Social media is widely used and easily accessible for adolescents, it has the potential to increase STEM (Science, Technology, Engineering, and Math) identity in girls. We aimed to investigate the effects of exposure to counter-stereotypical portrayals of women in STEM on social media on the STEM identity of adolescent girls. The study concluded that social media alone may not be an effective tool to increase STEM identity in girls. Social media can still be used as a complementary tool to support and encourage women in STEM, but it should not be relied upon solely to address the gender disparity in STEM fields.

In this study, the authors determined whether tautomerization dynamics in protic and aprotic solvents displayed differences in reaction rates and in the proportion of the keto and enol tautomers present.

In this study, the authors use existing mathematical models to how high school athletes pace 800 m, 1600 m, and 3200 m distance track events compared to elite athletes.

Reinforcement learning (RL) is a form of machine learning that can be harnessed to develop artificial intelligence by exposing the intelligence to multiple generations of data. The study demonstrates how reply buffer reward mechanics can inform the creation of new pruning methods to improve RL efficiency.

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.

Metal-organic frameworks (MOFs) are promising new nanomaterials for use in the fight against climate change that can efficiently capture and convert CO₂ to other useful carbon products. This research used computational models to determine the reaction conditions under which MOFs can more efficiently capture and convert CO₂. In a cost-efficient manner, this analysis tested the hypothesis that pressure and temperature affect the efficacy of carbon capture and conversion, and contribute to understanding the optimal conditions for MOF performance to improve the use of MOFs for controlling greenhouse CO₂ emissions.

Caenorhabditis elegans xpa-1 and him-1 are orthologs of human XPA and human SMC1A, respectively. Mutations in the XPA are correlated with Xeroderma pigmentosum, a condition that induces hypersensitivity to ultraviolet (UV) radiation. Alternatively, SMC1A mutations may lead to Cornelia de Lange Syndrome, a multi-organ disorder that makes patients more sensitive to UVinduced DNA damage. Both C. elegans genes have been found to be involved in protection against UV radiation, but their combined effects have not been tested when they are both knocked down. The authors hypothesized that because these genes are involved in separate pathways, the simultaneous knockdown of both of these genes using RNA interference (RNAi) in C. elegans will cause them to become more sensitive to UV radiation than either of them knocked down individually. UV protection was measured via the percent survival of C. elegans post 365 nm and 5.4x10-19 joules of UV radiation. The double xpa-1/him-1 RNAi knockdown showed a significantly reduced percent survival after 15 and 30 minutes of UV radiation relative to wild-type and xpa-1 and him-1 single knockdowns. These measurements were consistent with their hypothesis and demonstrated that xpa-1 and him-1 genes play distinct roles in resistance against UV stress in C. elegans. This result raises the possibility that the xpa-1/him-1 double knockdown could be useful as an animal model for studying the human disease Xeroderma pigmentosum and Cornelia de Lange Syndrome.

DegS is an integral inner membrane protein in E. coli that helps break down misfolded proteins. When it is mutated, there is a large increase in the production of outer membrane vesicles (OMVs), which are thought to play a role in pathogenesis. This study used mutant strains of uropathogenic E. coli (UPEC) to characterize the role of DegS and OMVs on UPEC virulence.

To best identify tuberculosis and pneumonia diagnoses in chest x-rays, the authors compare different deep learning convolution neural networks.

In an extensive study of gene mutations, and their resulting effect on protein-protein interactions, Desai and Stork found that HTT-PRPF40B-MECP2 interactions are weakened with progression of Lopes-Maciel-Rodan syndrome.