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Proteoheparan sulfate can be adsorbed onto a methylated silica surface in a monomolecular layer via its transmembrane hydrophobic protein core domain. Due to electrostatic repulsion, its anionic glycosaminoglycan side chains are stretched out into the blood substitute solution, thereby representing a receptor site for specific lipoprotein binding through basic amino acid-rich residues within their apolipoproteins. The binding process was studied by ellipsometric techniques suggesting that HDL has a high binding affinity and a protective effect on interfacial heparan sulfate proteoglycan layers with respect to LDL and Ca(2+) complexation. LDL was found to be deposited strongly at the proteoheparan sulfate-coated surface, particularly in the presence of Ca(2+), apparently through complex formation 'proteoglycan-low density lipoprotein-calcium'. This ternary complex build-up may be interpreted as arteriosclerotic nanoplaque formation on the molecular level responsible for the arteriosclerotic primary lesion. In a receptor-based biosensor application, this system was tested on its reliability to unveil possible acute pleiotropic effects of the lipid lowering drug fluvastatin. The VLDL/IDL/LDL and VLDL/IDL/LDL/HDL plasma fractions from a high risk patient with dyslipoproteinaemia and type 2 diabetes mellitus showed the start of arteriosclerotic nanoplaque formation at a normal blood Ca(2+) concentration, with a strong increase at higher Ca(2+) concentrations. Nanoplaque formation and size of the HDL-containing lipid fraction remained well below that of the LDL-containing lipid fraction. Fluvastatin, whether applied acutely to the patient (one single 80 mg slow release matrix tablet) or in a 2-month medication regimen, markedly slowed down this process of ternary aggregational nanoplaque build-up and substantially inhibited nanoplaque size development at all Ca(2+) concentrations used. The acute action gave no significant change in lipid concentrations of the patient. Furthermore, after nanoplaque generation, fluvastatin, similar to HDL, was able to reduce nanoplaque formation and size. These immediate effects of fluvastatin have to be taken into consideration when interpreting the clinical outcome of long-term studies.

Background: The metabolic syndrome describes a cluster of cardiovascular risk factors that frequently appear together. Its diagnosis is generally based on several well-recognized indicators in clinical practice, such as abdominal obesity, elevated triglycerides, reduced highdensity lipoprotein, raised blood pressure, and elevated fasting plasma glucose. Today, decisive importance must be attached to the metabolic syndrome since it leads to increased morbidity and mortality, and thus to a decreased life expectancy, and to higher direct and indirect healthcare costs. This is also due to the fact that its symptomatology irradiates on many organs of the body, which may thereby be damaged. Methods: In the present clinical trial on 11 metabolic syndrome patients treated with Ginkgo biloba (EGb 761, 2  120 mg/d) for two months, ellipsometry, fluorescence microscopy, photometric methods, ELISAs and EIAs were applied for biosensor profiling of metabolic syndrome risk, status and treatment outcome. Results: A spectrum of more than 20 arteriosclerotic, cytokinic, inflammatory, lipidic, and oxidative stress biomarkers served for a detailed diagnosis and therapy monitoring. After medication, the ratio oxLDL/LDL was reduced by 21.0%, 8-iso-PGF 2α 39.8%, MPO 29.6%, IL-6 12.9%, hs-CRP 39.3%, Lp(a) 26.3%, MMP-9 32.9%, insulin 9.4%, HOMA-IR 14.0%, ALP 14.8%, CREA 11.3%, URAC 10.6%, in vitro modelled nanoplaque formation 14.3% and size 23.4%, whereas SOD was augmented by 17.7%, GPx 11.6%, cAMP 43.5%, and cGMP 32.9%. Special focus was concentrated on the significance of lipid peroxidation for cardio-cerebro-vascular diseases. Through multiple correlations between the biomarkers and clinical parameters, their significance for and involvement in several clinical pictures could be elucidated. Conclusion: The present clinical observational study was helpful in unravelling this network of biomarker interactions and demonstrated its usefulness for theranostics. For personalized medicine, the selection of the biomarkers is of decisive importance. On the background of a growing obesity among children and adolescents with an increase in prevalence of the metabolic syndrome, diagnosing this syndrome in young subjects may be helpful in identifying a population of risk for increased subclinical arteriosclerosis.