Evidence map›Paper›PMID 41977176›Full record

ReviewInternational journal of molecular sciences2026

Application and Potential of Local Drug Delivery Systems for Antibacterial Treatment of Periodontitis.

Xinchao Wang, Fengli Wu, Jia Liu, Xingqi Hong, Shujun Dong

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 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

5 authors.

Xinchao WangHospital of Stomatology, Jilin University, Changchun 130012, China.
Fengli WuHospital of Stomatology, Jilin University, Changchun 130012, China.
Jia LiuHospital of Stomatology, Jilin University, Changchun 130012, China.
Xingqi HongHospital of Stomatology, Jilin University, Changchun 130012, China.
Shujun DongHospital of Stomatology, Jilin University, Changchun 130012, China.ORCID 0009-0005-8584-1013

Funding

the Healthcare Talent Development Project of the Finance Department of Jilin Province jcsz2023481-10
6 · The paper itself

Abstract

Periodontitis (PD) is a chronic inflammatory disease characterized by the progressive destruction of periodontal supporting tissues. As one of the most prevalent chronic diseases, PD affects more than 743 million people globally, some with serious systemic health implications. Plaque accumulation constitutes the key driver of periodontitis, initiating host inflammatory cascades and compromising periodontal microbiome equilibrium. Conventional treatment methods, such as scaling and root planing, are limited by a constrained operative field, resulting in blind spots that impede the complete eradication of bacterial biofilms and the modulation of the inflammatory microenvironment. Therefore, employing new therapeutic strategies (e.g., drug delivery systems) is essential. This review focuses on local drug delivery systems for the treatment of PD, including fibers, strips and films, microspheres, gels, nanoparticles, and vesicle systems, to deliver drugs directly into the periodontal pockets, targeting inflammation and providing sustained antibacterial effects while reducing systemic side effects. The characteristics and clinical implications of each type of local drug delivery system are discussed, along with emerging technologies such as 3D printing and nanotechnology.

Indexed as

Anti-Bacterial AgentsDrug Delivery SystemsPeriodontitisAnimalsHumansNanoparticlesAnti-Bacterial Agentsanti-microbial therapychronic inflammationlocal drug delivery systemsnanotechnologyperiodontitis

Identifiers

PMID41977176
PMCPMC13073990

What OpenQuestion holds

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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.