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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.

Saccharomyces cerevisiae yeast is used to produce bioethanol, an alternative to fossil fuels. In this study, authors take advantage of this well studied yeast by genetically engineering them to increase fatty acid biosynthesis and culturing in a cost-effective wastewater based medium; potentially providing a sustainable alternative to petrochemicals.

In this study, the authors test the longevity of a anti-mite compound, amitraz, in commercially-sold strips and the age-dependent efficacy of these strips in preventing honey bee colony collapse by ectoparasitic mite Varroa destructor.

In this study, the authors test whether excess copper exposure has neurobehavioral effects on Hirudo verbana leeches.

This study investigates the dynamic reaction between liquid gallium and aluminum, which poses a challenge when using high-performance gallium-rich thermal interface materials for electronic cooling. Through the usage of in-situ microscopy, we show that while aluminum oxide coatings slow gallium-induced damage, nanometer-thick iridium coatings effectively prevent reaction and surface degradation at device-operating temperatures. These findings highlight a promising thermal-cooling architecture for extending the lifespan and reliability of high-power electronic heat dissipation systems.

Studying cut-resistant socks for hockey players

Here, recognizing the recognizing the growing threat of non-biodegradable plastic waste, the authors investigated the ability to use a modified enzyme identified in bacteria to decompose polyethylene terephthalate (PET). They used simulations to screen and identify an optimized enzyme based on machine learning models. Ultimately, they identified a potential mutant PETases capable of decomposing PET with improved thermal stability.

In this study, the authors investigate the effect of disorganization and messiness on high school students' ability to perform well on a standardized test.

Here the authors investigated the relationship between fitness-related social media and the high usage of performance-enhancing drugs (PEDs) specifically by men in the US age 18-35. In a survey with 149 participants they identified that young men that use fitness-related social media are more likely to use PEDs. Their results suggest the necessity to consider potential risk behaviors which may be related to social media consumption.

Machine learning and deep learning techniques can be used to predict the early onset of breast cancer. The main objective of this analysis was to determine whether machine learning algorithms can be used to predict the onset of breast cancer with more than 90% accuracy. Based on research with supervised machine learning algorithms, Gaussian Naïve Bayes, K Nearest Algorithm, Random Forest, and Logistic Regression were considered because they offer a wide variety of classification methods and also provide high accuracy and performance. We hypothesized that all these algorithms would provide accurate results, and Random Forest and Logistic Regression would provide better accuracy and performance than Naïve Bayes and K Nearest Neighbor.