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Impact of gadodiamide (Omniscan) on a beef liver catalase ex vivo model

Hirsch et al. | Mar 10, 2023

Impact of gadodiamide (Omniscan) on a beef liver catalase <em>ex vivo</em> model
Image credit: Marcelo Leal

Here, seeking to better understand the effects of gadolinium-based contrast agents, dyes typically used for MRI scans, the authors evaluated the activity of catalase found in beef liver both with and without gadodiamide when exposed to hydrogen peroxide. They found that gadioamide did not significantly inhibit catalase's activity, attributing this lack of effects to the chelating agent found in gadodiamide.

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Can the nucleotide content of a DNA sequence predict the sequence accessibility?

Balachandran et al. | Mar 10, 2023

Can the nucleotide content of a DNA sequence predict the sequence accessibility?
Image credit: Warren Umoh

Sequence accessibility is an important factor affecting gene expression. Sequence accessibility or openness impacts the likelihood that a gene is transcribed and translated into a protein and performs functions and manifests traits. There are many potential factors that affect the accessibility of a gene. In this study, our hypothesis was that the content of nucleotides in a genetic sequence predicts its accessibility. Using a machine learning linear regression model, we studied the relationship between nucleotide content and accessibility.

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Toxicity of aminomethylphosphonic acid via the Wnt signaling pathway as a novel mechanism

Zhuang et al. | Mar 08, 2023

Toxicity of aminomethylphosphonic acid via the Wnt signaling pathway as a novel mechanism
Image credit: Image credit: Dapur Melodi

The Wnt signaling pathway, known to coordinate important aspects of cellular homeostasis ranging from differentiation, proliferation, migration, and much more, is dysregulated in many human diseases. This study demonstrates that aminomethylphosphonic acid, which is the main metabolite found in the common herbicide Glyphosate, is toxic to planaria and capable of binding to canonical Wnt proteins.

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Tomato disease identification with shallow convolutional neural networks

Trinh et al. | Mar 03, 2023

Tomato disease identification with shallow convolutional neural networks

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

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Employee resignation study in Fairfax County

Zhang et al. | Mar 03, 2023

Employee resignation study in Fairfax County

In this study, the authors address potential reasons why employees may voluntarily resign. This is in response to the currently observed economic trend The Great Resignation. Through analysis of federal and local government data along with survey results from Fairfax County, they concluded that adding additional benefits will help companies retain talented empolyees.

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