Evidence map›Paper›PMID 41749319›Full record

ArticleBMC pharmacology & toxicology2026

Penetration and disruption of Salmonella typhimurium biofilm using synthesized citric acid doped zein nanocomposites.

Venkteshwar Yadav, Dharm Pal, Anil Kumar Poonia

Abstract read
In one paragraph

Article in BMC pharmacology & toxicology, 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
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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

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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

3 authors.

Venkteshwar YadavDepartment of Chemical Engineering, National Institute of Technology Raipur, Raipur, Chhattisgarh, 492010, India.
Dharm PalDepartment of Chemical Engineering, National Institute of Technology Raipur, Raipur, Chhattisgarh, 492010, India. dpsingh.che@nitrr.ac.in.
Anil Kumar PooniaDepartment of Chemical Engineering, National Institute of Technology Raipur, Raipur, Chhattisgarh, 492010, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the current global scenario, antimicrobial resistance poses a major challenge and significantly contributes to increasing human mortality. Among resistant pathogens, the Salmonella genus, particularly Salmonella enterica serovar Typhimurium (S. Typhimurium), plays a prominent role, with resistance further intensified under mature biofilm conditions. To address this challenge and mitigate the pathogenicity of this Gram-negative bacterium, various strategies have been explored, among which nanodrug delivery using nanocomposites (NCs) has emerged as a promising approach. In the present study, NCs were developed by incorporating citric acid (CA) into zein nanoparticles (NPs) at defined concentrations. X-ray diffraction analysis confirmed the successful formation of CA@Zein NCs, while field-emission scanning electron microscopy (FE-SEM) verified the effective loading of CA onto the surface of zein NPs. Particle size, zeta potential, and polydispersity index analyses indicated optimal physicochemical properties for stable nanocomposite formation. The synthesised NCs were evaluated against both planktonic and biofilm forms of S. Typhimurium. The minimum inhibitory concentration and minimum biofilm inhibitory concentration of CA@Zein NCs were determined to be 64 µg/mL and 128 µg/mL, respectively. These results demonstrate the superior antibiofilm efficacy of CA@Zein NCs compared with CA and zein NPs alone. Furthermore, FE-SEM analysis provided direct evidence of EPS penetration and bacterial cell disruption by CA@Zein NCs. Overall, CA@Zein NCs exhibits strong potential as an effective antibiofilm agent against S. Typhimurium.

Indexed as

Anti-Bacterial AgentsBiofilmsCitric AcidNanocompositesSalmonella typhimuriumZeinMicrobial Sensitivity TestsAnti-Bacterial AgentsCitric AcidZeinBiofilmCitric acidNanocompositeS. typhimuriumZein NPs

Identifiers

PMID41749319
PMCPMC13041060

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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.