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Modern artificial neural networks have been remarkably successful in various applications, from speech recognition to computer vision. However, it remains less clear whether they can implement abstract concepts, which are essential to generalization and understanding. To address this problem, the authors investigated the above vs. below task, a simple concept-based task that honeybees can solve, using a conventional neural network. They found that networks achieved 100% test accuracy when a visual target was presented below a black bar, however only 50% test accuracy when a visual target was presented below a reference shape.

Enzyme chemotaxis is a thermodynamic phenomenon in which enzymes move along a substrate concentration gradient towards regions with higher substrate concentrations and can be used to steer nanovehicles towards targets along natural substrate concentrations. In patients with Alzheimer’s disease, a gradient of tau protein forms in the bloodstream. Tau protein is a substrate of the enzyme CDK5, which catalyzes the phosphorylation of tau protein and can travel using chemotaxis along tau protein gradients to increasing concentrations of tau and amyloid-beta proteins. The authors hypothesized that CDK5 would be able to overcome these barriers of Brownian motion and developed a quantitative model using Michaelis-Menten kinetics to define the necessary parameters to confirm and characterize CDK5’s chemotactic behavior to establish its utility in drug delivery and other applications.

Recognizing the need for a method to filter microplastics from polluted water the authors sought to use nonpolar solvents, palm oil and palm kernel oil, to filter microplastics out of model seawater. By relying on the separation of polar and nonpolar solvents followed by freezing the nonpolar solvent, they reported that microplastics could be extracted with percentages ranging from 96.2% to 94.2%. They also provided an estimation to use this method as part of container ships to clean the Pacific Ocean of microplastics.

In this article, the authors explored the locomotory movement of Euglena sp. and Tetrahymena pyriformis in response to light. Such research bears relevance to the migration and distribution patterns of both T. pyriformis and Euglena as they differ in their method of finding sustenance in their native environments. With little previous research done on the exploration of a potential response to photostimulation enacted by T. pyriformis, the authors found that T. pyriformis do not bias in distribution towards areas of light - unlike Euglena, which displayed an increased prevalence in areas of light.

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.

Here, the authors considered the stretching behavior of rubber bands by exposing the rubber bands to increasing loads and measuring their stretch response. They found that a linear stretch response was observed for intermediate loading steps, but this behavior was lost at lower or higher loads, deviating from Hooke's Law. The authors suggest that studies such as these can be used to evaluate other visco-elastic structures.

In this study, high school students and teachers responded to a survey consisting of Likert-type scale, multiple-choice, and open-ended questions regarding various aspects of remote instruction. After analyzing the data collected, they found that remote learning impacted high school students academically and socially. Students took longer to complete assignments, and both students and teachers felt that students do not learn as much in remote learning compared to in-person instruction. However, most high school students demonstrated a comprehensive understanding of the topics, and an overall negative impact on students' grades was not detected.

Infections caused by antibiotic resistance are a leading issue faced by the medical field. The authors studied the antibacterial effectiveness of turmeric against gram-positive Staphylococcus epidermidis using antibiotic sensitivity disks. They infused blank antibiotic sensitivity disks with a 5% concentrated solution of turmeric and placed them on agar plates inoculated with bacteria. Overall, there was no measurable ZOI surrounding the turmeric disk so the measurements for all trials were 0 cm, suggesting that turmeric at a 5% concentration is not an effective antibacterial against S. epidermidis.

Here, through protein-ligand docking, the authors investigated the effect of the interaction of emodin with serine/threonine kinases, a subclass of kinases that is overexpressed in many cancers, which is implicated in phosphorylation cascades. Through molecular dynamics theyfound that emodin forms favorable interactions with chitosan and chitosan PEG (polyethylene glycol) copolymers, which could aid in loading drugs into nanoparticles (NPs) for targeted delivery to cancerous tissue. Both polymers demonstrated reasonable entrapment efficiencies, which encourages experimental exploration of emodin through targeted drug delivery vehicles and their anticancer activity.

Regenerative medicine has become a mainstay in recent times, and employing stem cells to treat several degenerative, inflammatory conditions has resulted in very promising outcomes. These forms of cell-based therapies are novel approaches to existing treatment modalities. In this study, the authors compared the concentrations of the cytokines PDGF, IL-8, and VEGF between conditioned and spent media of mesenchymal stem cells (MSCs) to evaluate their potential therapeutic properties for wound healing in inflammatory conditions. They hypothesized that conditioned media contains higher concentrations of wound healing cytokines compared to spent media. The authors found that while IL-8 and VEGF were present in highest concentrations in conditioned media, PDGF was present in maximal amounts in spent media.