Berberis aetnensis and B. libanotica : a comparative study on the chemical composition, inhibitory effect on key enzymes linked to Alzheimer's disease and antioxidant activity

2013 ◽  
Vol 65 (12) ◽  
pp. 1726-1735 ◽  
Author(s):  
Marco Bonesi ◽  
Monica R. Loizzo ◽  
Filomena Conforti ◽  
Nicodemo G. Passalacqua ◽  
Antoine Saab ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Antioxidant Activity ◽  
Chemical Composition ◽  
Comparative Study ◽  
Inhibitory Effect ◽  
Key Enzymes

Аnticholinesterase and antioxidant activity of new binary conjugates of (с)-carbolines

2019 ◽  
Vol 484 (1) ◽  
pp. 104-108
Author(s):  
G. F. Makhaeva ◽  
E. F. Shevtsova ◽  
N. P. Boltneva ◽  
N. V. Kovaleva ◽  
E. V. Rudakova ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Antioxidant Activity ◽  
Anticholinesterase Activity ◽  
Amyloid Aggregation ◽  
Varying Length ◽  
Β Amyloid ◽  
New Compounds

This study presents the synthesis of binary tetrohydro-γ-carbolines with ditriazol spacers of varying length, which exhibit anticholinesterase and antioxidant activity, as compared to the original Dimebon prototype. Anticholinesterase activity suggests the potential ability of the new compounds to block β-amyloid aggregation induced by anticholinesterase, making them promising candidates for further research preparations for the treatment of Alzheimer's disease. Particular attention should be paid to the conjugate with an intertriazol hexamethylene spacer, which can be regarded as the leading compound in this series.

scholarly journals Chemical Composition, In Vitro and In Silico Antioxidant Potential of Melissa officinalis subsp. officinalis Essential Oil

Antioxidants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1081
Author(s):  
Matilda Rădulescu ◽  
Călin Jianu ◽  
Alexandra Teodora Lukinich-Gruia ◽  
Marius Mioc ◽  
Alexandra Mioc ◽  
...  
Keyword(s):  
Antioxidant Activity ◽  
Chemical Composition ◽  
Essential Oil ◽  
In Silico ◽  
Antioxidant Properties ◽  
Radical Scavenging ◽  
Inhibitory Effect ◽  
Melissa Officinalis ◽  
Β Carotene

The investigation aimed to study the in vitro and in silico antioxidant properties of Melissa officinalis subsp. officinalis essential oil (MOEO). The chemical composition of MOEO was determined using GC–MS analysis. Among 36 compounds identified in MOEO, the main were beta-cubebene (27.66%), beta-caryophyllene (27.41%), alpha-cadinene (4.72%), caryophyllene oxide (4.09%), and alpha-cadinol (4.07%), respectively. In vitro antioxidant properties of MOEO have been studied in 2,2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) free-radical scavenging, and inhibition of β-carotene bleaching assays. The half-maximal inhibitory concentration (IC50) for the radical scavenging abilities of ABTS and DPPH were 1.225 ± 0.011 μg/mL and 14.015 ± 0.027 μg/mL, respectively, demonstrating good antioxidant activity. Moreover, MOEO exhibited a strong inhibitory effect (94.031 ± 0.082%) in the β-carotene bleaching assay by neutralizing hydroperoxides, responsible for the oxidation of highly unsaturated β-carotene. Furthermore, molecular docking showed that the MOEO components could exert an in vitro antioxidant activity through xanthine oxidoreductase inhibition. The most active structures are minor MOEO components (approximately 6%), among which the highest affinity for the target protein belongs to carvacrol.

A Comparative Study of Alzheimer Detection Techniques

2021 ◽  
Vol 9 (8) ◽  
pp. 2877-2883
Author(s):  
Adwait Patil
Keyword(s):  
Machine Learning ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Deep Learning ◽  
Comparative Study ◽  
Fuzzy System ◽  
Early Stage ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Detection Techniques

Abstract: Alzheimer’s disease is one of the neurodegenerative disorders. It initially starts with innocuous symptoms but gradually becomes severe. This disease is so dangerous because there is no treatment, the disease is detected but typically at a later stage. So it is important to detect Alzheimer at an early stage to counter the disease and for a probable recovery for the patient. There are various approaches currently used to detect symptoms of Alzheimer’s disease (AD) at an early stage. The fuzzy system approach is not widely used as it heavily depends on expert knowledge but is quite efficient in detecting AD as it provides a mathematical foundation for interpreting the human cognitive processes. Another more accurate and widely accepted approach is the machine learning detection of AD stages which uses machine learning algorithms like Support Vector Machines (SVMs) , Decision Tree , Random Forests to detect the stage depending on the data provided. The final approach is the Deep Learning approach using multi-modal data that combines image , genetic data and patient data using deep models and then uses the concatenated data to detect the AD stage more efficiently; this method is obscure as it requires huge volumes of data. This paper elaborates on all the three approaches and provides a comparative study about them and which method is more efficient for AD detection. Keywords: Alzheimer’s Disease (AD), Fuzzy System , Machine Learning , Deep Learning , Multimodal data

Silibinin-Albumin Nanoparticles: Characterization and Biological Evaluation Against Oxidative Stress-Stimulated Neurotoxicity Associated with Alzheimer’s Disease

2021 ◽  
Vol 17 (6) ◽  
pp. 1123-1130
Author(s):  
Qichen Pan ◽  
Yunchao Ban ◽  
Lijun Xu
Keyword(s):  
Oxidative Stress ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Antioxidant Activity ◽  
Cell Viability ◽  
Antioxidant Activities ◽  
Drug Loading ◽  
Biological Evaluation ◽  
Neural Cells ◽  
Nanoparticles Characterization

Alzheimer’s disease (AD) is strongly associated with oxidative stress which can damage neural cells. Silibinin has shown potential antioxidative effects. However, due to its low solubility in water, silibinin provides low biological activity and bioavailability. Therefore, to increase its pharmacological effects, silibilin was encapsulated into human serum albumin (HSA) nanoparticles and well-characterized by DLS and TEM techniques. The antioxidant activity of silibinin-HSA nanoparticles was evaluated on LPS-induced oxidative stress in neuron-like cells (SH-SY5Y) through MTT, antioxidant activity and apoptotic assay. It was shown that the mean diameter of HSA and silibinin-HSA nanoparticles were 88 and 105 nm, respectively with a drug loading of 24.08%, drug encapsulation rate of 94.72%, and the yield of silibinin-HSA nanoparticles of around 83.41% and the HSA nano-formulation released silibinin for 15 h. The results displayed that cell viability was reduced by LPS (10 μg/mL), who’s also determined to stimulate oxidative stress and apoptosis. However, co-incubation of cells with silibinin (50 μg/mL) or silibinin-HSA nanoparticles led to the recovery of cell viability, activation of SOD and CAT, increase of GSH content, and reduction of ROS level, Caspase-3 activity and fragmentation of DNA. It was also indicated that the neuroprotective and antioxidant activities of silibinin-HAS nanoparticles was greater than free silibinin, indicating that using albumin can be a potential formulation approach for improving the antioxidant efficacy of silibinin.

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