Here, seeking to better understand the roles of glycans in the receptors of active sites of neuronal cells, the authors used molecular dynamics simulations to to uncover the dynamic nature of N-glycans on membrane proteins. The authors suggest the study of theinteractions of these membrane poreins could provide future potential therapeutic targets to treat mental diseases.

In order for cells to successfully multiply, a number of proteins are needed to correctly coordinate the replication and division process. In this study, students use fluorescence microscopy and molecular methods to study CCDC11, a protein critical in the formation of cilia. Interestingly, they uncover a new role for CCDC11, critical in the cell division across multiple human cell lines.

In this study, the authors develop a new hydrogel using photochemical crosslinking with bovine serum albumin and methylene blue. They find that this new hydrogel has some useful applications!

Malaria is a major public health issue, especially in developing countries, and vector control is a major facet of malaria eradication efforts. Recently, sterile insect technique (SIT), or the release of sterile mosquitoes into the wild, has shown significant promise as a method of keeping vector populations under control. In this study, the authors investigate the Anopheles gambiae transglutaminase 3 protein (AgT3), which is essential to the mating of the Anopheles mosquito. They show that an active site mutation is able to abolish the activity of the AgT3 enzyme and propose it as a potential target for chemosterilant inhibitors.

The authors investigate whether human blood cancers carrying mutations in DNA repair genes possess increased sensitivity to common chemotherapy drugs cisplatin or gemcitabine.

The Human Immunodeficiency Virus (HIV) infects approximately 40 million people globally, and one million people die every year from Acquired Immune Deficiency Syndrome (AIDS)-related illnesses. This study examined the interactions between the HIV-1 envelope glycoprotein gp120 and the human lymphocyte receptor integrin α4β7, the putative first long-range receptor for the envelope glycoprotein of the virus in mucosal tissues. Presented data support the claim that the V1 loop is involved in the binding between α4β7 and the HIV-1 envelope glycoprotein through molecular dockings.

The COVID-19 pandemic has caused disruption in social interactions. In this study, the authors tested if walking a dog will change human interactions and found that walking with a dog increased social interaction.

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.

In their paper, Kreiman et al. examined what it takes for an artificial neural network to be able to perform well on a new task without forgetting its previous knowledge. By comparing methods that stop task forgetting, they found that longer training times and maintenance of the most important connections in a particular task while training on a new one helped the neural network maintain its performance on both tasks. The authors hope that this proof-of-principle research will someday contribute to artificial intelligence that better mimics natural human intelligence.

Modern artificial neural networks have been remarkably successful in various applications, from speech recognition to computer vision. However, it remains less clear whether they can implement abstract concepts, which are essential to generalization and understanding. To address this problem, the authors investigated the above vs. below task, a simple concept-based task that honeybees can solve, using a conventional neural network. They found that networks achieved 100% test accuracy when a visual target was presented below a black bar, however only 50% test accuracy when a visual target was presented below a reference shape.