Browse Articles

The COVID-19 pandemic demonstrated the depth and significance of healthcare inequality in the United States. Xiao, Xiao, and Gong examine healthcare disparities in the Richmond (Virginia) metropolitan area by analyzing whether people from disadvantaged populations must travel for longer to reach healthcare facilities.

PVC is a widely used plastic that poses harmful health hazards when burned. In this study, the authors ask whether or not burned PVC (PVC char) affects bacterial transformation.

In organic synthesis, protecting groups are derivatives of reactive functionalities that play a key role in ensuring chemoselectivity of chemical transformations. To protect alcohols and amines, acid-labile tert-butyloxycarbonyl protecting groups are often employed but are avoided when the substrate is acid-sensitive. Thus, orthogonal base-labile protecting groups have been in demand to enable selective deprotection and to preserve the reactivity of acid-sensitive substrates. To meet this demand, we present 4-nitrophenyl carbonates and carbamates as orthogonal base-labile protecting group strategies.

Osteosarcoma is a type of bone cancer that affects young adults and children. Early diagnosis of osteosarcoma is crucial to successful treatment. The current methods of diagnosis, which include imaging tests and biopsy, are time consuming and prone to human error. Hence, we used deep learning to extract patterns and detect osteosarcoma from histological images. We hypothesized that the combination of two different technologies (transfer learning and data augmentation) would improve the efficacy of osteosarcoma detection in histological images. The dataset used for the study consisted of histological images for osteosarcoma and was quite imbalanced as it contained very few images with tumors. Since transfer learning uses existing knowledge for the purpose of classification and detection, we hypothesized it would be proficient on such an imbalanced dataset. To further improve our learning, we used data augmentation to include variations in the dataset. We further evaluated the efficacy of different convolutional neural network models on this task. We obtained an accuracy of 91.18% using the transfer learning model MobileNetV2 as the base model with various geometric transformations, outperforming the state-of-the-art convolutional neural network based approach.

The authors set out to develop an electrochemical device that would have efficient and sustained carbon dioxide capture.

As the world moves towards more eco-friendly methods for chemical synthesis, there's a strong interest in employing enzymes in chemical synthetic processes. Here, the authors explore how the activity of enzymes such as trypsin, lipase and nattokinase is affected by the electronic effects of the substrate they are acting on.

This study aimed to predict and explain chaotic behavior in the Mandelbrot Set, one of the world’s most popular models of fractals and exhibitors of Chaos Theory. The authors hypothesized that repeatedly iterating the Mandelbrot Set’s characteristic function would give rise to a more intricate layout of the fractal and elliptical models that predict and highlight “hotspots” of chaos through their overlaps. The positive and negative results from this study may provide a new perspective on fractals and their chaotic nature, helping to solve problems involving chaotic phenomena.

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 a world where water shortage is becoming an increasing concern, and where population increase seems inevitable, food shortage is an overwhelming concern for many. In this paper, the authors aim to characterize a drought-resistant strain of A. thaliana, investigating the cause for its water resistance. These and similar studies help us learn how plants could be engineered to improve their ability to flourish in a changing climate.

This study applies Taft linear free-energy relationships to study kinetic trends in the enzymatic hydrolysis of sterically hindered substrates.