the treadmill to run for 30 min once a day for 14 consecutive days starting 4 weeks after 6-OHDA injection. In the present results, extensive degeneration of the dopaminergic neurons in the substantia nigra with loss of dopaminergic fibers in the striatum were produced in the rats without treadmill running, which resulted in short-term memory impairment. However, the rats performing treadmill running for 2 weeks alleviated nigrostriatal dopaminergic cell loss and alleviated short-term memory impairment with increasing cell proliferation in the hippocampal dentate gyrus of Parkinson's rats. The present results show that treadmill exercise may provide therapeutic value for the Parkinson's disease.
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http://dx.doi.org/10.12965/jer.130048 | DOI Listing |
NPJ Sci Food
December 2024
Department of Bioscience and Biotechnology, Faculty of Agriculture, Graduate School of Kyushu University, Fukuoka, Japan.
In a series of studies on blood-brain barrier transportable peptides, a soybean dipeptide, Tyr-Pro, penetrated the mouse brain parenchyma after oral intake and improved short and long memory impairment in acute Alzheimer's model mice. Here, we aimed to clarify the anti-dementia effects of this peptide administered to SAMP8 mice prior to dementia onset. At the end of the 25-week protocol in 16-week-old SAMP8 mice, Tyr-Pro (10 mg/kg/day) significantly improved the reduced spatial learning ability compared with that in the control and amino acid (Tyr + Pro) groups as indicated by the results of Morris water maze tests conducted for five consecutive days.
View Article and Find Full Text PDFNat Commun
December 2024
Computational Neuroscience Unit, Intelligent Systems Labs, Faculty of Engineering, University of Bristol, Bristol, UK.
The brain must maintain a stable world model while rapidly adapting to the environment, but the underlying mechanisms are not known. Here, we posit that cortico-cerebellar loops play a key role in this process. We introduce a computational model of cerebellar networks that learn to drive cortical networks with task-outcome predictions.
View Article and Find Full Text PDFBrief Bioinform
November 2024
In-Service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, 250 Wuxing Street, 110, Taipei, Taiwan.
Accurate prediction of RNA modifications holds profound implications for elucidating RNA function and mechanism, with potential applications in drug development. Here, the RNA-ModX presents a highly precise predictive model designed to forecast post-transcriptional RNA modifications, complemented by a user-friendly web application tailored for seamless utilization by future researchers. To achieve exceptional accuracy, the RNA-ModX systematically explored a range of machine learning models, including Long Short-Term Memory (LSTM), Gated Recurrent Unit, and Transformer-based architectures.
View Article and Find Full Text PDFAdv Sci (Weinh)
December 2024
Department of Biomedical Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Kowloon, Hong Kong SAR, China.
The patch clamp technique is a fundamental tool for investigating ion channel dynamics and electrophysiological properties. This study proposes the first artificial intelligence framework for characterizing multiple ion channel kinetics of whole-cell recordings. The framework integrates machine learning for anomaly detection and deep learning for multi-class classification.
View Article and Find Full Text PDFBMC Med Res Methodol
December 2024
School of Public Health, Xuzhou Medical University, No. 209 Tongshan Road, Xuzhou, Jiangsu, 221004, China.
Background: The prediction of coronavirus disease in 2019 (COVID-19) in broader regions has been widely researched, but for specific areas such as urban areas the predictive models were rarely studied. It may be inaccurate to apply predictive models from a broad region directly to a small area. This paper builds a prediction approach for small size COVID-19 time series in a city.
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