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Public Perception of the Effects of Artificial Sweeteners on Diabetes Based on YouTube Comments

Kim et al. | Jun 25, 2024

Public Perception of the Effects of Artificial Sweeteners on Diabetes Based on YouTube Comments
Image credit: The authors

Artificial sweeteners are rising in popularity, in part due to the influence of social media platforms like YouTube. However, YouTube commenters often repeat information about artificial sweeteners that is not supported by scientific research. To investigate how misinformation about sweeteners spreads through social media, Kim and Yoo conduct a content analysis of YouTube comments to reveal how many comments repeat misinformation about artificial sweeteners' effects.

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Ramifications of natural and artificial sweeteners on the gastrointestinal system

Cowen et al. | Jun 19, 2023

Ramifications of natural and artificial sweeteners on the gastrointestinal system

This study aimed to determine whether artificial sweeteners are harmful to the human microbiome by investigating two different bacteria found to be advantageous to the human gut, Escherichia coli and Bacillus coagulans. Results showed dramatic reduction in bacterial growth for agar plates containing two artificial sweeteners in comparison to two natural sweeteners. This led to the conclusion that both artificial sweeteners inhibit the growth of the two bacteria and warrants further study to determine if zero-sugar sweeteners may be worse for the human gut than natural sugar itself.

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The effect of sports on teenagers’ depression symptoms during the COVID-19 pandemic

Düzgezen et al. | Jun 12, 2023

The effect of sports on teenagers’ depression symptoms during the COVID-19 pandemic
Image credit: Izuddin Helmi Adnan

Here, seeking to identify the possible role of sports in helping teenagers navigate the troubles associated with societal changes during a pandemic, the authors surveyed 50 adolescents to collect Beck Depression Inventory scores. They found that 9 out of students with severe depressions did not do sports, while no significant relationship between depressive symptoms and either gender or place of exercise was observed.

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Prediction of preclinical Aβ deposit in Alzheimer’s disease mice using EEG and machine learning

Igarashi et al. | Nov 29, 2022

Prediction of preclinical Aβ deposit in Alzheimer’s disease mice using EEG and machine learning

Alzheimer’s disease (AD) is a common disease affecting 6 million people in the U.S., but no cure exists. To create therapy for AD, it is critical to detect amyloid-β protein in the brain at the early stage of AD because the accumulation of amyloid-β over 20 years is believed to cause memory impairment. However, it is difficult to examine amyloid-β in patients’ brains. In this study, we hypothesized that we could accurately predict the presence of amyloid-β using EEG data and machine learning.

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