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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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Formation and sticking of air bubbles in water in d-block containers

Gupta et al. | Jun 21, 2021

Formation and sticking of air bubbles in water in d-block containers

Bubbles! In this study, the authors investigate the effects that different materials, temperature, and distance have on the formation of water bubbles on the surface of copper and steel. They calculated mathematical relations based on the outcomes to better understand whether interstitial hydrogen present in the d-block metals form hydrogen bonds with the water bubbles to account for the structural and mechanical stability.

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Development of Diet-Induced Insulin Resistance in Drosophila melanogaster and Characterization of the Anti-Diabetic Effects of Resveratrol and Pterostilbene

Dhar et al. | Jul 02, 2018

Development of Diet-Induced Insulin Resistance in Drosophila melanogaster and Characterization of the Anti-Diabetic Effects of Resveratrol and Pterostilbene

Dhar and colleagues established a Type II diabetes mellitus (T2DM) model in fruit flies, using this model to induce insulin resistance and characterize the effects Resveratrol and Pterostilbene on a number of growth and activity metrics. Resveratrol and Pterostilbene treatment notably overturned the weight gain and glucose levels. The results of this study suggest that Drosophila can be utilized as a model organism to study T2DM and novel pharmacological treatments.

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Differential privacy in machine learning for traffic forecasting

Vinay et al. | Dec 21, 2022

Differential privacy in machine learning for traffic forecasting

In this paper, we measured the privacy budgets and utilities of different differentially private mechanisms combined with different machine learning models that forecast traffic congestion at future timestamps. We expected the ANNs combined with the Staircase mechanism to perform the best with every value in the privacy budget range, especially with the medium high values of the privacy budget. In this study, we used the Autoregressive Integrated Moving Average (ARIMA) and neural network models to forecast and then added differentially private Laplacian, Gaussian, and Staircase noise to our datasets. We tested two real traffic congestion datasets, experimented with the different models, and examined their utility for different privacy budgets. We found that a favorable combination for this application was neural networks with the Staircase mechanism. Our findings identify the optimal models when dealing with tricky time series forecasting and can be used in non-traffic applications like disease tracking and population growth.

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The Effect of the Human MeCP2 gene on Drosophila melanogaster behavior and p53 inhibition as a model for Rett Syndrome

Ganga et al. | Sep 07, 2020

The Effect of the Human <i>MeCP2</i> gene on <i>Drosophila melanogaster</i> behavior and p53 inhibition as a model for Rett Syndrome

In this study, the authors observe if the symptoms of Rett Syndrome, a neurodegenerative disease in humans, are reflected in Drosophila melanogaster. This was achieved by differentiating the behavior and physical aspects of wild-type flies from flies expressing the full-length MeCP2 gene and the mutated MeCP2 gene (R106W). After conducting these experiments, some of the Rett Syndrome symptoms were recapitulated in Drosophila, and a subset of those were partially ameliorated by the introduction of pifithrin-alpha.

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Assessing CDK5 as a Nanomotor for Chemotactic Drug Delivery

Jiang et al. | Sep 08, 2022

Assessing CDK5 as a Nanomotor for Chemotactic Drug Delivery

Enzyme chemotaxis is a thermodynamic phenomenon in which enzymes move along a substrate concentration gradient towards regions with higher substrate concentrations and can be used to steer nanovehicles towards targets along natural substrate concentrations. In patients with Alzheimer’s disease, a gradient of tau protein forms in the bloodstream. Tau protein is a substrate of the enzyme CDK5, which catalyzes the phosphorylation of tau protein and can travel using chemotaxis along tau protein gradients to increasing concentrations of tau and amyloid-beta proteins. The authors hypothesized that CDK5 would be able to overcome these barriers of Brownian motion and developed a quantitative model using Michaelis-Menten kinetics to define the necessary parameters to confirm and characterize CDK5’s chemotactic behavior to establish its utility in drug delivery and other applications.

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