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The effects of stress on the bacterial community associated with the sea anemone Diadumene lineata

Cahill et al. | Feb 15, 2021

The effects of stress on the bacterial community associated with the sea anemone Diadumene lineata

In healthy ecosystems, organisms interact in a relationship that helps maintain one another's existence. Stress can disrupt this interaction, compromising the survival of some of the members of such relationships. Here, the authors investigate the effect of stress on the interaction between anemones and their microbiome. Their study suggests that stress changes the composition of the surface microbiome of the anemone D. lineata, which is accompanied by an increase in mucus secretion. Future research into the composition of this stress-induced mucus might reveal useful antimicrobial properties.

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A novel filtration model for microplastics using natural oils and its application to the environment

Park et al. | Jun 27, 2022

A novel filtration model for microplastics using natural oils and its application to the environment

Recognizing the need for a method to filter microplastics from polluted water the authors sought to use nonpolar solvents, palm oil and palm kernel oil, to filter microplastics out of model seawater. By relying on the separation of polar and nonpolar solvents followed by freezing the nonpolar solvent, they reported that microplastics could be extracted with percentages ranging from 96.2% to 94.2%. They also provided an estimation to use this method as part of container ships to clean the Pacific Ocean of microplastics.

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Propagation of representation bias in machine learning

Dass-Vattam et al. | Jun 10, 2021

Propagation of representation bias in machine learning

Using facial recognition as a use-case scenario, we attempt to identify sources of bias in a model developed using transfer learning. To achieve this task, we developed a model based on a pre-trained facial recognition model, and scrutinized the accuracy of the model’s image classification against factors such as age, gender, and race to observe whether or not the model performed better on some demographic groups than others. By identifying the bias and finding potential sources of bias, his work contributes a unique technical perspective from the view of a small scale developer to emerging discussions of accountability and transparency in AI.

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Racemic serine is less soluble than pure enantiomers due to stronger intermolecular hydrogen bonds

Ranka et al. | Nov 18, 2021

Racemic serine is less soluble than pure enantiomers due to stronger intermolecular hydrogen bonds

Seeking to develop a better understanding of the chemical and physical properties of amino acids that compose proteins, here the authors investigated the unusual relative insolubility of racemic mixtures of D- and L-serine compared to the solubility of pure D- or L-serine. The authors used a combination of microscopy and temperature measurements alongside previous X-ray diffraction studies to conclude that racemic DL-serine crystals consist of comparatively stronger hydrogen bond interactions compared to crystals of pure enantiomers. These stronger interactions were found to result in the unique release of heat during the crystallization of racemic mixtures.

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