Studying exoplanets, or planets that orbit a star other than the Sun, is critical to a greater understanding the formation of planets and how Earth's solar system differs from others. In this study the authors analyze the transit light curves of three hot Jupiter exoplanets to ultimately determine if and how these planets have changed since their discovery.
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Maternal mortality rates in the United States correlated with social determinants of health
This article helps in understanding the effect of various social determinants on maternal mortality in the United States. It explains the relationship between maternal mortality rates and factors like race, income, education, and health insurance access.
Read More...pH-dependent drug interactions with acid reducing agents
Some cancer treatments lose efficacy when combined with treatments for excessive stomach acid, due to the changes in the stomach environment caused by the stomach acid treatments. Lin and Lin investigate information on oral cancer drugs to see what information is available on interactions of these drugs.
Read More...Development of selective RAC1/KLRN inhibitors
Kalirin is a guanine nucleotide exchange factor (GEF) for the GTPase RAC1, linked to schizophrenia and Alzheimer’s Disease. It plays a crucial role in synaptic plasticity by regulating dendritic spine formation and actin cytoskeleton remodeling, which are essential for creating new synapses. Authors developed two novel compounds targeting kalirin, confirming that predictive modeling can indicate biological activity.
Read More...English learner status in Florida public schools is correlated with significantly lower graduation rates
The authors explore factors affecting graduation rates of students learning English as a second language across Florida counties.
Read More...Qualitative tracking of human and animation motions reveals differences in their walking gaits
In their attempt to evoke a greater emotional connection with viewers, animators have strived to replicate human movements in their animations. However, animation movements still appear distinct from human movements. With a focus on walking, we hypothesized that animations, unaffected by real external forces (e.g. gravity), would move with a universally distinct, gliding gait that is discernible from humans.
Read More...Do perceptions of beauty differ based on rates of racism, ethnicity, and ethnic generation?
The authors examine the relationships between race, racist beliefs, and perceptions of beauty across cultures and generations.
Read More...Parental exposure of cannabinoids THC and CBD reduces reproductive rates in Drosophila melanogaster
The authors looked at whether CBD and THC would decrease reproductive rates in a Drosophila melanogaster model. They found that CBD had a greater impact on reducing hatching rates than THC, and that THC resulted in unexpected mortalities.
Read More...Determining the relationship between unemployment and minimum wage in Turkey
The authors looked at the relationship between unemployment and minimum wage in Turkey (Türkiye). They found that there is a positive correlation between minimum wage and unemployment.
Read More...Predicting smoking status based on RNA sequencing data
Given an association between nicotine addiction and gene expression, we hypothesized that expression of genes commonly associated with smoking status would have variable expression between smokers and non-smokers. To test whether gene expression varies between smokers and non-smokers, we analyzed two publicly-available datasets that profiled RNA gene expression from brain (nucleus accumbens) and lung tissue taken from patients identified as smokers or non-smokers. We discovered statistically significant differences in expression of dozens of genes between smokers and non-smokers. To test whether gene expression can be used to predict whether a patient is a smoker or non-smoker, we used gene expression as the training data for a logistic regression or random forest classification model. The random forest classifier trained on lung tissue data showed the most robust results, with area under curve (AUC) values consistently between 0.82 and 0.93. Both models trained on nucleus accumbens data had poorer performance, with AUC values consistently between 0.65 and 0.7 when using random forest. These results suggest gene expression can be used to predict smoking status using traditional machine learning models. Additionally, based on our random forest model, we proposed KCNJ3 and TXLNGY as two candidate markers of smoking status. These findings, coupled with other genes identified in this study, present promising avenues for advancing applications related to the genetic foundation of smoking-related characteristics.
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