Evidence map›Paper›PMID 31040661›Full record

ArticleInternational journal of nanomedicine2019

Optical fiber-based sensing method for nanoparticle detection through supervised back-scattering analysis: a potential contributor for biomedicine.

Joana S Paiva, Pedro A S Jorge, Rita S R Ribeiro, Paula Sampaio, Carla C Rosa, João P S Cunha

Open access · goldAbstract read
In one paragraph

Article in International journal of nanomedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 39% of its field
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

3 citing papers in PubMed, 11 citations in OpenAlex.

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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

6 authors at 2 institutions in 2 countries.

Joana S PaivaINESC Technology and Science, Porto, Portugal, jipaiva@inesctec.pt.
Pedro A S JorgeINESC Technology and Science, Porto, Portugal, jipaiva@inesctec.pt.
Rita S R RibeiroINESC Technology and Science, Porto, Portugal, jipaiva@inesctec.pt.
Paula SampaioInstitute for Molecular and Cell Biology, i3S - Institute for Innovation and Research in Health, Porto, Portugal.
Carla C RosaINESC Technology and Science, Porto, Portugal, jipaiva@inesctec.pt.
João P S CunhaINESC Technology and Science, Porto, Portugal, jipaiva@inesctec.pt.
Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento · PTInstitut de Biologie Moléculaire et Cellulaire · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn view of the growing importance of nanotechnologies, the detection/identification of nanoparticles type has been considered of utmost importance. Although the characterization of synthetic/organic nanoparticles is currently considered a priority (eg, drug delivery devices, nanotextiles, theranostic nanoparticles), there are many examples of "naturally" generated nanostructures - for example, extracellular vesicles (EVs), lipoproteins, and virus - that provide useful information about human physiology or clinical conditions. For example, the detection of tumor-related exosomes, a specific type of EVs, in circulating fluids has been contributing to the diagnosis of cancer in an early stage. However, scientists have struggled to find a simple, fast, and low-cost method to accurately detect/identify these nanoparticles, since the majority of them have diameters between 100 and 150 nm, thus being far below the diffraction limit.

methodsThis study investigated if, by projecting the information provided from short-term portions of the back-scattered laser light signal collected by a polymeric lensed optical fiber tip dipped into a solution of synthetic nanoparticles into a lower features dimensional space, a discriminant function is able to correctly detect the presence of 100 nm synthetic nanoparticles in distilled water, in different concentration values. RESULTS AND DISCUSSION: This technique ensured an optimal performance (100% accuracy) in detecting nanoparticles for a concentration above or equal to 3.89 µg/mL (8.74E+10 particles/mL), and a performance of 90% for concentrations below this value and higher than 1.22E-03 µg/mL (2.74E+07 particles/mL), values that are compatible with human plasmatic levels of tumor-derived and other types of EVs, as well as lipoproteins currently used as potential biomarkers of cardiovascular diseases.

conclusionThe proposed technique is able to detect synthetic nanoparticles whose dimensions are similar to EVs and other "clinically" relevant nanostructures, and in concentrations equivalent to the majority of cell-derived, platelet-derived EVs and lipoproteins physiological levels. This study can, therefore, provide valuable insights towards the future development of a device for EVs and other biological nanoparticles detection with innovative characteristics.

Indexed as

Optical FibersBiomedical TechnologyBiosensing TechniquesDiscriminant AnalysisExosomesExtracellular VesiclesFourier AnalysisHumansNanoparticlesPolymersSolutionsPolymersSolutionsBrownian motiondiffusive analysisextracellular vesicles (EVs) detectionlight scattering effectslipoproteins detectionnanoparticlesnanoparticles detectionoptical fiber sensorsvirus detection

Identifiers

PMID31040661
PMCPMC6452810
OpenAlexW2934764925

What OpenQuestion holds

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LicenceCC BY-NC
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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.