The authors looked at the ability of berberine in combination with melatonin to have anticancer effects when tested in an in vitro cell model.
Read More...Novel anticancer effects of melatonin and berberine via signaling pathways in colorectal cancer and lymphoma
The authors looked at the ability of berberine in combination with melatonin to have anticancer effects when tested in an in vitro cell model.
Read More...Yeast catalysis of hydrogen peroxide as an enhanced chemical treatment method for harvested rainwater
The authors looked at different treatments to clean up rainwater collected at home. They found that chlorine treatment and treatment with hydrogen peroxide catalyzed by yeast showed similar potential for cleaning up contaminated rainwater, but that further studies are needed to better assess impact on specific contaminant levels still present.
Read More...Crystallization kinetics of vanillin thin films
In this study, the authors investigate the crystallization kinetics of vanillin thin films from a solution or a melt, as well as how a silane coating on the glass surface affects these properties.
Read More...High-performance liquid chromatography insight in pH-dependent hydrolysis of andrographolide acetonide
Andrographolide, a natural compound with anti-inflammatory, antidepressant, and anti-cancer properties, can be chemically modified by adding an acetonide group to form andrographolide acetonide, which is more potent and acts as a pH-dependent prodrug. Researchers investigated the hydrolysis of this acetonide group under mildly acidic conditions.
Read More...Monitoring drought using explainable statistical machine learning models
Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.
Read More...Adults’ attitudes toward non-alcoholic beer purchases and consumption by children and adolescents
Consumption of non-alcoholic beverages, like non-alcoholic beer, is growing in popularity in the United States. These beverages raise important societal questions, such as whether minors should be allowed to purchase or consume non-alcoholic beer. An and An investigate this issue by surveying adults to see if they support minors purchasing and consuming non-alcoholic beer.
Read More...Investigating cross-cultural emotional responses to world music under simulated hearing loss
The authors survey how emotional responses to music differ across cultures and the impact of hearing loss on these emotional responses.
Read More...Predictions of neural control deficits in elders with subjective memory complaints and Alzheimer’s disease
The authors compare neuroimaging datasets to identify potential new biomarkers for earlier detection of Alzheimer's disease.
Read More...Star anise and oregano essential oil: A comparative evaluation of antibacterial effect
The authors looked at the antibacterial effects of oregano and star anise essential oils against E. coli or S. epidermis. They found that oregano oil showed antibacterial activity against both E. coli or S. epidermis, and that star anise oil had a larger zone of inhibition in E. coli than tetracycline, a conventional antibiotic.
Read More...Automated classification of nebulae using deep learning & machine learning for enhanced discovery
There are believed to be ~20,000 nebulae in the Milky Way Galaxy. However, humans have only cataloged ~1,800 of them even though we have gathered 1.3 million nebula images. Classification of nebulae is important as it helps scientists understand the chemical composition of a nebula which in turn helps them understand the material of the original star. Our research on nebulae classification aims to make the process of classifying new nebulae faster and more accurate using a hybrid of deep learning and machine learning techniques.
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