{"doi":"10.1016/j.xpro.2025.104146","title":"Protocol to extract tear fluid for proteomics using Schirmer strips","abstract":"Schirmer strips are widely regarded as the gold standard for tear fluid collection. However, their use presents several challenges for proteomic analysis. Here, we present a protocol for extracting tear proteins from Schirmer strips. We describe steps for acquisition and handling of strips, extraction buffer preparation, strip preparation, and protein extraction. This protocol is designed to improve protein yield and facilitate proteomic workflows and is adaptable for various protein-based studies, particularly in the context of ocular disease research and diagnostics. • Protocol for quantifying tear volume for proteomic analysis using Schirmer strips • Procedures for protein extraction through a diffusion-based workflow • Guidance on optimizing for high-yield protein recovery and minimizing protein loss Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Schirmer strips are widely regarded as the gold standard for tear fluid collection. However, their use presents several challenges for proteomic analysis. Here, we present a protocol for extracting tear proteins from Schirmer strips. We describe steps for acquisition and handling of strips, extraction buffer preparation, strip preparation, and protein extraction. This protocol is designed to improve protein yield and facilitate proteomic workflows and is adaptable for various protein-based studies, particularly in the context of ocular disease research and diagnostics.","journal":"STAR Protocols","year":2025,"id":529102,"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":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9604,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1407875,"name":"Madhumeeta Chadha","orcid":null,"position":1,"is_corresponding":false},{"id":499043,"name":"Young Joo Sun","orcid":"0000-0002-8240-7378","position":2,"is_corresponding":false},{"id":346787,"name":"Gina Yu","orcid":null,"position":3,"is_corresponding":false},{"id":710023,"name":"Soo Hyun Lee","orcid":"0000-0001-9665-062X","position":4,"is_corresponding":false},{"id":1407369,"name":"Tsai-Chu Yeh","orcid":"0000-0002-1154-6119","position":5,"is_corresponding":false},{"id":1407370,"name":"David R.P. Almeida","orcid":"0000-0002-1742-1683","position":6,"is_corresponding":false},{"id":285420,"name":"Alexander G. Bassuk","orcid":"0000-0002-4067-2157","position":7,"is_corresponding":false},{"id":481036,"name":"Prithvi Mruthyunjaya","orcid":"0000-0003-1087-9736","position":8,"is_corresponding":false},{"id":213032,"name":"Antoine Dufour","orcid":"0000-0002-3429-4188","position":9,"is_corresponding":false},{"id":317223,"name":"Vinit B. Mahajan","orcid":"0000-0003-1886-1741","position":10,"is_corresponding":false},{"id":1387082,"name":"Gia-Han Ngo","orcid":null,"position":0,"is_corresponding":true}],"reference_count":22,"raw_metadata":null,"created_at":"2026-07-19T02:50:52.565868Z","pmid":"41108683","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":[]}