Here seeking to develop a method to diagnose, hypertrophic cardiomyopathy which can cause sudden cardiac death, the authors investigated the use of a convolutional neural network (CNN) and long short-term memory (LSTM) models to classify cardiac magnetic resonance and heart electrocardiogram scans. They found that the CNN model had a higher accuracy and precision and better other qualities, suggesting that machine learning models could be valuable tools to assist physicians in the diagnosis of hypertrophic cardiomyopathy.
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The effects of plasticizers on the mechanical properties and chemical composition of a gelatin biopolymer
Here, in an effort to identify alternatives to oil-based plastic, the authors sought to investigate the effects of plasticizers on the mechanical properties and chemical composition of gelatin bioplastic matrices. Through measurements of their tensile strength and elongation at break, along with FTIR spectroscopy, they identified 3% w/v polyethylene glycol film as having the best performance in their study..
Read More...Experimental characterization of thrust for ≤ 20 N-s impulse solid rocket motors
In this paper, Thomas et al. introduce a new, affordable way to study characteristics of rocket motors using small-scale rocket motors.
Read More...Investigating cross-cultural emotional responses to world music under simulated hearing loss
The authors survey how emotional responses to music differ across cultures and the impact of hearing loss on these emotional responses.
Read More...Transcriptomic profiling identifies differential gene expression associated with childhood abuse
Childhood abuse has severe and lasting effects throughout an individual's life, and may even have long-term biological effects on individuals who suffer it. To learn more about the effects of abuse in childhood, Li and Yearwood analyze gene expression data to look for genes differentially expressed genes in individuals with a history of childhood abuse.
Read More...Using Gravitational Waves to Determine if Primordial Black Holes are Sources of Dark Matter
In the quest to understand dark matter, scientists face a profound mystery. Two compelling candidates, Massive Compact Halo Objects (MACHOs) and Weakly Interacting Massive Particles (WIMPs), have emerged as potential sources. By analyzing gravitational waves from binary mergers involving these black holes, authors sought to determine if MACHOs could be the elusive dark matter.
Read More...The effects of age on quality of mental health during the COVID-19 pandemic
The impact of age on mental health is a crucial yet understudied aspect of public health. While mental health is gaining recognition as a vital component of overall well-being, its correlation with age remains largely unexplored. In Canada, where the median age has risen significantly over the past half-century, understanding this relationship becomes increasingly pertinent. Researchers hypothesized that older adults would exhibit lower rates of mental health disorders and report better perceived mental health due to increased emotional stability and maturity.
Read More...Mechanistic deconvolution of autoreduction in tetrazolium-based cell viability assays
Optical reporters like tetrazolium dyes, exemplified by 5-diphenyl tetrazolium bromide (MTT), are effective tools for quantifying cellular responses under experimental conditions. These dyes assess cell viability by producing brightly-colored formazan dyes when reduced inside active cells. However, certain small molecules, including reducing agents like ascorbic acid, cysteine, and glutathione (GSH), can interfere with MTT assays, potentially compromising accuracy.
Read More...Studying the effects of different anesthetics on quasi-periodic patterns in rat fMRI
The authors looked at the effects of commonly used anesthetics in rodents on brain activity (specifically quasi-periodic patterns). Understanding effects on brain activity is important for researchers to understand when choosing rodent models for disease.
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