Dynamic lateral organization of opioid receptors (kappa, mu and mu ) in the plasma membrane at the nanoscale level.

Opioid receptors are important pharmacological targets for the management of numerous medical conditions (eg, severe pain), but they are also the gateway to the development of deleterious side effects (eg, opiate addiction). Opioid receptor signaling cascades are well characterized. However, quantitative information regarding their lateral dynamics and nanoscale organization in the plasma membrane remains limited.

Molecular signatures of mu opioid receptor and somatostatin receptor 2 in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC), a particularly aggressive malignancy, has been linked to atypical levels, certain mutations, and aberrant signaling of G-protein-coupled receptors (GPCRs). GPCRs have been challenging to target in cancer because they organize into complex networks in tumor cells. To dissect such networks with nanometer-scale precision, here we combine traditional biochemical approaches with superresolution microscopy methods.

Superresolution localization methods.

Superresolution localization microscopy methods produce nanoscale images via a combination of intermittently active fluorescent probes and algorithms that can precisely determine the positions of these probes from single-molecule or few-molecule images. These algorithms vary widely in their underlying principles, complexity, and accuracy. In this review, we begin by surveying the principles of localization microscopy and describing the fundamental limits to localization precision.

Theoretical limits on errors and acquisition rates in localizing switchable fluorophores.

A variety of recent imaging techniques are able to beat the diffraction limit in fluorescence microcopy by activating and localizing subsets of the fluorescent molecules in the specimen, and repeating this process until all of the molecules have been imaged. In these techniques there is a tradeoff between speed (activating more molecules per imaging cycle) and error rates (activating more molecules risks producing overlapping images that hide information on molecular positions), and so intelligent image processing approaches are needed to identify and reject overlapping images. We introduce here a formalism for defining error rates, derive a general relationship between error rates, image acquisition rates, and the performance characteristics of the image processing algorithms, and show that there is a minimum acquisition time irrespective of algorithm performance.

Spatial distribution of VEGF isoforms and chemotactic signals in the vicinity of a tumor.

We propose a mathematical model that describes the formation of gradients of different isoforms of vascular endothelial growth factor (VEGF). VEGF is crucial in the process of tumor-induced angiogenesis, and recent experiments strongly suggest that the molecule is most potent when bound to the extracellular matrix (ECM). Using a system of reaction-diffusion equations, we study diffusion of VEGF, binding of VEGF to the ECM, and cleavage of VEGF from the ECM by matrix metalloproteases (MMPs).