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Quantifying natural recovery of dopamine deficits induced by chronic stress

Josyula et al. | Oct 27, 2025

Quantifying natural recovery of dopamine deficits induced by chronic stress
Image credit: Shawn Day

Here the authors investigated the natural recovery of stress-induced dopamine-related gene deficits in C. elegans by measuring the expression of cat-2 (dopamine biosynthesis) and sod-2 (oxidative stress) following exposure to starvation or hydrocortisone. They found that the reversibility of sod-2 and the expression of cat-2 were highly dependent on the type and severity of the stressor, suggesting that the body's natural ability to recover from dopamine dysfunction has biological limitations.

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Can the attributes of an app predict its rating?

Feng et al. | Jul 03, 2024

Can the attributes of an app predict its rating?
Image credit: Mika Baumeister

In this article the authors looked at different attributes of apps within the Google Play store to determine how those may impact the overall app rating out of five stars. They found that review count, amount of storage needed and when the app was last updated to be the most influential factors on an app's rating.

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Reddit v. Wall Street: Why Redditors beat Wall Street at its own game

Bhakar et al. | Sep 13, 2022

Reddit v. Wall Street: Why Redditors beat Wall Street at its own game

Here the authors investigated the motivation of a short squeeze of GameStop stock where users of the internet forum Reddit drove a sudden increase in GameStop stock price during the start of 2021. They relied on both qualitative and quantitative analyses where they tracked activity on the r/WallStreetBets subreddit in relation to mentions of GameStop. With these methods they found that while initially the short squeeze was driven by financial motivations, later on emotional motivations became more important. They suggest that social phenomena can be dynamic and evolve necessitating mixed method approaches to study them.

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Automated classification of nebulae using deep learning & machine learning for enhanced discovery

Nair et al. | Feb 01, 2024

Automated classification of nebulae using deep learning & machine learning for enhanced discovery

There are believed to be ~20,000 nebulae in the Milky Way Galaxy. However, humans have only cataloged ~1,800 of them even though we have gathered 1.3 million nebula images. Classification of nebulae is important as it helps scientists understand the chemical composition of a nebula which in turn helps them understand the material of the original star. Our research on nebulae classification aims to make the process of classifying new nebulae faster and more accurate using a hybrid of deep learning and machine learning techniques.

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Examining the impact of consecutive losses on gambling: When do we decide to quit?

Kim et al. | Apr 28, 2026

Examining the impact of consecutive losses on gambling: When do we decide to quit?
Image credit: Kim, Cragun, and Kim

This article explored the question of when do people decide to stop gambling and further tries to extrapolate why people stop gambling at that point. Their study showed that people tend to quit gambling after 4 consecutive losses, significantly more than 1-3 consecutive losses or a win previous to quitting. They also found that participants commonly quit at a point value approximately 5 points greater than or less than their starting balance. The authors concluded that these results may be important in understanding how to cut down on excessive gambling or in creating policies that make it easier for people to disengage from gambling.

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Interleukin family (IL-2 and IL-1β) as predictive biomarkers in Indian cancer patients: A proof of concept study

Parthasarathy et al. | Apr 03, 2023

Interleukin family (IL-2 and IL-1β) as predictive biomarkers in Indian cancer patients: A proof of concept study
Image credit: National Cancer Institute

Here, recognizing that the immune response to cancer results in biomarkers that can be used to assess the immune status of cancer patients, the authors investigated the concentrations of key cytokines (TH1 and TH2 cytokines) in healthy controls and cancer patients. They identified significant changes in resting and activated cytokine profiles, suggesting that data of biomarkers such as these could serve as a starting point for further treatment with regard to a patient's specific immune profile.

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Correlation between shutdowns and CO levels across the United States.

Gupta et al. | Dec 05, 2021

Correlation between shutdowns and CO levels across the United States.

Concerns regarding the rapid spread of Sars-CoV2 in early 2020 led company and local governmental officials in many states to ask people to work from home and avoid leaving their homes; measures commonly referred to as shutdowns. Here, the authors investigate how shutdowns affected carbon monoxide (CO) levels in 15 US states using publicly available data. Their results suggest that CO levels decreased as a result of these measures over the course of 2020, a trend which started to reverse after shutdowns ended.

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