Aging is an unavoidable process in the body that is accompanied by impaired tissue homeostasis and various changes. Carvacrol has attracted considerable attention for its wide range of pharmacological activities. Therefore, this study attempted to explore the protective effect of carvacrol in aged rats. The aged rats were given carvacrol (15 or 30 mg/kg/day) for 4 weeks. Morris water maze and passive avoidance tests were used to determine the learning and memory abilities of the rats. The hippocampus and cortex samples were taken for biochemical analysis. In comparison to young control rats, aged control rats showed learning and memory deficits. There was improvement in the Morris water navigation test and passive avoidance test performance in the treatment groups versus the aged control group. An increment in malondialdehyde (MDA) and a decrease in total thiol groups in the hippocampus and cortex samples of aged control rats in comparison to the young control group were observed. Carvacrol decreased MDA levels and increased total thiol groups in the hippocampus and cortex samples of aged rats. Carvacrol improved learning and memory in aged rats, probably through its anti-oxidation effects.
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http://dx.doi.org/10.1080/00207454.2023.2257877 | DOI Listing |
ACS Appl Mater Interfaces
December 2024
School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Although MoSe-based photodetectors have achieved excellent performance, the ultrafast photoresponse has limited their application as an optoelectronic synapse. In this paper, the enhancement of the rhodamine 6G molecule on the memory time of MoSe is reported. It is found that the memory time of monolayer MoSe can be obviously enhanced after assembly with rhodamine 6G exhibiting synaptic characteristics in comparison to pristine MoSe.
View Article and Find Full Text PDFBMC Psychiatry
December 2024
Department of Clinical, Neuro- and Developmental Psychology, Faculty of Behavioral and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Background: There is robust evidence that posttraumatic stress disorder (PTSD) is associated with neurocognitive deficits, such as executive dysfunction or memory dysfunction. Eye Movement Desensitization and Reprocessing (EMDR) is an evidence-based treatment for PTSD, in which eye movements (EMs) are performed during traumatic memory retrieval. We examined whether Eye Movement Desensitization (EMD) improves neurocognitive functioning in PTSD patients, in comparison with a retrieval-only control condition without EMs.
View Article and Find Full Text PDFSci Rep
December 2024
School of Human Sciences, University of Western Australia, Crawley, WA, 6009, Australia.
Hearing loss (HL) in mid-life has been suggested as a risk factor for cognitive decline. It is unclear whether this relationship is due to deprivation of auditory input alone, degenerative processes, or a combination. Animal models are useful to investigate underlying neural mechanisms as human studies can be confounded by various factors.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Electronics, Information and Communication Engineering, Kangwon National University, Samcheok, 25913, Republic of Korea.
Autism spectrum disorder (ASD) is a neurologic disorder considered to cause discrepancies in physical activities, social skills, and cognition. There is no specific medicine for treating this disorder; early intervention is critical to improving brain function. Additionally, the lack of a clinical test for detecting ASD makes diagnosis challenging.
View Article and Find Full Text PDFSci Rep
December 2024
College of Sciences, National University of Defense Technology, 410073, Changsha, China.
Deep Convolutional Neural Networks (DCNNs), due to their high computational and memory requirements, face significant challenges in deployment on resource-constrained devices. Network Pruning, an essential model compression technique, contributes to enabling the efficient deployment of DCNNs on such devices. Compared to traditional rule-based pruning methods, Reinforcement Learning(RL)-based automatic pruning often yields more effective pruning strategies through its ability to learn and adapt.
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