The authors test the antiproliferative and apoptosis-inducing properties of an extract created from a traditional Indian medicinal plant of the Amaranthus genus.
Read More...Cytotoxicity evaluation of Amaranthus extracts compared with AS20 on MCF-7 cancer cells
The authors test the antiproliferative and apoptosis-inducing properties of an extract created from a traditional Indian medicinal plant of the Amaranthus genus.
Read More...Myrtaceaes as antimicrobial agents against Staphylococcus aureus and Pseudomonas aeruginosa
In this study, the authors test new antimicrobials by measuring the ability of extracts from Australian-native Myrtaceae species to induce death of two bacteria S. aureus and P. aeruginosa.
Read More...Association of depression and suicidal ideation among adults with the use of H2 antagonists
In this study, the authors investigate associations between use of histamine H2 receptor antagonists and suicidal ideation in different age groups.
Read More...Investigating the Role of the Novel ESCRT-III Recruitment Factor CCDC11 in HIV Budding: A Potential Target for Antiviral Therapy
Acquired immunodeficiency syndrome (AIDS) is a life-threatening condition caused by the human immunodeficiency virus (HIV). In this work, Takemaru et al explored the role of Coiled-Coil Domain-Containing 11 (CCDC11) in HIV-1 budding. Their results suggest that CCDC11 is critical for efficient HIV-1 budding, potentially indicating CCDC11 a viable target for antiviral therapeutics without major side effects.
Read More...Effects of material advantage and space advantage on the Komodo and Stockfish chess engines
Chess engines, or computer programs built to play chess, outperform even the best human players. Kaushikan and Park investigate the inner workings of these chess engines by studying popular chess engines' evaluations of which side of a chess match is most likely to win, and how this is affected by the number of pieces and controlled squares on each side.
Read More...Mitigating microplastic exposure from water consumption in junior high students and teachers
Microplastics (MPs) are inorganic material that have been observed within items destined for human consumption, including water, and may pose a potential health hazard. Here we estimated the average amount of MPs junior high students and teachers consumed from different water sources and determined whether promoting awareness of microplastic (MP) exposure influenced choice of water source and potential MPs consumed.
Read More...Analyzing the effects of multiple adhesives on elastic collisions and energy loss in a Newton’s Cradle
The energy conservation in a system of objects in collision depends on the elasticity of the objects and environmental factors such as air resistance. One system that relies heavily on elasticity is the Newton’s Cradle. We aimed to determine the extent to which these adhesives serve to mitigate or worsen the chaotic movements and elastic collisions.
Read More...Seed priming with melatonin improves drought tolerance in maize
The authors test whether soaking maize seeds in a solution of melatonin improves seed germination and drought tolerance.
Read More...The effect of the pandemic on the behavior of junior high school students
Here, seeking to understand how the COVID-19 pandemic affected the social interactions of junior high school students, the authors surveyed students, teachers, and parents. Contrary to their initial hypotheses, the authors found positive correlation between increased virtual contact during social isolation and in-person conflict and disregard for social norms after the pandemic. While the authors identified the limitations of their study, they suggest that further research into the effect of online interactions is becoming increasingly important.
Read More...Evaluating machine learning algorithms to classify forest tree species through satellite imagery
Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.
Read More...Search articles by title, author name, or tags