The deposition of amyloid protein as senile plaques is the major signature of Alzheimer's disease (AD). It is produced by the sequential cleavage of the amyloid precursor protein by secretases. Moreover, peppers are noted for their antiaging and cognitive enhancing properties. Thus, in this study, the effects of polyphenol-rich extracts from bell pepper on amyloid production and aggregation in vitro were investigated. Bell pepper (ripe and unripe) was extracted with methanol-1 N HCl (1:1 v/v). Thereafter, the inhibitory potentials of the extracts on β-secretase and β-amyloid aggregation were determined. Phenolic composition of the pepper fruits was further determined by HPLC-DAD (high performance liquid chromatography-diode array detector). There was a dose-dependent inhibition of β-secretase by the pepper fruits with the ripe fruits (2.17 ± 0.17 μg/L) showing a significantly (P < .05) higher inhibitory effect than the unripe (3.44 ± 0.11 μg/L). Furthermore, Thioflavin-T and transmission electron microscopy analyses revealed that phenolic extracts from pepper fruits (1 and 10 μg/L) could counteract the initial aggregation of Aβ, as well as prevent further aggregation preformed fibrils. These inhibitory activities could be attributed to the predominant presence of phenolic constituents in the pepper fruits. It is possible to conclude that bell pepper could be a possible dietary intervention into the management of AD.
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http://dx.doi.org/10.1089/jmf.2016.0077 | DOI Listing |
ChemistryOpen
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Department of Food Processing, Vocational School of Technical Science, 72060, Batman, Türkiye.
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January 2025
State Key Laboratory of Vegetable Biobreeding, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture and Rural Affairs, Sino-Dutch Joint Laboratory of Horticultural Genomics, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing, China.
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January 2025
Amal Jyothi College of Engineering (Autonomous), Kanjirappally, Kerala, India.
In agriculture, promptly and accurately identifying leaf diseases is crucial for sustainable crop production. To address this requirement, this research introduces a hybrid deep learning model that combines the visual geometric group version 19 (VGG19) architecture features with the transformer encoder blocks. This fusion enables the accurate and précised real-time classification of leaf diseases affecting grape, bell pepper, and tomato plants.
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January 2025
Department of Biotechnology, Manipur University, Canchipur, Imphal, Manipur, India.
Pepper is an economically important crop grown worldwide for consumption as a vegetable and spice. Much waste, including crop plant waste, seeds, stalks, placenta, peels, and other processing byproducts, is generated by consumers during pepper crop production, processing, retail, and households. These peppers byproducts contain numerous bioactive compounds that can be used as ingredients for developing functional foods, nutraceuticals, and other food industries.
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