Clinical Efficacy of the Probiotic Weissella cibaria CMU in Adults with Gingivitis: A Randomized,Double-Blind,Placebo-Controlled Clinical Trial

Abstract

Periodontal disease results from dysbiotic oral biofilms and the host’s inflammatory response. Given the limitations of conventional therapies, this study aimed to evaluate the efficacy and safety of Weissella cibaria CMU (OraCMU) in improving gingival inflammation in individuals with gingivitis and incipient periodontitis. In this randomized, double-blind, placebo-controlled trial, 80 participants received either OraCMU tablets (2.0 × 10⁸ CFU/g; n = 40) or placebo (n = 40) twice daily for 8 weeks. The primary outcome was the gingival index (GI), and secondary outcomes included bleeding on probing (BOP), probing depth, clinical attachment level, gingival recession, plaque index, inflammation-related proteins, and oral microbiota. Clinical parameters were assessed at six preselected index teeth (#16, 12, 24, 32, 36, and 44). At week 8, the probiotic group showed significantly greater reductions in GI (−0.19 ± 0.03 vs. −0.08 ± 0.04; P = .035) and BOP (−7.74 ± 1.54 vs. −2.82 ± 1.60; P = .030) compared with the placebo group. Inflammatory markers, including fibroblast growth factor-5 (P = .003), thymic stromal lymphopoietin (P = .017), and the receptor activator of nuclear factor κB ligand/osteoprotegerin ratio (P = .021), were significantly decreased. The levels of Porphyromonas gingivalis (P = .001), Treponema denticola (P = .005), and Prevotella intermedia (P = .046) were also significantly reduced, while Weissella increased (P < .001) in the probiotic group. Eight-week supplementation with OraCMU improved gingival health and modulated the oral microbiota and inflammatory response. No serious adverse events were reported during the study period. These findings support the potential clinical utility of OraCMU as a probiotic adjunct for managing gingivitis.

Keywords

gingival index gingival inflammation oral microbiome randomized trial

INTRODUCTION

Gingivitis is a common reversible inflammatory condition of the gingiva that results from the host immune response to dental plaque.^1,2 Clinically, it manifests as gingival erythema, swelling, and bleeding on probing (BOP), without irreversible loss of periodontal support. If the inflammation persists, gingivitis can progress to periodontitis, leading to connective tissue breakdown, alveolar bone loss, and ultimately tooth loss.³ Because gingivitis is highly prevalent and preventable, early intervention and effective adjunctive therapies are important.

Mechanical plaque control (toothbrushing, interdental cleaning, and professional prophylaxis) remains the cornerstone of gingivitis management.⁴ However, its effectiveness depends heavily on patient compliance, dexterity, and consistency, resulting in variable clinical outcomes.⁵ Adjunctive antimicrobial agents improve clinical outcomes, but their prolonged use is limited by adverse effects (e.g., dysgeusia, staining, mucosal irritation), disruption of commensal flora, and concerns regarding antimicrobial resistance.⁶ Accordingly, alternative biological approaches that promote microbial balance and inflammation control are attracting interest.

Probiotics are defined by the World Health Organization as “live microorganisms which, when administered in adequate amounts, confer health benefits on the host.”⁷ Although initially developed for gastrointestinal applications, probiotics are being investigated for systemic conditions, including respiratory and metabolic health and, more recently, oral health.^8,9 In the oral cavity, probiotics may exert benefits by competitively inhibiting pathogen adhesion and biofilm formation, producing antimicrobial substances (e.g., organic acids and bacteriocins), and modulating host immune responses.^9,10 Clinical studies suggest that certain probiotic regimens can reduce plaque accumulation and gingival inflammation; however, efficacy is strain- and vehicle-dependent and remains inconsistent across studies.^10,11

Weissella cibaria CMU (OraCMU), a lactic acid bacterium isolated from the saliva of healthy children in Korea, is a promising oral probiotic.¹² Preclinical studies report that this strain inhibits volatile sulfur compound production, suppresses key periodontopathogens such as Fusobacterium nucleatum and Porphyromonas gingivalis, and reduces proinflammatory cytokine expression in vitro and in vivo.^12–15 Clinical trials have also reported improvements in oral malodor and periodontal indices following OraCMU administration.^16–18 Nevertheless, evidence in adults with gingivitis and incipient periodontitis, particularly without concurrent nonsurgical periodontal instrumentation, remains limited.

Most prior studies have evaluated the role of probiotics as adjuncts to professional instrumentation (e.g., scaling, root planing).^19,20 Few rigorously designed trials have evaluated probiotic supplementation under routine home oral hygiene maintenance conditions in adults with gingivitis or incipient periodontitis while concurrently linking clinical outcomes to oral microbial shifts and host inflammatory responses.

Therefore, we conducted a randomized, double-blind, placebo-controlled, parallel-group trial to evaluate the efficacy and safety of OraCMU tablets taken twice daily for eight weeks in adults with gingivitis or incipient periodontitis who practiced routine home oral hygiene. We hypothesized that OraCMU supplementation would reduce gingival inflammation compared with placebo. The primary objective was to compare changes in gingival index (GI) between groups; secondary objectives were to evaluate changes in BOP, probing depth (PD), clinical attachment level (CAL), gingival recession (GR), and plaque index (PI). Exploratory objectives were to characterize changes in nine key periodontopathogens, oral microbiome composition, and serum inflammation-related proteins.

MATERIALS AND METHODS

Study design and ethics

This single-center, randomized, double-blind, placebo-controlled, parallel-group trial was conducted from March 2024 to January 2025 at Chosun University Dental Hospital (Gwangju, Korea). Participants were recruited via hospital posters. The study was conducted in accordance with the Declaration of Helsinki (2013 revision) and Good Clinical Practice guidelines. Ethical approval was obtained from the Institutional Review Board of Chosun University Dental Hospital (Approval No. CUDHIRB 2401 005). All participants provided written informed consent.

Participants and eligibility criteria

Participants were adults aged 19–70 years diagnosed with generalized or localized gingivitis or stage 1 periodontitis according to the 2018 World Workshop classification.²¹ Inclusion criteria were BOP at ≥10% of sites; at least one tooth with PD >3 and ≤5 mm; and ≥20 natural teeth. Key exclusion criteria (listed in full in Supplementary Appendix SA1) included conditions or treatments likely to confound periodontal outcomes or interfere with study participation.

Sample size calculation

Sample size was determined as 30 participants per group for a two-sided superiority test with α = 0.05, power 80%, mean between-group difference of 0.44, and pooled standard deviation (SD) of 0.61, using the same clinical endpoints as Hashemi et al.²² Allowing for a 25% dropout rate, 80 participants were recruited (40 per group).

Randomization and blinding

Eligible participants were randomized 1:1 to the probiotic (test) or placebo group using block randomization. The allocation sequence was generated using SAS (version 9.4; SAS Institute Inc., Cary, NC, USA) by an independent statistician who had no involvement in the recruitment, clinical assessments, or analyses. All study products were provided in identical, coded packaging and assigned sequentially at baseline to ensure allocation concealment. Blinding was maintained until study completion, except in cases of serious adverse events (SAEs).

Intervention and compliance

The test product consisted of 1 g tablets containing OraCMU probiotic (2.0 × 10⁸ CFU/g; Oraticx, Inc., Seoul, Korea). Placebo tablets were identical in appearance and taste. Participants were instructed to take one tablet twice daily, in the morning and evening immediately after toothbrushing, for eight weeks. Tablets were dissolved slowly in the mouth without chewing or immediate swallowing, and participants were instructed to refrain from eating or drinking for approximately 30 minutes afterward. Compliance was assessed by counting remaining tablets at weeks 4 and 8.

Baseline oral hygiene instructions and restrictions

Participants received standardized home oral hygiene instructions (toothbrushing technique and interdental cleaning) at baseline and were instructed to perform only home oral hygiene practices during the eight-week period; additional professional periodontal treatment was prohibited. To minimize confounding, antiseptic mouthrinses and other probiotic-containing oral care products were not permitted throughout the study. Participants were instructed not to perform oral hygiene on scheduled visit days.

Clinical parameters

The primary outcome was change in GI; secondary outcomes included changes in BOP, PD, CAL, GR, and PI. Clinical parameters were measured at six predefined index teeth (#16, 12, 24, 32, 36, and 44), at six sites per tooth (mesial, mid, and distal on the buccal and lingual surfaces; total 36 sites). GI was assessed using a modified scoring system (0–4), and the mean GI was calculated by averaging scores across examined teeth.²³ BOP was recorded as positive if bleeding was observed within 30 seconds after probing, and BOP% was calculated as the ratio of BOP-positive sites to the total number of sites examined. PD was measured from the gingival margin to the base of the sulcus/pocket. GR was measured from the cementoenamel junction to the gingival margin, and CAL was calculated as PD + GR. PI was scored on a 0–5 scale.²⁴ Additional procedural details are provided in Supplementary Appendix SA1.

Oral microbiological assessments

Oral samples were collected at baseline and at week 8. For microbiome profiling, whole-mouth swab samples were obtained by gently rubbing a sterile swab 10 times across the buccal mucosa, tooth surfaces, and tongue dorsum (in that order) to capture supragingival and mucosal biofilm. Microbial DNA extraction and 16S rRNA gene-targeted next-generation sequencing were conducted by U2Bio Co., Ltd. (Seoul, Korea). 16S rRNA libraries were prepared following the Illumina 16S metagenomic sequencing library preparation protocol and sequenced on an Illumina MiSeq platform (2 × 250 bp). Reads were processed using the QIIME2 pipeline with insertion into the Greengenes 13_8 reference tree for phylogenetic analysis. Alpha diversity (Chao1, Observed, ACE, Shannon, Simpson, and Fisher indices) and beta diversity (Bray–Curtis distance principal coordinates analysis) were assessed, and between-group differences in community structure were evaluated using permutational analysis of variance (PERMANOVA). Differential taxa were explored using LEfSe with a log-linear discriminant analysis (LDA) score threshold >2 (Supplementary Appendix SA1).

For quantitative pathogen assessment, samples were obtained by gargling 12 mL of a commercially available mouthwash (Helixco Inc., Ulsan, Korea) for approximately 30 sec. Quantitative polymerase chain reaction (qPCR) for nine key periodontal pathogens (Supplementary Appendix SA1) was performed by Helixco. DNA was extracted from the mouthwash samples and periodontal pathogens (Aggregatibacter actinomycetemcomitans, Campylobacter rectus, Eikenella corrodens, Fusobacterium nucleatum, Peptostreptococcus anaerobius, Porphyromonas gingivalis, Prevotella intermedia, Tannerella forsythia, and Treponema denticola) were quantified using species-specific TaqMan assays. Standard curves from plasmid standards (10²–10⁹ copies) were used to estimate copy numbers (Supplementary Appendix SA1).²⁵

Inflammation-related protein profiling

Blood samples (2 mL) were collected at baseline and week 8 using BD Vacutainer^® tubes (Becton, Dickinson and Company, Franklin Lakes, NJ, USA). Samples were allowed to clot and then centrifuged at 1790 g for 10 min at 25°C to obtain serum. Inflammation-related proteins were quantified using the Olink^® Target 96 Inflammation panel (Olink Proteomics, Uppsala, Sweden), which uses proximity extension assay technology.²⁶ Analyses were performed at the Macrogen Precision Medicine Institute (Seoul, Korea), and results were reported as normalized protein expression values.

Safety evaluation

Safety assessments included AEs, clinical pathology, vital signs, and body weight. AEs and SAEs were identified through nondirective questioning, spontaneous reporting, and clinical assessments recorded at each visit. They were assessed for potential relatedness to the study product. Blood samples for hematological and biochemical analyses were collected at baseline and week 8.

Statistical analysis

Intention-to-treat analyses included all randomized participants, whereas per-protocol (PP) analyses included only participants who completed the study without major protocol deviations. Safety analyses included all participants who received at least one dose. Continuous variables are presented as means ± SDs unless otherwise stated; model-based change estimates are presented as least-squares means ± standard errors for analysis of covariance (ANCOVA) models. Categorical variables are presented as counts (%). All tests were two-sided with α = 0.05. Normality was assessed using the Shapiro–Wilk test.

Baseline between-group comparisons used two-sample t-tests or Wilcoxon rank-sum tests depending on distribution; categorical variables were analyzed using chi-square or Fisher’s exact tests. Within-group comparisons used paired t-tests or Wilcoxon signed-rank tests. Primary and secondary clinical endpoint changes were assessed using ANCOVA with baseline values as covariates. qPCR-derived bacterial counts were analyzed on the original scale. For microbiome analyses, alpha diversity indices were compared between groups using appropriate parametric or nonparametric tests, and beta diversity differences were assessed using PERMANOVA on Bray–Curtis distances. Olink NPX values were analyzed using ANCOVA with baseline adjustment; given the exploratory nature of the proteomic endpoints, nominal P-values are reported and interpreted cautiously.

All analyses were performed using SPSS version 29.0 (IBM Corp., Armonk, NY, USA) and microbiome pipelines/tools as described in Supplementary Appendix SA1. Exact n values for each analysis are provided in the Results section and figure legends (PP population: test, n = 40; placebo, n = 37).

RESULTS

Participant flow and baseline characteristics

Of 83 participants assessed for eligibility, 3 were excluded (2 did not meet the eligibility criteria, 1 withdrew consent). Eighty participants were randomized to the OraCMU group (n = 40) or placebo group (n = 40). Three placebo participants discontinued owing to antibiotic use (two at week 4 and one at week 8). Accordingly, 40 participants in the OraCMU group and 37 in the placebo group were included in the final PP analysis (Fig. 1). Baseline demographic and clinical characteristics did not differ significantly between groups (Table 1).

FIG. 1.

CONSORT flow diagram of participant enrollment, randomization, follow-up, and analysis.

TABLE 1.

Baseline Demographic and Oral Health Characteristics of the Analyzed Subjects

Variables	Test n = 40	Placebo n = 37	P-value
Gender (male/female)
n (%)	10 (25.00)/30 (75.00)	7 (18.90)/30 (81.10)	.520^a
Age (years)
Mean ± SD	63.63 ± 4.95	64.84 ± 4.69	.225^c
Weight (kg)
Mean ± SD	58.78 ± 10.33	58.88 ± 8.54	.687^c
Alcohol consumption status (yes/no)
n (%)	10 (25.00)/30 (75.00)	8 (21.60)/29 (78.40)	.726^a
Amount of alcohol consumption (g per week)
Mean ± SD	10.54 ± 28.75	8.21 ± 20.09	.752^c
Systemic disease (yes/no)
n (%)	25 (62.50)/15 (37.50)	23 (62.20)/14 (37.80)	.976^a
Calcium consumption (mg per day)
Mean ± SD	452.99 ± 248.44	415.19 ± 251.79	.482^c
Frequency of tooth brushing (time per day)
Mean ± SD	2.70 ± 0.56	2.84 ± 0.60	.320^c
Use of oral hygiene aids (yes/no)
n (%)	37 (92.50)/3 (7.50)	33 (89.20)/4 (10.80)	.705^b
Number of oral hygiene aids used
Mean ± SD	1.45 ± 0.85	1.27 ± 0.80	.306^c
Types of oral hygiene aids
n (%)
Dental floss	15 (37.50)	9 (24.30)	.212^a
Rubber interdental stimulator	1 (2.50)	0 (0.00)	1.000^b
Ultrathin toothbrush	2 (5.00)	3 (8.10)	.667^b
Interdental brush	22 (55.00)	20 (54.10)	.934^a
Tongue cleaner	4 (10.00)	6 (16.20)	.507^b
Toothpick	9 (22.50)	5 (13.50)	.307^a
Water jet	5 (12.50)	4 (10.80)	1.000^b

Chi-square test or ^bFisher’s exact test was used for categorical variables. Continuous variables were compared using a two-sample t-test when normally distributed; otherwise, ^cWilcoxon rank-sum test was used.

Compliance

Mean compliance in the PP population was 91.16% ± 10.21% in the OraCMU group and 93.28% ± 7.77% in the placebo group, with no significant between-group difference (P > .05).

Clinical outcomes

Clinical outcomes are summarized in Table 2. At week 4, changes in GI and BOP did not differ significantly between groups. By week 8, the OraCMU group showed significant within-group decreases in GI and BOP (both P < .001) and significant between-group differences compared with the placebo group (GI, P = .035; BOP, P = .030). PD showed a tendency to decrease in the OraCMU group and increase in the placebo group at weeks 4 and 8, but between-group differences were not significant. CAL and GR did not differ significantly between groups at week 8 (P > .05). PI decreased in both groups at week 8 (OraCMU P = .028; placebo P = .043), with no significant between-group difference.

TABLE 2.

Changes in Clinical Parameters Between the Test and Placebo Groups Before and After Taking the Study Product

Clinical parameters	Time point	Testn = 40	Placebon = 37	P-value^*	P-value^**
GI (score)	Baseline	0.48 ± 0.31	0.40 ± 0.27	.282^b
	Week 4	0.48 ± 0.54	0.39 ± 0.27	.781^b
	Week 8	0.27 ± 0.23	0.34 ± 0.26	.072^b
	Change (ΔV1)	0.01 ± 0.06	−0.03 ± 0.06		.652
	Change (ΔV2)	−0.19 ± 0.03	−0.08 ± 0.04		.035
	P-value^***	.074^d	.660^c
	P-value^****	<.001 ^c	.524^d
BOP (%)	Baseline	34.93 ± 15.99	32.58 ± 15.86	.431^b
	Week 4	29.72 ± 15.41	30.93 ± 16.33	.798^b
	Week 8	26.73 ± 13.61	30.26 ± 13.35	.139^b
	Change (ΔV1)	−4.72 ± 2.08	−2.18 ± 2.16		.399
	Change (ΔV2)	−7.74 ± 1.54	−2.82 ± 1.60		.030
	P-value^***	.070^d	.337^c
	P-value^****	<.001 ^c	.235^c
PD (mm)	Baseline	2.55 ± 0.37	2.56 ± 0.34	.814^b
	Week 4	2.54 ± 0.29	2.62 ± 0.31	.423^b
	Week 8	2.52 ± 0.35	2.59 ± 0.30	.426^b
	Change (ΔV1)	−0.01 ± 0.03	0.06 ± 0.03		.107
	Change (ΔV2)	−0.03 ± 0.04	0.03 ± 0.04		.299
	P-value^***	.780^c	.160^c
	P-value^****	.456^c	.606^c
CAL (mm)	Baseline	2.93 ± 0.47	2.91 ± 0.50	.721^b
	Week 4	2.93 ± 0.42	3.05 ± 0.59	.571^b
	Week 8	2.95 ± 0.48	3.06 ± 0.61	.485^b
	Change (ΔV1)	0.00 ± 0.05	0.14 ± 0.05		.049
	Change (ΔV2)	0.03 ± 0.05	0.14 ± 0.05		.124
	P-value^***	.984^c	.025 ^c
	P-value^****	.562^c	.037 ^d
GR (mm)	Baseline	0.39 ± 0.28	0.36 ± 0.41	.255^b
	Week 4	0.38 ± 0.28	0.43 ± 0.47	.642^b
	Week 8	0.43 ± 0.34	0.47 ± 0.46	.898^b
	Change (ΔV1)	0.00 ± 0.03	0.07 ± 0.04	.123^b	.162
	Change (ΔV2)	0.04 ± 0.04	0.10 ± 0.04		.236
	P-value^***	.509^d	.161^d
	P-value^****	.475^d	.003 ^d
PI (score)	Baseline	0.92 ± 0.55	0.98 ± 0.38	.440^b
	Week 4	0.89 ± 0.55	0.91 ± 0.50	.866^a
	Week 8	0.76 ± 0.54	0.84 ± 0.59	.560^b
	Change (ΔV1)	−0.03 ± 0.05	−0.07 ± 0.06		.652
	Change (ΔV2)	−0.17 ± 0.07	−0.13 ± 0.07		.722
	P-value^***	.577^c	.265^c
	P-value^****	.028 ^c	.043 ^d

Bold numbers indicate that p < .05 is statistically significant.

Values at each time point are expressed as means ± standard deviations (SDs). Changes are presented as least squares means (LSmean) ± standard errors (SEs), calculated using analysis of covariance (ANCOVA) adjusted for baseline values. ΔV1, Week 4—baseline; ΔV2, Week 8—baseline.

Compared between groups; P-value for ^atwo-sample t-test when normally distributed; otherwise, a ^bWilcoxon rank-sum test was used.

Compared between-group comparisons: P-value for ANCOVA-adjusted baseline.

^***Compared within-group (baseline to week 4); P-value for ^cpaired t-test when normally distributed; otherwise, a ^dWilcoxon signed-rank test was used.

****

Compared within-group (baseline to week 8); P-value for ^cpaired t-test when normally distributed; otherwise, a ^dWilcoxon signed-rank test was used.

GI, gingival index; BOP, bleeding on probing; PD, probing depth; CAL, clinical attachment level; GR, gingival recession; PI, plaque index.

Periodontitis-associated pathogens and oral microbiome

qPCR analysis revealed significant between-group differences at week 8 for P. gingivalis (P = .001), P. intermedia (P = .046), T. denticola (P = .005), and the total count of periodontal pathogens (P = .010) (Fig. 2). In 16S rRNA sequencing, alpha and beta diversity (Bray–Curtis) did not differ significantly between groups (Fig. 3A, B), and relative abundances by time point showed no major group differences (Fig. 3C). However, LDA revealed increased abundance of Weissella in the OraCMU group at week 8 (Fig. 3D). Changes in the relative abundance (%) of Aggregatibacter (P = .023) and Weissella (P < .001) differed significantly between groups (Table 3).

FIG. 2.

Change from baseline to week 8 in the quantities of nine periodontitis-associated bacteria and their total, measured by qPCR. Bars represent least squares mean (LSmean) ± standard error (SE) of the change (week 8—baseline) estimated using analysis of covariance (ANCOVA) adjusted for baseline values. *P < .05 for between-group differences. PP population (test, n = 40; placebo, n = 37). Aa, Aggregatibacter actinomycetemcomitans; Cr, Campylobacter rectus; Ec, Eikenella corrodens; Fn, Fusobacterium nucleatum; Pa, Peptostreptococcus anaerobius; PP, per-protocol; Pg, Porphyromonas gingivalis; Pi, Prevotella intermedia; qPCR, quantitative polymerase chain reaction; Tf, Tannerella forsythia; Td, Treponema denticola; Total, sum of the nine pathogens.

FIG. 3.

Changes in oral microbiota in the test and placebo groups assessed by 16S rRNA gene sequencing of oral samples at baseline and week 8. (A) Alpha diversity indices (Chao1, Observed, ACE, Shannon, Simpson, and Fisher) at baseline (0 Ww) and week 8 (8 Ww). Boxplots show medians and interquartile ranges; points represent individual participants. P-values indicate between-group comparisons at each time point. (B) Principal coordinates analysis (PCoA) based on Bray–Curtis dissimilarities; shaded ellipses denote 95% confidence regions. P-values were obtained using permutational analysis of variance (PERMANOVA). (C) Genus-level relative abundance profiles for each participant at baseline and week 8; low-abundance genera are grouped as “Others.” (D) Differential taxa identified by LEfSe (LDA score >2 and P < .05) and Weissella genus abundance across visits (filtered and log-transformed counts). PP population (test, n = 40; placebo, n = 37). LDA, log-linear discriminant analysis.

FIG. 3.

Continued.

TABLE 3.

Changes in Relative Abundance (%) of Oral Microbial Communities at the Genus and Phylum Levels in Oral Swab Samples Between the Test and Placebo Groups Before and After Taking the Study Product

Variables	Time point	Test n = 40	Placebo n = 37	P-value^*	P-value^**
Actinomyces	Baseline	3.46 ± 1.51	3.96 ± 2.09	.253^b
	Week 8	3.41 ± 1.55	3.75 ± 2.39	.935^b
	Change (ΔV)	−0.14 ± 0.26	−0.11 ± 0.27		.938
	P-value^***	.893^c	.274^c
Aggregatibacter	Baseline	0.12 ± 0.22	0.14 ± 0.18	.259^b
	Week 8	0.01 ± 0.03	0.05 ± 0.08	.054^b
	Change (ΔV)	−0.12 ± 0.01	−0.09 ± 0.01		.023
	P-value^***	<.001 ^d, ^*	.005 ^d, ^*
Bacteroides	Baseline	0.00 ± 0.00	0.00 ± 0.00	.535^b
	Week 8	0.00 ± 0.00	0.00 ± 0.01	.916^b
	Change (ΔV)	0.00 ± 0.00	0.00 ± 0.00		.925
	P-value^***	.593^d	1.000^d
Bifidobacterium	Baseline	0.01 ± 0.04	0.00 ± 0.02	.989^b
	Week 8	0.05 ± 0.23	0.04 ± 0.19	.099^b
	Change (ΔV)	0.03 ± 0.03	0.04 ± 0.03		.782
	P-value^***	.678^d	.193^d
Campylobacter	Baseline	0.69 ± 0.50	0.63 ± 0.51	.511^b
	Week 8	0.80 ± 0.61	0.74 ± 0.49	.943^b
	Change (ΔV)	0.13 ± 0.08	0.10 ± 0.09		.764
	P-value^***	.476^d	.150^c
Eikenella	Baseline	0.03 ± 0.06	0.03 ± 0.05	.617^b
	Week 8	0.03 ± 0.05	0.03 ± 0.04	.451^b
	Change (ΔV)	−0.01 ± 0.01	0.00 ± 0.01		.870
	P-value^***	.217^d	.893^d
Filifactor	Baseline	0.01 ± 0.02	0.01 ± 0.02	.889^b
	Week 8	0.03 ± 0.07	0.02 ± 0.04	.795^b
	Change (ΔV)	0.02 ± 0.01	0.01 ± 0.01		.541
	P-value^***	.042 ^d	.012 ^d
Fusobacterium	Baseline	4.91 ± 3.63	5.57 ± 3.62	.403^b
	Week 8	3.84 ± 3.12	3.35 ± 2.47	.617^b
	Change (ΔV)	−1.24 ± 0.36	−2.04 ± 0.37		.122
	P-value^***	.012 ^c	<.001 ^c
Lactobacillus	Baseline	0.00 ± 0.01	0.02 ± 0.13	.711^b
	Week 8	0.00 ± 0.00	0.00 ± 0.00	.139^b
	Change (ΔV)	−0.01 ± 0.00	−0.01 ± 0.00		.210
	P-value^***	.109^d	.715^d
Parvimonas	Baseline	0.34 ± 0.50	0.38 ± 0.44	.494^b
	Week 8	0.18 ± 0.29	0.23 ± 0.33	.561^b
	Change (ΔV)	−0.17 ± 0.04	−0.13 ± 0.04		.462
	P-value^***	.038 ^d	.038 ^d
Peptococcus	Baseline	0.08 ± 0.12	0.07 ± 0.12	.497^b
	Week 8	0.03 ± 0.06	0.04 ± 0.06	.713^b
	Change (ΔV)	−0.05 ± 0.01	−0.04 ± 0.01		.370
	P-value^***	.002 ^d	.048 ^d
Peptostreptococcus	Baseline	1.09 ± 1.10	1.26 ± 1.11	.359^b
	Week 8	0.65 ± 0.67	0.82 ± 0.75	.243^b
	Change (ΔV)	−0.52 ± 0.11	−0.36 ± 0.12		.347
	P-value^***	.017 ^d	.067^c
Porphyromonas	Baseline	2.43 ± 2.87	2.37 ± 2.29	.558^b
	Week 8	1.90 ± 2.40	1.69 ± 1.99	.534^b
	Change (ΔV)	−0.52 ± 0.25	−0.69 ± 0.26		.630
	P-value^***	.176^d	.012 ^d
Prevotella	Baseline	19.30 ± 7.51	19.46 ± 8.77	.775^b
	Week 8	3.57 ± 1.51	3.42 ± 1.75	.692^a
	Change (ΔV)	−15.81 ± 0.25	−15.96 ± 0.26		.672
	P-value^***	<.001 ^c	<.001 ^d
Scardovia	Baseline	0.00 ± 0.00	0.01 ± 0.02	.546^b
	Week 8	0.00 ± 0.01	0.00 ± 0.01	.315^b
	Change (ΔV)	0.00 ± 0.00	0.00 ± 0.00		.345
	P-value^***	.249^d	.499^d
Selemonas	Baseline	0.16 ± 0.31	0.09 ± 0.11	.838^b
	Week 8	0.13 ± 0.14	0.18 ± 0.30	.527^b
	Change (ΔV)	−0.01 ± 0.04	0.06 ± 0.04		.219
	P-value^***	.539^d	.310^d
Staphylococcus	Baseline	0.00 ± 0.01	0.01 ± 0.06	.722^b
	Week 8	0.00 ± 0.01	0.00 ± 0.01	.588^b
	Change (ΔV)	−0.01 ± 0.00	−0.01 ± 0.00		.757
	P-value^***	.859^d	.484^d
Streptococcus	Baseline	20.76 ± 7.98	20.13 ± 7.30	.886^b
	Week 8	21.58 ± 6.25	21.61 ± 5.56	.767^b
	Change (ΔV)	1.03 ± 0.86	1.26 ± 0.90		.856
	P-value^***	.494^c	.028 ^d
Tannerella	Baseline	0.05 ± 0.07	0.07 ± 0.13	.754^b
	Week 8	0.06 ± 0.06	0.08 ± 0.07	.164^b
	Change (ΔV)	0.00 ± 0.01	0.02 ± 0.01		.308
	P-value^***	.207^d	.116^d
Treponema	Baseline	0.08 ± 0.14	0.06 ± 0.07	.720^b
	Week 8	0.10 ± 0.24	0.05 ± 0.07	.681^b
	Change (ΔV)	0.02 ± 0.03	−0.01 ± 0.03		.398
	P-value^***	.561^d	.823^d
Veillonella	Baseline	6.20 ± 3.20	5.76 ± 3.31	.556^a
	Week 8	0.40 ± 0.40	0.37 ± 0.40	.683^b
	Change (ΔV)	−5.59 ± 0.06	−5.60 ± 0.06		.872
	P-value^***	<.001 ^c	<.001 ^c
Weissella	Baseline	0.00 ± 0.00	0.00 ± 0.00	1.000^b
	Week 8	0.69 ± 0.87	0.00 ± 0.00	<.001 ^b
	Change (ΔV)	0.69 ± 0.10	0.00 ± 0.10		<.001
	P-value^***	<.001 ^d	1.000^d
Firmicutes/Bacteroidetes ratio	Baseline	1.79 ± 1.14	2.57 ± 4.73	.919^b
	Week 8	2.03 ± 1.75	1.89 ± 1.55	.206^b
	Change (ΔV)	−0.10 ± 0.26	−0.31 ± 0.27		.582
	P-value^***	.015 ^d	.331^d

Bold numbers indicate that p < .05 is statistically significant.

Values at each time point are expressed as means ± SDs. Changes are presented as LSmean ± SE, calculated using ANCOVA adjusted for baseline values. ΔV, Week 8—baseline.

Compared between groups; P-value for ^atwo-sample t-test when normally distributed; otherwise, a ^bWilcoxon rank-sum test was used.

Compared between-group comparisons: P-value for ANCOVA-adjusted baseline.

***

Compared within-group (baseline to week 8); P-value for ^cpaired t-test when normally distributed; otherwise, a ^dWilcoxon signed-rank test was used.

Inflammation-related proteins

Among the 92 proteins evaluated (Supplementary Table S1), fibroblast growth factor 5 (FGF-5; P = .003), thymic stromal lymphopoietin (TSLP; P = .016), and the nuclear factor κB ligand (RANKL)/osteoprotegerin (OPG) ratio (P = .021) demonstrated significant between-group differences at week 8 (Table 4). No other proteins showed significant between-group differences (Fig. 4).

FIG. 4.

Change from baseline to week 8 in 92 inflammation-related proteins measured in serum using a proximity extension assay (Olink panel). Protein abbreviations are defined in Supplementary Table S1. Bars represent least squares means (LSmean) ± standard errors (SE) of the change in normalized protein expression (NPX) values (week 8—baseline) estimated using analysis of covariance (ANCOVA) adjusted for baseline values. *P < .05 for between-group differences; nominal P-values are shown without multiplicity adjustment. PP population (test, n = 40; placebo, n = 37).

TABLE 4.

Changes in Inflammation-Related Proteins Between the Test and Placebo Groups Before and After Taking the Study Product

Inflammatory proteins	Time point	Test n = 40	Placebo n = 37	P-value^*	P-value^**
FGF-5	Baseline	0.61 ± 0.28	0.58 ± 0.26	.661^a
	Week 8	0.53 ± 0.28	0.67 ± 0.22	.011 ^b
	Change (ΔV)	−0.08 ± 0.03	0.08 ± 0.04		.003
	P-value^***	.018 ^c	.102^c
TSLP	Baseline	0.36 ± 0.65	0.18 ± 0.76	.114^b
	Week 8	0.11 ± 0.77	0.32 ± 0.77	.475^b
	Change (ΔV)	−0.22 ± 0.09	0.11 ± 0.10		.016
	P-value^***	.021 ^c	.248^d
RANKL/OPG ratio	Baseline	0.44 ± 0.08	0.44 ± 0.08	.737^b
	Week 8	0.42 ± 0.07	0.44 ± 0.09	.156^b
	Change (ΔV)	−0.02 ± 0.01	0.00 ± 0.01		.021
	P-value^***	.002 ^c	.723^d

Bold numbers indicate that p < .05 is statistically significant.

Values at each time point are expressed as means ± SDs. Changes are presented as LSmean ± SE, calculated using ANCOVA adjusted for baseline values. ΔV, Week 8—baseline.

Compared between groups; P-value for ^atwo-sample t-test when normally distributed; otherwise, a ^bWilcoxon rank-sum test was used.

Compared between-group comparisons: P-value for ANCOVA-adjusted baseline.

***

Compared within-group (baseline to week 8); P-value for ^cpaired t-test when normally distributed; otherwise, a ^dWilcoxon signed-rank test was used.

FGF-5, fibroblast growth factor-5; RANKL/OPG, receptor activator of nuclear factor κB ligand/osteoprotegerin; TSLP, thymic stromal lymphopoietin.

Safety

No SAEs were reported. Five AEs (including mild diarrhea) occurred in the placebo group and were judged unrelated to the intervention. AE incidence (P > .05), vital signs, and body weight did not differ between groups. Laboratory parameters (including platelet counts and blood glucose) remained within normal ranges and were clinically unremarkable (Supplementary Tables S2, S3,S4, and S5).

DISCUSSION

This randomized, double-blind, placebo-controlled trial evaluated the effects of OraCMU supplementation on gingival health in adults with gingivitis and incipient periodontitis. Compared with placebo, OraCMU led to significantly greater reductions in GI and BOP over 8 weeks, while PD, CAL, GR, and PI showed no significant between-group differences. These clinical improvements were accompanied by reductions in selected periodontopathogens and a few inflammation-related proteins. No SAEs occurred, supporting the short-term safety of OraCMU in this population.

Probiotics have attracted attention as adjuncts for plaque-induced gingival inflammation because they may promote microbial homeostasis and modulate host responses without the drawbacks associated with long-term antiseptic or antibiotic use.⁹ However, clinical evidence in dentistry remains heterogeneous,^10,11 with outcomes varying by strain, viability, dose, formulation, and baseline disease severity.¹¹

Most clinical trials have focused on periodontitis and used probiotics as adjuncts to nonsurgical periodontal therapy.^{19,20,27–29} Lactobacillus reuteri lozenges in combination with subgingival instrumentation have been reported to improve GI and BOP and reduce specific periodontopathogens, although the effects on PD and CAL have been inconsistent.²⁷ Probiotics containing Streptococcus salivarius, Bifidobacterium species, and mixed strains, delivered via lozenges, chewing gums, mouthrinses, or dairy-based vehicles, have shown variable effects on plaque accumulation, GI, BOP, and oral microbiota.^28,29

In contrast, the present study targeted gingivitis and incipient periodontitis without subgingival instrumentation, and the findings suggest that OraCMU may provide measurable benefits even under routine home oral hygiene conditions. GI and BOP, which primarily reflect gingival inflammation and bleeding tendency, showed improvement, whereas PD, CAL, and GR, which reflect periodontal tissue destruction and attachment loss generally associated with periodontitis,³ did not show significant between-group differences. This pattern of clinical outcomes supports an anti-inflammatory effect within a short time frame rather than structural periodontal regeneration.

The decline in PI in both groups in this study likely reflects improved home care following standardized instructions and the Hawthorne effect associated with clinical trial participation.³⁰ Importantly, despite similar plaque reduction, the OraCMU group showed greater improvements in GI and BOP, suggesting that the probiotic may have effects beyond simple plaque quantity reduction. Potential mechanisms include modulation of plaque composition toward less inflammatory profiles, competitive exclusion of specific pathogens, and reduced host inflammatory response.^12–15

Consistent with this interpretation, qPCR in our study revealed targeted reductions in several periodontitis-associated pathogens, including P. gingivalis, T. denticola, and P. intermedia, as well as a reduction in total pathogen load after eight weeks. These pathogens belong to the red complex (P. gingivalis, T. forsythia, T. denticola), which is strongly associated with clinical indicators such as bleeding and deep pockets, and the orange complex (P. intermedia), which is implicated in disease progression.³¹ Although the trial’s sampling relied on mouthwash collection rather than direct subgingival plaque, the observed reductions in these key species align with improved gingival inflammatory indices.

These microbial shifts support a plausible host–microbe pathway for reducing gingival inflammation despite similar plaque reductions in both groups. Lowering the burden of periodontopathogen-associated proinflammatory stimuli may reduce epithelial activation and downstream recruitment of inflammatory cells, thereby decreasing bleeding tendency and erythema. In addition to competitive effects within the oral biofilm, OraCMU has demonstrated antibacterial activity against periodontal pathogens and immunomodulatory responses in vitro, which may contribute to clinical and microbiological improvements.^12,15

Oral colonization is a key challenge for many probiotic products.^32–35 Probiotics derived from the oral cavity are more likely to persist in the oral environment and exert localized effects.³² Prior studies suggest that OraCMU can colonize or at least persist transiently in the oral cavity in preclinical and clinical settings,^16,18,36 which may help explain the observed increase in Weissella in this study. Although sequencing cannot definitively attribute Weissella reads to the administered strain, the directional increase supports exposure and potential ecological effects.

The exploratory proteomic findings provide further insights into potential mechanisms. Conventional inflammatory markers in gingival crevicular fluid (e.g., IL-1β, IL-6, MMPs) are difficult to detect or show small dynamic ranges in mild gingivitis.^37,38 Therefore, we used a high-throughput proximity extension assay to capture a broader set of immune-related proteins.²⁶ Among the 92 proteins assessed, only FGF-5, TSLP, and the RANKL/OPG ratio differed significantly between groups. Although these findings should be interpreted cautiously given the multiple comparisons and the exploratory nature of proteomic endpoints, they are biologically plausible.³⁹ TSLP can be induced in epithelial tissues under inflammatory stimuli and may amplify immune activation⁴⁰; its reduction is consistent with decreased inflammatory signaling. The decrease in the RANKL/OPG ratio may indicate a systemic shift toward reduced osteoclastogenic signaling,⁴¹ which could be relevant to periodontal tissue stability, although a longer follow-up would be required to assess clinical correlates.

Despite these promising findings, the study has limitations. First, the eight-week duration is adequate to detect changes in gingival inflammation and short-term microbiological or proteomic signals but is likely insufficient to observe changes in periodontal support (e.g., CAL gain) or stable long-term microbial remodeling. Second, although oral hygiene instructions were standardized, variability in adherence, dietary habits, and other behavioral factors could have influenced outcomes, but we did not formally quantify these covariates. Third, clinical assessments were limited to six index teeth rather than full-mouth evaluation, limiting generalizability. Fourth, microbiological assessments relied on whole-mouth swabs and mouthwash samples for feasibility and standardization; these methods may not fully capture subgingival communities relevant to periodontitis progression. Fifth, the proteomic analysis was exploratory and not powered for multiple-testing-adjusted inference; therefore, these findings should be viewed as hypothesis-generating. Finally, as this was a single-center study in a Korean population, confirmation in other settings and longer trials is warranted.

CONCLUSION

OraCMU supplementation for eight weeks improved clinical signs of gingival inflammation (GI and BOP) and reduced selected periodontopathogens without safety concerns in adults with gingivitis or incipient periodontitis receiving routine oral hygiene care. Longer term trials with full-mouth periodontal assessments, subgingival microbiological monitoring, and prespecified mechanistic endpoints are needed to confirm durability and clarify effects on periodontal disease progression.

AUTHORS’ CONTRIBUTIONS

H.-W.J.: Investigation (lead), formal analysis (lead), data curation (lead), writing—original draft (lead), and visualization (lead). K.-I.Y.: Writing—review and editing (equal) and visualization (supporting). S.-J.Y.: Writing—review and editing (equal) and visualization (supporting). M.-S.K.: Conceptualization (supporting), resources (lead), methodology (supporting), writing—review and editing (equal), and funding acquisition (lead). W.-P.L.: Conceptualization (lead), methodology (lead), validations (lead), supervision (lead), project administration (lead), and writing—review and editing (equal). All the authors approved the final version and agreed to be accountable for all aspects of the work.

Footnotes

ACKNOWLEDGMENT

The authors thank Editage () for editing and reviewing this article for English language. This study was supported by a research fund from the Chosun University, 2022.

CONSENT TO PARTICIPATE

All participants provided written informed consent.

DATA AVAILABILITY

The datasets generated and analyzed during the current study are not publicly available due to privacy concerns and ethical restrictions related to participant information. However, deidentified data may be made available by the corresponding author upon reasonable request and with approval from the Institutional Review Board. This clinical trial was registered with the Clinical Research Information Service (CRIS) of the Korea Disease Control and Prevention Agency (Registration No.: KCT0009810).

AUTHOR DISCLOSURE STATEMENT

M.S.K. is an employee of Oraticx, Inc. The other authors report no competing financial interests.

FUNDING INFORMATION

This study was funded by the Health Functional Food Development Support program (no. RS-2022–00167206), supported by the Ministry of Small and Medium Enterprises and Startups (Korea).

Supplemental Material

References

Murakami

, Mealey

, Mariotti

, et al. Dental plaque-induced gingival conditions. J Periodontol, 2018; 89(Suppl 1):S17–S27; doi: 10.1002/JPER.17-0095

Trombelli

. Gingivitis: The past, the present, the future. J Periodontal Res, 2025; 60(9):851–853; doi: 10.1111/jre.70041

Tonetti

, Greenwell

, Kornman

. Staging and grading of periodontitis: Framework and proposal of a new classification and case definition. J Periodontol, 2018; 89,(Suppl 1):S159–S172; doi: 10.1002/jper.18-0006

Chapple

, Van der Weijden

, Doerfer

, et al. Primary prevention of periodontitis: Managing gingivitis. J Clin Periodontol, 2015; 42(Suppl 1):S71–S76; doi: 10.1111/jcpe.12366

Jamjoom

, Zahid

. Systematic review of experimental gingivitis induction methods: Methodological variations and their impact on inflammation progression. Patient Prefer Adherence, 2025; 19:3835–3848; doi: 10.2147/PPA.S564132

Frieri

, Kumar

, Boutin

. Antibiotic resistance. J Infect Public Health, 2017; 10(4):369–378; doi: 10.1016/j.jiph.2016.08.007

Hill

, Guarner

, Reid

, et al. Expert consensus document. The International Scientific Association for Probiotics and Prebiotics consensus statement on the scope and appropriate use of the term probiotic. Nat Rev Gastroenterol Hepatol, 2014; 11(8):506–514; doi: 10.1038/nrgastro.2014.66

Martín

, Langella

. Emerging health concepts in the probiotics field: Streamlining the definitions. Front Microbiol, 2019; 10:1047; doi: 10.3389/fmicb.2019.01047

Mahasneh

, Mahasneh

. Probiotics: A promising role in dental health. Dent J (Basel), 2017; 5(4):26; doi: 10.3390/dj5040026

10.

Benavides-Reyes

, Cabello

, Magán-Fernández

, et al. Clinical effects of probiotics on the treatment of gingivitis and periodontitis: A systematic review and meta-analysis. BMC Oral Health, 2025; 25(1):490; doi: 10.1186/s12903-025-05888-5

11.

Alkaya

, Laleman

, Keceli

, et al. Clinical effects of probiotics containing Bacillus species on gingivitis: A pilot randomized controlled trial. J Periodontal Res, 2017; 52(3):497–504; doi: 10.1111/jre.12415

12.

Kang

, Kim

, Chung

, et al. Inhibitory effect of Weissella cibaria isolates on the production of volatile sulphur compounds. J Clin Periodontol, 2006; 33(3):226–232; doi: 10.1111/j.1600-051X.2006.00893.x

13.

, Park

, Kang

, et al. Effects of Weissella cibaria CMU on halitosis and calculus, plaque, and gingivitis indices in beagles. J Vet Dent, 2019; 36(2):135–142; doi: 10.1177/0898756419872562

14.

Kim

, Jung

, Lee

, et al. Effect of Weissella cibaria on the reduction of periodontal tissue destruction in mice. J Periodontol, 2020; 91(10):1367–1374; doi: 10.1002/JPER.19-0288

15.

Kim

, You

, Kang

, et al. Weissella cibaria CMU exerts an anti-inflammatory effect by inhibiting Aggregatibacter actinomycetemcomitans-induced NF-κB activation in macrophages. Mol Med Rep, 2020; 22(5):4143–4150; doi: 10.3892/mmr.2020.11512

16.

Kang

, Lee

, et al. Effects of probiotic bacterium Weissella cibaria CMU on periodontal health and microbiota: A randomised, double-blind, placebo-controlled trial. BMC Oral Health, 2020; 20(1):243; doi: 10.1186/s12903-020-01231-2

17.

Lee

, Lee

, Kim

, et al. Reduction of halitosis by a tablet containing Weissella cibaria CMU: A randomized, double-blind, placebo-controlled study. J Med Food, 2020; 23(6):649–657; doi: 10.1089/jmf.2019.4603

18.

Han

, Yum

, Cho

, et al. Improvement of halitosis by probiotic bacterium Weissella cibaria CMU: A randomized controlled trial. Front Microbiol, 2023; 14:1108762; doi: 10.3389/fmicb.2023.1108762

19.

Alshareef

, Attia

, Almalki

, et al. Effectiveness of probiotic lozenges in periodontal management of chronic periodontitis patients: Clinical and immunological study. Eur J Dent, 2020; 14(2):281–287; doi: 10.1055/s-0040-1709924

20.

Laleman

, Pauwels

, Quirynen

, et al. A dual-strain Lactobacilli reuteri probiotic improves the treatment of residual pockets: A randomized controlled clinical trial. J Clin Periodontol, 2020; 47(1):43–53; doi: 10.1111/jcpe.13198

21.

Chapple

ILC

, Mealey

, Van Dyke

, et al. Periodontal health and gingival diseases and conditions on an intact and a reduced periodontium: Consensus report of workgroup 1 of the 2017 World Workshop on the Classification of Periodontal and Peri-Implant Diseases and Conditions. J Periodontol, 2018; 89,(Suppl 1):S74–S84; doi: 10.1002/JPER.17-0719

22.

Hashemi

, Hashempur

, Lotfi

, et al. The efficacy of asafoetida (Ferula assa-foetida oleo-gum resin) versus chlorhexidine gluconate mouthwash on dental plaque and gingivitis: A randomized double-blind controlled trial. Eur J Intern Med, 2019; 29:100929; doi: 10.1016/j.eujim.2019.100929

23.

Hasturk

, Hajishengallis

, Lambris

, et al.; Forsyth Institute Center for Clinical and Translational Research staff. Phase IIa clinical trial of complement C3 inhibitor AMY-101 in adults with periodontal inflammation. J Clin Invest, 2021; 131(23):e152973; doi: 10.1172/JCI152973

24.

Adam

, Erb

, Grender

. Randomized controlled trial assessing plaque removal of an oscillating-rotating electric toothbrush with micro-vibrations. Int Dent J, 2020; 70(Suppl 1):S22–S27; doi: 10.1111/idj.12568

25.

Kim

, Joo

, Lee

, et al. Grading system for periodontitis by analyzing levels of periodontal pathogens in saliva. PLoS One, 2018; 13(11):e0200900; doi: 10.1371/journal.pone.0200900

26.

Assarsson

, Lundberg

, Holmquist

, et al. Homogenous 96-plex PEA immunoassay exhibiting high sensitivity, specificity, and excellent scalability. PLoS One, 2014; 9(4):e95192; doi: 10.1371/journal.pone.0095192

27.

Tekce

, Ince

, Gursoy

, et al. Clinical and microbiological effects of probiotic lozenges in the treatment of chronic periodontitis: A 1-year follow-up study. J Clin Periodontol, 2015; 42(4):363–372; doi: 10.1111/jcpe.12387

28.

Chen

, Sharma

, Shao

, et al. Adjunctive use of Streptococcus salivarius M18 probiotic in the treatment of periodontitis: A randomized controlled trial. 3 Biotech, 2025; 15(6):192; doi: 10.1007/s13205-025-04363-w

29.

Cernioglo

, Kalanetra

, Meier

, et al. Multi-strain probiotic supplementation with a product containing human-native S. salivarius K12 in healthy adults increases oral S. salivarius. Nutrients, 2021; 13(12):4392; doi: 10.3390/nu13124392

30.

Abdulraheem

, Bondemark

. Hawthorne effect reporting in orthodontic randomized controlled trials: Truth or myth? Blessing or curse? Eur J Orthod, 2018; 40(5):475–479; doi: 10.1093/ejo/cjx089

31.

Socransky

, Haffajee

, Cugini

, et al. Microbial complexes in subgingival plaque. J Clin Periodontol, 1998; 25(2):134–144; doi: 10.1111/j.1600-051x.1998.tb02419.x

32.

Van Holm

, Lauwens

, De Wever

, et al. Probiotics for oral health: Do they deliver what they promise? Front Microbiol, 2023; 14:1219692; doi: 10.3389/fmicb.2023.1219692

33.

Yli-Knuuttila

, Snäll

, Kari

, et al. Colonization of Lactobacillus rhamnosus GG in the oral cavity. Oral Microbiol Immunol, 2006; 21(2):129–131; doi: 10.1111/j.1399-302X.2006.00258.x

34.

Caglar

, Topcuoglu

, Cildir

, et al. Oral colonization by Lactobacillus reuteri ATCC 55730 after exposure to probiotics. Int J Paediatr Dent, 2009; 19(5):377–381; doi: 10.1111/j.1365-263X.2009.00989.x

35.

Udawatte

, Liu

, Staples

, et al. Short-term probiotic colonization alters molecular dynamics of 3D oral biofilms. Int J Mol Sci, 2025; 26(13):6403; doi: 10.3390/ijms26136403

36.

, Boo

, You

, et al. Preventive effects of Weissella cibaria CMU on the progression of periodontitis in a rat model. J Oral Microbiol, 2025; 17(1):2469895; doi: 10.1080/20002297.2025.2469895

37.

Fatima

, Khurshid

, Rehman

, et al. Gingival crevicular fluid (GCF): A diagnostic tool for the detection of periodontal health and diseases. Molecules, 2021; 26(5):1208; doi: 10.3390/molecules26051208

38.

Nędzi-Góra

, Górska

, Górski

. The utility of gingival crevicular fluid matrix metalloproteinase-8 provides site-specific diagnostic value for periodontal grading. Cent Eur J Immunol, 2021; 46(2):236–243; doi: 10.5114/ceji.2021.107031

39.

Regeenes

, Silva

, Chang

, et al. Fibroblast growth factor receptor 5 (FGFR5) is a co-receptor for FGFR1 that is up-regulated in beta-cells by cytokine-induced inflammation. J Biol Chem, 2018; 293(44):17218–17228; doi: 10.1074/jbc.RA118.003036

40.

, Geha

. Thymic stromal lymphopoietin. Ann N Y Acad Sci, 2010; 1183(1):13–24; doi: 10.1111/j.1749-6632.2009.05128.x

41.

AlQranei

, Chellaiah

. Osteoclastogenesis in periodontal diseases: Possible mediators and mechanisms. J Oral Biosci, 2020; 62(2):123–130; doi: 10.1016/j.job.2020.02.002

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.03 MB

0.00 MB

0.05 MB