{"doi":"10.3390/cells11152367","title":"Aberrant Expression of COX-2 and FOXG1 in Infrapatellar Fat Pad-Derived ASCs from Pre-Diabetic Donors","abstract":"Osteoarthritis (OA) is a degenerative joint disease resulting in limited mobility and severe disability. Type II diabetes mellitus (T2D) is a weight-independent risk factor for OA, but a link between the two diseases has not been elucidated. Adipose stem cells (ASCs) isolated from the infrapatellar fat pad (IPFP) may be a viable regenerative cell for OA treatment. This study analyzed the expression profiles of inflammatory and adipokine-related genes in IPFP-ASCs of non-diabetic (Non-T2D), pre-diabetic (Pre-T2D), and T2D donors. Pre-T2D ASCs exhibited a substantial decrease in levels of mesenchymal markers CD90 and CD105 with no change in adipogenic differentiation compared to Non-T2D and T2D IPFP-ASCs. In addition, Cyclooxygenase-2 (COX-2), Forkhead box G1 (FOXG1) expression and prostaglandin E2 (PGE2) secretion were significantly increased in Pre-T2D IPFP-ASCs upon stimulation by interleukin-1 beta (IL-1β). Interestingly, M1 macrophages exhibited a significant reduction in expression of pro-inflammatory markers TNFα and IL-6 when co-cultured with Pre-T2D IPFP-ASCs. These data suggest that the heightened systemic inflammation associated with untreated T2D may prime the IPFP-ASCs to exhibit enhanced anti-inflammatory characteristics via suppressing the IL-6/COX-2 signaling pathway. In addition, the elevated production of PGE2 by the Pre-T2D IPFP-ASCs may also suggest the contribution of pre-diabetic conditions to the onset and progression of OA.","journal":"Cells","year":2022,"id":266641,"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":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9571,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":470707,"name":"Tia Monjure","orcid":null,"position":1,"is_corresponding":false},{"id":470014,"name":"Sara Al‐Ghadban","orcid":"0000-0001-8544-5751","position":2,"is_corresponding":false},{"id":470706,"name":"Clara Ives","orcid":null,"position":3,"is_corresponding":false},{"id":470015,"name":"Michael L’Ecuyer","orcid":"0000-0002-1316-603X","position":4,"is_corresponding":false},{"id":357205,"name":"Claire Rhee","orcid":null,"position":5,"is_corresponding":false},{"id":355414,"name":"Mónica Romero-López","orcid":"0000-0003-0148-6033","position":6,"is_corresponding":false},{"id":230912,"name":"Zhong Li","orcid":"0000-0002-6009-629X","position":7,"is_corresponding":false},{"id":231542,"name":"Stuart B. Goodman","orcid":"0000-0002-1919-3717","position":8,"is_corresponding":false},{"id":230915,"name":"Hang Lin","orcid":"0000-0002-0781-6630","position":9,"is_corresponding":false},{"id":230916,"name":"Rocky S. Tuan","orcid":"0000-0001-6067-6705","position":10,"is_corresponding":false},{"id":282160,"name":"Bruce A. Bunnell","orcid":"0000-0001-6196-3722","position":11,"is_corresponding":false},{"id":355416,"name":"Benjamen O’Donnell","orcid":"0000-0002-3529-231X","position":0,"is_corresponding":true}],"reference_count":66,"raw_metadata":null,"created_at":"2026-07-19T00:26:58.102271Z","pmid":"35954211","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":[]}