Density-based clustering algorithms are commonly used in machine learning and data mining due to their ability to identify clusters with different shapes and noisy objects. These algorithms are famous in data analysis and the use of their analysis output in industry and business. However, traditional clustering algorithms may have difficulty with datasets with different densities and overlapping neighboring clusters. To address these challenges, a new density-based clustering algorithm is proposed in this article. In this algorithm, the dependency matrix and the first-level search graph are used to find the dense points and the connection between the points, the concept of the relevant space is introduced to define the local and global density, and a central point identification method is used to identify the cluster structures. This algorithm also uses an allocation strategy based on the relevant space for the remaining objects to achieve accurate clustering results. Experimental results on real data sets show the effectiveness of the proposed method in clustering performance.

The aim of the present study was the histological evaluation of Enamel Matrix Derivative (EMD) effectiveness for regeneration of periodontal defects. EMD activates cementum synthesis, PDL and bone during the maturation stage of follicole. In this research, EMD was used in surgical defects of premolar teeth in four adult sheep. Muccoperiosteal flap was reflected in buccal site of teeth. The buccal bone plate was removed from mesial to distal in 4 mm depth. After eliminating the cementum by bur and its etching, EMD was applied on exposed dentine and flap was sutured. In opposite sites of those teeth (control sites) the same process was performed without etching. After 100 days, sheep were sacrificed and histological study through light microscopic was performed on black sections of operation sites. The results showed that in test sites, regeneration of cementum and bone was 62/5% and 42/5-50% respectively. But in control sites regeneration of cementum and bone was 37.5% and 32/5-42/5% respectively. Also the migration of junctional epithelium in control sites was 8-10% more than test sites. The important point is that in test sites, cementum was completely attached to undermining dentine. But, in control sites, the gap between cementum and dentine was visible. As a result, this study suggests that EMD promotes periodontal regeneration, and EMD application is a successful achievement in regenerative periodontal therapy.

Background and the purpose of the study: Affinity-based target deconvolution is an emerging method for the identification of interactions between drugs/drug candidates and cellular proteins, and helps to predict potential activities and side effects of a given compound. In the present study, we hypothesized that a part of safranal pharmacological effects, one of the major constituent of Crocus sativus L., relies on its physical interaction with target proteins.Methods: Affinity chromatography solid support was prepared by covalent attachment of safranal to agarose beads.After passing tissue lysate through the column, safranal-bound proteins were isolated and separated on SDS-PAGE or two-dimensional gel electrophoresis. Proteins were identified using MALDI-TOF/TOF mass spectrometry and Mascot software.Results and major conclusion: Data showed that safranal physically binds to beta actin, cytochrome b-c1 complex sub-unit 1, trifunctional enzyme sub-unit beta and ATP synthase sub-unit alpha and beta. These interactions may explain part of safranal’s pharmacological effects. However, phenotypic and/or biological relevance of these interactions remains to be elucidated by future pharmacological studies.