Evidence map›Paper›PMID 41436763›Full record

ArticleScientific reports2025

Synthesis of an enhanced nanobiocatalyst system from Aspergillus niger as single green source.

Mohamed G Radwan, Tarek M Mohamed, Radwa H Abou-Saleh, Hamed A Abosharaf

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. 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.

Mohamed G RadwanHealth Sector, Faculty of Science, Galala University, Suez, 43511, Egypt.
Tarek M MohamedBiochemistry Division, Chemistry Department, Faculty of Science, Tanta University, Tanta, 31527, Egypt.
Radwa H Abou-SalehNanoscience and technology, Physics Department, Faculty of Science, Galala University, Suez, 43511, Egypt. r.h.saleh@gu.edu.eg.
Hamed A AbosharafBiochemistry Division, Chemistry Department, Faculty of Science, Tanta University, Tanta, 31527, Egypt. hamed_biochemistry@science.tanta.edu.eg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development of sustainable nanobiocatalysts is a focal challenge in green chemistry, requiring robust and eco-friendly production methods. This study introduces a single-source strategy that addresses this challenge. By utilizing the fungus Aspergillus niger as a single biological factory to simultaneously produce a lipase enzyme and biosynthesize the iron oxide nanoparticles (IONPs) that serve as lipase matrix support. This integrated approach ensures a high degree of compatibility between the enzyme and its nanoparticle support, which was confirmed during the immobilization step by an 81.73% yield and a remarkable 97.4% activity retention. The resulting nanobiocatalyst demonstrated a distinct operational stability, broad pH tolerance, and maintained over 80% of its activity after eight consecutive reuse cycles. In practical applications, the catalyst showed powerful bioremediation capabilities, achieving near-complete (> 95%) removal of industrial dyes and effective oil-stain removal from fabric. Our findings could establish that using a single biological source for both the enzyme and its immobilization matrix offers a new benchmark for future enzyme immobilization technologies.

Indexed as

Aspergillus nigerEnzymes, ImmobilizedGreen Chemistry TechnologyLipaseBiocatalysisBiodegradation, EnvironmentalHydrogen-Ion ConcentrationEnzymes, ImmobilizedLipaseAspergillus nigerBiogenic iron oxide nanoparticlesImmobilizationLipaseNanobiocatalystSingle-source synthesis

Identifiers

PMID41436763
PMCPMC12738789

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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.