Evidence map›Paper›PMID 39248229›Full record

ArticleJournal of cosmetic dermatology2024

Preparation and In Vitro Evaluation of Protective Effects of Quercetin-Loaded Solid Lipid Nanoparticles on Human Hair Against UV-B Radiation.

Anayatollah Salimi, Behzad Sharif Makhmalzadeh, Mandana Salahshoori

Abstract read
In one paragraph

Article in Journal of cosmetic dermatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Anayatollah SalimiNanotechnology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, IR Iran.ORCID https://orcid.org/0000-0003-1505-7969
Behzad Sharif MakhmalzadehNanotechnology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, IR Iran.ORCID https://orcid.org/0000-0002-1441-3127
Mandana SalahshooriNanotechnology Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, IR Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this study was to investigate the protective effect of quercetin loaded on solid lipid nanoparticles (SLN) in protecting human hair from ultraviolet-B (UV-B) light in vitro.

methodsIn this study, solvent-emulsified diffusion method was used to fabricate nanoparticle formulations and then particle size, loading, and drug release tests were performed from different formulations. Variables include oily part proportion, liquid to solid oil part ratio, and surfactant to lipid ratio. The optimal formulation was prepared by examining the eight formulations and optimizing them. Six groups of hair with different treatments were exposed to UV light for 600 h and the changes were investigated by examining four factors: RMS (root mean square average, the microscopic profile peaks and valleys), peak to valley roughness, the amount of chemical changes by Fourier transform infrared spectroscopy (FTIR), and the amount of protein loss.

resultsThe selected formulation had a suitable particle size, loading percent, and release rate for penetration to hair. Quercetin-loaded SLN controlled RMS factor, peak to valley roughness, and reduced chemical changes and protein loss compared to other treatments.

conclusionThe optimize formulation showed positive effects in protecting the hair strands from UV-B radiation.

Indexed as

HairNanoparticlesParticle SizeQuercetinUltraviolet RaysDrug LiberationHumansIn Vitro TechniquesLipidsLiposomesSpectroscopy, Fourier Transform InfraredLipid NanoparticlesLipidsLiposomesQuercetinhairquercetinSLNUV‐B radiation

Identifiers

PMID39248229
PMCPMC11626359

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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.