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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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The effect of the pandemic on the behavior of junior high school students

Kong Grisius et al. | May 01, 2023

The effect of the pandemic on the behavior of junior high school students
Image credit: Chris Montgomery

Here, seeking to understand how the COVID-19 pandemic affected the social interactions of junior high school students, the authors surveyed students, teachers, and parents. Contrary to their initial hypotheses, the authors found positive correlation between increased virtual contact during social isolation and in-person conflict and disregard for social norms after the pandemic. While the authors identified the limitations of their study, they suggest that further research into the effect of online interactions is becoming increasingly important.

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Identification of microwave-related changes in tissue using an ultrasound scan

Shariff et al. | Apr 24, 2024

Identification of microwave-related changes in tissue using an ultrasound scan
Image credit: Shariff and Shariff 2024

Microwave energy (ME) is used in the medical field to denature protein structures, resulting in inactivation or destruction of abnormal cells. Identifying the extent of destruction of abnormal tissue (cancer tissue or tissue with abnormal electrical activity) is essential for accomplishing successful therapy and reducing collateral damage. Our study was an ex vivo assessment of the changes on ultrasound scans (US) in chicken tissue exposed to ME. We hypothesized that any changes in tissue structures would be recognized on the reflected ultrasound waves. Ultrasound scans of tissues change with exposure to microwaves with increasing reflection of ultrasound waves. With exposure to microwaves, surface level brightness on the ultrasound scans increases statistically significantly. The findings could be used in heat related (ME and radiofrequency) procedures where clinicians would be able to actively assess lesions in real-time. Further studies are required to assess changes in tissue during active exposure to different types of energies.

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The Bioactive Ingredients in Niuli Lactucis Agrestibus Possess Anticancer Effects

Zhu et al. | Sep 17, 2019

The Bioactive Ingredients in Niuli Lactucis Agrestibus Possess Anticancer Effects

In​ the​ field​ of​ medicine,​ natural​ treatments​ are​ becoming ​increasingly ​vital ​towards ​the ​cure ​of ​cancer. Zhu et al. wanted to investigate the effects of lettuce extract on cancer cell survival and proliferation. They used an adenocarcinoma cell line, COLO320DM, to determine whether crude extract from a lettuce species called Niuli​ Lactucis Agrestibus​ would affect cancer cell survival, migration, and proliferation. They found that Niuli extract inhibited cancer cell survival, increased expression of cell cycle inhibitors p21 and p27, and inhibited migration. However, Niuli extract did not have these effects on healthy cells. This work reveals important findings about a potential new source of anti-colorectal cancer compounds.

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Open Source RNN designed for text generation is capable of composing music similar to Baroque composers

Goel et al. | May 05, 2021

Open Source RNN designed for text generation is capable of composing music similar to Baroque composers

Recurrent neural networks (RNNs) are useful for text generation since they can generate outputs in the context of previous ones. Baroque music and language are similar, as every word or note exists in context with others, and they both follow strict rules. The authors hypothesized that if we represent music in a text format, an RNN designed to generate language could train on it and create music structurally similar to Bach’s. They found that the music generated by our RNN shared a similar structure with Bach’s music in the input dataset, while Bachbot’s outputs are significantly different from this experiment’s outputs and thus are less similar to Bach’s repertoire compared to our algorithm.

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