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Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Dao et al. | Jun 27, 2021

Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Engineered bacteria that degrade oil are currently being considered as a safe option for the treatment of oil spills. For this approach to be successful, the bacteria must effectively express oil-degrading genes they uptake as part of an external genoming vehicle called a "plasmid". Using a computational approach, the authors investigate plasmid-bacterium compatibility to find pairs that ensure high levels of gene expression.

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Computational Structure-Activity Relationship (SAR) of Berberine Analogs in Double-Stranded and G-Quadruplex DNA Binding Reveals Both Position and Target Dependence

Sun et al. | Dec 18, 2020

Computational Structure-Activity Relationship (SAR) of Berberine Analogs in Double-Stranded and G-Quadruplex DNA Binding Reveals Both Position and Target Dependence

Berberine, a natural product alkaloid, and its analogs have a wide range of medicinal properties, including antibacterial and anticancer effects. Here, the authors explored a library of alkyl or aryl berberine analogs to probe binding to double-stranded and G-quadruplex DNA. They determined that the nature of the substituent, the position of the substituent, and the nucleic acid target affect the free energy of binding of berberine analogs to DNA and G-quadruplex DNA, however berberine analogs did not result in net stabilization of G-quadruplex DNA.

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Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

Ramprasad et al. | Mar 18, 2020

Assessing and Improving Machine Learning Model Predictions of Polymer Glass Transition Temperatures

In this study, the authors test whether providing a larger dataset of glass transition temperatures (Tg) to train the machine-learning platform Polymer Genome would improve its accuracy. Polymer Genome is a machine learning based data-driven informatics platform for polymer property prediction and Tg is one property needed to design new polymers in silico. They found that training the model with their larger, curated dataset improved the algorithm's Tg, providing valuable improvements to this useful platform.

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Combined Progestin-Estrogenic Contraceptive Pills May Promote Growth in Crop-Plants

Saha et al. | Feb 21, 2020

Combined Progestin-Estrogenic Contraceptive Pills May Promote Growth in Crop-Plants

Ethinyl estradiol and progestin norgestrel are commonly present in contraceptive tablets and it is unknown how they affect the environment. In this study, the authors investigate the role that ethinyl estradiol and progestin norgestrel have on the growth of flowering plants. The percentage germination, embryonic and adventitious tissue proliferation, root length, and shoot length were measured in V. radiata and T. aestivum treated with each compound and results demonstrate that ethinyl estradiol and progestin norgestrel can induce growth in both plants at certain concentrations. These findings have important implications as societal use of chemicals increases and more make their way into the environment.

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