When mechanical factors underlie growth, development, disease or healing, they often function through local regions of tissue where deformation is highly concentrated. Current optical techniques to estimate deformation can lack precision and accuracy in such regions due to challenges in distinguishing a region of concentrated deformation from an error in displacement tracking. Here, we present a simple and general technique for improving the accuracy and precision of strain estimation and an associated technique for distinguishing a concentrated deformation from a tracking error. The strain estimation technique improves accuracy relative to other state-of-theart algorithms by directly estimating strain fields without first estimating displacements, resulting in a very simple method and low computational cost. The technique for identifying local elevation of strain enables for the first time the successful identification of the onset and consequences of local strain concentrating features such as cracks and tears in a highly strained tissue. We apply these new techniques to demonstrate a novel hypothesis in prenatal wound healing. More generally, the analytical methods we have developed provide a simple tool for quantifying the appearance and magnitude of localized deformation from a series of digital images across a broad range of disciplines.
Neural circuit analysis relies on having molecular markers for specific cell types. However, for a cell type identified only by its circuit function, the process of identifying markers remains laborious. We developed physiological optical tagging sequencing (PhOTseq), a technique for tagging and expression profiling of cells on the basis of their functional properties. PhOTseq was capable of selecting rare cell types and enriching them by nearly 100-fold. We applied PhOTseq to the challenge of mapping receptor-ligand pairings among pheromone-sensing neurons in mice. Together with in vivo ectopic expression of vomeronasal chemoreceptors, PhOTseq identified the complete combinatorial receptor code for a specific set of ligands.
Neural circuit analysis relies on having molecular markers for specific cell types. However, for a cell type identified only by its circuit function, the process of identifying markers remains laborious. Here, we report physiological optical tagging sequencing (PhOTseq), a technique for tagging and expression-profiling cells based on their functional properties. We demonstrate that PhOTseq is capable of selecting rare cell types and enriching them by nearly one hundred-fold. We applied PhOTseq to the challenge of mapping receptor-ligand pairings among vomeronasal pheromone-sensing neurons in mice. Together with in vivo ectopic expression of vomeronasal chemoreceptors, PhOTseq identified the complete combinatorial receptor code for a specific set of ligands, and revealed that the primary sequence of a chemoreceptor was an unexpectedly strong predictor of functional similarity.Molecular markers have been a powerful tool for labeling and analyzing neuronal cell types.However, in many cases a single marker is insufficient to define a unique cell type, and may la-
Traditional whole-body PET scanner is limited in resolution due to large detector crystal size, finite positron range and non-collinearity of annihilation photons. Our lab has developed a prototype half ring insert PET system that can improve resolution and radionuclide contrast recovery by using (1) smaller size of the detector crystals (2) virtual pinhole PET geometry obtained by placing the insert close to the imaging subject. This design allows for zooming-in to an area of interest while still maintaining the scanners whole-body imaging capability. To find the limits of the image resolution and contrast recovery, we performed a set of Monte Carlo simulations for a clinical PET system with and without half ring insert. The reconstructed images show the improvement in image resolution, with 3 mm diameter tumors resolvable with insert at a contrast ratio of 9:1, compared to scanner without insert where smallest tumors resolvable was 6 mm.
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