S2E8: What is bioengineering?

It’s one of the fastest growing and changing fields in the world of engineering. Bioengineering, or biomedical engineering, is changing the way we do everything from producing fuel and paper to unlocking new ways to improve animal and human health. It’s a growing field — particularly for young women aspiring to be engineers. Karissa Tilbury, an assistant professor of biomedical engineering at UMaine, helps us explore this relative newcomer to the world of engineering

Differentiation of Col I and Col III Isoforms in Stromal Models of Ovarian Cancer by Analysis of Second Harmonic Generation Polarization and Emission Directionality

AbstractA profound remodeling of the extracellular matrix occurs in many epithelial cancers. In ovarian cancer, the minor collagen isoform of Col III becomes upregulated in invasive disease. Here we use second harmonic generation (SHG) imaging microscopy to probe structural differences in fibrillar models of the ovarian stroma comprised of mixtures of Col I and III. The SHG intensity and forward-backward ratios decrease with increasing Col III content, consistent with decreased phasematching due to more randomized structures. We further probe the net collagen α-helix pitch angle within the gel mixtures using what is believed to be a new pixel-based polarization-resolved approach that combines and extends previous analyses. The extracted pitch angles are consistent with those of peptide models and the method has sufficient sensitivity to differentiate Col I from the Col I/Col III mixtures. We further developed the pixel-based approach to extract the SHG signal polarization anisotropy from the same polarization-resolved image matrix. Using this approach, we found that increased Col III results in decreased alignment of the dipole moments within the focal volume. Collectively, the SHG measurements and analysis all indicate that incorporation of Col III results in decreased organization across several levels of collagen organization. Furthermore, the findings suggest that the collagen isoforms comingle within the same fibrils, in good agreement with ultrastructural data. The pixel-based polarization analyses (both excitation and emission) afford determination of structural properties without the previous requirement of having well-aligned fibers, and the approaches should be generally applicable in tissue

Maine Impact Week 2021 Faculty Mentor Impact Awards : Karissa Tilbury

Earlier this year, we asked students to nominate faculty members who had an important impact on them and the response was incredible. Through online videos and announcements, we are featuring the nine faculty members who won 2021 Faculty Mentor Impact Awards. Click the download button for a machine-generated, English transcript

Fluorescence lifetime imaging microscopy (FLIM) reveals spatial-metabolic changes in 3D breast cancer spheroids

Cancer cells are mechanically sensitive to physical properties of the microenvironment, which can affect downstream signaling to promote malignancy, in part through the modulation of metabolic pathways. Fluorescence Lifetime Imaging Microscopy (FLIM) can be used to measure the fluorescence lifetime of endogenous fluorophores, such as the metabolic co-factors NAD(P)H and FAD, in live samples. We used multiphoton FLIM to investigate the changes in cellular metabolism of 3D breast spheroids derived from MCF-10A and MD-MB-231 cell lines embedded in collagen with varying densities (1 vs. 4 mg/ml) over time (Day 0 vs. Day 3). MCF-10A spheroids demonstrated spatial gradients, with the cells closest to the spheroid edge exhibiting FLIM changes consistent with a shift towards oxidative phosphorylation (OXPHOS) while the spheroid core had changes consistent with a shift towards glycolysis. The MDA-MB-231 spheroids had a large shift consistent with increased OXPHOS with a more pronounced change at the higher collagen concentration. The MDA-MB-231 spheroids invaded into the collagen gel over time and cells that traveled the farthest had the largest changes consistent with a shift towards OXPHOS. Overall, these results suggest that the cells in contact with the extracellular matrix (ECM) and those that migrated the farthest had changes consistent with a metabolic shift towards OXPHOS. More generally, these results demonstrate the ability of multiphoton FLIM to characterize how spheroids metabolism and spatial metabolic gradients are modified by physical properties of the 3D ECM.1830878 - National Science Foundation; W81XWH-15-1-0070 - U.S. Department of Defense; 113098-5093071 - Harvard School of Public HealthPublished versio

Multiscale anisotropy analysis of second-harmonic generation collagen imaging of human pancreatic cancer

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers with a minority (\u3c 10%) of patients surviving five years past diagnosis. This could be improved with the development of new imaging modalities for early differentiation of benign and cancerous fibrosis. This study intends to explore the application of a two-photon microscopy technique known as second harmonic generation to PDAC using the 2D Wavelet Transform Modulus Maxima (WTMM) Anisotropy method to quantify collagen organization in fibrotic pancreatic tissue. Forty slides from PDAC patients were obtained and eight images were captured per each tissue category on each slide. Brownian surface motion and white noise images were generated for calibration and testing of a new variable binning approach to the 2D WTMM Anisotropy method. The variable binning method had greater resistance to wavelet scaling effects and white noise images were found to have the lowest anisotropy factor. Cancer and fibrosis had greater anisotropy factors (Fa) at small wavelet scales than normal and normal adjacent tissue. At a larger scale of 21 μm this relationship changed with normal tissue having a higher Fa than all other tissue groups. White noise is the best representative image for isotropy and the 2D WTMM anisotropy method is sensitive to changes induced in collagen by PDAC

OpenSFDI: an open-source guide for constructing a spatial frequency domain imaging system.

Significance: Spatial frequency domain imaging (SFDI) is a diffuse optical measurement technique that can quantify tissue optical absorption (μa) and reduced scattering (μs') on a pixel-by-pixel basis. Measurements of μa at different wavelengths enable the extraction of molar concentrations of tissue chromophores over a wide field, providing a noncontact and label-free means to assess tissue viability, oxygenation, microarchitecture, and molecular content. We present here openSFDI: an open-source guide for building a low-cost, small-footprint, three-wavelength SFDI system capable of quantifying μa and μs' as well as oxyhemoglobin and deoxyhemoglobin concentrations in biological tissue. The companion website provides a complete parts list along with detailed instructions for assembling the openSFDI system. Aim: We describe the design of openSFDI and report on the accuracy and precision of optical property extractions for three different systems fabricated according to the instructions on the openSFDI website. Approach: Accuracy was assessed by measuring nine tissue-simulating optical phantoms with a physiologically relevant range of μa and μs' with the openSFDI systems and a commercial SFDI device. Precision was assessed by repeatedly measuring the same phantom over 1 h. Results: The openSFDI systems had an error of 0  ±  6  %   in μa and -2  ±  3  %   in μs', compared to a commercial SFDI system. Bland-Altman analysis revealed the limits of agreement between the two systems to be   ±  0.004  mm  -  1 for μa and -0.06 to 0.1  mm  -  1 for μs'. The openSFDI system had low drift with an average standard deviation of 0.0007  mm  -  1 and 0.05  mm  -  1 in μa and μs', respectively., Conclusion: The openSFDI provides a customizable hardware platform for research groups seeking to utilize SFDI for quantitative diffuse optical imaging

3D texture analysis for classification of second harmonic generation images of human ovarian cancer

Remodeling of the collagen architecture in the extracellular matrix (ECM) has been implicated in ovarian cancer. To quantify these alterations we implemented a form of 3D texture analysis to delineate the fibrillar morphology observed in 3D Second Harmonic Generation (SHG) microscopy image data of normal (1) and high risk (2) ovarian stroma, benign ovarian tumors (3), low grade (4) and high grade (5) serous tumors, and endometrioid tumors (6). We developed a tailored set of 3D filters which extract textural features in the 3D image sets to build (or learn) statistical models of each tissue class. By applying k-nearest neighbor classification using these learned models, we achieved 83–91% accuracies for the six classes. The 3D method outperformed the analogous 2D classification on the same tissues, where we suggest this is due the increased information content. This classification based on ECM structural changes will complement conventional classification based on genetic profiles and can serve as an additional biomarker. Moreover, the texture analysis algorithm is quite general, as it does not rely on single morphological metrics such as fiber alignment, length, and width but their combined convolution with a customizable basis set