{"doi":"10.4049/jimmunol.204.supp.148.42","title":"High dimensional cellular profiling of the myeloid compartment in the geriatric mouse model","abstract":"<jats:title>Abstract</jats:title>\n               <jats:p>Aging, and age-related physiological changes, have been heavily implicated in declining immune functions. Many of these changes to the immune system include changes to the myeloid subsets, which have been poorly studied so far. Myeloid cells play crucial roles in acute infection and are involved in antigen presentation to cells of the adaptive immune system. Consequently, deciphering these age-related mechanisms holds great potential for targeting age-related changes in immunity. Here, we developed a model to map age related phenotypic changes in the myeloid compartment in all immunologically relevant murine organs. Using mass cytometry analysis (CyTOF), we assessed over 35 cell surface parameters on myeloid cells using a geriatric healthy mouse model. Results indicates age-related changes affecting the frequency and cell surface density of lineage markers on myeloid cells. Concretely, we see significant changes to cellular frequencies and marker expression within various resident myeloid populations, and exemplar organs will be presented here. Such age-related patterns may contribute to the impaired immune decline observed in aging. We are currently continually expanding this study and will validate the implications of these findings using spectral flow cytometry analysis.</jats:p>","journal":"The Journal of Immunology","year":2020,"id":595561,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":71117,"name":"Florian Ingelfinger","orcid":"0000-0001-6890-9753","position":1,"is_corresponding":false},{"id":1460387,"name":"Ekaterina Friebel","orcid":"0000-0003-1419-2376","position":2,"is_corresponding":false},{"id":1525107,"name":"Dilay Cansever","orcid":null,"position":3,"is_corresponding":false},{"id":65555,"name":"Burkhard Becher","orcid":"0000-0002-1541-7867","position":4,"is_corresponding":false},{"id":1525100,"name":"Sinduya Krishnarajah","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"High dimensional cellular profiling of the myeloid compartment in the geriatric mouse model","abstract":"<jats:title>Abstract</jats:title>\n               <jats:p>Aging, and age-related physiological changes, have been heavily implicated in declining immune functions. Many of these changes to the immune system include changes to the myeloid subsets, which have been poorly studied so far. Myeloid cells play crucial roles in acute infection and are involved in antigen presentation to cells of the adaptive immune system. Consequently, deciphering these age-related mechanisms holds great potential for targeting age-related changes in immunity. Here, we developed a model to map age related phenotypic changes in the myeloid compartment in all immunologically relevant murine organs. Using mass cytometry analysis (CyTOF), we assessed over 35 cell surface parameters on myeloid cells using a geriatric healthy mouse model. Results indicates age-related changes affecting the frequency and cell surface density of lineage markers on myeloid cells. Concretely, we see significant changes to cellular frequencies and marker expression within various resident myeloid populations, and exemplar organs will be presented here. Such age-related patterns may contribute to the impaired immune decline observed in aging. We are currently continually expanding this study and will validate the implications of these findings using spectral flow cytometry analysis.</jats:p>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"21097893","pmcid":null,"openalex_id":"https://openalex.org/W4313373161","authors":[],"funders":[],"total_grants":0,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"closed","license":"https://academic.oup.com/pages/standard-publication-reuse-rights","oa_locations":[{"url":"https://academic.oup.com/jimmunol/article/204/1_Supplement/148.42/7948506","host_type":"publisher"},{"url":"https://doi.org/10.4049/jimmunol.204.supp.148.42","host_type":"journal"}],"fields_of_study":["Immune cells in cancer","Neuroinflammation and Neurodegeneration Mechanisms","Single-cell and spatial transcriptomics"],"mesh_terms":[],"keywords":["Myeloid","Immune system","Myeloid cells","Mass cytometry","Biology","Immunosenescence","Phenotype","Immunology","Compartment (ship)","Flow cytometry","Acquired immune system","Cell biology","Genetics","Gene"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Good health and well-being"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-27T17:38:10.284668Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}