Polo-like kinase 1 (Plk1) is a master regulator of mitosis, initiating key steps of cell cycle regulation, and its overexpression is associated with certain types of cancer. In this study, the authors carefully designed peptides that were able to bind to Plk1 at a location that is important for its proper localization and function. Future studies could further develop these peptides to selectively target Plk1 in cancer cells and induce mitotic arrest.

Here recognizing the growing amount of plastic waste in the oceans, the authors sought to develop and test laser imaging for the identification of waste in water. They found that while possible, limitations such as increasing depth and water turbidity result in increasing blurriness in laser images. While their image processing methods were somewhat insufficient they identified recent methods to use deep learning-based techniques as a potential avenue to viability for this method.

Anti-diabetic drugs like Metformin are known to increase gut permeability, and this has a negative impact on patient health. These authors hypothesized that this can be mitigated using purple sweet potato extract, which is high anthocyanin content, that feeds bacteria metabolism to decrease gut permeability.

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

In this study, the authors developed and assessed the accuracy of a machine learning algorithm to identify skin cancers using images of biopsies.

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.

The authors test the feasibility of using thermoelectric modules as a power source and as an air conditioner to decrease reliance on fossil fuels. The results showed that, at its peak, their battery generated 27% more power – in watts per square inch – than a solar panel, and the thermoelectric air conditioner operated despite an unsteady input voltage. The battery has incredible potential, especially if its peak power output can be maintained.

In this study, the authors investigate just how effectively paper towels can absorb different types of liquid and whether changing the properties of the towel (such as folding it) affects absorbance. Using variables of either different liquid types or the folded state of the paper towels, they used thorough approaches to make some important and very useful conclusions about optimal ways to use paper towels. This has important implications as we as a society continue to use more and more paper towels.

The traditional alert system in California consists of Wireless Emergency Alerts (WEAs), which lack location specificity, and sign-up-based technology which is limited by the number of sign ups. Those who do not have phones or have a silence option on their devices are most at risk from the current alert system. Here the authors developed cloud-enabled crisis connection for disaster alerts (CRISIS-CONNECT) to mitigate problems associated with the current alert system.

The authors investigate whether amylase or yeast had a more prominent role in determining the bioethanol concentration and bioethanol yield of banana samples. They hypothesized that amylase would have the most significant impact on the bioethanol yield and concentration of the samples. They found that while yeast is an essential component for producing bioethanol, the proportion of amylase supplied through a joint amylase-yeast mixture has a more significant impact on the bioethanol yield. This study provides a greater understanding of the mechanisms and implications involved in enzyme-based biofuel production, specifically of those pertaining to amylase and yeast.