Neurodegenerative diseases are driven by several mechanisms such as inflammation, abnormal protein aggregation, excitotoxicity, mitochondrial dysfunction and oxidative stress. So far, no therapeutic strategies are available for neurodegenerative diseases and in recent years the research is focusing on bioactive molecules present in food. In particular, extra-virgin olive oil (EVOO) phenols have been associated to neuroprotection. In this study, we investigated the potential antioxidant and neuroprotective activity of two different EVOO extracts obtained from Quercetano cultivar trees grown in two different areas (plain and hill) of the Tuscany region (Italy). The different geographical origin of the orchards influenced phenol composition. Plain extract presented a higher content of phenyl ethyl alcohols, cinnammic acids, oleacein, oleocanthal and flavones; meanwhile, hill extract was richer in lignans. Hill extract was more effective in protecting differentiated SH-SY5Y cells from peroxide stress thanks to a marked upregulation of the antioxidant enzymes heme oxygenase 1, NADPH quinone oxidoreductase 1, thioredoxin Reductase 1 and glutathione reductase. Proteomic analysis revealed that hill extract plays a role in the regulation of proteins involved in neuronal plasticity and activation of neurotrophic factors such as BDNF. In conclusion, these data demonstrate that EVOOs can have important neuroprotective activities, but these effects are strictly related to their specific phenol composition.
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http://dx.doi.org/10.3390/antiox10030421 | DOI Listing |
Obes Rev
January 2025
Obesity Institute, School of Health, Leeds Beckett University, Leeds, UK.
Background: There is limited evidence and clinical guidelines on the behavior change support required for low-calorie diet programs. This systematic review aimed to establish the behavior change technique(s) (BCT) implemented in weight loss interventions (≤1200 kcal/d) and how these contribute to effectiveness.
Methods: Databases were searched from inception to April 2022.
ScientificWorldJournal
January 2025
Department of Microbiology, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India.
Infection by human herpes simplex virus type 1 and type 2 (HSV-1/2) is common globally though with wide regional variability. Seroepidemiology of HSV-1/2 infections is of utmost importance in formulating control strategies, but there is a paucity of data from many regions of India. This study aimed to determine the prevalence of anti-HSV-1/2 antibodies in Uttarakhand and adjoining areas and to study its pattern and distribution in different subgroups.
View Article and Find Full Text PDFJ Food Sci
January 2025
College of Food Science and Engineering, Nanjing University of Finance and Economics/Collaborative Innovation Center for Modern Grain Circulation and Safety, Nanjing, China.
Pleurotus ostreatus is a nutrient-dense edible fungus renowned for its delicate texture, appealing flavor, and numerous potential health benefits. Simultaneous extraction within the framework of food resource processing facilitates the concurrent isolation and analysis of multiple target compounds. In this study, an ethanol/salt aqueous two-phase system (ATPS) was employed to extract polysaccharides (PS) and proteins from P.
View Article and Find Full Text PDFEnviron Sci Technol Lett
January 2025
EaStCHEM School of Chemistry, University of Edinburgh, Joseph Black Building, David Brewster Rd, Edinburgh, EH9 3FJ, United Kingdom.
Detecting and quantifying tire wear particles (TWPs) in the environment pose a unique environmental challenge due to their chemical complexity. There are emerging concerns around TWPs due to their potential high numbers of particles released, outnumbering microplastics, as well as the leaching of toxic additives such as 6-PPD which has been linked to the death of salmon even when present at very low levels (<0.1 μg/L).
View Article and Find Full Text PDFResearch (Wash D C)
January 2025
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Spatially resolved transcriptomics enable comprehensive measurement of gene expression at subcellular resolution while preserving the spatial context of the tissue microenvironment. While deep learning has shown promise in analyzing SCST datasets, most efforts have focused on sequence data and spatial localization, with limited emphasis on leveraging rich histopathological insights from staining images. We introduce GIST, a deep learning-enabled gene expression and histology integration for spatial cellular profiling.
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