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The characterization of quorum sensing trajectories of Vibrio fischeri using longitudinal data analytics

Abdel-Azim et al. | Dec 16, 2023

The characterization of quorum sensing trajectories of <i>Vibrio fischeri</i> using longitudinal data analytics

Quorum sensing (QS) is the process in which bacteria recognize and respond to the surrounding cell density, and it can be inhibited by certain antimicrobial substances. This study showed that illumination intensity data is insufficient for evaluating QS activity without proper statistical modeling. It concluded that modeling illumination intensity through time provides a more accurate evaluation of QS activity than conventional cross-sectional analysis.

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A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood

Adami et al. | Sep 20, 2023

A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood
Image credit: National Cancer Institute

Here, recognizing the difficulty associated with tracking the progression of dementia, the authors used machine learning models to predict between the presence of cognitive normalcy, mild cognitive impairment, and Alzheimer's Disease, based on blood DNA methylation levels, sex, and age. With four machine learning models and two dataset dimensionality reduction methods they achieved an accuracy of 53.33%.

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Rhizosphere metagenome analysis and wet-lab approach to derive optimal strategy for lead remediation in situ

Bhat et al. | Jul 18, 2023

Rhizosphere metagenome analysis and wet-lab approach to derive optimal strategy for lead remediation <i>in situ</i>
Image credit: Karolina Grabowska

The Environmental Protection Agency (EPA) reports a significant number of heavy metal-contaminated sites across the United States. To address this public health concern, rhizoremediation using microbes has emerged as a promising solution. Here, a combination of soil microbes were inoculated in the rhizosphere in soil contaminated with 500 parts per million (ppm) of lead. Results showed rhizoremediation is an effective bioremediation strategy and may increase crop productivity by converting nonarable lands into arable lands.

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Antibacterial properties of household spices and toothpaste against oral bacteria

Toliver et al. | Apr 24, 2023

Antibacterial properties of household spices and toothpaste against oral bacteria

Bacteria cause tooth decay, plaque, bad breath, and other diseases. Despite being cleaned with water and toothpaste, oral bacteria live on our toothbrushes. Bacterial growth has been shown to be inhibited by different toothpastes and common household spices. This study tested how different toothpastes and common household spices, including cinnamon, cumin, nutmeg, and ground white pepper, can inhibit bacteria from growing on toothbrushes

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