Evidence map›Paper›PMID 34835843›Full record

ArticleNanomaterials (Basel, Switzerland)2021

Quantitative Estimation of Cell-Associated Silver Nanoparticles using the Normalized Side Scattering Intensities of Flow Cytometry.

Yoo Jin Shim, My Kieu Ha, Tae Hyun Yoon

Open access · goldAbstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2021. 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
0.5field-weighted citation impact, top 42% 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, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

3 authors at 2 institutions in 1 country.

Yoo Jin ShimDepartment of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea.
My Kieu HaDepartment of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea.
Tae Hyun YoonDepartment of Chemistry, College of Natural Sciences, Hanyang University, Seoul 04763, Korea.ORCID 0000-0002-2743-6360
Hanyang University · KRHanyang Cyber University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantification of cellular nanoparticles (NPs) is one of the most important steps in studying NP-cell interactions. Here, a simple method for the estimation of cell-associated silver (Ag) NPs in lung cancer cells (A549) is proposed based on their side scattering (SSC) intensities measured by flow cytometry (FCM). To estimate cellular Ag NPs associated with A549 cells over a broad range of experimental conditions, we measured the normalized SSC intensities (nSSC) of A549 cells treated with Ag NPs with five different core sizes (i.e., 40-200 nm, positively charged) under various exposure conditions that reflect different situations of agglomeration, diffusion, and sedimentation in cell culture media, such as upright and inverted configurations with different media heights. Then, we correlated these nSSC values with the numbers of cellular Ag NPs determined by inductively coupled plasma mass spectrometry (ICPMS) as a well-established cross-validation method. The different core sizes of Ag NPs and the various exposure conditions tested in this study confirmed that the FCM-SSC intensities are highly correlated with their core sizes as well as the amount of cellular Ag NPs over a linear range up to ~80,000 Ag NPs/cell and ~23 nSSC, which is significantly broader than those of previous studies.

Indexed as

cellular association of nanoparticlesflow cytometrysilver nanoparticles

Identifiers

PMID34835843
PMCPMC8619494
OpenAlexW3213558942

What OpenQuestion holds

Textmetadata
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.