Evidence map›Paper›PMID 41566439›Full record

ArticleBMC microbiology2026

Tagatose attenuates streptococcus mutans-induced dental caries by modulating oral microbiota and inflammatory responses in mice.

Lili Zhao, Huakai Wang, Chengyi Miao, Qianqian Chen, Weiwei Wang, Wenjing Ma, Wenhui Zhang, Qingyu Wen, Ran Wang, Wanli Zhang and 1 more

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In one paragraph

Article in BMC microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

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No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Lili Zhao *Food Laboratory of Zhongyuan, Luohe, 462300, China.
Huakai Wang *Food Laboratory of Zhongyuan, Luohe, 462300, China.
Chengyi MiaoFood Laboratory of Zhongyuan, Luohe, 462300, China.
Qianqian ChenFood Laboratory of Zhongyuan, Luohe, 462300, China.
Weiwei WangFood Laboratory of Zhongyuan, Luohe, 462300, China.
Wenjing MaFood Laboratory of Zhongyuan, Luohe, 462300, China.
Wenhui ZhangFood Laboratory of Zhongyuan, Luohe, 462300, China.
Qingyu WenFood Laboratory of Zhongyuan, Luohe, 462300, China.
Ran WangFood Laboratory of Zhongyuan, Luohe, 462300, China.
Wanli ZhangFood Laboratory of Zhongyuan, Luohe, 462300, China.
Wei XiongFood Laboratory of Zhongyuan, Luohe, 462300, China. xiongwei@zyfoodlab.cn.

Funding

Foundation of Key Technology Research Project of Henan Province 242102110039
6 · The paper itself

Abstract

backgroundDental caries is one of the most common chronic infectious oral diseases worldwide, leading to destruction of dental hard tissues and is associated with systemic diseases. Traditional caries prevention methods have limitations in terms of their applicability to specific populations or potential side effects. Therefore, exploring new, green, safe, and efficient caries prevention substances holds significant public health implications.

methodsThis study employed a mouse experimental caries model induced by Streptococcus mutans (S. mutans), combined with 16 S rRNA sequencing analysis of oral microbiota dynamics and detection of inflammatory factors to evaluate the anti-caries effects of tagatose.

resultsThe results showed that tagatose intervention significantly reduced the severity of dental caries in mice in a dose-dependent manner. It inhibited cariogenic bacteria (Staphylococcus), promoted beneficial bacteria (Streptococcus), and regulated inflammatory factors (inhibiting pro-inflammatory factors such as IL-17, IL-6, and IFN-γ, and promoting anti-inflammatory factors such as IL-10 and IL-4), with lower concentrations showing better efficacy than xylitol.

conclusionsIn summary, tagatose exhibits remarkable potential in the field of caries prevention, providing new scientific evidence and insights for the further development of natural anti-caries products based on tagatose.

Indexed as

Dental CariesHexosesMicrobiotaMouthStreptococcus mutansAnimalsCytokinesDisease Models, AnimalFemaleInflammationMiceRNA, Ribosomal, 16SCytokinesHexosesRNA, Ribosomal, 16StagatoseDental cariesInflammatory factorsOral microbiotaStreptococcus mutansTagatose

Identifiers

PMID41566439
PMCPMC12951980

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LicenceCC BY
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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.