Microbial differences between dental plaque and historic dental calculus are related to oral biofilm maturation stage

Dental calculus, calcified oral plaque biofilm, contains microbial and host biomolecules that can be used to study historic microbiome communities and host responses. Dental calculus does not typically accumulate as much today as historically, and clinical oral microbiome research studies focus primarily on living dental plaque biofilm. However, plaque and calculus reflect different conditions of the oral biofilm, and the differences in microbial characteristics between the sample types have not yet been systematically explored. Here, we compare the microbial profiles of modern dental plaque, modern dental calculus, and historic dental calculus to establish expected differences between these substrates.- Background - Results -- Authentication of a preserved oral biofilm in calculus samples -- Dental calculus and plaque biofilm communities are distinct -- Health-associated communities of dental plaque and calculus are distinct -- Signatures of health and of disease are shared in modern and historic calculus samples -- Microbial community differences between health and disease in calculus are poorly resolved -- Absence of caries-specific microbial profiles in dental calculus -- Microbial co-exclusion patterns in plaque and calculus reflect biofilm maturity -- Microbial complexes in plaque and calculus -- Functional prediction in calculus is poorly predictive of health status -- Proteomic profiles of historic healthy site calculus -- Correlations between taxonomic, proteomic, and metabolomic profiles - Discussion - Conclusions - Materials and methods --Historic and modern calculus sample collection DNA extraction -- DNA library construction and high-throughput sequencing -- DNA sequence processing -- Genetic assessment of historic calculus sample preservation -- Genetic microbial taxonomic profiling -- Principal component analysis -- Assessment of differentially abundant taxa -- Sparse partial least squares-discriminant analysis -- Assessment of microbial co-exclusion patterns -- Gene functional categorization with SEED -- Proteomics -- Metabolomics -- Regularized canonical correlation analysi

The association between rheumatoid arthritis and periodontal disease

Chronic, plaque-associated inflammation of the gingiva and the periodontium are among the most common oral diseases. Periodontitis (PD) is characterized by the inflammatory destruction of the periodontal attachment and alveolar bone, and its clinical appearance can be influenced by congenital as well as acquired factors. The existence of a rheumatic or other inflammatory systemic disease may promote PD in both its emergence and progress. However, there is evidence that PD maintains systemic diseases. Nevertheless, many mechanisms in the pathogenesis have not yet been examined sufficiently, so that a final explanatory model is still under discussion, and we hereby present arguments in favor of this. In this review, we also discuss in detail the fact that oral bacterial infections and inflammation seem to be linked directly to the etiopathogenesis of rheumatoid arthritis (RA). There are findings that support the hypothesis that oral infections play a role in RA pathogenesis. Of special importance are the impact of periodontal pathogens, such as Porphyromonas gingivalis on citrullination, and the association of PD in RA patients with seropositivity toward rheumatoid factor and the anti-cyclic citrullinated peptide antibody

Long-Range Temporal Correlations Reflect Treatment Response in the Electroencephalogram of Patients with Infantile Spasms

Infantile spasms syndrome is an epileptic encephalopathy in which prompt diagnosis and treatment initiation are critical to therapeutic response. Diagnosis of the disease heavily depends on the identification of characteristic electroencephalographic (EEG) patterns, including hypsarrhythmia. However, visual assessment of the presence and characteristics of hypsarrhythmia is challenging because multiple variants of the pattern exist, leading to poor inter-rater reliability. We investigated whether a quantitative measurement of the control of neural synchrony in the EEGs of infantile spasms patients could be used to reliably distinguish the presence of hypsarrhythmia and indicate successful treatment outcomes. We used autocorrelation and Detrended Fluctuation Analysis (DFA) to measure the strength of long-range temporal correlations in 21 infantile spasms patients before and after treatment and 21 control subjects. The strength of long-range temporal correlations was significantly lower in patients with hypsarrhythmia than control patients, indicating decreased control of neural synchrony. There was no difference between patients without hypsarrhythmia and control patients. Further, the presence of hypsarrhythmia could be classified based on the DFA exponent and intercept with 92% accuracy using a support vector machine. Successful treatment was marked by a larger increase in the DFA exponent compared to those in which spasms persisted. These results suggest that the strength of long-range temporal correlations is a marker of pathological cortical activity that correlates with treatment response. Combined with current clinical measures, this quantitative tool has the potential to aid objective identification of hypsarrhythmia and assessment of treatment efficacy to inform clinical decision-making