Evidence map›Paper›PMID 36116117›Full record

ArticleChemistry (Weinheim an der Bergstrasse, Germany)2022

Correct Identification of the Core-Shell Structure of Cell Membrane-Coated Polymeric Nanoparticles.

Lizhi Liu, Wei Yu, Jani Seitsonen, Wujun Xu, Vesa-Pekka Lehto

Abstract read
In one paragraph

Article in Chemistry (Weinheim an der Bergstrasse, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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  8. Printable and Antiferromagnetic Mn(OH)Chemistry of materials : a publication of the American Chemical Society · 2026
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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

5 authors.

Lizhi LiuDepartment of Applied Physics, University of Eastern Finland, 70210, Kuopio, Finland.ORCID http://orcid.org/0000-0003-4206-4558
Wei YuGanjiang Chinese Medicine Innovation Center, Nanchang, 330000, China.
Jani SeitsonenNanomicroscopy Center Department of Applied Physics, Aalto University PO BOX 11000, FI-00076 Aalto, Espoo, Finland.
Wujun XuDepartment of Applied Physics, University of Eastern Finland, 70210, Kuopio, Finland.
Vesa-Pekka LehtoDepartment of Applied Physics, University of Eastern Finland, 70210, Kuopio, Finland.ORCID http://orcid.org/0000-0001-8153-1070

Funding

Academy of Finland 314412Ganjiang New Area: Program for High-Level Talents Introduction
6 · The paper itself

Abstract

Transmission electron microscopy (TEM) observations of negatively stained cell membrane (CM)-coated polymeric nanoparticles (NPs) reveal a characteristic core-shell structure. However, negative staining agents can create artifacts that complicate the determination of the actual NP structure. Herein, it is demonstrated with various bare polymeric core NPs, such as poly(lactic-co-glycolic acid) (PLGA), poly(ethylene glycol) methyl ether-block-PLGA, and poly(caprolactone), that certain observed core-shell structures are actually artifacts caused by the staining process. To address this issue, fluorescence quenching was applied to quantify the proportion of fully coated NPs and statistical TEM analysis was used to identify and differentiate whether the observed core-shell structures of CM-coated PLGA (CM-PLGA) NPs are due to artifacts or to the CM coating. Integrated shells in TEM images of negatively stained CM-PLGA NPs are identified as artifacts. The present results challenge current understanding of the structure of CM-coated polymeric NPs and encourage researchers to use the proposed characterization approach to avoid misinterpretations.

Indexed as

Cell Membraneartifactscell membrane coatingcore-shell structurenegative stainingpolymeric nanoparticles

Identifiers

PMID36116117
PMCPMC10091812

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Registered trials

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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.