Evidence map›Paper›PMID 39804668›Full record

ArticleAnalytical chemistry2025

Single Extracellular VEsicle Nanoscopy-Universal Protocol (SEVEN-UP): Accessible Imaging Platform for Quantitative Characterization of Single Extracellular Vesicles.

Andras Saftics, Benjamin Purnell, Balint Beres, S Thompson, Nan Jiang, Ima Ghaeli, Carinna Lima, Brian Armstrong, Kendall Van Keuren-Jensen, Tijana Jovanovic-Talisman

Abstract read
In one paragraph

Article in Analytical chemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Andras SafticsDepartment of Cancer Biology and Molecular Medicine, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, California 91010, United States.ORCID 0000-0001-7129-6142
Benjamin PurnellDepartment of Cancer Biology and Molecular Medicine, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, California 91010, United States.
Balint BeresDepartment of Cancer Biology and Molecular Medicine, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, California 91010, United States.
S ThompsonDepartment of Cancer Biology and Molecular Medicine, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, California 91010, United States.
Nan JiangDepartment of Cancer Biology and Molecular Medicine, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, California 91010, United States.
Ima GhaeliDepartment of Cancer Biology and Molecular Medicine, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, California 91010, United States.
Carinna LimaDepartment of Cancer Biology and Molecular Medicine, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, California 91010, United States.
Brian ArmstrongLight Microscopy/Digital Imaging Core, City of Hope Comprehensive Cancer Center, Duarte, California 91010, United States.
Kendall Van Keuren-JensenNeurogenomics Division, Translational Genomics Research Institute, Phoenix, Arizona 85004, United States.
Tijana Jovanovic-TalismanDepartment of Cancer Biology and Molecular Medicine, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, California 91010, United States.ORCID 0000-0003-1928-4763

Funding

Transgenic Mouse FacilityP30CA033572 · NCI · CITY OF HOPE/BECKMAN RESEARCH INSTITUTE · PI John Charles Williams · 1985 to 2026
$86.3M
Molecular dissection and imaging of extracellular vesicles to define their origin and targetsUH3TR002878 · NCATS · MASSACHUSETTS GENERAL HOSPITAL · PI DAS, SAUMYA, TALISMAN, TIJANA · 2021 to 2022
$2.2M
Molecular dissection and imaging of extracellular vesicles to define their origin and targetsUG3TR002878 · NCATS · MASSACHUSETTS GENERAL HOSPITAL · PI DAS, SAUMYA, TALISMAN, TIJANA · 2019 to 2020
$939k
DIABETES PREVENTION / RISK / OMICS / METABOLISM / THERAPY (PROMT) INTERDISCIPLINARY TRAININGT32DK131943 · NIDDK · BECKMAN RESEARCH INSTITUTE/CITY OF HOPE · PI RAMA NATARAJAN, Debbie C Thurmond · 2023 to 2026
$478k
NCATS NIH HHS UG3 TR002878NCATS NIH HHS UH3 TR002878NCI NIH HHS P30 CA033572NIDDK NIH HHS T32 DK131943
6 · The paper itself

Abstract

Extracellular vesicles (EVs), membrane-encapsulated nanoparticles shed from all cells, are tightly involved in critical cellular functions. Moreover, EVs have recently emerged as exciting therapeutic modalities, delivery vectors, and biomarker sources. However, EVs are difficult to characterize, because they are typically small and heterogeneous in size, origin, and molecular content. Recent advances in single EV methods have addressed some of these challenges by providing sensitive tools for assessing individual vesicles; one example is our recently developed Single Extracellular VEsicle Nanoscopy (SEVEN) approach. However, these tools are typically not universally available to the general research community, as they require highly specialized equipment. Here, we show how single EV studies may be democratized via a novel method that employs super-resolution radial fluctuations (SRRF) microscopy and advanced data analysis. SRRF is compatible with a wide range of microscopes and fluorophores. We herein quantified individual EVs by combining affinity isolation (analytical protocol based on SEVEN) with SRRF microscopy and new analysis algorithms supported by machine learning-based EV assessment. Using SEVEN, we first optimized the workflow and validated the data obtained on wide-field and total internal reflection fluorescence microscopes. We further demonstrated that our approach, which we call the SEVEN-Universal Protocol (SEVEN-UP), can robustly assess the number, size, and content of plasma and recombinant EVs. Finally, we used the platform to assess RNA in EVs from conditioned cell culture media. Using SYTO RNASelect dye, we found that 18% of EVs from HEK 293T cells appear to contain RNA; these EVs were significantly larger compared with the general EV population. Altogether, we developed an economical, multiparametric, single EV characterization approach for the research community.

Indexed as

Extracellular VesiclesHumansMicroscopy, Fluorescence

Identifiers

PMID39804668
PMCPMC11780574

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.