Evidence map›Paper›PMID 40703002›Full record

ArticleJournal of cellular and molecular medicine2025

Niosomal Hydrogel Loaded With Bromelain: A Promising Solution for Reducing Skin Collagen in Scleroderma Patients.

Hanieh Ardeshiri, Mina Ghorbani, Mohammad Ali Nazarinia, Kimia Falamarzi, Ali Mohammad Tamaddon, Negar Azarpira

Abstract read
In one paragraph

Article in Journal of cellular and molecular medicine, 2025. 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. Article
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.

Hanieh ArdeshiriDepartment of Medical Nanotechnology, School of Advanced Medical Sciences and Technologies, Shiraz, Iran.ORCID 0000-0001-6309-1593
Mina GhorbaniChemical Engineering Department, University of Waterloo, Waterloo, Ontario, Canada.
Mohammad Ali NazariniaDepartment of Internal Medicine, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
Kimia FalamarziStudent Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran.
Ali Mohammad TamaddonDepartment of Pharmaceutics, School of Pharmacy, Shiraz University of Medical Sciences, Shiraz, Iran.
Negar AzarpiraTransplant Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skin fibrosis in scleroderma is a chronic and debilitating condition that affects the quality of life of patients. In this study, we fabricated a niosomal hydrogel containing bromelain to reduce skin collagen and improve skin softness in scleroderma patients. The niosomes were prepared using the thin film hydration method and exhibited a drug loading efficiency of 52.2%. They demonstrated high monodispersity, with mean sizes lower than 200 nm. The results showed a significant reduction in mean dermal thickness from 1195 μm before treatment to 750 μm after the 2-month treatment period. This reduction in dermal thickness and improved skin softness can be attributed to the decomposition of accumulated skin collagen in individuals with scleroderma. Additionally, the treatment was found to be effective in reducing skin collagen levels compared to conventional treatment options that merely impede collagen synthesis. The current study underscores the potential of bromelain niosomal hydrogel as a promising strategy for managing skin fibrosis in scleroderma.

Indexed as

BromelainsCollagenHydrogelsLiposomesScleroderma, SystemicSkinAdultFemaleFibrosisHumansMaleMiddle AgedBromelainsCollagenHydrogelsLiposomesbromelaindrug deliveryfibrosisnanoparticleniosomescleroderma

Identifiers

PMID40703002
PMCPMC12287664

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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.