C-Telopeptide Pyridinoline Cross-Links: Sensitive Indicators of Periodontal Tissue Destruction

C-telopeptides and related pyridinoline cross-links of bone Type I collagen are sensitive markers of bone resorption in osteolytic diseases such as osteoporosis and osteoarthritis. We have studied the release of C-telopeptide pyridinoline crosslinks of Type I collagen as measures of bone destruction in periodontal disease. Studies in preclinical animal models and humans have demonstrated the relationship between radiographic bone loss and crevicular fluid C-telopeptide levels. We have recently found that C-telopeptide levels correlate strongly with microbial pathogens associated with periodontitis and around endosseous dental implants. Host-modulation of bone-related collagen breakdown has been shown by studies in humans demonstrating that MMP inhibition blocks tissue destruction and release of C-telopeptides in patients with active periodontal disease.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/72598/1/j.1749-6632.1999.tb07698.x.pd

Empirical Evidence on the Use of Credit Scoring for Predicting Insurance Losses with Psycho-social and Biochemical Explanations

An important development in personal lines of insurance in the United States is the use of credit history data for insurance risk classification to predict losses. This research presents the results of collaboration with industry conducted by a university at the request of its state legislature. The purpose was to see the viability and validity of the use of credit scoring to predict insurance losses given its controversial nature and criticism as redundant of other predictive variables currently used. Working with industry and government, this study analyzed more than 175,000 policyholders’ information for the relationship between credit score and claims. Credit scores were significantly related to incurred losses, evidencing both statistical and practical significance. We investigate whether the revealed relationship between credit score and incurred losses was explainable by overlap with existing underwriting variables or whether the credit score adds new information about losses not contained in existing underwriting variables. The results show that credit scores contain significant information not already incorporated into other traditional rating variables (e.g., age, sex, driving history). We discuss how sensation seeking and self-control theory provide a partial explanation of why credit scoring works (the psycho-social perspective). This article also presents an overview of biological and chemical correlates of risk taking that helps explain why knowing risk-taking behavior in one realm (e.g., risky financial behavior and poor credit history) transits to predicting risk-taking behavior in other realms (e.g., automobile insurance incurred losses). Additional research is needed to advance new nontraditional loss prediction variables from social media consumer information to using information provided by technological advances. The evolving and dynamic nature of the insurance marketplace makes it imperative that professionals continue to evolve predictive variables and for academics to assist with understanding the whys of the relationships through theory development.IC2 Institut

The effect of asymmetries on stock index return value-at-risk estimates

It is widely accepted that equity return volatility increases more following negative shocks rather than positive shocks. However, much of value-at-risk (VaR) analysis relies on the assumption that returns are normally distributed (a symmetric distribution). This article considers the effect of asymmetries on the evaluation and accuracy of VaR by comparing estimates based on various models

Strong measures of group coherence and the probability that a pairwise majority rule winner exists

Condorcet winner, Majority rule winner, Coherent preferences,

The Unexpected Behavior of Plurality Rule

voting rules, Condorcet efficieny, single-peaked preferences, D7,

Validation of a computer based system for assessing dietary intake

Dietary intake was assessed in 50 patients in hospital by using a dietary history method and computer based system for data collection and standard food tables to calculate the composition of nutrients. The results were compared with those from a weighed assessment that was calculated by using both food tables and manufacturers' food analyses. The use of the food tables overestimated mean (SEM) individual nutrient intakes by between 2.5% (1.5%) and 15.5% (3.0%). The mean errors associated with the dietary history assessment varied from -23% (7.8%) for fat intake to +21.4% (8.5%) for carbohydrate intake. Overall, 30% of the assessments of total nutrient intakes that were calculated using this method were within -20% to +20% of actual values; 18% were within -10% to +10%. The mean errors associated with the computer based assessment varied from -1.0% (4.3%) for carbohydrate intake to +8.5% (3.4%) for protein intake. Overall, 56% of the assessments of total nutrient intakes were within -20% to +20% of actual intakes; 31% were within -10% to +10%. The computer based system provides an accurate, reproducible, convenient, and inexpensive method for assessing dietary intake.Peer reviewedFinal Published versio

Thermodynamic modelling of cements clinkering process as a tool for optimising the proportioning of raw meals containing alternative materials

The data contained in this workbook has been used to create the following figures in the journal article: Costa, A. R. D., Coppe, M. V., Bielefeldt, W. V., Bernal, S. A., Black, L., Kirchheim, A. P. and Gonçalves, J. P, 2023. Thermodynamic modelling of cements clinkering process as a tool for optimising the proportioning of raw meals containing alternative materials. Scientific Reports. https://doi.org/10.1038/s41598-023-44078-