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Here, seeking to identify the possible role of sports in helping teenagers navigate the troubles associated with societal changes during a pandemic, the authors surveyed 50 adolescents to collect Beck Depression Inventory scores. They found that 9 out of students with severe depressions did not do sports, while no significant relationship between depressive symptoms and either gender or place of exercise was observed.

The authors look at malnutrition in children and how socio-economic factors impact this.

Here, recognizing that the immune response to cancer results in biomarkers that can be used to assess the immune status of cancer patients, the authors investigated the concentrations of key cytokines (TH1 and TH2 cytokines) in healthy controls and cancer patients. They identified significant changes in resting and activated cytokine profiles, suggesting that data of biomarkers such as these could serve as a starting point for further treatment with regard to a patient's specific immune profile.

In this study the authors look at the use of Indole 3 Carbinol as a treatment for Type II Diabetes finding that it may be an effective treatment.

The authors investigate how improper disposal of medication can be mitigated through community education efforts.

In this study, the impact of shutting down schools on the emotional aspects of high school students was analyzed using survey responses.

In this study, the authors investigate the effects of the COVID-19 pandemic on South Korean international school students' anxiety, well being and their learning habits.

In this study, potential physiological effects of Red 40 food dye, found in many different food products, are tested using Daphnia magna, a small freshwater crustacean.

Food spoilage leads to a significant loss in agricultural produce each year. Here, the authors investigate whether certain essential oils can protect against fungus-mediated spoilage of fruits and vegetables. Their results suggest that the compounds they tested might indeed inhibit fungal growth, at various temperatures, a promising result that could reduce food wasting.

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.