In this study, the impact of shutting down schools on the emotional aspects of high school students was analyzed using survey responses.
Read More...COVID-19 pandemic impact on emotional aspects of high school students
In this study, the impact of shutting down schools on the emotional aspects of high school students was analyzed using survey responses.
Read More...siRNA-dependent KCNMB2 silencing inhibits lung cancer cell proliferation and promotes cell death
Here, seeking to better understand the genetic associations underlying non-small cell lung cancer, the authors screened hundreds of genes, identifying that KCNMB2 upregulation was significantly correlated with poor prognoses in lung cancer patients. Based on this, they used small interfering RNA to decrease the expression of KCNMB2 in A549 lung cancer cells, finding decreased cell proliferation and increased lung cancer cell death. They suggest this could lead to a new potential target for lung cancer therapies.
Read More...Evolution of Neuroplastin-65
Human intelligence is correlated with variation in the protein neuroplastin-65, which is encoded by the NPTN gene. The authors examine the evolution of this gene across different animal species.
Read More...Identification of a Free Radical Scavenger as an Additive for Lung Transplant Preservation Solution to Inhibit Coagulative Necrosis and Extend Organ Preservation
During transfer of organs from a donor to a patient, the organs deteriorate in part due to damage by free radicals. Application of antioxidant solutions could extend organ preservation times. The authors found that vitamin E and butylated hydroxytoluene seemed to be most effective in arresting cell damage of a bovine lung.
Read More...Breaking the Ice: A Scientific Take on the Ice Melting Abilities of Household Salts
The use of salt to melt ice is a common and important practice to keep roadways safe during winter months. However, various subtypes of salt differ in their chemical and physical properties, as well as their environmental impact. In this study, the authors measure the effectiveness of different salts at disrupting ice structures and identify calcium chloride as the most effective.
Read More...The Impact of Age on Post-Concussive Symptoms: A Comparative Study of Symptoms Related and Not Related to the Default Mode Network
The Default Mode Network (DMN) is a network of connected brain regions that are active when the brain is not focused on external tasks. Minor brain injuries, such as concussions, can affect this network and manifest symptoms. In this study, the authors examined correlations between DMN age and post-concussion symptoms in previously concussed individuals and healthy controls.
Read More...Variations in Heat Absorption and Release of Earth Surfaces During Fall in Laramie, Wyoming
Here the authors investigate the contributions of man-made surfaces in Laramie, Wyoming to the Urban Heat Island (UHI) effect. Heat absorption and release by five surfaces were measured in the autumn of 2018. By recording temperatures of man-made and natural surfaces at early morning, mid-afternoon, and evening using an infrared thermometer, the authors determined that man-made surfaces retained more heat in fall than natural surfaces.
Read More...Functional Network Connectivity: Possible Biomarker for Autism Spectrum Disorders (ASD)
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder and is difficult to diagnose in young children. Here magnetoencephalography was used to compare the brain activity in patients with ASD to patients in a control group. The results show that patients with ASD have a high level of activity in different areas of the brain than those in the control group.
Read More...An explainable model for content moderation
The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.
Read More...Statistical models for identifying missing and unclear signs of the Indus script
This study utilizes machine learning models to predict missing and unclear signs from the Indus script, a writing system from an ancient civilization in the Indian subcontinent.
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