Browse Articles

Here, seeking to better understand the genetic associations underlying non-small cell lung cancer, the authors screened hundreds of genes, identifying that KCNMB2 upregulation was significantly correlated with poor prognoses in lung cancer patients. Based on this, they used small interfering RNA to decrease the expression of KCNMB2 in A549 lung cancer cells, finding decreased cell proliferation and increased lung cancer cell death. They suggest this could lead to a new potential target for lung cancer therapies.

Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are allosteric inhibitors that bind to the HIV reverse transcriptase and prevent replication. Indolyl aryl sulfones (IAS) and IAS derivatives have been found to be highly effective against mutant strains of HIV-1 reverse transcriptase. Here, we analyzed molecules designed using aryl sulfone scaffolds paired to cyclic compounds as potential NNRTIs through the computational design and docking of 100 novel NNRTI candidates. Moreover, we explored the specific combinations of functional groups and aryl sulfones that resulted in the NNRTI candidates with the strongest binding affinity while testing all compounds for carcinogenicity. We hypothesized that the combination of an IAS scaffold and pyrimidine would produce the compounds with the best binding affinity. Our hypothesis was correct as the series of molecules with an IAS scaffold and pyrimidine exhibited the best average binding affinity. Additionally, this study found 32 molecules designed in this procedure with higher or equal binding affinities to the previously successful IAS derivative 5-bromo-3-[(3,5-dimethylphenyl)sulfonyl]indole-2-carboxyamide when docked to HIV-1 reverse transcriptase.

The authors looked at non-natural factors that influenced the spread rate of fire ants in multiple cities in China.

Organic and non-organic contaminants in tap water have been linked to adverse health effects. Tap water is a major source of lead, which is neurotoxic and poses a major health risk, particularly to children and pregnant women. Using publicly available annual water quality reports data for the state of Missouri, the authors show that communities with lower median household income and lower per capita incomes had significantly higher lead levels in their tap water.

The discussion surrounding self-medication with non-prescription medicines has gained significance in healthcare and public health, particularly given the global increase in consumption of non-prescription drugs. This study aimed to examine the association between the frequency of general practitioner (GP) consultations and the proportion of economic resources spent on OTC medicine.

This study aimed to obtain an optimal non-antibiotic method to suppress the growth of pathogenic bacteria within the body. The two-fold purpose of this project was to determine which combination of bacteria would result in the most biofilm formation and then to assess the effect of ayurvedic plant extracts on the biofilm. The results show that the addition of a plant extract can affect the biofilm growth of a bacteria combination. The applications of this study can be used to design probiotic supplements with added beneficial plant extracts.

We know relatively little about how vegan diets and non-vegan diets compare when it comes to the gut microbiome. Gollamudi and Gollamudi tackle this challenge by investigating how changes in a participant's diet affected the diversity of their intestinal microbiome.

The authors test the durability of synthetic versus non-synthetic fabrics though loose thread counts, color fade over time, and shrinkage tests.

The authors propose a method to recycle Christmas tree needles into a non-toxic reducing agent for synthesizing copper nanoparticles.

Here, recognizing the recognizing the growing threat of non-biodegradable plastic waste, the authors investigated the ability to use a modified enzyme identified in bacteria to decompose polyethylene terephthalate (PET). They used simulations to screen and identify an optimized enzyme based on machine learning models. Ultimately, they identified a potential mutant PETases capable of decomposing PET with improved thermal stability.