The authors looked at 5-FU resistant HeLa cells and the ability of an herbal extract to show anti-inflammatory properties.

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.

Here, recognizing the difficulty associated with tracking the progression of dementia, the authors used machine learning models to predict between the presence of cognitive normalcy, mild cognitive impairment, and Alzheimer's Disease, based on blood DNA methylation levels, sex, and age. With four machine learning models and two dataset dimensionality reduction methods they achieved an accuracy of 53.33%.

The water we use must be treated and cleaned before we release it back into the environment. Here, the authors investigate two new techniques for purifying dissolved impurities from waste water. Their findings may give rise to more cheaper and more efficient water treatment and help keep the planet greener.

With herbal plants providing an address to the adverse effects of oxidative stress found within the body, the authors of this article develop and assess a novel compound (“MAT20”) that blends three herbal plants for optimal oxidative stress relief.

A common form of Acne is caused by a species of bacterium called Cutibacterium acnes. By using a predictive algorithm and structural analysis, the authors identified 5 small molecules with high affinity to growth factors in Catibacterium acnes. This has potential implications for supplemental skincare products.

The authors propose a method to recycle Christmas tree needles into a non-toxic reducing agent for synthesizing copper nanoparticles.

In this study, three models are used to test the hypothesis that data-centric artificial intelligence (AI) will improve the performance of machine learning.

In this study, the authors investigate the antimicrobial effects of berberine and berberine analogs. Berberine is extracted from plants and is a naturally occurring alkaloid, and is also excited photochemically. Using three different assays, the authors tested whether these compounds would inhibit bacterial growth. They found that these compounds were antibacterial and even more so when used with photoirradiation. This study has important antibacterial implications.

In this study, a deep learning model is used to classify post-traumatic stress disorder patients through novel markers to assist in finding candidate biomarkers for the disorder.