A supervised graph-based deep learning algorithm to detect and quantify clustered particles.

Considerable efforts are currently being devoted to characterizing the topography of membrane-embedded proteins using combinations of biophysical and numerical analytical approaches. In this work, we present an end-to-end (, human intervention-independent) algorithm consisting of two concatenated binary Graph Neural Network (GNNs) classifiers with the aim of detecting and quantifying dynamic clustering of particles. As the algorithm only needs simulated data to train the GNNs, it is parameter-independent.

Volume-Conducted Origin of the Field Potential at the Lateral Habenula.

Field potentials (FPs) are easily reached signals that provide information about the brain's processing. However, FP should be interpreted cautiously since their biophysical bases are complex. The lateral habenula (LHb) is a brain structure involved in the encoding of aversive motivational values.

Antibody-induced crosslinking and cholesterol-sensitive, anomalous diffusion of nicotinic acetylcholine receptors.

Synaptic strength depends on the number of cell-surface neurotransmitter receptors in dynamic equilibrium with intracellular pools. Dysregulation of this homeostatic balance occurs, for example in myasthenia gravis, an autoimmune disease characterized by a decrease in the number of postsynaptic nicotinic acetylcholine receptors (nAChRs). Monoclonal antibody mAb35 mimics this effect.

Cholesterol modulates acetylcholine receptor diffusion by tuning confinement sojourns and nanocluster stability.

Translational motion of neurotransmitter receptors is key for determining receptor number at the synapse and hence, synaptic efficacy. We combine live-cell STORM superresolution microscopy of nicotinic acetylcholine receptor (nAChR) with single-particle tracking, mean-squared displacement (MSD), turning angle, ergodicity, and clustering analyses to characterize the lateral motion of individual molecules and their collective behaviour. nAChR diffusion is highly heterogeneous: subdiffusive, Brownian and, less frequently, superdiffusive.