Global Research Trends in the Detection and Diagnosis of Dental Caries: A Bibliometric Analysis

This study aims to provide an overview of the global research trends in the detection and diagnosis of dental caries in the past 20 years. A literature search was conducted in the Scopus Database to retrieve studies on the diagnostic approaches for dental caries published from January 2003 to December 2023. The diagnostic approaches in the retrieved studies were examined and the studies were categorized according to the diagnostic approaches investigated. Bibliometric data including journals, countries, affiliations, authors, and numbers of citations of the publications were summarised. The publications' keyword co-occurrence was analysed using VOSviewer. This bibliometric analysis included 1879 publications investigating seven categories of caries diagnostic approaches, including visual and/or tactile (n = 459; 19%), radiation-based (n = 662; 27%), light-based (n = 771; 32%), ultrasound-based (n = 28; 1%), electric-based (n = 51; 2%), molecular-based (n = 196; 8%) diagnostic approaches, as well as AI-based diagnostic interpretation aids (n = 265; 11%). An increase in the annual number of publications on caries diagnostic approaches was observed in the past 20 years. Caries Research (n = 103) presented the highest number of publications on caries diagnostic approaches. The country with the highest number of publications was the United States (n = 1092). The University of São Paulo was the institution that published the highest number of articles (n = 195). The publication with the highest citation has been cited 932 times. VOS viewer revealed that the most frequently occurring keywords were 'Deep Learning', 'Artificial Intelligence', 'Laser Fluorescence' and 'Radiography'. This bibliometric analysis highlighted an emerging global research trend in the detection and diagnosis approaches for dental caries in the past 20 years. An evident increase in publications on molecular-based caries diagnostic approaches and AI-based diagnostic interpretation aids was perceived over the last 5 years.

Periodontal disease in down syndrome: Predisposing factors and potential non-surgical therapeutic approaches

BACKGROUND

Periodontal diseases (PDs) have been documented to be significantly more prevalent and severe in patients with Down syndrome (DS). Different immunological and microbiological factors contributed to predisposing these patients to progressive and recurrent PDs.

AIM

The aim of this review was to investigate the altered immunological responses and oral microbiota disorders as well as focus on adjunctive non-surgical methods for the treatment of PDs and its applicability in patients with DS.

MATERIAL AND METHODS

A literature review was conducted addressing the following topics: (1) the altered immunological responses, (2) orofacial disorders related to DS patients, (3) oral microbiota changing, and (4) adjunctive non-surgical treatment and its efficacy in patients with DS.

RESULTS

Due to the early onset of PDs in children with DS, the need for prompt and effective treatment in these patients is essential.

DISCUSSION AND CONCLUSION

So, investigating underlying factors may open a new window to better understand the pathology of PDs in DS people and thus, find better strategies for treatment in such group. Although non-surgical treatments such as photodynamic therapy and probiotic consumption represented acceptable outcomes in different examined patients without DS, data about the application of these convenience and no need for local anesthesia methods in patients with DS is limited.

Histopathological diagnosis in pediatric stomatology: A 43-year retrospective study of 1,480 cases from a Brazilian institution

OBJECTIVES

the aim of this study was to analyze the prevalence of histopathological diagnoses in oral biopsied tissues obtained from a Brazilian pediatric population.

METHODS

an analytical, cross-sectional retrospective study was performed with biopsy files of patients ≤14 years of age from a Brazilian oral pathology laboratory over a 43-year period. Data included sex, age, location, and diagnoses. The prevalence was calculated by means of relative frequency. Associations between sex, age groups and diagnoses were verified with Pearson's chi-square test.

RESULTS

from 19,456 oral biopsies, 1480 (7.6%) were obtained from patients aged ≤14 years. Most children were 10-14 years of age (60.1%) and females (55.1%), with an overall M:F of 1:1.2. Children aged 0-9 years and males had a higher frequency of lesions of the oral mucosa, whilst the 10-14 year age group showed a higher frequency of cysts, odontogenic tumors, and salivary gland lesions. The latter was also significantly higher in females. Samples consisted mostly of soft tissue lesions (53%) obtained from the lower lip (30.7%). Intraosseous lesions showed a slight predilection for the mandible (21.2%). Salivary gland lesions (28.8%) was the most common diagnostic category, followed by reactive lesions (18.8%), and cysts (16.1%). Mucocele (33.5%), dentigerous cyst (6.7%), and fibrous hyperplasia (5.9%) were the top three histopathological diagnoses. Malignant lesions affected only 0.9% of this population.

CONCLUSION

our results were similar to other retrospective studies. Due to the low frequency of oral biopsies in children, data on the prevalence of oral pathology in this population might aid in the clinical and histopathologic diagnoses.

Proteomic Identification of Saliva Proteins as Noninvasive Diagnostic Biomarkers

Many biomedically relevant biomarkers are proteins with characteristic biochemical properties and a relatively restricted subcellular distribution. The comparative and mass spectrometry-based proteomic analysis of body fluids can be particularly instrumental for the targeted identification of novel protein biomarkers with pathological relevance. In this respect, new research efforts in biomarker discovery focus on the systematic mapping of the human saliva proteome, as well as the pathobiochemical identification of disease-related modifications or concentration changes in specific saliva proteins. As a product of exocrine secretion, saliva can be considered an ideal source for the biochemical identification of new disease indicators. Importantly, saliva represents a body fluid that is continuously available for diagnostic and prognostic assessments. This chapter gives an overview of saliva proteomics, including a discussion of the usefulness of both liquid chromatography and two-dimensional gel electrophoresis for efficient protein separation in saliva proteomics.

The New Era of Salivaomics in Dentistry: Frontiers and Facts in the Early Diagnosis and Prevention of Oral Diseases and Cancer

Nowadays, with the development of new and highly sensitive, blood is not the only medium of choice for the diagnosis of several diseases and pathological conditions. Saliva is now considered a safe and non-invasive sample to study oral and systemic diseases, showing great diagnostic potential. According to several recent studies, saliva has emerged as an emerging biofluid for the early diagnosis of several diseases, indicated as a mirror of oral and systemic health and a valuable source of clinically relevant information. Indeed, several studies have observed that saliva is useful for detecting and diagnosing malignant tumours, human immunodeficiency virus, heart disease, and autoimmune diseases. The growing realisation that saliva is an inexhaustible source of information has led to the coining of the term ‘Salivaomics’, which includes five “omics” in connection with the main constituents of saliva: genome and epigenome, transcriptomics, metabolomics, lipidomics, proteomics and microbiota. All those may be changed by disease state, so they offer significant advantages in the early diagnosis and prognosis of oral diseases. The aim of the present review isto update and highlight the new frontiers of salivaomics in diagnosing and managing oral disorders, such as periodontitis, premalignant disorders, and oral squamous cell carcinoma (OSCC).

Salivary Microbiota and Host-Inflammatory Responses in Periodontitis Affected Individuals With and Without Rheumatoid Arthritis

Objectives

Periodontitis and rheumatoid arthritis (RA) are two widespread chronic inflammatory diseases with a previously suggested association. The objective of the current study was to compare the oral microbial composition and host´s inflammatory mediator profile of saliva samples obtained from subjects with periodontitis, with and without RA, as well as to predict biomarkers, of bacterial pathogens and/or inflammatory mediators, for classification of samples associated with periodontitis and RA.

Methods

Salivary samples were obtained from 53 patients with periodontitis and RA and 48 non-RA with chronic periodontitis. The microbial composition was identified using 16S rRNA gene sequencing and compared across periodontitis patients with and without RA. Levels of inflammatory mediators were determined using a multiplex bead assay, compared between the groups and correlated to the microbial profile. The achieved data was analysed using PCoA, DESeq2 and two machine learning algorithms, OPLS-DA and sPLS-DA.

Results

Differential abundance DESeq2 analyses showed that the four most highly enriched (log2 FC >20) amplicon sequence variants (ASVs) in the non-RA periodontitis group included Alloprevotella sp., Prevotella sp., Haemophilus sp., and Actinomyces sp. whereas Granulicatella sp., Veillonella sp., Megasphaera sp., and Fusobacterium nucleatum were the most highly enriched ASVs (log2 FC >20) in the RA group. OPLS-DA with log2 FC analyses demonstrated that the top ASVs with the highest importance included Vampirovibrio sp. having a positive correlation with non-RA group, and seven ASVs belonging to Sphingomonas insulae, Sphingobium sp., Novosphingobium aromaticivorans, Delftia acidovorans, Aquabacterium spp. and Sphingomonas echinoides with a positive correlation with RA group. Among the detected inflammatory mediators in saliva samples, TWEAK/TNFSF12, IL-35, IFN-α2, pentraxin-3, gp130/sIL6Rb, sIL-6Ra, IL-19 and sTNF-R1 were found to be significantly increased in patients with periodontitis and RA compared to non-RA group with periodontitis. Moreover, correlations between ASVs and inflammatory mediators using sPLS-DA analysis revealed that TWEAK/TNFSF12, pentraxin-3 and IL-19 were positively correlated with the ASVs Sphingobium sp., Acidovorax delafieldii, Novosphingobium sp., and Aquabacterium sp.

Conclusion

Our results suggest that the combination of microbes and host inflammatory mediators could be more efficient to be used as a predictable biomarker associated with periodontitis and RA, as compared to microbes and inflammatory mediators alone.

Optimization and Standardization of Human Saliva Collection for MALDI-TOF MS

SARS-CoV-2 outbreak led to unprecedented innovative scientific research to preclude the virus dissemination and limit its impact on life expectancy. Waiting for the collective immunity by vaccination, mass-testing, and isolation of positive cases remain essential. The development of a diagnosis method requiring a simple and non-invasive sampling with a quick and low-cost approach is on demand. We hypothesized that the combination of saliva specimens with MALDI-TOF MS profiling analyses could be the winning duo. Before characterizing MS saliva signatures associated with SARS-CoV-2 infection, optimization and standardization of sample collection, preparation and storage up to MS analyses appeared compulsory. In this view, successive experiments were performed on saliva from healthy healthcare workers. Specimen sampling with a roll cotton of Salivette^® devices appeared the most appropriate collection mode. Saliva protein precipitation with organic buffers did not improved MS spectra profiles compared to a direct loading of samples mixed with acetonitrile/formic acid buffer onto MS plate. The assessment of sample storage conditions and duration revealed that saliva should be stored on ice until MS analysis, which should occur on the day of sampling. Kinetic collection of saliva highlighted reproducibility of saliva MS profiles over four successive days and also at two-week intervals. The intra-individual stability of saliva MS profiles should be a key factor in the future investigation for biomarkers associated with SARS-CoV-2 infection. However, the singularity of MS profiles between individuals will require the development of sophisticated bio-statistical analyses such as machine learning approaches. MALDI-TOF MS profiling of saliva could be a promising PCR-free tool for SARS-CoV-2 screening.

Saliva as a Source of Biomarkers for Periodontitis and Periimplantitis

Saliva has the potential to be used as a diagnostic and monitoring tool for various diseases if biomarkers of an adequate sensitivity and specificity could be identified. Several reviews and even meta-analyses have been performed in recent years, which have found some candidate biomarkers for periodontitis, like macrophage inflammatory protein-1 alpha, interleukin-1ß, interleukin-6, matrix metalloproteinase-8, or hemoglobin. However, none of those are currently in use to replace conventional periodontal diagnostics with a periodontal probe. For periimplantitis, to date, heterogeneity of different study protocols and implant types did not permit to discover clear biomarkers, which were able to distinguish between healthy and diseased implants. Few proinflammatory cytokines, similar to periodontitis, have been characterized as adjunct tools to clinical diagnosis. The additional determination of antimicrobial peptides, bone turnover markers, and bacteria could help to enhance sensitivity and specificity in a combined model for periodontitis and periimplantitis. Furthermore, proteomic approaches might be preferred over single biomarker determinations. A global consensus is also needed to harmonize salivary sampling methods as well as procedures of biomarker analysis to ensure future comparability.

Analytical Strategies in Lipidomics for Discovery of Functional Biomarkers from Human Saliva

Human saliva is increasingly being used and validated as a biofluid for diagnosing, monitoring systemic disease status, and predicting disease progression. The discovery of biomarkers in saliva biofluid offers unique opportunities to bypass the invasive procedure of blood sampling by using oral fluids to evaluate the health condition of a patient. Saliva biofluid is clinically relevant since its components can be found in plasma. As salivary lipids are among the most essential cellular components of human saliva, there is great potential for their use as biomarkers. Lipid composition in cells and tissues change in response to physiological changes and normal tissues have a different lipid composition than tissues affected by diseases. Lipid imbalance is closely associated with a number of human lifestyle-related diseases, such as atherosclerosis, diabetes, metabolic syndromes, systemic cancers, neurodegenerative diseases, and infectious diseases. Thus, identification of lipidomic biomarkers or key lipids in different diseases can be used to diagnose diseases and disease state and evaluate response to treatments. However, further research is needed to determine if saliva can be used as a surrogate to serum lipid profiles, given that highly sensitive methods with low limits of detection are needed to discover salivary biomarkers in order to develop reliable diagnostic and disease monitoring salivary tests. Lipidomic methods have greatly advanced in recent years with a constant advance in mass spectrometry (MS) and development of MS detectors with high accuracy and high resolution that are able to determine the elemental composition of many lipids.

HS-SPME-GC-MS approach for the analysis of volatile salivary metabolites and application in a case study for the indirect assessment of gut microbiota

In this work, a straightforward analytical approach based on headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry was developed for the analysis of salivary volatile organic compounds without any prior derivatization step. With a sample volume of 500 μL, optimal conditions were achieved by allowing the sample to equilibrate for 10 min at 50 °C and then extracting the samples for 10 min at the same temperature, using a carboxen/polydimethylsiloxane fibre. The method allowed the simultaneous identification and quantification of 20 compounds in sample headspace, including short-chain fatty acids and their derivatives which are commonly analysed after analyte derivatization. The proof of applicability of the methodology was performed with a case study regarding the analysis of the dynamics of volatile metabolites in saliva of a single subject undergoing 5-day treatment with rifaximin antibiotic. Non-stimulated saliva samples were collected over 3 weeks from a nominally healthy volunteer before, during, and after antibiotic treatment. The variations of some metabolites, known to be produced by the microbiota and by bacteria that are susceptible to antibiotics, suggest that the study of the dynamics of salivary metabolites can be an excellent indirect method for analysing the gut microbiota. This approach is novel from an analytical standpoint, and it encourages further studies combining saliva metabolite profiles and gut microbiota dynamics. Graphical abstract.

Biomarkers: paving stones on the road towards the personalized precision medicine for oral squamous cell carcinoma

Traditional therapeutics have encountered a bottleneck caused by diagnosis delay and subjective and unreliable assessment. Biomarkers can overcome this bottleneck and guide us toward personalized precision medicine for oral squamous cell carcinoma. To achieve this, it is important to efficiently and accurately screen out specific biomarkers from among the huge number of molecules. Progress in omics-based high-throughput technology has laid a solid foundation for biomarker discovery. With credible and systemic biomarker models, more precise and personalized diagnosis and assessment would be achieved and patients would be more likely to be cured and have a higher quality of life. However, this is not straightforward owing to the complexity of molecules involved in tumorigenesis. In this context, there is a need to focus on tumor heterogeneity and homogeneity, which are discussed in detail. In this review, we aim to provide an understanding of biomarker discovery and application for precision medicine of oral squamous cell carcinoma, and have a strong belief that biomarker will pave the road toward future precision medicine.

Saliva as a source of new phosphopeptide biomarkers: Development of a comprehensive analytical method based on shotgun peptidomics

The paper describes the development of an enrichment method for the analysis of the endogenous phosphopeptides in saliva. The method was based on magnetic solid phase extraction by a magnetic graphitized carbon black-TiO₂ composite material and was developed considering different saliva pre-treatments, namely C18 solid phase extraction for purification, direct dilution in loading buffer or acetonitrile precipitation. The method was based on a shotgun proteomics workflow and the enriched peptide mixture was analysed by nanoHPLC and high resolution tandem mass spectrometry. Acetonitrile precipitation provided the best results, with up to 165 endogenous phosphopeptides identified in saliva samples from healthy individuals. The physico-chemical features of the identified endogenous phosphopeptides indicated that such peptides were large, hydrophilic and basic.

Omics-based molecular techniques in oral pathology centred cancer: prospect and challenges in Africa

BACKGROUND

The completion of the human genome project and the accomplished milestones in the human proteome project; as well as the progress made so far in computational bioinformatics and "big data" processing have contributed immensely to individualized/personalized medicine in the developed world.

MAIN BODY

At the dawn of precision medicine, various omics-based therapies and bioengineering can now be applied accurately for the diagnosis, prognosis, treatment, and risk stratification of cancer in a manner that was hitherto not thought possible. The widespread introduction of genomics and other omics-based approaches into the postgraduate training curriculum of diverse medical and dental specialties, including pathology has improved the proficiency of practitioners in the use of novel molecular signatures in patient management. In addition, intricate details about disease disparity among different human populations are beginning to emerge. This would facilitate the use of tailor-made novel theranostic methods based on emerging molecular evidences.

CONCLUSION

In this review, we examined the challenges and prospects of using currently available omics-based technologies vis-à-vis oral pathology as well as prompt cancer diagnosis and treatment in a resource limited setting.

Salivary and pellicle proteome: A datamining analysis

We aimed to comprehensively compare two compartmented oral proteomes, the salivary and the dental pellicle proteome. Systematic review and datamining was used to obtain the physico-chemical, structural, functional and interactional properties of 1,515 salivary and 60 identified pellicle proteins. Salivary and pellicle proteins did not differ significantly in their aliphatic index, hydrophaty, instability index, or isoelectric point. Pellicle proteins were significantly more charged at low and high pH and were significantly smaller (10–20 kDa) than salivary proteins. Protein structure and solvent accessible molecular surface did not differ significantly. Proteins of the pellicle were more phosphorylated and glycosylated than salivary proteins. Ion binding and enzymatic activities also differed significantly. Protein-protein-ligand interaction networks relied on few key proteins. The identified differences between salivary and pellicle proteins could guide proteome compartmentalization and result in specialized functionality. Key proteins could be potential targets for diagnostic or therapeutic application.

Prediction of Periodontal Inflammation via Metabolic Profiling of Saliva

Periodontal disease is characterized by chronic inflammation in subgingival areas, where a vast array of inflammation-associated metabolites are likely produced from tissue breakdown, increased vascular permeability, and microbial metabolism and then eventually show a steady flow into saliva. Thus, prolonged periodontal inflammation is a key feature of disease activity. Although salivary metabolomics has drawn attention for its potential use in diagnosis of periodontal disease, few authors have used that to investigate periodontal inflammation detection. In this pilot study, the authors explored the use of salivary metabolites to reflect periodontal inflammation severity with a recently proposed parameter-periodontal inflamed surface area (PISA)-used to quantify the periodontal inflammatory burden of individual patients with high accuracy. Following PISA determination, whole saliva samples were collected from 19 subjects before and after removal of supragingival plaque and calculus (debridement) with an ultrasonic scaler to assess the influence of the procedure on salivary metabolic profiles. Metabolic profiling of saliva was performed with gas chromatography coupled to time-of-flight mass spectrometry, followed by multivariate regression analysis with orthogonal projections to latent structures (OPLS) to investigate the relationship between PISA and salivary metabolic profiles. Sixty-three metabolites were identified. OPLS analysis showed that postdebridement saliva provided a more refined model for prediction of PISA than did predebridement samples, which indicated that debridement may improve detection of metabolites eluted from subgingival areas in saliva, thus more accurately reflecting the pathophysiology of periodontitis. Based on the variable importance in the projection values obtained via OPLS, 8 metabolites were identified as potential indicators of periodontal inflammation, of which the combination of cadaverine, 5-oxoproline, and histidine yielded satisfactory accuracy (area under the curve = 0.881) for diagnosis of periodontitis. The authors' findings identified potential biomarkers that may be useful for reflecting the severity of periodontal inflammation as part of monitoring disease activity in periodontitis patients.