Evidence map›Paper›PMID 33850948›Full record

ArticleIranian journal of biotechnology2020

Facile Method for Morphological Characterization at Nano Scale.

Ali Dinari, Seyedeh Sahar Mortazavi Farsani, Soheila Mohammadi, Farhood Najafi, Mahdi Abdollahi

Abstract read
In one paragraph

Article in Iranian journal of biotechnology, 2020. 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
–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

3 citing papers in PubMed.

  1. Article
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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.

Ali DinariPolymer Reaction Engineering Department, Faculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran.
Seyedeh Sahar Mortazavi FarsaniDepartment of Genetics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran.
Soheila MohammadiNano Drug Delivery Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Farhood NajafiDepartment of Resin and Additives, Institute for Color Science and Technology, Tehran, Iran.
Mahdi AbdollahiPolymer Reaction Engineering Department, Faculty of Chemical Engineering, Tarbiat Modares University, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDynamic light scattering (DLS) and electron microscopy (EM) are the most practical techniques for nanoparticles (NPs) characterization. However, the impediments which involved the sample preparation method lead to failure in provided results of mentioned device analysis. These problems will be intensifying, if the examined samples are the soft nanocarriers such as organic ones or biological samples.

objectivesIn order to achieve the appropriate results from DLS and EM analysis, an optimized protocol was introduced by this research which would prepare samples with high degree of quality and accuracy. MATERIALS AND

methodsMorphological analysis of prepared polymeric nanocarriers (micelles, nanogels) by this protocol were done. Filtration, dilution and sonication as three crucial and effectiveness steps of sample preparation were assessed through DLS data and EM images.

resultsThis research has tried to introduce a facile method with novelty of simplicity and rapidity. These triple steps could improve the quality of morphological data. The obtained results indicated that sample preparation methods have the most effective factors on sample size distribution and homogeneity of desired samples.

conclusionThe suggested optimized preparation method will be helpful for all soft nanomaterial's samples.

Indexed as

Dynamic light scattering (DLS), EMSoft nanocarriersTriple steps

Identifiers

PMID33850948
PMCPMC8035413

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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.