The scaffold protein POSH regulates T lymphocyte function

T lymphocytes are critical mediators of the adaptive immune response. T cell receptor (TCR) mediated cJUN NH2-terminal kinase (JNK) activation is required for mounting proper T cell mediated immune responses. However, little is know as to how JNK activation is coupled to the TCR. This dissertation shows that the scaffold protein Plenty of SH3s (POSH) is required for optimal JNK activation and effector function in both CD4+ and CD8+ T cells. Additionally, this work shows that POSH is dispensable for JNK activation and positive and negative selection in developing thymocytes. Thus, POSH couples the TCR to JNK activation in a cell type and developmental stage dependent manner. This work also revels a novel target for the treatment of autoimmune disorders such as Type I Diabetes and Multiple Sclerosis

Changing portrayals of medicine and patients in eighteenth-century medical writing : Lexical bundles in Public Health, Methods, and case studies

Peer reviewe

Towards new knowledge : The corpus of Late Modern English Medical Texts

Peer reviewe

Scientific Periodicals : The Philosophical Transactions and the Edinburgh Medical Journal

Peer reviewe

Manual to the LMEMT corpus

Peer reviewe

Sociohistorical and cultural context of Late Modern English Medical Texts

Peer reviewe

Public health

Peer reviewe

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery