2 resultados para Rabbit articular cartilage
em AMS Tesi di Laurea - Alm@DL - Università di Bologna
Resumo:
This thesis work has been developed in collaboration between the Department of Physics and Astronomy of the University of Bologna and the IRCCS Rizzoli Orthopedic Institute during an internship period. The study aims to investigate the sensitivity of single-sided NMR in detecting structural differences of the articular cartilage tissue and their correlation with mechanical behavior. Suitable cartilage indicators for osteoarthritis (OA) severity (e.g., water and proteoglycans content, collagen structure) were explored through four NMR parameters: T2, T1, D, and Slp. Structural variations of the cartilage among its three layers (i.e., superficial, middle, and deep) were investigated performing several NMR pulses sequences on bovine knee joint samples using the NMR-MOUSE device. Previously, cartilage degradation studies were carried out, performing tests in three different experimental setups. The monitoring of the parameters and the best experimental setup were determined. An NMR automatized procedure based on the acquisition of these quantitative parameters was implemented, tested, and used for the investigation of the layers of twenty bovine cartilage samples. Statistical and pattern recognition analyses on these parameters have been performed. The results obtained from the analyses are very promising: the discrimination of the three cartilage layers shows very good results in terms of significance, paving the way for extensive use of NMR single-sided devices for biomedical applications. These results will be also integrated with analyses of tissue mechanical properties for a complete evaluation of cartilage changes throughout OA disease. The use of low-priced and mobile devices towards clinical applications could concern the screening of diseases related to cartilage tissue. This could have a positive impact both economically (including for underdeveloped countries) and socially, providing screening possibilities to a large part of the population.
Parametric Sensitivity Analysis of the Most Recent Computational Models of Rabbit Cardiac Pacemaking
Resumo:
The cellular basis of cardiac pacemaking activity, and specifically the quantitative contributions of particular mechanisms, is still debated. Reliable computational models of sinoatrial nodal (SAN) cells may provide mechanistic insights, but competing models are built from different data sets and with different underlying assumptions. To understand quantitative differences between alternative models, we performed thorough parameter sensitivity analyses of the SAN models of Maltsev & Lakatta (2009) and Severi et al (2012). Model parameters were randomized to generate a population of cell models with different properties, simulations performed with each set of random parameters generated 14 quantitative outputs that characterized cellular activity, and regression methods were used to analyze the population behavior. Clear differences between the two models were observed at every step of the analysis. Specifically: (1) SR Ca2+ pump activity had a greater effect on SAN cell cycle length (CL) in the Maltsev model; (2) conversely, parameters describing the funny current (If) had a greater effect on CL in the Severi model; (3) changes in rapid delayed rectifier conductance (GKr) had opposite effects on action potential amplitude in the two models; (4) within the population, a greater percentage of model cells failed to exhibit action potentials in the Maltsev model (27%) compared with the Severi model (7%), implying greater robustness in the latter; (5) confirming this initial impression, bifurcation analyses indicated that smaller relative changes in GKr or Na+-K+ pump activity led to failed action potentials in the Maltsev model. Overall, the results suggest experimental tests that can distinguish between models and alternative hypotheses, and the analysis offers strategies for developing anti-arrhythmic pharmaceuticals by predicting their effect on the pacemaking activity.