Deep Learning Coordinate-Free Quantum Chemistry.

Computing quantum chemical properties of small molecules and polymers can provide insights valuable into physicists, chemists, and biologists when designing new materials, catalysts, biological probes, and drugs. Deep learning can compute quantum chemical properties accurately in a fraction of time required by commonly used methods such as density functional theory. Most current approaches to deep learning in quantum chemistry begin with geometric information from experimentally derived molecular structures or pre-calculated atom coordinates. These approaches have many useful applications, but they can be costly in time and computational resources. In this study, we demonstrate that accurate quantum chemical computations can be performed without geometric information by operating in the coordinate-free domain using deep learning on graph encodings. Coordinate-free methods rely only on molecular graphs, the connectivity of atoms and bonds, without atom coordinates or bond distances. We also find that the choice of graph-encoding architecture substantially affects the performance of these methods. The structures of these graph-encoding architectures provide an opportunity to probe an important, outstanding question in quantum mechanics: what types of quantum chemical properties can be represented by local variable models? We find that Wave, a local variable model, accurately calculates the quantum chemical properties, while graph convolutional architectures require global variables. Furthermore, local variable Wave models outperform global variable graph convolution models on complex molecules with large, correlated systems.

Clinically isolated descending thoracic aortitis in a healthy older woman: a diagnostic challenge.

A woman travelling to Australia in her early 70s presents to a regional emergency department with chest pain and associated shortness of breath. Her medical history was that of seasonal affective disorder treated with citalopram, and an allergy to ibuprofen. Subsequent CT imaging revealed aortic wall thickening and associated periaortic fluid, and a moderate pleural effusion. This was successfully treated with oral prednisolone, responding within 1 day. Further blood tests revealed a high CD4/CD8 T-cell ratio, which can be seen in autoimmune disease, sarcoidosis and haematological malignancies. Without evidence for other autoimmune processes, the patient was given a provisional diagnosis of descending thoracic aortitis secondary to sarcoidosis, prescribed a weaning regimen of prednisolone, and asked to seek further investigation and management in her home country. This is a case with several learning points; rare disease can cause common presentations/reports, and sometimes empirical therapy is the only therapy.