In this study, the authors test whether excess copper exposure has neurobehavioral effects on Hirudo verbana leeches.
Read More...Effects of copper sulfate exposure on the nervous system of the Hirudo verbana leech
In this study, the authors test whether excess copper exposure has neurobehavioral effects on Hirudo verbana leeches.
Read More...A novel CNN-based machine learning approach to identify skin cancers
In this study, the authors developed and assessed the accuracy of a machine learning algorithm to identify skin cancers using images of biopsies.
Read More...The influence of working memory on auditory category learning in the presence of visual stimuli
Here in an effort to better understand how our brains process and remember different categories of information, the authors assessed working memory capacity using an operation span task. They found that individuals with higher working memory capacity had higher overall higher task accuracy regardless of the type of category or the type of visual distractors they had to process. They suggest this may play a role in how some students may be less affected by distracting stimuli compared to others.
Read More...Anticancer, anti-inflammatory, and apoptotic activities of MAT20, a poly-herbal formulation.
Kashyap Jha et al. look at the formulation of MAT20, a crude extract of the moringa, amla, and tulsi leaves, as a potential complementary and alternative medicine. Using HeLa cells, they find MAT20 up-regulates expression of inflammation and cell cytotoxicity markers. Their data is important for understanding the anti-cancer and anti-inflammatory properties of MAT20.
Read More...Impact of light intensity and electrolyte volume on performance of photo-electrochemical (PEC) solar cell
Here, seeking to develop more efficient solar cells, the authors investigated photo-electrochemical (PEC) solar cells, specifically molybdenum diselenide (MoSe2) based on its high resistance to corrosion. They found that the percentage efficiency of these PEC solar cells was proportional to light intensity–0.9 and that performance was positively influenced by increasing the electrolyte volume. They suggest that studies such as these can lead to new insight into reaction-based solar cells.
Read More...Evaluating cinnamaldehyde as an antibacterial agent in a produce wash for leafy greens
Recognizing a growing demand for organic produce, the authors sought to investigate plant-based antibiotic solutions to meet growing consumer demand for safe produce and also meet microbial standards of the USDA. The authors investigated the use of cinnamaldehyde as an antibacterial again E. coli, finding that lettuce treated with cinnamaldehyde displayed significantly lower colony-forming units of E. coli when compared to lettuce treated with chlorine bleach.
Read More...TNF signaling pathway upregulation as a potential pharmaceutical target for cocaine-addicted individuals
In this article, the authors investigate the RNA expression differences between groups of chronic cocaine abusers and drug-free subjects.
Read More...Predicting asthma-related emergency department visits and hospitalizations with machine learning techniques
Seeking to investigate the effects of ambient pollutants on human respiratory health, here the authors used machine learning to examine asthma in Lost Angeles County, an area with substantial pollution. By using machine learning models and classification techniques, the authors identified that nitrogen dioxide and ozone levels were significantly correlated with asthma hospitalizations. Based on an identified seasonal surge in asthma hospitalizations, the authors suggest future directions to improve machine learning modeling to investigate these relationships.
Read More...Characterizing the evolution of antibiotic resistance in commercial Lactobacillus strains
In this study, the authors studied the ability for bacteria to develop antibiotic resistance over successive generations and modeled the trajectory to predict how antibiotic resistance is developed.
Read More...The Effect of Anubias barteri Plant Species on Limiting Freshwater Acidification
Research relating to freshwater acidification is minimal, so the impact of aquatic plants, Anubias barteri var. congensis and Anubias barteri var. nana, on minimizing changes in pH was explored in an ecosystem in Northern California. Creek water samples, with and without the aquatic plants, were exposed to dry ice to simulate carbon emissions and the pH was monitored over an eight-hour period. There was a 25% difference in the observed pH based on molar hydrogen ion concentration between the water samples with plants and those without plants, suggesting that aquatic plants have the potential to limit acidification to some extent. These findings can guide future research to explore the viable partial solution of aquatic plants in combating freshwater acidification.
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