In this study the authors looked at the extract of Stephania tetrandra and its impact on symptoms related to obsessive compulsive disorder in fruit flies.

The authors use the Lanczos algorithm to computationally solve the Schrodinger equation for 2D potentials with a Python program

Semantic segmentation - labelling each pixel in an image to a specific class- models require large amounts of manually labeled and collected data to train.

The authors looked at 5-FU resistant HeLa cells and the ability of an herbal extract to show anti-inflammatory properties.

The authors found that treatment with AS20 suppressed phorbol 12-myristate 13-acetate (PMA) and 5-flurouracil (5-FU) induction of COX2 expression. We also observed AS20 treated cells showed DNA fragmentation in HeLa cells.

These authors mathematically deduce a model that explains the interesting (and unintuitive) physical phenomenon that occurs when water falls.

The authors seek to accelerate wound healing by reducing inflammation with a cocktail containing growth factors and bioactive modulators.

The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.

This study aimed to determine whether artificial sweeteners are harmful to the human microbiome by investigating two different bacteria found to be advantageous to the human gut, Escherichia coli and Bacillus coagulans. Results showed dramatic reduction in bacterial growth for agar plates containing two artificial sweeteners in comparison to two natural sweeteners. This led to the conclusion that both artificial sweeteners inhibit the growth of the two bacteria and warrants further study to determine if zero-sugar sweeteners may be worse for the human gut than natural sugar itself.

Irrespective of the final application of a molecule, synthetic accessibility is the rate-determining step in discovering and developing novel entities. However, synthetic complexity is challenging to quantify as a single metric, since it is a composite of several measurable metrics, some of which include cost, safety, and availability. Moreover, defining a single synthetic accessibility metric for both natural products and non-natural products poses yet another challenge given the structural distinctions between these two classes of compounds. Here, we propose a model for synthetic accessibility of all chemical compounds, inspired by the Central Limit Theorem, and devise a novel synthetic accessibility metric assessing the overall feasibility of making chemical compounds that has been fitted to a Gaussian distribution.