Photography and Illustrations

First Place: Microstructural Heterogeneity of a Healing Wound

January-February 2012
Kyle P. Quinn, Postdoctoral Scholar, Biomedical Engineering, School of Engineering
Benjamin D. Almquist, Postdoctoral Fellow, Chemical Engineering, MIT
Paula T. Hammond, Professor, Chemical Engineering, MIT
Irene Georgakoudi, Associate Professor, Biomedical Engineering, School of Engineering

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Non-linear optical microscopy is a powerful, non-destructive imaging technique that is capable of detecting different tissue microstructure without the need for the stains or dyes typically used in histology. Here, we utilize two different non-linear optical processes, two-photon excited fluorescence (TPEF) and second harmonic generation (SHG), to assess differences in tissue organization along a cross-section of a healing skin wound. Using a titanium:sapphire laser tuned to specific excitation wavelengths and photomultiplier tube detectors collecting at specific emission wavelengths, we are able to isolate the autofluorescence of cell metabolic cofactors (NADH in green, FAD in blue). In addition, the non-centrosymmetric organization of collagen molecules produces a SHG signal (red) that is most evident in the uninjured dermal layer of the skin at the wound edges. In the middle of the wound, the reduced SHG from newly-formed collagen and increased cellular density associated with immune cell and fibroblast migration to the wound is evident from these images. By detecting differences in cell metabolism and tissue microstructure, quantitative TPEF and SHG imaging outcomes can be used to non-invasively characterize wound properties in vivo, and have potential utility in diagnosing chronic wounds and evaluating therapeutic efficacy. Insets correspond to a 238×238µm field of view.

Second Place: Sphere Packing on Ellipsoidal Surfaces

Christopher Burke, Graduate Student, Tufts School of Arts and Sciences
Badel Mbanga, Postdoctoral Associate, Tufts School of Arts and Sciences
Timothy Atherton, Assistant Professor, Physics, Tufts School of Arts and Sciences

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Understanding how particles pack on curved surfaces is important for applications in medicine and the food industry in which colloidal particles are embedded, for example, on oil-water interfaces in emulsions. Packing spherical particles on a curved interface is bound to result in a configuration with defects. On a flat surface, particles tend to pack in an orderly hexagonal lattice. However, the presence of curvature makes this type of configuration impossible to obtain, and results in particles having more or fewer than six neighbors. These regions which deviate from a hexagonal lattice are referred to as defects.

Pictured here are configurations of spherical particles packed on ellipsoidal surfaces. Red particles have six neighboring particles, and defects are shown as blue particles which have five neighbors, green particles which have seven neighbors, and occasionally yellow particles which have eight neighbors. The black lines indicate the axis about which the ellipsoidal surfaces are symmetric. Configuration (a) illustrates how defects tend to form in regions of high curvature. The relatively flat center has a lower density of defects. Another striking feature in these images is the presence of chains of defects in a 5-7-…-5 pattern, known as scars, which are prominent in configuration (c). We also see star-like patterns as in configuration (b). These sorts of defect structures form because they relieve stress in the configuration and thus are energetically favored over isolated defects when you have large numbers of particles. Our group is in the process of investigating when scars form with respect to the number of particles in the configuration, as well as how they are oriented on the surface with respect to directions of higher and lower curvature. These configurations were generated using a packing algorithm written in Fortran and visualized using Mathematica.

Third Place: Visualization Of The Limbal Vasculature Using Swept Source Optical Coherence Tomography Following Speckle Variance Processing

Mehreen Adhi, Postdoctoral Scholar, Opthalmology, Tufts School of Medicine
Kevin Sitko, Clinical Associate, Opthalmology, Tufts School of Medicine
Jay S Duker, Professor and Chair, Opthalmology, Tufts School of Medicine
Chandrasekharan Krishnan, Assistant Professor, Opthalmology, Tufts School of Medicine

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Optical coherence tomography (OCT) has evolved over the past decade into one of the most important ancillary tests in ophthalmic practice. It is a noninvasive imaging technique and provides high-resolution cross-sectional images of the retina, the retinal nerve fiber layer, optic nerve head. New innovations in OCT technology include a prototype swept source OCT (SS-OCT) system, which employs a tunable frequency swept laser light source, that sequentially emits various frequencies in time, and the interference spectrum is measured by photo-detectors to provide high signal quality in various tissues of the eye. The present illustration is an example of a new utilization of OCT to visualize the scleral and episcleral vasculature that delivers blood supply to the anterior segment of the eye in a three-dimensional projection, also known as the en-face view. Visualization of the blood vessels on an en-face view is further enhanced using a novel technique called “speckle variance processing”. This involves obtaining multiple images at the same location and decorrelation of speckle patterns over these multiple images is calculated. After correcting for motion, the remaining motion due to blood flow within the vessels, results in an increased variance of speckle patterns, enabling visualization of small vessels that are not discernible using standard en-face view. This information of the vasculature in the sclera adjacent to the cornea may have clinical utility in the monitoring and diagnosis of various ischemic and inflammatory conditions involving the anterior segment of the eye.