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Phages Can Be More Effective and Specific Than Antibiotics in Combating Bacteria

Wu et al. | Feb 17, 2019

Phages Can Be More Effective and Specific Than Antibiotics in Combating Bacteria

Phage therapy has been suggested as an alternative to antibiotics because bacteria resistant to antibiotics may still be susceptible to phages. However, phages may have limited effectiveness in combating bacteria since bacteria possess several antiviral defense mechanisms and can quickly develop resistance to phages. In this study, Wu and Pinta compare the effectiveness and specificity of antibiotics and phages in combating bacteria. They found that T4 phages are more specific and effective in fighting or inhibiting both antibiotic-resistant and sensitive bacteria than antibiotics, suggesting that phage therapy can be developed as an efficient tool to combat antibiotic-resistant bacteria.

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Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Sirohi et al. | Sep 25, 2022

Risk assessment modeling for childhood stunting using automated machine learning and demographic analysis

Over the last few decades, childhood stunting has persisted as a major global challenge. This study hypothesized that TPTO (Tree-based Pipeline Optimization Tool), an AutoML (automated machine learning) tool, would outperform all pre-existing machine learning models and reveal the positive impact of economic prosperity, strong familial traits, and resource attainability on reducing stunting risk. Feature correlation plots revealed that maternal height, wealth indicators, and parental education were universally important features for determining stunting outcomes approximately two years after birth. These results help inform future research by highlighting how demographic, familial, and socio-economic conditions influence stunting and providing medical professionals with a deployable risk assessment tool for predicting childhood stunting.

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Characterizing Quorum Sensing-Induced Bioluminescence in Variable Volumes With Vibrio fischeri Using Computer Processing Methods

Abdel-Azim et al. | Jun 22, 2020

Characterizing Quorum Sensing-Induced Bioluminescence in Variable Volumes With <em>Vibrio fischeri</em> Using Computer Processing Methods

Understanding how bacteria respond to other bacteria could facilitate their ability to initiate and maintain their infectiousness. The phenomenon by which bacteria signal to each other via chemical signals is called quorum sensing, which could be targeted to deter bacterial infection in some cases if better understood. In this article, the authors study how a bacterium called V. fischeri uses quorum sensing to change bioluminescence, an easy readout that facilitates studying quorum sensing in this strain.

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Developing a Method to Remove Inorganic Arsenic from Rice with Natural Substances

Mukai et al. | Oct 27, 2020

Developing a Method to Remove Inorganic Arsenic from Rice with Natural Substances

In this study, the authors tested different approaches for removing arsenic from rice. Due to higher arsenic levels in water, some areas grow rice with higher levels as well. This is a health hazard and so developing methods to remove arsenic from the rice will be helpful to many. Using a rapid arsenic kit, the authors found that activated charcoal was the most effective at removing arsenic from rice.

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