Browse Articles

This study investigates the presence of alkaloids in a variety of medicinal plants using the Marquis reagent. They reveal some surprising results and how useful the Marquis reagent is.

Fossil fuels are a limited resource; thus, it is important to explore new sources of energy. The authors examine the ability of switchgrass to produce ethanol and test the effects of pretreatment and grinding on ethanol yield.

DegS is an integral inner membrane protein in E. coli that helps break down misfolded proteins. When it is mutated, there is a large increase in the production of outer membrane vesicles (OMVs), which are thought to play a role in pathogenesis. This study used mutant strains of uropathogenic E. coli (UPEC) to characterize the role of DegS and OMVs on UPEC virulence.

Fat can be chemically altered during cooking through a process called lipid oxidation, which can have a negative impact on health. In this study, the authors measured the extracted fat in raw, fried and hard-boiled eggs and found that cooking eggs to a higher temperature resulted in a lower amount of extracted fat, indicating a greater amount of oxidized fat.

The authors used machine learning to predict the presence of anxiety and burnout in students based on facial expressions and demographic information.

The authors looked at the ability of different deep learning models to predict the presence of lung cancer from chest CT scans. They found that a pre-trained CNN model performed better than an autoencoder model.

This study investigates the effects of the PROTAC compound A1874 on CT26 colon carcinoma cells, focusing on its ability to degrade the protein BRD4 and reduce cell viability. While A1874 had previously shown effectiveness in other colon cancer cell lines, its impact on CT26 cells was unknown.

Building on previous work by earlier astronomers, the authors investigate the correlation between the density and size of celestial objects in the universe, including neutron stars, galaxies, and galaxy clusters.

Here the authors investigated air quality forecasting in India, comparing traditional time series models like SARIMA with deep learning models like LSTM. The research found that SARIMA models, which capture seasonal variations, outperform LSTM models in predicting Air Quality Index (AQI) levels across multiple Indian cities, supporting the hypothesis that simpler models can be more effective for this specific task.

Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.