Evidence map›Paper›PMID 37886549›Full record

ArticleResearch square2023

Molecular fingerprinting of biological nanoparticles with a label-free optofluidic platform.

Alexia Stollmann, Jose Garcia-Guirado, Jae-Sang Hong, Hyungsoon Im, Hakho Lee, Jaime Ortega Arroyo, Romain Quidant

Abstract readPreprint
In one paragraph

Article in Research square, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Alexia StollmannNanophotonic Systems Laboratory, Department of Mechanical and Process Engineering, ETH Zurich, 8092 Zurich, Switzerland.
Jose Garcia-GuiradoNanophotonic Systems Laboratory, Department of Mechanical and Process Engineering, ETH Zurich, 8092 Zurich, Switzerland.
Jae-Sang HongCenter for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts 02114, United States.
Hyungsoon ImCenter for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts 02114, United States.ORCID 0000-0002-0626-1346
Hakho LeeCenter for Systems Biology, Massachusetts General Hospital, Boston, Massachusetts 02114, United States.ORCID 0000-0002-0087-0909
Jaime Ortega ArroyoNanophotonic Systems Laboratory, Department of Mechanical and Process Engineering, ETH Zurich, 8092 Zurich, Switzerland.ORCID 0000-0002-0657-051X
Romain QuidantNanophotonic Systems Laboratory, Department of Mechanical and Process Engineering, ETH Zurich, 8092 Zurich, Switzerland.

Funding

Early Detection through Novel OCEAN Technology - Ovarian Cancer Exosomal Analysis with NanoplasmonicsU01CA233360 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI CASTRO, CESAR M, DINULESCU, DANIELA M · 2018 to 2022
$3.5M
Clinical platform for high-throughput analyses of extracellular vesiclesR01CA229777 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI LEE, HAKHO, SKOG, JOHAN · 2018 to 2022
$3.2M
Imaging and Liquid Biopsy for Glioma Diagnosis and Treatment MonitoringR01CA239078 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI BALAJ, LEONORA, LEE, HAKHO · 2020 to 2024
$3.1M
Standardized Molecular Analyses of Glioma EVsR01CA237500 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI CARTER, BOB S, LEE, HAKHO · 2020 to 2024
$3.0M
High throughput nanoplasmonic exosome testing (NEXT) of immunotherapies in bladder cancerR01CA264363 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI CASTRO, CESAR M, LEE, HAKHO · 2021 to 2024
$2.4M
Development of plasmon-enhanced biosensing for multiplexed profiling of extracellular vesiclesR01GM138778 · NIGMS · MASSACHUSETTS GENERAL HOSPITAL · PI IM, HYUNGSOON · 2020 to 2024
$2.3M
3D Fourier Imaging System for High Throughput Analyses of Cancer OrganoidsR21CA267222 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI LEE, HAKHO · 2022 to 2024
$613k
Nano-plasmonic technology for high-throughput single exosome analysesR21CA217662 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI IM, HYUNGSOON · 2019 to 2021
$585k
NCI NIH HHS R01 CA229777NCI NIH HHS R01 CA237500NCI NIH HHS R01 CA239078NCI NIH HHS R01 CA264363NCI NIH HHS R21 CA217662NCI NIH HHS R21 CA267222NCI NIH HHS U01 CA233360NIGMS NIH HHS R01 GM138778
6 · The paper itself

Abstract

Label-free detecting multiple analytes in a high-throughput fashion has been one of the long-sought goals in biosensing applications. Yet, for all-optical approaches, interfacing state-of-the-art label-free techniques with microfluidics tools that can process small volumes of sample with high throughput, and with surface chemistry that grants analyte specificity, poses a critical challenge to date. Here, we introduce an optofluidic platform that brings together state-of-the-art digital holography with PDMS microfluidics by using supported lipid bilayers as a surface chemistry building block to integrate both technologies. Specifically, this platform fingerprints heterogeneous biological nanoparticle populations via a multiplexed label-free immunoaffinity assay with single particle sensitivity. Herein, we first thoroughly characterise the robustness and performance of the platform, and then apply it to profile four distinct ovarian cell-derived extracellular vesicle populations over a panel of surface protein biomarkers, thus developing a unique biomarker fingerprint for each cell line. We foresee that our approach will find many applications where routine and multiplexed characterisation of biological nanoparticles is required.

Indexed as

Extracellular vesiclesholographyimmunoassayslabel-free imagingmicrofluidicsmultiplexingsupported lipid bilayer

Identifiers

PMID37886549
PMCPMC10602063

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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.