The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.
Read More...Decline in vocabulary richness in individuals with Alzheimer's disease
The authors looked at how vocabulary is impacted in Alzheimer's disease and whether it could be used a predictor of disease onset.
Read More...Modular mimics of neuroactive alkaloids - design, synthesis, and cholinesterase inhibitory activity of rivastigmine analogs
Naturally occurring neuroactive alkaloids are often studied for their potential to treat Neurological diseases. This team of students study Rivastigmine, a potent cholinesterase inhibitor that is a synthetic analog of physostigmine, which comes from the Calabar bean plant Physostigma venenosum. By comparing the effects of optimized synthetic analogs to the naturally occurring alkaloid, they determine the most favorable analog for inhibition of acetylcholinesterase (AChE), the enzyme that breaks down the neurotransmitter acetylcholine (ACh) to terminate neuronal transmission and signaling between synapses.
Read More...Student work preferences: Typing or handwriting in the digital era
The authors survey high school students regarding preferences for taking notes by hand versus typing.
Read More...Astragalus membranaceus Root Concentration and Exposure Time: Role in Heat Stress Diminution in C. elegans
In this study, the authors investigated the biological mechanism underlying the actions of a traditional medicinal plant, Astragalus membranaceus. Using C. elegans as an experimental model, they tested the effects of AM root on heat stress responses. Their results suggest that AM root extract may enhance the activity of endogenous pathways that mediate cellular responses to heat stress.
Read More...The impact of conceptual versus memorization-based teaching methods on student performance
The authors looked at how students performed on standardized tests when they were taught material via memorization vs. conceptual based approaches.
Read More...Evaluating the feasibility of SMILES-based autoencoders for drug discovery
The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.
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