Background: Cardiovascular disease (CVD) is the primary cause of premature death and disability worldwide. There is extensive evidence that inflammation represents an important pathogenetic mechanism in the development and prognosis of CVD. C-reactive protein (CRP) is a potential marker of vascular inflammation and plays a direct role in CVD by promoting vascular inflammation. The objective of this study (ClinTrials.gov identifier: NCT01045070) was to assess the prognostic impact of CRP protein levels and genetic variants of CRP gene events on cardiovascular (CV) outcome (10-year follow-up) in patients suffering from CVD. Methods: CVD patients were prospectively included in this study (n = 1002) and followed up (10 years) regarding combined CV endpoint (CV death, death from stroke, myocardial infarction (MI), and stroke/transient ischemic attack (TIA)). CRP protein level (particle-enhanced immunological turbidity test) and genetic variants (rs1130864, rs1417938, rs1800947, rs3093077; polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) after DNA extraction from EDTA-blood) were evaluated. Results: In survival analyses, increased CRP protein levels of ≥5 mg/L (log-rank test: p < 0.001, Cox regression: p = 0.002, hazard ratio = 1.49) and CT + TT genotype of rs1130864 (log-rank test: p = 0.041; Cox regression: p = 0.103, hazard ratio = 1.21) were associated with a weaker CV prognosis considering combined CV endpoint. Conclusions: Elevated CRP level and genetic variant (rs1130864) were proven to provide prognostic value for adverse outcome in CVD patients within the 10-year follow-up period.

Background: Worldwide, cardiovascular disease (CVD) is the leading cause of premature death. The proinflammatory cytokine interleukin 6 (IL-6) is a essential marker of innate immunity that is considered to play an important proatherogenic role for cardiovascular disease. The aim of this study (substudy of ClinTrials.gov identifier: NCT01045070) was to evaluate IL-6 protein level and genetic variants (rs1800795, rs1800797) with respect to CV outcome (combined endpoint: myocardial infarction, stroke/transient ischemic attack, cardiac death, death according to stroke) among patients CVD within 10-years follow-up. Material and methods: Overall 1002 in-patients with CVD were included. IL-6 protein level was determined by electrochemiluminescence immunoassay (fasting, between 7 and 8 a.m.). Genetic analyses were carried out by single specific primer-polymerase chain reaction. Results: In survival analyses, IL-6 protein levels of ≥6.4 pg/mL (log-rank test: p = 0.034; cox regression: p = 0.032, hazard ratio = 1.29) and CC genotype of rs1800795 (log-rank test: p < 0.001, cox regression: p < 0.001, hazard ratio = 1.72) and AA genotype of rs180797 (log-rank test: p = 0.002, cox regression: p < 0.001, hazard ratio = 1.62) were associated with a poorer CV prognosis considering combined CV endpoint. Conclusion: This study was the first to investigate both elevated IL-6 levels and genetic variants for their prognostic value for adverse CV outcomes in CVD patients within the 10-year follow-up period.

Background: Cardiovascular diseases (CVDs) represent major medical and socio-economic challenges worldwide. There is substantial evidence that CVD is closely linked to inflammatory changes triggered by a complex cytokine network. In this context, interleukin 10 (IL-10) plays an important role as a pleiotropic cytokine with an anti-inflammatory capacity. In this study (a substudy of ClinTrials.gov, identifier: NCT01045070), the prognostic relevance of IL-10 levels and IL-10 haplotypes (rs1800896/rs1800871/rs1800872) was assessed regarding adverse cardiovascular outcomes (combined endpoint: myocardial infarction, stroke/transient ischemic attack, cardiac death and death according to stroke) within a 10-year follow-up. Patients and methods: At baseline, 1002 in-patients with CVD were enrolled. Serum levels of IL-10 were evaluated utilizing flow cytometry (BD™ Cytometric Bead Array). Haplotype analyses were carried out by polymerase chain reactions with sequence-specific primers (PCR-SSP). Results: In a survival analysis, IL-10 haplotypes were not proven to be cardiovascular prognostic factors in a 10-year follow-up (Breslow test: p = 0.423). However, a higher IL-10 level was associated with adverse cardiovascular outcomes (Breslow test: p = 0.047). A survival analysis considering adjusted hazard ratios (HRs) could not confirm this correlation (Cox regression: adjusted HR = 1.26, p = 0.168). Conclusion: In the present study, an elevated IL-10 level but not IL-10 haplotypes was linked to adverse cardiovascular outcomes (10-year follow-up) in a cohort of CVD patients.

The purpose of this randomized, split-mouth-designed controlled and single-blinded clinical study was to evaluate the 3-year clinical performance of Class I and Class II resin composite restorations placed with or without cavity lining with a flowable composite. Fifty patients with treatment needs in two premolars or molars were included. One of the teeth was restored using the nanohybrid composite (Grandio^®SO, control group), in the test group a high viscosity flowable composite was additionally applied as a first layer. In both groups, the same self-etch adhesive system was applied. Clinical evaluation after 3 years was carried out using the modified USPHS/Ryge criteria. At the 3-year follow-up the recall rate was 92%. Four restorations failed in the test group (8.7%), three due to the loss of vitality and one after fracture. The control group exhibited a cumulative success rate of 100%, while the test group achieved a success rate of 91.3%. This led to significant differences in the annual failure rate (AFR) between the two groups, with rates of 0% and 2.9% (p < 0.05; Mann–Whitney U-test). After 3 years the cumulative survival rate including all restorations was 95.7%. Statistical analysis revealed significant differences for the parameters: tooth vitality, marginal discoloration, success rate, and AFR. The other parameters exhibited no significant differences. Consequently, the nanohybrid composite demonstrated excellent performance over a 3-year period, whereas the utilization of a flowable composite for the cavity lining did not appear to exert a beneficial influence on clinical outcomes.

The objective of this review is to investigate the effect of an additional layer of flowable composite for cavity lining on the clinical outcome of direct posterior composite restorations. The PICO question (patient, intervention, comparison, and outcome) was stated as follows: Does the additional application of a flowable composite as a cavity liner improve the clinical outcome of Class-I and Class-II restorations? The electronic databases MEDLINE, Web of Science, LILAS, and BBO were assessed for identifying relevant clinical studies. After removal of duplicate records, 309 records could be identified and, after a screening of the title and abstract, 20 articles were selected for full-text analysis. Finally, six studies met the eligibility criteria and were included in this review for further investigation. Four of the included studies have a follow-up period of two years, while the other two studies had an observation period of three and seven years, respectively. No significant differences in annual failure rates were observed between restorations with and without a flowable composite liner. Consequently, the additional usage of flowable composites as a cavity liner seems to have no effect on the clinical longevity of direct composite restorations in Class-I and Class-II cavities. Therefore, the application of a flowable composite is a possible option in everyday dental clinical practice.

Background/Objectives: Root canal treatment (RCT) is a common dental procedure performed to preserve teeth by removing infected or at-risk pulp tissue caused by caries, trauma, or other pulpal conditions. A successful outcome, among others, depends on accurate identification of the root canal anatomy, planning a suitable therapeutic strategy, and ensuring a bacteria-tight root canal filling. Despite advances in dental techniques, there remains limited integration of computational methods to support key stages of treatment. This review aims to provide a comprehensive overview of computational methods applied throughout the full workflow of RCT, examining their potential to support clinical decision-making, improve treatment planning and outcome assessment, and help bridge the interdisciplinary gap between dentistry and computational research. Methods: A comprehensive literature review was conducted to identify and analyze computational methods applied to different stages of RCT, including root canal segmentation, morphological analysis, treatment planning, quality evaluation, follow-up, and prognosis prediction. In addition, a taxonomy based on application was developed to categorize these methods based on their function within the treatment process. Insights from the authors’ own research experience were also incorporated to highlight implementation challenges and practical considerations. Results: The review identified a wide range of computational methods aimed at enhancing the consistency and efficiency of RCT. Key findings include the use of advanced image processing for segmentation, image analysis for diagnosis and treatment planning, machine learning for morphological classification, and predictive modeling for outcome estimation. While some methods demonstrate high sensitivity and specificity in diagnostic and planning tasks, many remain in experimental stages and lack clinical integration. There is also a noticeable absence of advanced computational techniques for micro-computed tomography and morphological analysis. Conclusions: Computational methods offer significant potential to improve decision-making and outcomes in RCT. However, greater focus on clinical translation and development of cross-modality methodology is needed. The proposed taxonomy provides a structured framework for organizing existing methods and identifying future research directions tailored to specific phases of treatment. This review serves as a resource for both dental professionals, computer scientists and researchers seeking to bridge the gap between clinical practice and computational innovation.