Resonance frequency analysis in relation to jawbone characteristics and during early healing of implant installation

OBJECTIVES: To monitor resonance frequency analysis (RFA) in relation to the jawbone characteristics and during the early phases of healing and incorporation of Straumann dental implants with an SLA surface. MATERIAL AND METHODS: 17 Straumann 4.1 mm implants (10 mm) and 7 Straumann 4.8 mm implants (10 mm) were installed and ISQ determined at baseline and after 1, 2, 3, 4, 5, 6, 8 and 12 weeks. Central bone cores were analyzed from the 4.1 mm implants using micro CT for bone volume density (BVD) and bone trabecular connectivity (BTC). RESULTS: Pocket probing depths ranged from 2-4 mm and bleeding on probing from 5-20%. At baseline, BVD varied between 24% and 65% and BTC between 4.9 and 25.4 for the 4.1 mm implants. Baseline ISQ varied between 55 and 74 with a mean of 61.4. No significant correlations were found between BVD or BTC and ISQ Values. For the 4.8 mm diameter implants baseline ISQ values ranged from 57-70 with a mean of 63.3. Over the healing period ISQ values increased at 1 week and decreased after 2-3 weeks. After 4 weeks ISQ values, again increased slightly, no significant differences were noted over time. One implant (4.1 mm) lost stability at 3 weeks. Its ISQ value had dropped from 68 to 45. However the latter value was determined after the clinical diagnosis of instability. CONCLUSION: ISQ values of 57-70 represented homeostasis and implant stability. However no predictive value for loosing implant stability can be attributed to RFA since the decrease occurred after the fact.

Proteomics in cardiovascular surgery

Proteomics describes, analogous to the term genomics, the study of the complete set of proteins present in a cell, organ, or organism at a given time. The genome tells us what could theoretically happen, whereas the proteome tells us what does happen. Therefore, a genomic-centered view of biologic processes is incomplete and does not describe what happens at the protein level. Proteomics is a relatively new methodology and is rapidly changing because of extensive advances in the underlying techniques. The core technologies of proteomics are 2-dimensional gel electrophoresis, liquid chromatography, and mass spectrometry. Proteomic approaches might help to close the gap between traditional pathophysiologic and more recent genomic studies, assisting our basic understanding of cardiovascular disease. The application of proteomics in cardiovascular medicine holds great promise. The analysis of tissue and plasma/serum specimens has the potential to provide unique information on the patient. Proteomics might therefore influence daily clinical practice, providing tools for diagnosis, defining the disease state, assessing of individual risk profiles, examining and/or screening of healthy relatives of patients, monitoring the course of the disease, determining the outcome, and setting up individual therapeutic strategies. Currently available clinical applications of proteomics are limited and focus mainly on cardiovascular biomarkers of chronic heart failure and myocardial ischemia. Larger clinical studies are required to test whether proteomics may have promising applications for clinical medicine. Cardiovascular surgeons should be aware of this increasingly pertinent and challenging field of science.

Fixed block configuration GDDs with block size 6 and (3, r)-regular graphs

Chapter 1 is used to introduce the basic tools and mechanics used within this thesis. Most of the definitions used in the thesis will be defined, and we provide a basic survey of topics in graph theory and design theory pertinent to the topics studied in this thesis. In Chapter 2, we are concerned with the study of fixed block configuration group divisible designs, GDD(n; m; k; λ1; λ2). We study those GDDs in which each block has configuration (s; t), that is, GDDs in which each block has exactly s points from one of the two groups and t points from the other. Chapter 2 begins with an overview of previous results and constructions for small group size and block sizes 3, 4 and 5. Chapter 2 is largely devoted to presenting constructions and results about GDDs with two groups and block size 6. We show the necessary conditions are sufficient for the existence of GDD(n, 2, 6; λ1, λ2) with fixed block configuration (3; 3). For configuration (1; 5), we give minimal or nearminimal index constructions for all group sizes n ≥ 5 except n = 10, 15, 160, or 190. For configuration (2, 4), we provide constructions for several families ofGDD(n, 2, 6; λ1, λ2)s. Chapter 3 addresses characterizing (3, r)-regular graphs. We begin with providing previous results on the well studied class of (2, r)-regular graphs and some results on the structure of large (t; r)-regular graphs. In Chapter 3, we completely characterize all (3, 1)-regular and (3, 2)-regular graphs, as well has sharpen existing bounds on the order of large (3, r)- regular graphs of a certain form for r ≥ 3. Finally, the appendix gives computational data resulting from Sage and C programs used to generate (3, 3)-regular graphs on less than 10 vertices.