Evidence map›Paper›PMID 41540957›Full record

ArticleAustralian endodontic journal : the journal of the Australian Society of Endodontology Inc2026

NIR-Activated Polydopamine Nanoparticles for Enterococcus faecalis Biofilm Eradication in Root Canal Disinfection.

Jiahe Li, Yong Wang

Abstract readComparative Study
In one paragraph

Article in Australian endodontic journal : the journal of the Australian Society of Endodontology Inc, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

2 authors.

Jiahe LiState Key Laboratory of Oral Diseases, West China College of Stomatology, Sichuan University, Chengdu, China.ORCID https://orcid.org/0009-0006-3372-0727
Yong WangBeijing Stomatological Hospital & School of Stomatology, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Persistent bacterial infection remains the primary cause of root canal treatment failure, posing a significant challenge in endodontics. Enterococcus faecalis, with its ability to form biofilms and resist conventional disinfectants, is one of the most commonly isolated species in failed cases. Herein, we developed a novel polydopamine (PDA) nanoparticle-based phototherapy system activated by 808 nm near-infrared (NIR) light for enhanced root canal disinfection. The PDA + NIR group exhibited a significantly superior antibacterial effect compared to 2.5% NaOCl, achieving a bactericidal rate of 97.87%. SEM and TEM observations revealed that PDA + NIR treatment caused complete bacterial cell disintegration and ultrastructural destruction, whereas 2.5% NaOCl only induced partial surface damage. Furthermore, PDA + NIR effectively eradicated mature E. faecalis biofilms in simulated root canal models. These findings demonstrate that PDA-mediated NIR phototherapy possesses powerful bactericidal and antibiofilm capabilities. This nanotechnology-based approach may offer a promising alternative strategy for clinical root canal disinfection.

Indexed as

BiofilmsDental Pulp CavityDisinfectionEnterococcus faecalisIndolesInfrared RaysNanoparticlesPolymersAnti-Bacterial AgentsHumansMicroscopy, Electron, ScanningMicroscopy, Electron, TransmissionPhotochemotherapyRoot Canal IrrigantsSodium HypochloriteAnti-Bacterial AgentsIndolespolydopaminePolymersRoot Canal IrrigantsSodium HypochloritebiofilmsE. faecalisnear‐infrared lightphotodynamic therapypolydopamineroot canal disinfection

Identifiers

PMID41540957
PMCPMC13436065

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.