Evidence map›Paper›PMID 40329373›Full record

ArticleMicrobial cell factories2025

Nutritional optimization for bioprocess production of staphyloxanthin from Staphylococcus aureus with response surface methodology: promising anticancer scaffold targeting EGFR inhibition.

Ahmed M Nosair, Ahmed A Abdelaziz, Amal M Abo-Kamer, Lamiaa A Al-Madboly, Mahmoud H Farghali

Abstract read
In one paragraph

Article in Microbial cell factories, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Optimization of Pyocyanin Production byAntibiotics (Basel, Switzerland) · 2026
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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

5 authors.

Ahmed M NosairDepartment of Microbiology and Immunology, Faculty of Pharmacy, Tanta University, Tanta, Egypt. ahmed.nosir@pharm.tanta.edu.eg.
Ahmed A AbdelazizDepartment of Microbiology and Immunology, Faculty of Pharmacy, Tanta University, Tanta, Egypt.
Amal M Abo-KamerDepartment of Microbiology and Immunology, Faculty of Pharmacy, Tanta University, Tanta, Egypt.
Lamiaa A Al-MadbolyDepartment of Microbiology and Immunology, Faculty of Pharmacy, Tanta University, Tanta, Egypt.
Mahmoud H FarghaliDepartment of Microbiology and Immunology, Faculty of Pharmacy, Tanta University, Tanta, Egypt.ORCID http://orcid.org/0000-0001-5954-7842

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStaphyloxanthin (STX) is a secondary metabolite pigment associated with membrane structures, recognized for its significant antioxidant properties. It plays a crucial role in combating reactive oxygen species (ROS), positioning it as a promising and effective alternative in cancer treatment. This study focused on enhancing the production of STX pigment by employing statistical optimization of media components, alongside the evaluation of its safety and anticancer properties.

resultsA total of 59 Staphylococcus aureus isolates were screened and quantitatively estimated for STX production. The best pigment-producing isolate was identified based on molecular phylogenetic analysis as S. aureus A2, with accession number PP197164. A Box-Wilson central composite design was employed to evaluate the intricate interactions among six variables affecting the pigment yield. The most optimal conditions resulted in the highest production of STX of OD

conclusionThe bioprocess for optimized production, combined with the biological profiling and low cytotoxicity, substantiates the potential application of STX pigment in combating lung cancer.

Indexed as

Antineoplastic AgentsErbB ReceptorsStaphylococcus aureusXanthophyllsA549 CellsAnimalsApoptosisChlorocebus aethiopsHumansMolecular Docking SimulationVero CellsAntineoplastic AgentsEGFR protein, humanErbB ReceptorsstaphyloxanthinXanthophyllsApoptosisEGFRNSC lung cancerRSM optimizationStaphyloxanthin

Identifiers

PMID40329373
PMCPMC12054202

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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.