Neuromorphic computing at scale.

Neuromorphic computing is a brain-inspired approach to hardware and algorithm design that efficiently realizes artificial neural networks. Neuromorphic designers apply the principles of biointelligence discovered by neuroscientists to design efficient computational systems, often for applications with size, weight and power constraints. With this research field at a critical juncture, it is crucial to chart the course for the development of future large-scale neuromorphic systems.

Targeting protein-ligand neosurfaces with a generalizable deep learning tool.

Molecular recognition events between proteins drive biological processes in living systems. However, higher levels of mechanistic regulation have emerged, in which protein-protein interactions are conditioned to small molecules. Despite recent advances, computational tools for the design of new chemically induced protein interactions have remained a challenging task for the field.

To conjugate or not to conjugate? evaluating the potential use of cell-penetrating peptides for conjugation or complexation with oligonucleotides by surface plasmon resonance.

Oligonucleotides represent a class of molecules that exhibit remarkable therapeutic potential due to their unparalleled target specificity, yet they suffer from limited cellular uptake and lack of tissue selectivity. Extensive research is conducted with cell-penetrating peptides (CPPs) as delivery excipients due to their ability to translocate across cellular membranes and deliver cargo into cells. This study aims to investigate an innovative approach to rapidly, and with small amounts of compound, analyze and compare complexation of CPPs to oligonucleotides.

BindCraft: one-shot design of functional protein binders.

Protein-protein interactions (PPIs) are at the core of all key biological processes. However, the complexity of the structural features that determine PPIs makes their design challenging. We present BindCraft, an open-source and automated pipeline for protein binder design with experimental success rates of 10-100%.

The impact of the COVID-19 pandemic on first-episode psychosis presentations in two early intervention in psychosis services.

Objectives: To assess the impact of the COVID-19 pandemic on first-episode psychosis (FEP) presentations across two Early Intervention in Psychosis (EIP) services in Ireland, by comparing pre-pandemic and post-pandemic cohorts.

Methods: A cross-sectional observational design with retrospective medical record review was employed. The study population comprised 187 FEP patients (77 in pre-pandemic and 110 in post-pandemic cohort).