Explorer probing of root caries lesions: an in vitro study

Mass spectrometry-based proteomic approaches for salivary protein biomarkers discovery and dental caries diagnosis: A critical review

Dental caries is a multifactorial chronic disease resulting from the intricate interplay among acid-generating bacteria, fermentable carbohydrates, and several host factors such as saliva. Saliva comprises several proteins which could be utilized as biomarkers for caries prevention, diagnosis, and prognosis. Mass spectrometry-based salivary proteomics approaches, owing to their sensitivity, provide the opportunity to investigate and unveil crucial cariogenic pathogen activity and host indicators and may demonstrate clinically relevant biomarkers to improve caries diagnosis and management. The present review outlines the published literature of human clinical proteomics investigations on caries and extensively elucidates frequently reported salivary proteins as biomarkers. This review also discusses important aspects while designing an experimental proteomics workflow. The protein-protein interactions and the clinical relevance of salivary proteins as biomarkers for caries, together with uninvestigated domains of the discipline are also discussed critically.

In Vitro Models Used in the Formation of Root Caries Lesions-A Review of the Literature

The management of root caries remains a challenge for clinicians due to its unique anatomical location and structure. There is increasing interest in utilising artificial root caries lesions to develop new strategies for remineralisation. An ideal protocol has not yet been agreed upon. The aim of this review is to provide a structured overview of previously reported in vitro root caries models. The literature was screened and mined for information mainly on substrate selection, model systems utilised, and variables used in the models. Human roots (60%) were the most frequently used substrates, followed by bovine roots (40%). Chemical models (69%) were the most frequently utilised model systems, followed by microbiological models (27%), to form root caries lesions. Acetate buffer solution (80%), pH 5.0 or above (40%), and a demineralisation time of five days (25%) were the common variables used in the chemical systems, while mono-species biofilm was most frequently used (73%) in microbiological models and Streptococcus mutans was the most common bacterial strain utilised in these models (80%). This review highlights the variability amongst the experimental approaches, discusses the advantages and limitations of these approaches, and emphasises that standardisation of experimental conditions along with sustained research will benefit root caries research.

Evaluation of a novel caries detecting oral rinse

AIM

LumiCare™ Caries Detection Rinse (LC Rinse), a starch-based rinse, illuminates active initial caries (positive response) using dental curing light, thus augmenting the dentist's visual examination. This clinical study investigated if active caries as assessed by the International Caries Detection and Assessment System (ICDAS) were more likely to have positive LC Rinse response than sound surfaces and inactive caries.

METHODS

25 subjects participated in the study. Caries was assessed on selected teeth and the entire dentition, firstly using ICDAS and then by fluorescence evaluation after LC Rinse application. Data were statistically analyzed using Diagnostic Odds Ratio (OR) and Chi-square test X² (α = 0.05). Sensitivity (Se), specificity (Sp), and Diagnostic accuracy (DA) were calculated.

RESULTS

With selected teeth, active caries were 638.6 times (60.05 with full dentition) more likely to have positive LC Rinse response than sound surfaces and inactive caries combined (X², p < 0.01) and 191.67 times (18.35 with full dentition) than inactive lesions only (X², p < 0.01). With combined sound surfaces and inactive caries, Se, Sp, and DA of LC Rinse assessment were 0.94, 0.98, and 0.96 respectively.

CONCLUSIONS

LC Rinse can distinguish between active caries, inactive caries and hypomineralization, and can augment caries detection with high sensitivity, specificity, and diagnostic accuracy.

Detecting demineralization of enamel and cementum after gamma irradiation using radiographic densitometry

The purpose of this study was to evaluate the ability of radiographic densitometry in detecting the early demineralization of human enamel and cementum in irradiated and non-irradiated teeth. Sixty extracted teeth were divided into two groups: irradiated group and non-irradiated group. After irradiation, the groups were subjected to demineralization-remineralization (PH) cycling. Radiographic densitometric measurements (gray values) of a selected area of interest in the enamel and in the cementum of each tooth were performed at baseline and after PH cycling. After PH cycling, there was a significant reduction in gray values for both groups. The difference between "baseline" and "after PH cycling" values represents the reduction in the mineral content of the hard tissue, i.e., the demineralization. Results show that the demineralization of irradiated tooth enamel and cementum was significantly higher compared to that of non-irradiated tissues as determined by gray-level values. It is concluded that densitometric measurements by means of digital radiographs allow for the detection of demineralization of enamel and cementum, and can be used successfully for diagnosis of the early carious lesions in patients who received head and neck radiotherapy. This will allow implementation of remineralizing therapy and avoid the risk of progression of radiation caries. Furthermore, it is concluded that gamma irradiation with typical therapeutic doses for head and neck carcinoma is a direct cause of demineralization of tooth enamel and cementum.

Demineralization Depth Using QLF and a Novel Image Processing Software

Quantitative Light-Induced fluorescence (QLF) has been widely used to detect tooth demineralization indicated by fluorescence loss with respect to surrounding sound enamel. The correlation between fluorescence loss and demineralization depth is not fully understood. The purpose of this project was to study this correlation to estimate demineralization depth. Extracted teeth were collected. Artificial caries-like lesions were created and imaged with QLF. Novel image processing software was developed to measure the largest percent of fluorescence loss in the region of interest. All teeth were then sectioned and imaged by polarized light microscopy. The largest depth of demineralization was measured by NIH ImageJ software. The statistical linear regression method was applied to analyze these data. The linear regression model was Y = 0.32X + 0.17, where X was the percent loss of fluorescence and Y was the depth of demineralization. The correlation coefficient was 0.9696. The two-tailed t-test for coefficient was 7.93, indicating the P-value = .0014. The F test for the entire model was 62.86, which shows the P-value = .0013. The results indicated statistically significant linear correlation between the percent loss of fluorescence and depth of the enamel demineralization.

Diagnostic tools for early caries detection

BACKGROUND

Management of dental caries demands early detection of carious lesions. This article provides an overview of the state-of-the-art methodologies for the detection and assessment of early carious lesions.

TYPES OF STUDIES REVIEWED

The authors reviewed MEDLINE for available literature on new caries detection methodology and tools, using terms such as "early caries detection," "fluorescence" and "transillumination." Their review was not a systematic review of the literature. They included in their review in vitro, in situ, in vivo and clinical studies, as well as position papers, editorials and consensus conferences statements published in English.

RESULTS

Each early caries detection tool has advantages and disadvantages; some perform better on certain surfaces than others. Therefore, their performance threshold and the operator's influence on performance must be considered. Not all methods accurately detect early lesions, and false positives and false negatives may occur. Detecting early lesions in combination with assessing activity status is essential for establishing the prognosis and threshold required for preventive intervention. Clinically useful tools to help make such decisions are under development.

CLINICAL IMPLICATIONS

Early caries detection methods should be an adjunct to clinical decision making, supporting preventive treatment planning in conjunction with caries risk assessment but not justifying premature restorative intervention.