The global mental health crisis has led to increased substance abuse among youth. Prescription drug abuse causes approximately 115 American deaths daily. Understanding intergenerational transmission of substance abuse is complex due to lengthy human studies and socioeconomic variables. Recent FDA guidelines mandate abuse liability testing for neuro-active drugs but overlook intergenerational transfer. Brown planaria, due to their nervous system development similarities with mammals, offer a novel model.
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The frequency and psychological effects of name mispronunciation in an independent school
The authors survey high school students regarding the frequency of microaggressions such as name mispronunciation.
Read More...Analyzing breath sounds by using deep learning in diagnosing bronchial blockages with artificial lung
Many common respiratory illnesses like bronchitis, asthma, and chronic obstructive pulmonary disease (COPD) lead to bronchial inflammation and, subsequently, a blockage. However, there are many difficulties in measuring the severity of the blockage. A numeric metric to determine the degree of the blockage severity is necessary. To tackle this demand, we aimed to develop a novel human respiratory model and design a deep-learning program that can constantly monitor and report bronchial blockage by recording breath sounds in a non-intrusive way.
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.
Read More...Modeling the heart’s reaction to narrow blood vessels
Cardiovascular diseases are the largest cause of death globally, making it a critical area of focus. The circulatory system is required to make the heart function. One component of this system is blood vessels, which is the focus of our study. Our work aims to demonstrate the numeric relationship between a blood vessel's diameter and the number of pumps needed to transport blood.
Read More...Predicting the Instance of Breast Cancer within Patients using a Convolutional Neural Network
Using a convolution neural network, these authors show machine learning can clinically diagnose breast cancer with high accuracy.
Read More...Role of bacterial flagella in bacterial adhesion of Escherichia coli to glass surface
In this study, the authors investigate the effects that flagella have on E. coli's ability to adhere to glass surfaces.
Read More...Reducing PMA-induced COX-2 expression using a herbal formulation in MCF-7 breast cancer cells
In this study, the authors investigate the effect of a herbal formulation on Cyclooxygenase-2 (COX-2) expression in cancer cells. High levels of COX-2 correlates with worsened cancer outcomes and the authors hypothesize that the formulation will inhibit COX-2 levels.
Read More...Behavioral Longevity: The Impact of Smoking, Alcohol Consumption, and Obesity on Life Expectancy
In this article, the authors look into what is already known about the factor affecting longevity and determine the importance of behavioral factors including alcohol consumption, smoking, and obesity on longevity. The authors quantify data from over 150 countries and, interestingly, find that the impact each factor has on longevity is at least in part dependent on the country's economic development status. Overall, they conclude that an average person’s life expectancy can increase by more than 3 years if smoking and alcohol consumption is reduced by a half and weight is decreased by 10%.
Read More...Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes
People with Type One diabetes often rely on Continuous Blood Glucose Monitors (CGMs) to track their blood glucose and manage their condition. Researchers are now working to help people with Type One diabetes more easily monitor their health by developing models that will future blood glucose levels based on CGM readings. Jalla and Ghanta tackle this issue by exploring the use of AI models to forecast blood glucose levels with CGM data.
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