Although some central effects of citral have been reported, cognitive effects on spatial memory have not been investigated. The evidence showed that citral can regulate the synthesis of retinoic acid (RA), which exerts a vital function in the development and maintenance of spatial memory. In this study, we applied Morris water maze to test the effect of citral on animals' spatial learning and memory. To elucidate the mechanism of this effect, we also measured the retinoic acid concentration in rats' hippocampus by high performance liquid chromatography (HPLC). Our data implied biphasic effects of citral. The low dose (0.1 mg/kg) of citral improved the spatial learning capability, and enhanced the spatial reference memory of rats, whereas the high dose (1.0 mg/kg) was like to produce the opposite effects. Meanwhile, the low dose of citral increased the hippocampal retinoic acid concentration, while the high dose decreased it. Due to the quick elimination and non-bioaccumulation in the body, effects of citral on spatial memory in this study seemed to be indirect actions. The change in hippocampal retinoic acid concentration induced by different doses of citral might be responsible for the biphasic effect of citral on spatial learning and memory.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.pbb.2009.05.016 | DOI Listing |
Sci Rep
January 2025
Department of Computer Science and Engineering, E.G.S. Pillay Engineering College, Nagapattinam, 611002, Tamil Nadu, India.
In response to the pressing need for the detection of Monkeypox caused by the Monkeypox virus (MPXV), this study introduces the Enhanced Spatial-Awareness Capsule Network (ESACN), a Capsule Network architecture designed for the precise multi-class classification of dermatological images. Addressing the shortcomings of traditional Machine Learning and Deep Learning models, our ESACN model utilizes the dynamic routing and spatial hierarchy capabilities of CapsNets to differentiate complex patterns such as those seen in monkeypox, chickenpox, measles, and normal skin presentations. CapsNets' inherent ability to recognize and process crucial spatial relationships within images outperforms conventional CNNs, particularly in tasks that require the distinction of visually similar classes.
View Article and Find Full Text PDFSci Data
January 2025
Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, 100091, China.
The vegetation index is a key satellite-based variable used to monitor global vegetation distribution and growth. However, existing vegetation index datasets face limitations in achieving both high spatial and temporal resolution, restricting their application potential. This study revised a machine learning spatiotemporal fusion model (InENVI) to produce a high-resolution NDVI dataset with 8-day temporal and 30 m spatial resolution, covering China from 2001 to 2020.
View Article and Find Full Text PDFWater Res
January 2025
State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China.
Cyanobacterial blooms are increasingly becoming major threats to global inland aquatic ecosystems. Phycocyanin (PC), a pigment unique to cyanobacteria, can provide important reference for the study of cyanobacterial blooms warning. New satellite technology and cloud computing platforms have greatly improved research on PC, with the average number of studies examining it having increased from 5 per year before 2018 to 17 per year thereafter.
View Article and Find Full Text PDFSci Data
January 2025
Remote Sensing Centre for Earth System Research (RSC4Earth), Leipzig University, Leipzig, 04103, Germany.
With climate extremes' rising frequency and intensity, robust analytical tools are crucial to predict their impacts on terrestrial ecosystems. Machine learning techniques show promise but require well-structured, high-quality, and curated analysis-ready datasets. Earth observation datasets comprehensively monitor ecosystem dynamics and responses to climatic extremes, yet the data complexity can challenge the effectiveness of machine learning models.
View Article and Find Full Text PDFNat Commun
January 2025
Center for Advanced Radiation Sources, University of Chicago, Chicago, IL, USA.
Phase transitions in the mantle control its internal dynamics and structure. The post-spinel transition marks the upper-lower mantle boundary, where ringwoodite dissociates into bridgmanite plus ferropericlase, and its Clapeyron slope regulates mantle flow across it. This interaction has previously been assumed to have no lateral spatial variations, based on the assumption of a linear post-spinel boundary in pressure and temperature.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!