Evidence map›Paper›PMID 40664949›Full record

ArticleScientific reports2025

Ecofriendly silver nanoparticles biosynthesis from Penicillium commune NRC 2016-3 as antimicrobial agents for textile materials.

Sayeda Abdelrazek Abdelhamid, Sahar S Mohamed, Fatma Abdelghaffar

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Sayeda Abdelrazek AbdelhamidMicrobial Biotechnology Department, National Research Centre, Dokki, 12622, Giza, Egypt. sayeda.abdelrazek@yahoo.com.
Sahar S MohamedMicrobial Biotechnology Department, National Research Centre, Dokki, 12622, Giza, Egypt.
Fatma AbdelghaffarDyeing, Printing, and Textile Auxiliaries Department, Textile Research and Technology Institute, National Research Centre, Dokki, 12622, Giza, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The biological synthesis of silver nanoparticles (AgNPs) using fungi has received considerable attention, given that they are environmentally friendly, non-toxic, and inexpensive. Therefore, the current work investigates the biological synthesis of silver nanoparticles (AgNPs) using the extracellular filtrate of Penicillium commune NRC 2016-3. Physicochemical analyses confirmed the formation of AgNPs with a surface plasmon resonance peak at 420 nm. Transmission electron microscopy (TEM) and Scanning electron microscopy (SEM) revealed spherical particles ranging in size from 3.69 to 9.61 nm, with a zeta potential of -30.5 mV, indicating good stability. The biosynthesized AgNPs exhibited strong antibacterial and antifungal activity against various test microorganisms, with inhibition zones ranging from 30 to 33 mm for Gram-positive and 26 to 30 mm for Gram-negative bacteria. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values were found to be 2-5 µg/mL and 20-30 µg/mL, respectively. Furthermore, the AgNPs-treated fabrics revealed good antimicrobial properties and demonstrated their durability even after multiple washing cycles. This finding highlights the potential of green-synthesized AgNPs for creating durable antimicrobial textiles.

Indexed as

Anti-Infective AgentsMetal NanoparticlesPenicilliumSilverTextilesAnti-Bacterial AgentsAntifungal AgentsGreen Chemistry TechnologyMicrobial Sensitivity TestsAnti-Bacterial AgentsAntifungal AgentsAnti-Infective AgentsSilverAntimicrobialFabricsNano-silverPenicillium commune NRC 2016-3

Identifiers

PMID40664949
PMCPMC12264172

What OpenQuestion holds

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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.