![Analysis of the lung microbiome in cystic fibrosis patients using 16S sequencing](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBdThPIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--93c46fa461c039a2ff8a33afe7f643474034d5af/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJYW5CbkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--a3b53ba1a0f83efef18f6e75a8d4ce784384bee2/Figure2.jpg)
In this article the authors look at the lung microbiome in patients with cystic fibrosis to determine what the major bacterial species present are.
Read More...Analysis of the lung microbiome in cystic fibrosis patients using 16S sequencing
In this article the authors look at the lung microbiome in patients with cystic fibrosis to determine what the major bacterial species present are.
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To address whether odor sensory circuits are organized topographically, the authors investigate whether the neuronal responses to similar odors amongst different mice mapped similarly in brain.
Read More...The Effect of Different Concentrations of Iron on the Growth of Egeria (Elodea) Densa
Minerals such as iron are essential for life, but too much of a good thing can be poisonous. Here the authors investigate the effect of iron concentrations on the growth of an aquatic plant and find that supplementing small amounts of iron can help, but adding too much can be bad for the plant. These results should help inform decisions on allowable iron concentrations in the environment, aquatic farming, and even home aquariums.
Read More...Determining the best convolutional neural network for identifying tuberculosis and pneumonia in chest x-rays
To best identify tuberculosis and pneumonia diagnoses in chest x-rays, the authors compare different deep learning convolution neural networks.
Read More...Temperature and Precipitation Responses to a Stratospheric Aerosol Geoengineering Experiment Using the Community Climate System Model 4
We are changing our environment with steadily increasing carbon dioxide emissions, but we might be able to help. The authors here use a computer program called Community Climate System Model 4 to predict the effects of spraying small particles into the atmosphere to reflect away some of the sun's rays. The software predicts that this could reduce the amount of energy the Earth's atmosphere absorbs and may limit but will not completely counteract our carbon dioxide production.
Read More...Entropy-based subset selection principal component analysis for diabetes risk factor identification
In this article, the authors looked at developing a strategy that would allow for earlier diagnosis of Diabetes as that improves long-term outcomes. They were able to find that BMI, tricep skin fold thickness, and blood pressure are the risk factors with the highest accuracy in predicting diabetes risk.
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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...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...Groundwater prediction using artificial intelligence: Case study for Texas aquifers
Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.
Read More...Sports Are Not Colorblind: The Role of Race and Segregation in NFL Positions
In this study, the authors conducted a statistical investigation into the history of position-based racial segregation in the NFL. Specifically, they focused on the cornerback position, which they hypothesized would be occupied disproportionately by black players due to their historical stereotyping as more suitable for positions requiring extreme athletic ability. Using publicly available datasets on the demographics of NFL players over the past several decades, they confirmed their hypothesis that the cornerback position is skewed towards black players. They additionally discovered that, unlike in the quarterback position, this trend has shown no sign of decreasing over time.
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