Hyaluronic acid alters vessel behavior in CXCL12-treated HUVECs

Hyaluronic acid (HA) is a key component of the extracellular matrix known for absorbing water, swelling, and altering solid stress of tumors. HA’s anionic behavior may provide important biochemical effects toward tumor progression as well. Tumors obtain nutrients by relying on signaling molecules such as CXCL12 to recruit blood vessels and promote vessel leakage. Recent work suggests that additional positively-charged residues on CXCL12’s β and γ isoforms cause different biochemical functionality compared to the well-studied α isoform. These studies aimed to determine whether the presence of HA in a tumor’s microenvironment could alter the relative response strength of CXCL12’s various isoforms on blood vessel sprouting and apparent vascular permeability. The vessel microenvironment was modeled using a 3-channel microfluidic device with Human Umbilical Vein Endothelial Cells (HUVECs) in the outer channels forming monolayers against a 3D collagen or collagen/HA matrix in the center channel. HUVECs were cultured with media containing recombinant CXCL12 (α, β or γ). Results show that total HUVEC sprouting area follows an α>β>γ trend in isoform-treated HUVECs within a collagen matrix, matching the binding affinity order of CXCL12 to endothelial CXCR4 receptors. The presence of HA decreased overall sprouting response but shifted pro-angiogenic potency towards CXCL12’s γ isoform. Vascular permeability studies also showed an α>β>γ trend for HUVECs in collagen. With HA added, control and α-treated HUVECs became less permeable while γ-treated HUVECs became more permeable. Overall results suggest that an HA-infused collagen matrix facilitates γ isoform binding, leading to a stronger isoform-specific vessel response. Knowing how HA impacts CXCL12 isoform potency on vessels will help in the future design of CXCL12-targeted cancer therapies.The American Heart AssociationInstitute for Materials Research at OSULumley Engineering FundPelotoniaA one-year embargo was granted for this item.Academic Major: Chemical Engineerin

Barcoding a Quantified Food Web: Crypsis, Concepts, Ecology and Hypotheses

The efficient and effective monitoring of individuals and populations is critically dependent on correct species identification. While this point may seem obvious, identifying the majority of the more than 100 natural enemies involved in the spruce budworm (Choristoneura fumiferana – SBW) food web remains a non-trivial endeavor. Insect parasitoids play a major role in the processes governing the population dynamics of SBW throughout eastern North America. However, these species are at the leading edge of the taxonomic impediment and integrating standardized identification capacity into existing field programs would provide clear benefits. We asked to what extent DNA barcoding the SBW food web would alter our understanding of the diversity and connectence of the food web and the frequency of generalists vs. specialists in different forest habitats. We DNA barcoded over 10% of the insects collected from the SBW food web in three New Brunswick forest plots from 1983 to 1993. For 30% of these specimens, we amplified at least one additional nuclear region. When the nodes of the food web were estimated based on barcode divergences (using molecular operational taxonomic units (MOTU) or phylogenetic diversity (PD) – the food web became much more diverse and connectence was reduced. We tested one measure of food web structure (the “bird feeder effect”) and found no difference compared to the morphologically based predictions. Many, but not all, of the presumably polyphagous parasitoids now appear to be morphologically-cryptic host-specialists. To our knowledge, this project is the first to barcode a food web in which interactions have already been well-documented and described in space, time and abundance. It is poised to be a system in which field-based methods permit the identification capacity required by forestry scientists. Food web barcoding provided an effective tool for the accurate identification of all species involved in the cascading effects of future budworm outbreaks. Integrating standardized barcodes within food webs may ultimately change the face of community ecology. This will be most poignantly felt in food webs that have not yet been quantified. Here, more accurate and precise connections will be within the grasp of any researcher for the first time

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Anatomical Modeling of Brain Vasculature in Two-Photon Microscopy by Generalizable Deep Learning

Objective and Impact Statement. Segmentation of blood vessels from two-photon microscopy (2PM) angiograms of brains has important applications in hemodynamic analysis and disease diagnosis. Here, we develop a generalizable deep learning technique for accurate 2PM vascular segmentation of sizable regions in mouse brains acquired from multiple 2PM setups. The technique is computationally efficient, thus ideal for large-scale neurovascular analysis. Introduction. Vascular segmentation from 2PM angiograms is an important first step in hemodynamic modeling of brain vasculature. Existing segmentation methods based on deep learning either lack the ability to generalize to data from different imaging systems or are computationally infeasible for large-scale angiograms. In this work, we overcome both these limitations by a method that is generalizable to various imaging systems and is able to segment large-scale angiograms. Methods. We employ a computationally efficient deep learning framework with a loss function that incorporates a balanced binary-cross-entropy loss and total variation regularization on the network’s output. Its effectiveness is demonstrated on experimentally acquired in vivo angiograms from mouse brains of dimensions up to 808×808×702 μm. Results. To demonstrate the superior generalizability of our framework, we train on data from only one 2PM microscope and demonstrate high-quality segmentation on data from a different microscope without any network tuning. Overall, our method demonstrates 10× faster computation in terms of voxels-segmented-per-second and 3× larger depth compared to the state-of-the-art. Conclusion. Our work provides a generalizable and computationally efficient anatomical modeling framework for brain vasculature, which consists of deep learning-based vascular segmentation followed by graphing. It paves the way for future modeling and analysis of hemodynamic response at much greater scales that were inaccessible before

Five Design Challenges

PLEASE NOTE: Where applicable, the audio has been removed from this file due to copyrighted material. The garments shown here represent the Classes of \u2712, \u2711 and \u2710 . The garments were created in response to the following five design challenges: Sophomores, Class of \u2712: Re-Innovative Design: explore the properties of recycled materials other than fabric while creating a wearable piece. Print Design Project create a garment that makes optimal use of an assigned printed fabric. Juniors, Class of \u2710: Knitwear Design: explore the properties of knits and design cut-and-sew and machine-knit garments. Tailoring Project: interpret traditional tailoring techniques to create a look with a jacket. Seniors, Class of \u2709: Coat Collection: design a collection with a coat as the key piece