{"id":{"repo_id":"ku","oai_identifier":"oai:kuscholarworks.ku.edu:1808/37890"},"canonical_url":"https://search.dev.ndltd.org/etd/ku/oai:kuscholarworks.ku.edu:1808/37890","repository":{"repo_id":"ku","name":"University of Kansas","base_url":"https://kuscholarworks.ku.edu/server/oai/request"},"display":{"title":"Heterogeneity of Lymph Node Stromal Cells: Bridging the Gap Between Common Practice and New Understandings","abstract":"Lymph Nodes are some of the most important organs in the body due to their ability to filter lymph and house the adaptive immune response. Without them, lymph would not drain from extremities, causing swelling, and lymphocytes would struggle to find matching receptors for activation. Historically, methods to replicate lymph node function in-vitro have focused on the immune cells and not the stromal cells that surround them. In this work, I describe the design challenges facing engineers as they attempt to build a functional lymph node. These challenges revolve around the complexity of structure, function, and interactions between cells, but could be resolved by focusing our research on Lymph Node Stromal Cells (LNSCs). Upon generating my own cell line of LNSCs, I demonstrate an issue with the most common method to identify them: they are heterogeneous populations, so using only three markers for identification fails to properly describe the population being reported on. I also show that the ratio of subpopulations shifts over time, so a full identification early on may not reflect the population being used in experiments. To bridge this gap, I explore a way to use flow cytometry to compare populations at two different time points and glean information about their heterogeneity. I demonstrate how this method can identify shifts in subpopulations and inform future experimental designs. New subpopulations of these cells continue to be discovered and added to a list of populations with a diverse array of functions. Some of these functions, such as extracellular matrix production and self-organization, were observed in this work. By generating a cell line that contains the level of heterogeneity found in lymph nodes, we could have the key to recreating lymph node function in-vitro.","abstract_html":"Lymph Nodes are some of the most important organs in the body due to their ability to filter lymph and house the adaptive immune response. Without them, lymph would not drain from extremities, causing swelling, and lymphocytes would struggle to find matching receptors for activation. Historically, methods to replicate lymph node function in-vitro have focused on the immune cells and not the stromal cells that surround them. In this work, I describe the design challenges facing engineers as they attempt to build a functional lymph node. These challenges revolve around the complexity of structure, function, and interactions between cells, but could be resolved by focusing our research on Lymph Node Stromal Cells (LNSCs). Upon generating my own cell line of LNSCs, I demonstrate an issue with the most common method to identify them: they are heterogeneous populations, so using only three markers for identification fails to properly describe the population being reported on. I also show that the ratio of subpopulations shifts over time, so a full identification early on may not reflect the population being used in experiments. To bridge this gap, I explore a way to use flow cytometry to compare populations at two different time points and glean information about their heterogeneity. I demonstrate how this method can identify shifts in subpopulations and inform future experimental designs. New subpopulations of these cells continue to be discovered and added to a list of populations with a diverse array of functions. Some of these functions, such as extracellular matrix production and self-organization, were observed in this work. By generating a cell line that contains the level of heterogeneity found in lymph nodes, we could have the key to recreating lymph node function in-vitro.","abstract_has_math":false,"creators":["Heon, Mikala Esther-May"],"institution":"University of Kansas","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Rosa-Molinar, Eduardo","Shontz, Suzanne M."],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-08-31","date_published":"2025-08-31","updated_at":"2026-07-24T02:45:07Z","subjects":["Bioengineering","Bioinformatics","Immunology","Cell Heterogeneity","Flow Cytometry","Lymph Node","Lymph Node Stromal Cells","Tissue Engineering"],"languages":["en"],"rights":["This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["https://www.proquest.com/LegacyDocView/DISSNUM/32168399"],"render_values":[{"text":"https://www.proquest.com/LegacyDocView/DISSNUM/32168399","href":"https://www.proquest.com/LegacyDocView/DISSNUM/32168399","code":true}]}]},"links":{"outbound_url":"https://hdl.handle.net/1808/37890","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Rosa-Molinar, Eduardo","Shontz, Suzanne M."]},{"key":"dc:creator","label":"Author","values":["Heon, Mikala Esther-May"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2026-04-21T21:34:21Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2026-04-21T21:34:21Z"]},{"key":"dc:date.issued","label":"Date","values":["2025-08-31"]},{"key":"dc:publisher","label":"Institution","values":["University of Kansas"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Bioengineering","Bioinformatics","Immunology","Cell Heterogeneity","Flow Cytometry","Lymph Node","Lymph Node Stromal Cells","Tissue Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["This item is protected by copyright and unless otherwise specified the copyright of this thesis/dissertation is held by the author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["https://www.proquest.com/LegacyDocView/DISSNUM/32168399"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/1808/37890"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Lymph Nodes are some of the most important organs in the body due to their ability to filter lymph and house the adaptive immune response. Without them, lymph would not drain from extremities, causing swelling, and lymphocytes would struggle to find matching receptors for activation. Historically, methods to replicate lymph node function in-vitro have focused on the immune cells and not the stromal cells that surround them. In this work, I describe the design challenges facing engineers as they attempt to build a functional lymph node. These challenges revolve around the complexity of structure, function, and interactions between cells, but could be resolved by focusing our research on Lymph Node Stromal Cells (LNSCs). Upon generating my own cell line of LNSCs, I demonstrate an issue with the most common method to identify them: they are heterogeneous populations, so using only three markers for identification fails to properly describe the population being reported on. I also show that the ratio of subpopulations shifts over time, so a full identification early on may not reflect the population being used in experiments. To bridge this gap, I explore a way to use flow cytometry to compare populations at two different time points and glean information about their heterogeneity. I demonstrate how this method can identify shifts in subpopulations and inform future experimental designs. New subpopulations of these cells continue to be discovered and added to a list of populations with a diverse array of functions. Some of these functions, such as extracellular matrix production and self-organization, were observed in this work. By generating a cell line that contains the level of heterogeneity found in lymph nodes, we could have the key to recreating lymph node function in-vitro."]},{"key":"dc:title","label":"Title","values":["Heterogeneity of Lymph Node Stromal Cells: Bridging the Gap Between Common Practice and New Understandings"]}]}],"canonical_facts":{"dc:contributor.advisor":["Rosa-Molinar, Eduardo","Shontz, Suzanne M."],"dc:creator":["Heon, Mikala Esther-May"],"dc:date.accessioned":["2026-04-21T21:34:21Z"],"dc:date.available":["2026-04-21T21:34:21Z"],"dc:date.issued":["2025-08-31"],"dc:description.abstract":["Lymph Nodes are some of the most important organs in the body due to their ability to filter lymph and house the adaptive immune response. Without them, lymph would not drain from extremities, causing swelling, and lymphocytes would struggle to find matching receptors for activation. Historically, methods to replicate lymph node function in-vitro have focused on the immune cells and not the stromal cells that surround them. In this work, I describe the design challenges facing engineers as they attempt to build a functional lymph node. These challenges revolve around the complexity of structure, function, and interactions between cells, but could be resolved by focusing our research on Lymph Node Stromal Cells (LNSCs). Upon generating my own cell line of LNSCs, I demonstrate an issue with the most common method to identify them: they are heterogeneous populations, so using only three markers for identification fails to properly describe the population being reported on. I also show that the ratio of subpopulations shifts over time, so a full identification early on may not reflect the population being used in experiments. To bridge this gap, I explore a way to use flow cytometry to compare populations at two different time points and glean information about their heterogeneity. I demonstrate how this method can identify shifts in subpopulations and inform future experimental designs. New subpopulations of these cells continue to be discovered and added to a list of populations with a diverse array of functions. Some of these functions, such as extracellular matrix production and self-organization, were observed in this work. 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