Introduction & Objective: Recently, it has been suggested that there might be an association between oral diseases such as dental caries, as well as periodontitis and general health . Re-garding the fact that albumin is an indicator of general health, the aim of the present study was to evaluate the relationship of salivary albumin concentration with dental caries.

Materials & Methods: In this descriptive-analytical study 108 patients aged 13-19 years old who had teeth caries were placed in 3 groups with mild, moderate and severe dental caries according to their DMFT value (n=36). Five ml of unstimulated saliva were taken from each participant via Navazesh method and their albumin concentrations were assessed by nephelometery method. Data were analyzed by t-test and ANOVA.

Results: The mean concentration of salivary albumin in three experimental groups was 84.442±42.915, 97.964±66.717 and 89.850±33.003, respectively. ANOVA showed that the difference among the mean values was not significant (P=0.09) but the relationship between salivary albumins and sex was significant (P=0.009).

Conclusion: According to the results of the present study there was no significant relationship between albumin and dental caries in 13-19 year old individuals.

Introduction & Objective: Study of bone quality before treatment is very important. The aims of this study were to assess bone quality with density values obtained by cone-beam computed tomography (CBCT) and to determine the correlations between bone density and primary stability of dental implants.

Materials & Methods: In this experimental in vitro study 32 implants were inserted into fresh sheep bone. The bone densities of implant recipient sites were determined by CBCT. The maximum insertion torque value of each implant was recorded and stability was measured by Osstell. Spearman’s correlation coefficient was used to evaluate the correlations among the variables.

Results: The mean density value, insertion torque, and Osstell value were 1481.78?166.614, 74.69?16.33 and 73.78?4.025 N/cm2 respectively. Statistically no significant correlations were found among the variables.

Conclusion: The bone quality evaluated by CBCT showed no correlation with the primary stability of the implants.

Introduction & Objective: Cox model is a common method to estimate survival and validity of the results is dependent on the proportional hazards assumption. K- Nearest neighbor is a nonparametric method for survival probability in heterogeneous communities. The purpose of this study was to compare the performance of k- nearest neighbor method (K-NN) with Cox model.

Materials & Methods: This retrospective cohort study was conducted in Hamadan Province, on 475 patients who had undergone kidney transplantation from 1994 to 2011. Data were extracted from patients’ medical records using a checklist. The duration of the  time between kidney transplantation and rejection was considered as the surviv­al time. Cox model and k- nearest neighbor method were used for Data modeling.  The prediction error Brier score was used to compare the performance models.

Results:  Out of 475 transplantations, 55 episodes of rejection occurred. 5, 10 and 15 year survival rates of transplantation were 91.70 %, 84.90% and 74.50%, respectively. The number of neighborhood optimized using cross validation method was 45. Cumulative Brier score of k-NN algorithm for t=5, 10 and 15 years were 0.003, 0.006 and 0.007, respectively. Cumulative Brier of score Cox model for t=5, 10 and 15 years were 0.036, 0.058 and 0.058, respectively.  Prediction error of k-NN algorithm for t=5, 10 and 15 years was less than Cox model that shows that the k-NN method outperforms.

Conclusions: The results of this study show that the predictions of KNN has higher accuracy than the Cox model when sample sizes and the number of predictor variables are high.

Introduction: In studies of the adsorption of pollutants onto different adsorbents, determining the adsorbent dose of the most important characteristics must be considered. The aim of the study was the determination and modeling of dose-response bone char fluoride removal from aqueous solutions and comparison of the adsorption isotherm models with dose-response models from the perspective of adsorption.

Methods: In this experimental study, bone char was prepared by using an electric furnace at 450˚C in two hours. Sorting the adsorbent was conducted by standard sieve ASTM in the range of 18-35 meshes and its characteristics were determined with conventional methods. The concentration of fluoride was measured according to the recommendation of manufacturer (HACH) with Dr-5000 of regent fluoride. Dose-response models were fit to the data and parameters were estimated. Based on the quality of fitness indicators, the adsorption isotherm models were compared with dose-response models. Analysis of the data in this study was performed using the R software version 3.1.2 and stats package.

Results: Fit indexes (AIC and R²) showed that the most appropriate model for the data in pH= 10, concentration = 10 and pH = 7, concentration = 20 was the Emax model and in pH = 7, concentration = 10 and pH = 7, concentration = 15 the quadratic model. According to these models, the median of effective dose on bone char at removal of fluoride was determined 0.11 g in concentration of 10 mg/L and pH = 10. The maximum effective dose was determined 1.25 g in concentration of 20 mg/L and pH = 7. The index (AIC) showed that quadratic dose-response models better fit to adsorption data than adsorption isotherm models.

Conclusions: The median and maximum effective doses of bone char at removal of fluoride were estimated by statistical models more accurately. In addition, determining the goal dose was performed using modeling method, which was more economic than repeated testing, and the performance time was also more cost-effective. Quadratic dose-response model can be a good alternative for adsorption isotherm models in the adsorption behavior.