Evidence map›Paper›PMID 41721856›Full record

ArticleApplied microbiology and biotechnology2026

Clove oil and selenium nanoparticles as eco-friendly antifungal agents for photographic preservation.

Heba El-Sayed, Mohamed E Osman, Nesma Ali, Eslam T Mohamed

Abstract read
In one paragraph

Article in Applied microbiology and biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Heba El-SayedBotany and Microbiology Department, Faculty of Science, Helwan University, Helwan, 11795, Egypt. HebaElsayed@science.helwan.edu.eg.
Mohamed E OsmanBotany and Microbiology Department, Faculty of Science, Helwan University, Helwan, 11795, Egypt.
Nesma AliMinistry of Tourism and Antiquities, Cairo, Egypt.
Eslam T MohamedBotany and Microbiology Department, Faculty of Science, Helwan University, Helwan, 11795, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microbial biodeterioration represents a major challenge in the conservation of photographic heritage, particularly silver gelatin prints. In this study, the antifungal efficacy of clove essential oil (Syzygium aromaticum) and selenium nanoparticles (SeNPs) was evaluated separately against Aspergillus flavus. Both treatments significantly inhibited fungal growth and sporulation, with SeNPs showing superior activity at lower concentrations, while clove oil exhibited strong inhibition at higher doses. Computational analyses revealed distinct mechanisms: clove oil phytochemicals targeted ergosterol biosynthesis, cell wall organization, and lipid metabolism, whereas SeNPs induced oxidative stress and disrupted antioxidant defenses. This work provides the first integrated experimental and computational framework applying these eco-friendly agents directly to photographic materials, establishing a mechanistic basis for sustainable antifungal strategies in heritage preservation. KEY POINTS: • Clove oil and selenium nanoparticles effectively prevent fungal damage to photographs. • Different antifungal mechanisms were observed through computational analyses. • Provides a sustainable, eco-friendly strategy for cultural heritage preservation.

Indexed as

Antifungal AgentsAspergillus flavusClove OilMetal NanoparticlesNanoparticlesPhotographySeleniumSpores, FungalAntifungal AgentsClove OilSeleniumAspergillus flavusEco-friendly antifungal agentsEssential oilsMolecular dockingSelenium nanoparticlesSilver gelatin photographs

Identifiers

PMID41721856
PMCPMC12924790

What OpenQuestion holds

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LicenceCC BY
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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.