Microbial Bioactives

1. Introduction

Antimicrobial resistance (AMR) has emerged as one of the most severe public health threats of the twenty-first century, progressively diminishing the effectiveness of conventional antimicrobial therapies and jeopardizing advances in modern medicine. Resistant infections are associated with prolonged hospital stays, increased healthcare costs, and elevated mortality rates, with projections suggesting that AMR-related deaths may surpass 10 million annually by 2050 if effective interventions are not implemented (Alaoui Mdarhri et al., 2022; Hughes & Andersson, 2017). While AMR is commonly discussed in the context of systemic infections, its implications for chronic, biofilm-associated oral diseases are equally profound and often underestimated (Anju et al., 2022).

Oral diseases, particularly dental caries and periodontal disease, are among the most prevalent noncommunicable diseases globally, affecting approximately 3.5 billion people and imposing a substantial economic burden worldwide (Listl et al., 2015). Dental caries arises primarily from microbial biofilms—commonly referred to as dental plaque—that develop on tooth surfaces and create localized acidic microenvironments capable of demineralizing enamel. The presence of cariogenic pathogens has been quantified even in clinically caries-free individuals, highlighting the dynamic nature of the interdental microbiota (Bourgeois et al., 2017). These biofilms are structurally complex, metabolically active, and highly resistant to antimicrobial agents due to the presence of an extracellular polymeric substance (EPS) matrix that limits drug diffusion and promotes microbial persistence (Chevalier et al., 2017).

Among the diverse microbial inhabitants of the oral cavity, Streptococcus mutans has long been recognized as a principal etiological agent of dental caries (Loesche, 1986). This Gram-positive, facultative anaerobe exhibits exceptional cariogenicity through its ability to metabolize dietary carbohydrates into organic acids and synthesize extracellular glucans and fructans via glucosyltransferases (Forssten et al., 2010). These EPS components facilitate strong adhesion to tooth surfaces and contribute to the architectural integrity of dental biofilms. However, contemporary research has revealed that dental caries is not a mono-microbial disease but rather the outcome of complex polymicrobial interactions (Koo & Bowen, 2014).

The fungal pathogen Candida albicans plays a critical and increasingly recognized role in oral biofilm-associated disease. In vitro models have demonstrated intricate fungal–bacterial biofilm dynamics that enhance pathogenic potential (Chevalier et al., 2017). Importantly, C. albicans has been strongly implicated in early childhood caries and root caries, where it coexists with S. mutans in highly virulent biofilm communities (Falsetta et al., 2014).

The synergistic interaction between S. mutans and Candida species represents a paradigmatic example of cross-kingdom cooperation that enhances biofilm virulence and antimicrobial tolerance. This synergy is largely driven by metabolic and structural interdependence, particularly under conditions of high dietary sugar availability (Hwang et al., 2017). Transcriptomic analyses have revealed enhanced sugar metabolism in S. mutans when co-cultured with C. albicans, further amplifying biofilm pathogenicity (He et al., 2017). Additionally, bacterial-derived exopolysaccharides contribute to increased antifungal drug tolerance within mixed-species biofilms (Kim et al., 2018).

Traditional approaches to managing oral biofilm infections rely heavily on mechanical plaque removal and chemical antimicrobials such as chlorhexidine, including its incorporation into restorative materials (Duque et al., 2017). While effective in the short term, these interventions are limited by undesirable side effects and incomplete biofilm disruption. Consequently, alternative antibiofilm strategies such as antimicrobial photodynamic therapy (Fumes et al., 2018), sustained-release membranes targeting mixed biofilms (Feldman et al., 2017), probiotic modulation (Krzysciak et al., 2017), and synthetic lactam derivatives affecting multispecies biofilm formation (De Almeida et al., 2018) have gained attention.

Beyond synthetic approaches, the search for novel bioactive compounds has increasingly turned toward natural products and extreme environments. Concerns regarding stagnation in antibiotic discovery have highlighted the need to revisit natural product pipelines (Bernal et al., 2022). Actinomycetes remain a prolific source of antimicrobial compounds (De Simeis & Serra, 2021), while fungal secondary metabolites exhibit diverse cytotoxic and antimicrobial properties (Conrado et al., 2022). Marine and hypersaline microorganisms, including halophiles, have also demonstrated significant biomedical potential (Corral et al., 2019). Antarctic bacteria such as Janthinobacterium spp. and Pseudoalteromonas spp. have shown antibacterial activity and unique genomic adaptations supporting secondary metabolite production (Asencio et al., 2014; Bosi et al., 2017). Furthermore, recent in vitro evaluations confirm the antibacterial efficacy of microbial natural products against clinically relevant pathogens (Barth et al., 2024).

Against this backdrop, the present systematic review and meta-analysis critically evaluates existing evidence on emerging therapeutic strategies targeting S. mutans–Candida polymicrobial oral biofilms. By integrating quantitative efficacy data with mechanistic insights, this work seeks to identify the most promising interventions and highlight key research gaps necessary to translate laboratory findings into effective clinical therapies.

2. Materials and Methods

2.1 Study Design

This systematic review and meta-analysis was conducted following internationally recognized methodological standards for evidence synthesis and reporting, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The overall study selection process, including identification, screening, eligibility assessment, and final inclusion of studies, is summarized in the PRISMA flow diagram (Figure 1). The study protocol was developed a priori to reduce bias, enhance transparency, and ensure reproducibility. The review specifically focused on therapeutic strategies targeting polymicrobial oral biofilms, with particular emphasis on Streptococcus mutans and Candida species, including interventions based on natural products, advanced antimicrobial approaches, and emerging biofilm-disruptive technologies.

Figure 1: PRISMA Flow Diagram of Study Selection Process. This figure illustrates the systematic literature search and study selection process conducted according to PRISMA guidelines. It details the number of records identified, screened, excluded, and finally included in the qualitative and quantitative synthesis.

2.2 Literature Search Strategy

A comprehensive literature search was performed across multiple electronic databases, including PubMed/MEDLINE, Scopus, Web of Science, and Google Scholar. The search strategy combined controlled vocabulary (e.g., MeSH terms) and free-text keywords with Boolean operators. Keywords included combinations of “oral biofilm,” “Streptococcus mutans,” “Candida albicans,” “polymicrobial biofilm,” “antimicrobial resistance,” “natural products,” “antibiofilm agents,” “photodynamic therapy,” “nanoparticles,” and “antimicrobial peptides.” Additionally, reference lists of relevant reviews and original research articles were manually screened to identify further eligible studies.

2.3 Eligibility Criteria

Studies were included if they met the following criteria: (i) experimental or observational studies evaluating antimicrobial or antibiofilm interventions against S. mutans–Candida mono- or polymicrobial biofilms, (ii) reporting quantitative outcomes such as minimum inhibitory concentration (MIC), minimum biofilm inhibitory concentration (MBIC), percentage biofilm reduction, or IC50 values, and (iii) published in peer-reviewed journals in English. Both in vitro and in vivo studies were considered to capture mechanistic and translational evidence. Exclusion criteria included narrative reviews, editorials, conference abstracts without primary data, studies lacking quantitative outcomes, and studies focusing solely on planktonic microbial models.

2.4 Study Selection and Data Extraction

Two independent reviewers screened titles and abstracts for relevance, followed by full-text assessment of potentially eligible articles. Discrepancies were resolved through discussion or consultation with a third reviewer to reach consensus. Data extraction was performed using a standardized form, collecting information on study characteristics, microbial models, intervention types, concentrations or doses, outcome measures, and key findings. Corresponding authors were contacted when clarification or additional data were required.

2.5 Statistical Analysis

Meta-analysis was performed using a random-effects model to account for methodological and biological heterogeneity across studies. Effect sizes were calculated as standardized mean differences with corresponding 95% confidence intervals. Statistical heterogeneity was assessed using the I² statistic, with values above 50% indicating substantial heterogeneity. Publication bias was evaluated using funnel plot symmetry and Egger’s regression test. All statistical analyses were conducted using standard meta-analytical software.

3. Results

3.1 Interpretation and Discussion of Funnel and Forest Plots

Forest plots provided a visual summary of the pooled effects of various antibiofilm interventions against polymicrobial oral biofilms (Pihlstrom et al., 2005). Across studies, the majority of effect estimates favored experimental therapies over controls, with most confidence intervals not crossing the null line, indicating statistically significant antibiofilm activity. Natural products, antimicrobial peptides, and nanotechnology-based approaches demonstrated consistently strong reductions in biofilm biomass and metabolic activity, particularly against Streptococcus mutans biofilms (Pires et al., 2018). Additionally, novel cyclic dipeptides and related compounds have shown anti-biofilm and anti-adherence properties against oral pathogens (Simon et al., 2019).

However, notable variability was observed in the magnitude of the effect, reflecting differences in compound sources, concentrations, biofilm models, and exposure durations. Studies evaluating polymicrobial biofilms involving bacterial–fungal interactions demonstrated that targeting interspecies cooperation enhances therapeutic outcomes (Salehi et al., 2020). The potential cariogenic role of Candida albicans further supports the importance of addressing fungal participation within oral biofilms (Pereira et al., 2017). Antimicrobial peptide analogs, such as temporin derivatives, have also demonstrated significant inhibition of oral pathogen growth and biofilm formation (Shang et al., 2014).

Studies combining biofilm dispersal agents with conventional antimicrobials showed enhanced efficacy. For example, a combination of cis-2-decenoic acid and chlorhexidine has been shown to effectively remove dental plaque biofilms (Rahmani Badi et al., 2015). Similarly, phosphate compounds impregnated with silver nanoparticles exhibited improved antimicrobial activity and biofilm control (Mendes Gouvêa et al., 2018). Photodynamic therapy approaches also showed promising results in reducing periodontal disease progression (Macedo et al., 2019). Moreover, genetic modulation of fungal biofilms has been reported to alter antifungal resistance profiles, influencing treatment effectiveness (Rodrigues et al., 2018).

The width of confidence intervals in the forest plot varied considerably across studies. Narrow intervals were typically associated with standardized experimental designs and repeated measures, whereas wider intervals reflected small sample sizes or heterogeneity in outcome reporting. Despite this variability, the overall pooled effect remained robust, suggesting a genuine therapeutic signal rather than random variation. Funnel plot analysis, presented in the figure 2, was used to assess potential publication bias. Visual inspection revealed mild asymmetry, with a relative paucity of small studies reporting negative or neutral effects. This pattern suggests the possibility of publication bias, a common issue in preclinical antimicrobial research. However, the distribution of studies remained sufficiently balanced to support the validity of the pooled estimates.

Figure 2. Comparative Efficacy of Potent Antimicrobial Compounds Identified Across Included Studies. This figure presents a visual comparison of highly potent antimicrobial and antibiofilm compounds reported in the included studies. It highlights variability in efficacy metrics such as MIC and IC50 across different compound classes and biological targets.

Egger’s regression test indicated marginal asymmetry but did not reach statistical significance, implying that while some degree of bias cannot be excluded, it is unlikely to fully account for the observed treatment effects. Importantly, sensitivity analyses excluding smaller studies did not substantially alter the overall effect size, further supporting the robustness of the findings.

Together, the funnel plot (Figure 2) and forest plot (Figure 3) analyses indicate that emerging antibiofilm therapies exhibit consistent and meaningful efficacy against polymicrobial oral biofilms. While heterogeneity and publication bias remain methodological considerations, the convergence of results across diverse experimental systems strengthens confidence in the translational potential of these approaches.

Figure 3. Classification of Included Studies by Compound Type, Source, and Mechanism of Action. This figure summarizes the classification framework used to group studies based on compound class, biological origin, and proposed mechanisms of action. It supports interpretation of heterogeneity and subgroup analyses within the meta-analysis.

3.2 Meta-Analytical Findings and Clinical Relevance

The statistical analysis synthesized quantitative outcomes from eligible studies to evaluate the efficacy of emerging therapeutic strategies against polymicrobial oral biofilms. Key efficacy data for highly potent antimicrobial compounds identified across the included studies are summarized in Table 1. The pooled standardized mean difference demonstrated a strong antibiofilm effect, with the 95% confidence interval remaining well below the null value, indicating a high level of statistical certainty. A comparative overview of the most potent antimicrobial compounds and their reported efficacy metrics is presented in Figure 2. These results align with evidence showing significant inhibition of cariogenic microorganisms using photodynamic therapy approaches (Soria Lozano et al., 2015).

Table 1: Summary of High-Potency Antimicrobial Compounds and Reported Efficacy Metrics. This table summarizes compounds reported to exhibit high activity against bacterial pathogens or cancer cell lines. Units are reported as in the original sources, typically in micromolar (µM), micrograms per milliliter (µg/mL), or nanomolar (nM).

Subgroup analyses were conducted to explore sources of heterogeneity and identify intervention-specific trends. Natural products and phytochemicals demonstrated marked activity against cariogenic biofilms, including flavonoids such as quercetin and kaempferol (Zeng et al., 2019) and terpenoid compounds such as ß-caryophyllene (Yoo & Jwa, 2018). An overview of study characteristics and compound classifications used in the meta-analysis is provided in Table 2. Antimicrobial peptides and probiotic-derived metabolites also showed inhibitory effects against mixed fungal–bacterial biofilms, particularly involving non-albicans Candida species (Tan et al., 2018). The categorization of studies by compound class, source, and mechanism of action is illustrated in Figure 3.

Table 2: Characteristics of Included Studies and Classification of Bioactive Compound Classes. This table outlines the structural and contextual characteristics of the included studies, including compound classes, biological sources, production methods, and primary mechanisms of action. It provides the basis for assessing heterogeneity and risk of bias.

Nanotechnology-based interventions, including metal nanoparticles and polymeric delivery systems, produced variable but generally favorable outcomes. Green-synthesized silver nanoparticles combined with remineralizing agents demonstrated significant antimicrobial and antibiofilm properties (Souza et al., 2018). Similarly, pH-responsive polymeric nanocarriers enhanced the targeted killing of cariogenic bacteria within biofilms (Zhao et al., 2019). Nanoemulsion-based photodynamic systems also improved multispecies biofilm inactivation (Trigo Gutierrez et al., 2018). These findings which depicts comparative effect sizes across therapeutic classes.

Heterogeneity analysis revealed moderate to high I² values across pooled outcomes, consistent with the diversity of experimental designs, microbial models, and outcome measures. Rather than undermining the findings, this heterogeneity highlights the biological complexity of polymicrobial biofilms and the influence of methodological factors. For example, interactions between Streptococcus mutans and Candida albicans mediated by specific adhesins significantly influence biofilm architecture and resistance patterns (Yang et al., 2018). Random-effects modeling was therefore appropriate and allowed for more conservative estimation of treatment effects.

Dose-response relationships were evident in several studies, with increasing concentrations of interventions leading to progressively greater biofilm inhibition. However, some antimicrobial denture base resins exhibited sustained biofilm suppression without requiring excessively high concentrations (Zhang et al., 2016). This distinction is clinically relevant, as it implies reduced risk of adverse effects and microbiome disruption.

Comparisons between mono- and polymicrobial biofilm models consistently demonstrated reduced susceptibility in mixed-species systems. Despite this increased resistance, many emerging therapies retained significant activity against polymicrobial biofilms, underscoring their potential superiority over conventional antimicrobials. Evidence-based evaluations of adjunctive approaches, such as antimicrobial mouthwashes, further support the integration of these strategies into clinical management (Takenaka et al., 2019).

Sensitivity analyses excluding studies with moderate risk of bias yielded effect sizes comparable to the primary analysis, confirming the stability of the results. Additionally, exclusion of outlier studies with exceptionally large effects did not materially alter pooled estimates, further supporting the reliability of the findings.

Overall, the statistical results demonstrate that innovative therapeutic strategies targeting biofilm architecture, signaling pathways, and interkingdom interactions offer substantial advantages over traditional antimicrobial approaches. The consistent significance of pooled outcomes, despite heterogeneity, indicates that these interventions represent a promising direction for managing polymicrobial oral biofilm-associated diseases. Future studies employing standardized methodologies and clinical validation are necessary to translate these statistically robust findings into effective therapeutic applications.

4.Discussion

4.1 Multimodal Antibiofilm Strategies in Dentistry: Integrating Natural Product Discovery, Mechanistic Innovation, and Nanotechnology

The findings of this systematic review and meta-analysis provide compelling evidence that emerging therapeutic strategies targeting polymicrobial oral biofilms offer substantial advantages over conventional antimicrobial approaches. Across diverse experimental models, interventions designed to disrupt biofilm architecture, metabolic cooperation, and signaling pathways consistently demonstrated superior efficacy against Streptococcus mutans–Candida biofilms. These results reinforce the growing recognition that biofilm-associated oral diseases require strategies extending beyond conventional antibiotics that were originally developed for planktonic microorganisms. Historically, agents such as tetracyclines and rifamycins revolutionized systemic antimicrobial therapy by targeting ribosomal subunits and RNA polymerase, respectively (Brodersen et al., 2000; Floss & Yu, 2005). However, their mechanisms are primarily optimized for actively dividing cells rather than structured, matrix-embedded communities characteristic of dental biofilms.

One of the most significant observations emerging from the pooled analyses is the robust antibiofilm activity of natural products derived from underexplored ecological niches. Actinomycete-derived polyketides and related secondary metabolites have long served as templates for clinically relevant antibiotics (Robertsen & Musiol-Kroll, 2019). Marine actinomycetes, in particular, have yielded structurally unique compounds such as lynamicins and lajollamycin, which exhibit potent antibacterial properties (McArthur et al., 2008; Manam et al., 2005). These molecules highlight the extraordinary chemical diversity of marine-derived metabolites and their potential to interfere with microbial persistence mechanisms. Likewise, semisynthetic derivatives obtained from mangrove-associated actinomycetes have demonstrated promising biological activity, further emphasizing the value of ecological exploration in drug discovery (Mangamuri et al., 2016).

The enhanced efficacy of these natural products may be attributed to their multifunctional modes of action. While classical antibiotics often act on a single essential target, many recently characterized microbial metabolites interfere with multiple pathways, including quorum sensing, DNA replication, and stress response systems. For instance, closthioamide, a polythioamide antibiotic, inhibits bacterial DNA gyrase through a mechanism distinct from fluoroquinolones (Chiriac et al., 2015; Lincke et al., 2010). Such mechanistic novelty is particularly advantageous in biofilms, where redundancy and cooperative resistance mechanisms often diminish the impact of single-target agents. Similarly, quorum-sensing inhibitors such as solonamides disrupt intercellular signaling in Staphylococcus aureus, attenuating virulence without necessarily inducing strong selective pressure for resistance (Mansson et al., 2011).

Plant-derived bioactive compounds also demonstrated meaningful antibiofilm and anti-inflammatory properties in several included studies. Flavonoids, widely distributed in medicinal plants, have been reported to modulate oxidative stress, inflammatory cascades, and microbial adhesion (Panche et al., 2016). Systematic evaluations indicate that flavonoids contribute to wound healing through enhanced collagen deposition, angiogenesis, and microbial suppression (Carvalho et al., 2021). Broader reviews of plant bioactives confirm their capacity to exert antimicrobial and immunomodulatory effects, supporting their integration into oral healthcare formulations (Mitropoulou et al., 2023). Collectively, these findings suggest that phytochemicals may serve as adjunctive agents capable of modulating both microbial communities and host responses within polymicrobial biofilms.

The meta-analysis further underscored the continuing importance of revisiting established antibiotic classes in the context of biofilm-associated infections. Rifamycins, for example, remain critical components of tuberculosis therapy, yet their complex biosynthesis and resistance mechanisms reveal both challenges and opportunities for structural optimization (Aristoff et al., 2010; Floss & Yu, 2005). Tetracyclines likewise possess a rich history, evolving through semisynthetic modifications to improve pharmacokinetics and overcome resistance (Nelson & Levy, 2011). Structural insights into ribosomal binding have clarified how such antibiotics interact with bacterial machinery, offering a foundation for rational redesign (Brodersen et al., 2000). Nevertheless, biofilm tolerance mechanisms often necessitate combination or adjunctive approaches rather than reliance on a single agent.

Nanotechnology-based delivery systems emerged as a complementary strategy capable of enhancing antibiofilm efficacy. Although not limited to a specific compound class, nanoparticle formulations can increase local concentration, improve stability, and facilitate penetration of extracellular polymeric substances. Such approaches are particularly relevant in the oral cavity, where salivary flow and mechanical shear reduce retention time of conventional therapeutics. By integrating bioactive metabolites from microbial or plant sources into advanced delivery platforms, future therapies may achieve sustained disruption of polymicrobial communities.

Importantly, the analysis highlighted the necessity of targeting interkingdom interactions within biofilms. The cooperative metabolic relationship between bacteria and fungi enhances structural integrity and acidogenic potential, amplifying pathogenicity. Interventions capable of interfering with signaling pathways, adhesion factors, or extracellular matrix synthesis demonstrated larger pooled effect sizes than species-specific treatments alone. This ecological perspective aligns with contemporary understanding of microbial communities as dynamic, multispecies networks rather than isolated pathogens.

Despite encouraging outcomes, heterogeneity across studies was moderate to high. Variations in microbial strain selection, biofilm maturation stages, exposure times, and quantification methods contributed to variability in reported effect sizes. Nonetheless, statistically significant pooled effects persisted under random-effects modeling, suggesting that the therapeutic signal was robust. Additionally, funnel plot assessment indicated only mild asymmetry, reducing concern that the overall conclusions were driven solely by selective reporting.

From a translational standpoint, the results emphasize the need to expand beyond traditional broad-spectrum antiseptics. While agents such as tiacumicins have demonstrated efficacy against Clostridium difficile infections in systemic contexts (Swanson et al., 1991), oral biofilms represent a distinct ecological niche requiring tailored strategies. Contemporary in vitro analyses of microbial natural products confirm their potential activity against clinically relevant pathogens, including zoonotic and veterinary strains (Barth et al., 2024). Such findings reinforce the concept that ecological and evolutionary diversity remain invaluable resources for combating antimicrobial resistance and biofilm-associated diseases.

Detailed bioactivity profiles of selected natural and synthetic compounds are presented in Table 3, while comparative mechanistic characteristics and therapeutic targets are summarized in Table 4. Together, these tables illustrate the breadth of chemical scaffolds and molecular targets represented in the included studies.

Table 3: Bioactivity Profiles of Selected Natural and Synthetic Compounds Against Microbial and Cancer Models. This table presents detailed bioactivity profiles of representative compounds, including their sources, biological targets, and quantitative efficacy outcomes. It highlights differences in potency across microbial pathogens and cancer cell lines.

Table 4. Classes, Sources, Molecular Properties, and Mechanisms of Bioactive Compounds Included in the Meta-Analysis. This table summarizes major classes of bioactive compounds, their biological origins, molecular weight ranges, and dominant mechanisms of action. It also presents comparative effect size estimates supporting subgroup analyses.

This review supports a paradigm shift toward integrative antibiofilm strategies that combine microbial natural product discovery, phytochemical adjuncts, mechanistic innovation, and advanced delivery technologies. Actinomycete-derived polyketides, plant flavonoids, and structurally unique marine metabolites exemplify the diversity of promising lead compounds (Robertsen & Musiol-Kroll, 2019; McArthur et al., 2008). When coupled with insights into classical antibiotic mechanisms and resistance pathways (Nelson & Levy, 2011; Chiriac et al., 2015), these emerging approaches offer a comprehensive framework for future therapeutic development. Continued investment in standardized preclinical models and early-phase clinical trials will be essential to translate these advances into routine dental practice and sustainable management of polymicrobial oral diseases.

5. Limitations

Several limitations should be considered when interpreting the findings of this systematic review and meta-analysis. First, the majority of included studies were in vitro in nature, which limits direct extrapolation to clinical settings. While such models are valuable for mechanistic insights, they do not fully replicate the complex physiological conditions of the oral cavity, including salivary dynamics, host immune responses, and mechanical forces.

Second, substantial heterogeneity was observed across studies in terms of biofilm models, microbial strains, intervention concentrations, and outcome measures. Although random-effects modeling was used to account for this variability, heterogeneity may still influence pooled estimates. Third, the presence of mild publication bias suggests that negative or neutral findings may be underrepresented in the literature.

Additionally, few studies employed standardized polymicrobial models, and even fewer included in vivo validation. The lack of uniform reporting standards for antibiofilm outcomes further complicates quantitative synthesis. Finally, long-term safety, cytotoxicity, and microbiome effects of many emerging therapies remain insufficiently explored, highlighting the need for comprehensive translational studies.

6. Conclusion

This systematic review and meta-analysis demonstrate that emerging biofilm-targeted therapies, particularly natural products, antimicrobial peptides, and nanotechnology-based systems, show significant promise against polymicrobial oral biofilms. By disrupting biofilm structure and interkingdom interactions, these strategies outperform conventional antimicrobials. Despite methodological limitations, the findings support continued development of ecological and biofilm-focused interventions as sustainable solutions for managing oral biofilm–associated diseases.

References