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Cellular Network Interactions Comprising the Pancreatic Ductal Adenocarcinoma (PDAC) Microenvironment
(2025-02-05) Torabian, Pedram; Bathe, Oliver; Minoo, Parham; Wang, Edwin; Schaeffer, David; Bose, Pinaki
Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers, marked by complex interactions between tumor and stromal cells and significant resistance to treatment. Understanding the cellular and molecular heterogeneity within the PDAC tumor microenvironment is crucial for developing more targeted therapeutic strategies. Spatial transcriptomics offers a powerful approach to capture cell-to-cell interactions within the tumor microenvironment, revealing tissue architecture and providing insights into the spatial organization of cellular populations. Methods: Spatial transcriptomics was performed on three PDAC samples from a single patient to explore cellular and genetic complexities within the tumor microenvironment. Cells were manually annotated; however, some cells remained unclassified based on stringent criteria. To address this, an XGBoost machine learning classifier was developed, utilizing differentially expressed genes from tumor cells and fibroblasts as classification features. After sample integration, the number of clusters for tumor cells and fibroblasts was calculated, resulting in the identification of three tumor clusters (T1, T2, T3) and three fibroblast clusters (F1, F2, F3). The spatial organization of these clusters was further investigated using the BuildNicheAssay function, which applies a KNN algorithm to define the local neighborhood of each cell, followed by K-means clustering to categorize cells into three spatial niches based on prior knowledge. Results: Three distinct cell niches were identified: T1F2 (the proliferating hub), T2F3 (the metabolic battery), and T3F1 (the adaptive core). Each niche displayed unique functional properties. The T1F2 niche, containing proliferating tumor cells supported by fibroblasts, was associated with enhanced tumor growth and angiogenesis. The T2F3 niche demonstrated considerable metabolic plasticity, supporting energy demands. The T3F1 niche was characterized by epithelial-mesenchymal transition (EMT)-driven tumor cells interacting with fibroblasts, coupled with WNT/β-catenin and hedgehog signaling pathways, providing insights into PDAC invasion and metastasis mechanisms. Conclusion: Our study reveals a niche-based model of PDAC progression, where specialized microenvironments contribute distinct functionalities to tumor growth and adaptation. This model enhances our understanding of PDAC heterogeneity, offering insights that may guide the development of more targeted and effective therapies.
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(Bow Valley College, 2025-02-10) Bow Valley College
At Bow Valley College, we appreciate that learners lead busy lives. This is why we take a flexible approach to your
education, one that is responsive to your needs and learning style. We have put together options that allow our learners to study with us full-time, part-time, in-class, online, or in a blended format.
The Tuniit World in Flux: A Zooarchaeological Analysis of a Late Paleo-Inuit Household in Umingmak Nuna/Ellesmere Island
(2025-01-29) Taylor, Gillian Bronwyn; Walls, Matthew; Amundsen-Meyer, Lindsay; Hayashi, Naotaka; Perić, Sabrina
This thesis explores the environmental choices and adaptive strategies of the Late Tuniit (Dorset) at the SiFi-4 site, located in Franklin Pierce Bay in northern Umingmak Nuna (Ellesmere Island). After over 3,000 years in the eastern Arctic, the Tuniit represent the culmination of generations of environmental knowledge, innovation, and experience in a challenging landscape that requires intimate knowledge and planning for periods of resource scarcity. SiFi-4, a unique site consisting of a single Late Tuniit dwelling and associated midden, represents a departure from typical Tuniit sites surrounding Pikialasorsuaq (North Water polynya) and provides a rare opportunity to study the subsistence strategies of an isolated Tuniit household at a pivotal point in time. This research involves the zooarchaeological analysis of the SiFi-4 dwelling and midden, focusing on the midden faunal remains to analyze how hunting, resource management, and environmental stewardship were practiced during this period of transformation. New radiocarbon dates suggest that SiFi-4 was occupied at the very end of the Paleo-Inuit period, contemporaneous with the arrival of Inuit ancestors in the Pikialasorsuaq area. The study offers insights into their final adaptations within their environment and reveals that, rather than passive victims of climate or social upheaval, the Tuniit made deliberate choices that reflect both a deep understanding of their environment and a proactive approach to managing resources in a changing world affected by the Medieval Warming Period, Little Ice Age, and the arrival of early Inuit and Norse in the area. The SiFi-4 site suggests a pattern of avoidance of these newcomers by this Late Tuniit family. By examining the environmental decisions made by this isolated household, this thesis sheds light on broader human-environment relationships and provides lessons on resilience and ecological creativity in the face of radical environmental and cultural change—topics highly relevant in today’s context of climate challenges.
Multiple Autonomous Vehicle Extended Reality Immersive Control Systems: A Conceptual Exploration & Empirical Evaluation
(2025-02-05) Lawton, Bryson Robert Mitchell; Maurer, Frank; Costa Sousa, Mario; Ramirez-Serrano, Alex
This research investigates the potential impacts of extended reality technologies on ground control station (GCS) interfaces for multi-vehicle operations. To do so a prototype XR software was developed, designed for multiple autonomous vehicle extended reality immersive control (MAVERIC). A usability study was then conducted to determine the comparative usability of this prototype against VCSi, a modern commercial GCS software, for accomplishing tasks in a flight route planning scenario and multi-drone management scenario. Participants' usability evaluations and feedback revealed that the prototype's XR approach offered unique advantages in enhancing spatial awareness, task performance, and user satisfaction. For both scenarios, participants perceived the MAVERIC approach as generally more intuitive as well as easier and less frustrating to use. Participants found its hands-on spatial interactions offered a more natural and intuitive approach for placing route waypoints in 3D, which they generally perceived as being faster, easier to learn, and supporting better task success compared to VCSi's desktop-style interface. Many also reported its easily scalable immersive workspaces aided situational understanding during multi-drone management workflows while also making them feel more effective at handling its complexity with less cognitive effort. Despite these strengths, limitations such as increased physical demand, ergonomic discomfort, and precise waypoint placement challenges were noted, indicating the need for iterative design improvements. Some participant feedback also indicated that cross-reality GCS interfaces could be valuable to explore, as integrating the strengths of both conventional and XR approaches may help mitigate each other's weaknesses when used together. This work's findings are hoped to inform future research in the XR and MAVERIC research domains, especially those aimed at further exploring and refining our understanding of how XR technologies may be best used to benefit the diverse civilian applications of drones and other robotic vehicles.
Collagen structure within aneurysm tissue in bicuspid aortic valve patients
(2025-01-31) Bozorgmehr, Zahra; Di Martino, Elena; Badv, Maryam; Kallos, Michael S.; Deniset, Justin
Aortic aneurysms pose a substantial clinical problem, especially in individuals with bicuspid aortic valve (BAV) disease, as aneurysm formation is 50% more common in these populations. Although the exact cause of aortic aneurysms in BAV patients is still unknown, a growing body of research points to changes in the elastin and collagen composition of the aneurysm tissue as a key component influencing the course of the disease. The purpose of this thesis is to clarify collagen's contributions to aneurysm development, progression, and clinical consequences by examining its presence and type within aneurysm tissue in BAV patients and exploring the relationship between collagen content and type and its mechanical characteristics assessed on the same tissue patients. For this purpose we followed three steps including 1) developing a protocol to extract the protein from the tissue and performing ELISA tests; 2) examining the changes in the structure of the tissue before and after the tissue processing using SEM images for a representative sample, and 3) comparing the ELISA results to the mechanical properties obtained on the same tissue specimens -same region and same layer - to explore the possible correlation between the collagen content and the mechanical properties. The analysis of collagen composition and mechanical properties on the same tissues revealed some interesting results; first of all, high Wall Shear Stress (WSS) in the greater curvature region correlated with lower collagen content in Greater Curvature (GC). Further, we found that higher collagen contents correlated with stiffness but not strength. Moreover, results for both collagen-I ɑ-2 and collagen-III showed a bimodal distribution with a clear patient effect: for each patient with a high amount of collagen-III, the amount of collagen-I ɑ-2 was also high, regardless of layer and region, suggesting that collagen deposition could be different in different patients, possibly on account of the different stage/progression of the disease, as well as differences in genetics. These findings suggest a specific collagen signature associated with aortic pathophysiology in BAV patients. Further studies should clarify whether the patient-specific differences observed are associated with disease development and if lack of collagen renewal plays a role in aneurysm progression.