The essential oils of 14 species and hybrids, respectively, of the genus Mentha were examined for their antioxidant capacity in the ABTS (2,2'-azinobis(3-ethylbenzothiazoline-6-sulfonic acid)) assay and in a lipid-peroxidation (LPO) assay. The ABTS(.+) -scavenging capacity of pure essential-oil components and mixtures of them was also tested. In both assays, Mentha×dumetorum (classification not fully confirmed), Mentha suaveolens, and Mentha×villosa (classification not fully confirmed) showed the highest antioxidant capacity, which was ascribed to the components germacrene D, piperitone oxide, and piperitenone oxide. The high antioxidant activity in the LPO assay of the two hybrids Mentha×gracilis and, to a lower degree, of Mentha×dalmatica (classification not fully confirmed) was ascribed to their high contents of cis-ocimene and β-caryophyllene. Of the pure components tested (germacrene D, piperitone oxide, and piperitenone oxide were not tested, as not commercially available), only cis-ocimene showed a distinct antioxidant effect, whereas dihydrocarvone and linalool had pro-oxidant effects in the ABTS assay.
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http://dx.doi.org/10.1002/cbdv.201400100 | DOI Listing |
Alzheimers Dement
December 2024
Division of Neurology, University of Toronto, Toronto, Ontario, Canada.
Introduction: Psychotropic medication (PM) use in behavioral-variant frontotemporal dementia (bvFTD) is higher than in other dementias. However, no information exists on whether PM use differs between sporadic and genetic bvFTD.
Methods: We analyzed data from sporadic and genetic bvFTD participants with PM prescriptions in the Advancing Research and Treatment in Frontotemporal Lobar Degeneration/Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects study.
Eur Heart J Imaging Methods Pract
October 2024
Department for Internal Medicine and Cardiology, Herzzentrum Dresden, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Fetscherstr. 76, 01307 Dresden, Germany.
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Cureus
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General Surgery, Centro Hospitalar Barreiro Montijo, Barreiro, PRT.
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December 2024
School of Automation, Hangzhou Dianzi University, Hangzhou, 310018 Zhejiang China.
Brain-computer interface (BCI) based on the motor imagery paradigm typically utilizes multi-channel electroencephalogram (EEG) to ensure accurate capture of physiological phenomena. However, excessive channels often contain redundant information and noise, which can significantly degrade BCI performance. Although there have been numerous studies on EEG channel selection, most of them require manual feature extraction, and the extracted features are difficult to fully represent the effective information of EEG signals.
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December 2024
Rehabilitation and Physical Therapy Department, Shandong University of Traditional Chinese Medicine Affiliated Hospital, NO.42, Wenhuaxi Road, Jinan, 250014 Shandong Province People's Republic of China.
Transformer neural networks based on multi-head self-attention are effective in several fields. To capture brain activity on electroencephalographic (EEG) signals and construct an effective pattern recognition model, this paper explores the multi-channel deep feature decoding method utilizing the self-attention mechanism. By integrating inter-channel features with intra-channel features, the self-attention mechanism generates a deep feature vector that encompasses information from all brain activities.
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