Alzheimer’s disease (AD) is a common disease affecting 6 million people in the U.S., but no cure exists. To create therapy for AD, it is critical to detect amyloid-β protein in the brain at the early stage of AD because the accumulation of amyloid-β over 20 years is believed to cause memory impairment. However, it is difficult to examine amyloid-β in patients’ brains. In this study, we hypothesized that we could accurately predict the presence of amyloid-β using EEG data and machine learning.

In this article the authors created an interaction map of proteins involved in colorectal cancer to look for driver vs. non-driver genes. That is they wanted to see if they could determine what genes are more likely to drive the development and progression in colorectal cancer and which are present in altered states but not necessarily driving disease progression.

The authors analyze political endorsement patterns and impacts from the 2018 and 2020 midterm elections and find that such endorsements may be predictable based on the ideological and demographic factors of the endorser.

Does the overuse of plastic in Japan poses an ecological risk to marine species and their consumers? Using visual and chemical dissection, all fish in this study were found to have microplastics present in their gastrointestinal tract, including two species that are typically eaten whole in Japan. Overall, these results are concerning as previous studies have found that microplastics can carry persistent organic pollutants. It is presumed that the increasing consumption of microplastics will have negative implications on organ systems such as the liver, gut, and hormones.

In this study, the authors investigate the demographic indicators for voter shift between the 2016 and 2020 presidential elections based on demographic data put through a K-nearest neighbors classification algorithm and Principal Component Analysis.

Here the authors investigated the role of agricultural fertilizers as potential contributors to greenhouse gas emissions. In contrast to the typical investigations that consider microbiological processes, the authors considered purely chemical processes. Based on their results they found that as much as 20.41% of all CO₂ emission from land-based activities could be a result of mineral nitrogen fertilizers.

Here, the authors investigated alternative methods to irrigate plants based on the their identification that current irrigation systems waste a large amount of fresh water. They compared three different delivery methods for water: conventional sprinkler, underground cloth, and a perforated pipe embedded in the soil. They found the cloth method to save the most water, although plant growth was slightly less in comparison to plants watered with the sprinkler method or pipe method.

The authors investigate how well AI-detection machine learning models can detect real versus AI-generated art across different art styles.

The sequence of nitrogenous bases that make up the DNA of organisms can contain hidden mathematical sequences. Here the authors used BioPython, a programming tool, to find an organism that displays Gijswijt’s Sequence in its genome. In this manner they found that the common carp best displays Gijswijt’s Sequence in its genome.

Here, seeking to develop more efficient solar cells, the authors investigated photo-electrochemical (PEC) solar cells, specifically molybdenum diselenide (MoSe₂) based on its high resistance to corrosion. They found that the percentage efficiency of these PEC solar cells was proportional to light intensity^–0.9 and that performance was positively influenced by increasing the electrolyte volume. They suggest that studies such as these can lead to new insight into reaction-based solar cells.