{"doi":"10.1063/5.0218986","title":"Extracellular vesicle and lipoprotein diagnostics (ExoLP-Dx) with membrane sensor: A robust microfluidic platform to overcome heterogeneity","abstract":"The physiological origins and functions of extracellular vesicles (EVs) and lipoproteins (LPs) propel advancements in precision medicine by offering non-invasive diagnostic and therapeutic prospects for cancers, cardiovascular, and neurodegenerative diseases. However, EV/LP diagnostics (ExoLP-Dx) face considerable challenges. Their intrinsic heterogeneity, spanning biogenesis pathways, surface protein composition, and concentration metrics complicate traditional diagnostic approaches. Commonly used methods such as nanoparticle tracking analysis, enzyme-linked immunosorbent assay, and nuclear magnetic resonance do not provide any information about their proteomic subfractions, including active proteins/enzymes involved in essential pathways/functions. Size constraints limit the efficacy of flow cytometry for small EVs and LPs, while ultracentrifugation isolation is hampered by co-elution with non-target entities. In this perspective, we propose a charge-based electrokinetic membrane sensor, with silica nanoparticle reporters providing salient features, that can overcome the interference, long incubation time, sensitivity, and normalization issues of ExoLP-Dx from raw plasma without needing sample pretreatment/isolation. A universal EV/LP standard curve is obtained despite their heterogeneities.","journal":"Biomicrofluidics","year":2024,"id":440812,"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":0.9554,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":361515,"name":"Satyajyoti Senapati","orcid":"0000-0001-7999-1561","position":1,"is_corresponding":false},{"id":361516,"name":"Hsueh‐Chia Chang","orcid":"0000-0003-2147-9260","position":2,"is_corresponding":false},{"id":1059210,"name":"Sonu Kumar","orcid":"0000-0001-8983-3647","position":0,"is_corresponding":true}],"reference_count":170,"raw_metadata":null,"created_at":"2026-07-19T02:01:01.842286Z","pmid":"39056024","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":[]}