Identifying treatments that can stimulate hair growth use could help those struggling with undesirable hair loss. Here, the authors show that Fibroblast Growth Factors can stimulate the division of cells isolated from the mouse hair follicle. Their results suggest that this family of growth factors might be helpful in stimulating hair growth in living animals as well.

Methane is a naturally-occurring gas that could be utilized as a renewable source of energy. In this study, authors isolated microorganisms from the Puget Sound region that could produce methane biofuel from composted waste.

The authors looked at the effect of microconvection on displacing bubbles during electrolysis. They found that microconvection does have a role in bubble displacement in water electrolysis which can be applied in the production of hydrogen.

The authors test the effects of common food industry preservatives on the heart rate of the freshwater crustacean Daphnia magna.

In this study, the authors investigate the effects of acidity on the survival of commercial probiotic Lovebug bacterial strains.

The authors test electrocardiography biofeedback as a treatment for individuals with Postural Orthostatic Tachycardia Syndrome.

In this study, the authors analyze gene expression datasets to determine if there is a core set of genes dysregulated during nonalcoholic steatohepatitis.

Scientist are investigating the use of methane-consuming bacteria to aid the growing problem of rising greenhouse gas emissions. While previous studies claim that low-frequency electromagnetic fields can accelerate the growth rate of these bacteria, Chu et al. demonstrate that this fundamental ideology is not on the same wavelength with their data.

In this study, the authors investigate the effects of acetone on the color of copper chloride (CuCl₂) solution, which has important implications for detecting copper in the environment.

The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.