Browse Articles

Here, seeking to address the growing threat of multidrug-resistant bacteria (MDR). the authors used in silico virtual screening to target MDR Pseudomonas aeruginosa. They considered a key protein in its biosynthesis and virtually screened 20,000 candidates and 30 derivatives of brequinar. In the end, they identified a possible candidate with the highest degree of potential to inhibit the pathogen's lipid A synthesis.

Did the COVID-19 pandemic and travel restrictions improve air quality? The authors investigate this question in New York City using existing pollution data and forecasting trends.

In this study, the authors survey students and adults to better understand their basic financial knowledge and money saving skills to measure the extent of knowledge in each group and make comparisons between.

Diabetes is a serious worldwide epidemic that affects a growing portion of the population. While the most common method for testing blood glucose levels involves finger pricking, it is painful and inconvenient for patients. The authors test a non-invasive method to measure glucose levels from diabetic patients, and investigate whether the method is clinically accurate and universally applicable.

Previous studies have found that how a food item is labeled may influence people's liking of it. This study used a cookie taste test to investigate whether people's liking of a dessert item would be swayed by the use of different labels.

Recent observations by the “Extremely Metal-Poor Representatives Explored by the Subaru Survey” (EMPRESS) collaboration found normal deuterium levels but unexpectedly low helium-4, challenging current cosmological theories. This study used simulations with the PRyMordial package to test whether dark matter particles interacting with neutrinos in the early universe could explain the discrepancy.

The authors assessed the correlation between the stock, commodity, and consumer markets with the housing market.

This manuscript explores the performance of five different machine learning models in classifying brain tumors from a dataset of MRI scans. The authors find that several of the models showed >90% accuracy. Thus, the authors suggest that machine learning models demonstrate potential for effective implementation in clinical settings, including as a diagnostic tool that can be used to complement the expertise of neuroradiologists.

The authors demonstrate computationally that two types of nanoplastics can bind to estrogen receptor beta and potentially disrupt endocrine systems.

The authors test different machine learning algorithms to remove background noise from audio to help people with hearing loss differentiate between important sounds and distracting noise.