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Herbal Extracts Alter Amyloid Beta Levels in SH-SY5Y Neuroblastoma Cells

Xu et al. | Feb 25, 2020

Herbal Extracts Alter Amyloid Beta Levels in SH-SY5Y Neuroblastoma Cells

Alzheimer’s disease (AD) is a type of dementia that affects more than 5.5 million Americans, and there are no approved treatments that can delay the advancement of the disease. In this work, Xu and Mitchell test the effects of various herbal extracts (bugleweed, hops, sassafras, and white camphor) on Aβ1-40 peptide levels in human neuroblastoma cells. Their results suggest that bugleweed may have the potential to reduce Aβ1-40 levels through its anti-inflammatory properties.

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Leveraging transfer learning with convolutional neural networks for cardiovascular disease detection

Chen et al. | May 25, 2026

Leveraging transfer learning with convolutional neural networks for cardiovascular disease detection
Image credit: Stephen Andrews

This study shows the efficacy of leveraging transfer learning, specifically from residual networks, to detect CVDs and possible signs of CVDs. The findings indicate that leveraging transfer learning from residual networks alongside medical professionals is a highly promising approach for CVD detection and diagnosis, warranting further investigation.

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A multi-dimensional analysis of NFL red zone efficiency

Kim et al. | Mar 16, 2026

A multi-dimensional analysis of NFL red zone efficiency
Image credit: Ben Hershey

Here the authors investigated the relationship between offensive play-calling styles and scoring success within the NFL's red zone by analyzing play-by-play data and expected points metrics. Their findings suggest that a conservative approach to play design and execution is more strongly associated with maximizing efficiency and point-value gains than aggressive strategies.

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The effect of Poisson sprinkling methods on causal sets in 1+1-dimensional flat spacetime

Deshpande et al. | Feb 14, 2025

The effect of Poisson sprinkling methods on causal sets in 1+1-dimensional flat spacetime
Image credit: Deshpande and Pitu et al. 2025

The causal set theory (CST) is a theory of the small-scale structure of spacetime, which provides a discrete approach to describing quantum gravity. Studying the properties of causal sets requires methods for constructing appropriate causal sets. The most commonly used approach is to perform a random sprinkling. However, there are different methods for sprinkling, and it is not clear how each commonly used method affects the results. We hypothesized that the methods would be statistically equivalent, but that some noticeable differences might occur, such as a more uniform distribution for the sub-interval sprinkling method compared to the direct sprinkling and edge bias compensation methods. We aimed to assess this hypothesis by analyzing the results of three different methods of sprinkling. For our analysis, we calculated distributions of the longest path length, interval size, and paths of various lengths for each sprinkling method. We found that the methods were statistically similar. However, one of the methods, sub-interval sprinkling, showed some slight advantages over the other two. These findings can serve as a point of reference for active researchers in the field of causal set theory, and is applicable to other research fields working with similar graphs.

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Nanotexturing as a method to reduce dust accumulation on solar panels

Choi et al. | Jan 30, 2025

Nanotexturing as a method to reduce dust accumulation on solar panels

Dust accumulation on solar panels can reduce electricity output by 20–50%, posing a major challenge for solar energy collection. Instead of altering panel design, we explored a simpler approach by modifying surface energy through nanotexturing, predicting that hydrophobic surfaces would repel both water and dust. This study found that treating glass and silicone surfaces with potassium hydroxide (KOH) for 13 and 10 minutes, respectively, created optimal nanotextures (445 nm for glass, 205 nm for silicone), significantly reducing dirt accumulation and improving solar energy capture.

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Qualitative tracking of human and animation motions reveals differences in their walking gaits

Baily et al. | Oct 04, 2024

Qualitative tracking of human and animation motions reveals differences in their walking gaits

In their attempt to evoke a greater emotional connection with viewers, animators have strived to replicate human movements in their animations. However, animation movements still appear distinct from human movements. With a focus on walking, we hypothesized that animations, unaffected by real external forces (e.g. gravity), would move with a universally distinct, gliding gait that is discernible from humans.

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Substance Abuse Transmission-Impact of Parental Exposure to Nicotine/Alcohol on Regenerated Planaria Offspring

Bennet et al. | Jul 02, 2024

Substance Abuse Transmission-Impact of Parental Exposure to Nicotine/Alcohol on Regenerated Planaria Offspring

The global mental health crisis has led to increased substance abuse among youth. Prescription drug abuse causes approximately 115 American deaths daily. Understanding intergenerational transmission of substance abuse is complex due to lengthy human studies and socioeconomic variables. Recent FDA guidelines mandate abuse liability testing for neuro-active drugs but overlook intergenerational transfer. Brown planaria, due to their nervous system development similarities with mammals, offer a novel model.

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