Investigation of nutriactive phytochemical – gamma‐oryzanol in experimental animal models

Szcześniak, K. A.; Ostaszewski, Paweł; Ciecierska, Anna; Sadkowski, Tomasz

doi:10.1111/jpn.12428

Cited by 43 publications

(29 citation statements)

References 65 publications

(96 reference statements)

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“…γ-Oryzanol has been proven safe for consumption with no major side effect [11,12]. Numerous studies have reported health-beneficial properties of γ-oryzanol including anti-hyperlipidemic, anti-ulcerogenic, anti-carcinogenic, anti-inflammatory, anti-diabetic, and antioxidant effects [10,11]. We recently demonstrated the mechanism by which γ-oryzanol regulates cellular redox homeostasis [13].…”

Section: Introductionmentioning

confidence: 99%

γ-Oryzanol Improves Cognitive Function and Modulates Hippocampal Proteome in Mice

et al. 2019

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Rice (Oryza sativa L.) is the richest source of γ-oryzanol, a compound endowed with antioxidant and anti-inflammatory properties. γ-Oryzanol has been demonstrated to cross the blood-brain barrier in intact form and exert beneficial effects on brain function. This study aimed to clarify the effects of γ-oryzanol in the hippocampus in terms of cognitive function and protein expression. Adult mice were administered with γ-oryzanol 100 mg/kg or vehicle (control) once a day for 21 consecutive days following which cognitive behavior and hippocampal proteome were investigated. Cognitive tests using novel object recognition and Y-maze showed that long-term consumption of γ-oryzanol improves cognitive function in mice. To investigate the hippocampal proteome modulated by γ-oryzanol, 2D-difference gel electrophoresis (2D-DIGE) was performed. Interestingly, we found that γ-oryzanol modulates quantitative changes of proteins involved in synaptic plasticity and neuronal trafficking, neuroprotection and antioxidant activity, and mitochondria and energy metabolism. These findings suggested γ-oryzanol as a natural compound able to maintain and reinforce brain function. Although more intensive studies are needed, we propose γ-oryzanol as a putative dietary phytochemical for preserving brain reserve, the ability to tolerate age-related changes, thereby preventing clinical symptoms or signs of neurodegenerative diseases.

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Section: Introductionmentioning

confidence: 99%

γ-Oryzanol Improves Cognitive Function and Modulates Hippocampal Proteome in Mice

et al. 2019

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“…However, the most of the data available comes from studies in vitro or from animal models. In a recent study, Szcześniak et al revised several of these studies and concluded that beneficial effects of Orz are due to its antioxidant activity and modifications in lipids metabolism [ 11 ]. A remarkable lack of specific dosages have used in animal models (doses range to 1–2000 mg/kg of body weight), or in vitro (doses range to 0.1–1000 µmol) [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

“…In a recent study, Szcześniak et al revised several of these studies and concluded that beneficial effects of Orz are due to its antioxidant activity and modifications in lipids metabolism [ 11 ]. A remarkable lack of specific dosages have used in animal models (doses range to 1–2000 mg/kg of body weight), or in vitro (doses range to 0.1–1000 µmol) [ 11 ]. Nevertheless, is still necessary to clarify the exact mechanisms of action and confirm the results obtained in human studies.…”

Section: Introductionmentioning

confidence: 99%

Antioxidant Activity of γ-Oryzanol: A Complex Network of Interactions

Minatel

Francisqueti

Corrêa

et al. 2016

IJMS

123

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γ-oryzanol (Orz), a steryl ferulate extracted from rice bran layer, exerts a wide spectrum of biological activities. In addition to its antioxidant activity, Orz is often associated with cholesterol-lowering, anti-inflammatory, anti-cancer and anti-diabetic effects. In recent years, the usefulness of Orz has been studied for the treatment of metabolic diseases, as it acts to ameliorate insulin activity, cholesterol metabolism, and associated chronic inflammation. Previous studies have shown the direct action of Orz when downregulating the expression of genes that encode proteins related to adiposity (CCAAT/enhancer binding proteins (C/EBPs)), inflammatory responses (nuclear factor kappa-B (NF-κB)), and metabolic syndrome (peroxisome proliferator-activated receptors (PPARs)). It is likely that this wide range of beneficial activities results from a complex network of interactions and signals triggered, and/or inhibited by its antioxidant properties. This review focuses on the significance of Orz in metabolic disorders, which feature remarkable oxidative imbalance, such as impaired glucose metabolism, obesity, and inflammation.

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“…Gambogic acid may ameliorate angiogenesis in mice with diabetic retinopathy ( Cui et al, 2018 ). Gamma-oryzanol was shown to be safe and effective in improving the conditions of diabetes mellitus in several animal studies ( Szcześniak et al, 2016 ). Octopamine may be involved in central blood pressure regulation ( Delbarre et al, 1982 ).…”

Section: Resultsmentioning

confidence: 99%

A Deep Learning-Based Approach for Identifying the Medicinal Uses of Plant-Derived Natural Compounds

et al. 2020

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Medicinal plants and their extracts have been used as important sources for drug discovery. In particular, plant-derived natural compounds, including phytochemicals, antioxidants, vitamins, and minerals, are gaining attention as they promote health and prevent disease. Although several in vitro methods have been developed to confirm the biological activities of natural compounds, there is still considerable room to reduce time and cost. To overcome these limitations, several in silico methods have been proposed for conducting large-scale analysis, but they are still limited in terms of dealing with incomplete and heterogeneous natural compound data. Here, we propose a deep learning-based approach to identify the medicinal uses of natural compounds by exploiting massive and heterogeneous drug and natural compound data. The rationale behind this approach is that deep learning can effectively utilize heterogeneous features to alleviate incomplete information. Based on latent knowledge, molecular interactions, and chemical property features, we generated 686 dimensional features for 4,507 natural compounds and 2,882 approved and investigational drugs. The deep learning model was trained using the generated features and verified drug indication information. When the features of natural compounds were applied as input to the trained model, potential efficacies were successfully predicted with high accuracy, sensitivity, and specificity.

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Investigation of nutriactive phytochemical – gamma‐oryzanol in experimental animal models

Cited by 43 publications

References 65 publications

γ-Oryzanol Improves Cognitive Function and Modulates Hippocampal Proteome in Mice

γ-Oryzanol Improves Cognitive Function and Modulates Hippocampal Proteome in Mice

Antioxidant Activity of γ-Oryzanol: A Complex Network of Interactions

A Deep Learning-Based Approach for Identifying the Medicinal Uses of Plant-Derived Natural Compounds

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