Compositional protein analysis of high density lipoproteins in hypercholesterolemia by shotgun LC-MS/MS and probabilistic peptide scoring

A protein of a biological sample is usually quantified by immunological techniques based on antibodies. Mass spectrometry offers alternative approaches that are not dependent on antibody affinity and avidity, protein isoforms, quaternary structures, or steric hindrance of antibody-antigen recognition in case of multiprotein complexes. One approach is the use of stable isotope-labeled internal standards; another is the direct exploitation of mass spectrometric signals recorded by LC-MS/MS analysis of protein digests. Here we assessed the peptide match score summation index based on probabilistic peptide scores calculated by the PHENYX protein identification engine for absolute protein quantification in accordance with the protein abundance index as proposed by Mann and co-workers (Rappsilber, J., Ryder, U., Lamond, A. I., and Mann, M. (2002) Large-scale proteomic analysis of the human spliceosome. Genome Res. 12, 1231-1245). Using synthetic protein mixtures, we demonstrated that this approach works well, although proteins can have different response factors. Applied to high density lipoproteins (HDLs), this new approach compared favorably to alternative protein quantitation methods like UV detection of protein peaks separated by capillary electrophoresis or quantitation of protein spots on SDS-PAGE. We compared the protein composition of a well defined HDL density class isolated from plasma of seven hypercholesterolemia subjects having low or high HDL cholesterol with HDL from nine normolipidemia subjects. The quantitative protein patterns distinguished individuals according to the corresponding concentration and distribution of cholesterol from serum lipid measurements of the same samples and revealed that hypercholesterolemia in unrelated individuals is the result of different deficiencies. The presented approach is complementary to HDL lipid analysis; does not rely on complicated sample treatment, e.g. chemical reactions, or antibodies; and can be used for projective clinical studies of larger patient groups.

Temperature Prediction Model for Bone Drilling Based on Density Distribution and In Vivo Experiments for Minimally Invasive Robotic Cochlear Implantation

Surgical robots have been proposed ex vivo to drill precise holes in the temporal bone for minimally invasive cochlear implantation. The main risk of the procedure is damage of the facial nerve due to mechanical interaction or due to temperature elevation during the drilling process. To evaluate the thermal risk of the drilling process, a simplified model is proposed which aims to enable an assessment of risk posed to the facial nerve for a given set of constant process parameters for different mastoid bone densities. The model uses the bone density distribution along the drilling trajectory in the mastoid bone to calculate a time dependent heat production function at the tip of the drill bit. Using a time dependent moving point source Green's function, the heat equation can be solved at a certain point in space so that the resulting temperatures can be calculated over time. The model was calibrated and initially verified with in vivo temperature data. The data was collected in minimally invasive robotic drilling of 12 holes in four different sheep. The sheep were anesthetized and the temperature elevations were measured with a thermocouple which was inserted in a previously drilled hole next to the planned drilling trajectory. Bone density distributions were extracted from pre-operative CT data by averaging Hounsfield values over the drill bit diameter. Post-operative [Formula: see text]CT data was used to verify the drilling accuracy of the trajectories. The comparison of measured and calculated temperatures shows a very good match for both heating and cooling phases. The average prediction error of the maximum temperature was less than 0.7 °C and the average root mean square error was approximately 0.5 °C. To analyze potential thermal damage, the model was used to calculate temperature profiles and cumulative equivalent minutes at 43 °C at a minimal distance to the facial nerve. For the selected drilling parameters, temperature elevation profiles and cumulative equivalent minutes suggest that thermal elevation of this minimally invasive cochlear implantation surgery may pose a risk to the facial nerve, especially in sclerotic or high density mastoid bones. Optimized drilling parameters need to be evaluated and the model could be used for future risk evaluation.