Expression of activation molecules in neutrophils, monocytes and lymphocytes from patients with unstable angina treated with stent implantation.

Coronary angioplasty is known to mediate an inflammatory response. Recently, we have characterized the transient systemic inflammatory response after coronary stent implantation in patients with unstable angina by measuring different soluble protein markers. In the present study we have characterized the expression of various cellular activation markers in neutrophils, monocytes and lymphocytes from the same group of patients. Peripheral blood samples were taken before and 24 h, 48 h and 7 days after successful coronary stenting in 58 patients. Cell surface markers (CD11b/CD18 and CD38) were analyzed by flow cytometry to determine the activation of neutrophils, monocytes and T lymphocytes. We found that coronary angioplasty with stent implantation produces an increase in the cell surface expression of CD11b/CD18 in neutrophils and CD38 in monocytes, following a similar time-course with a peak after 24 h, returning to basal levels after 48 h and a second peak after 7 days. However, T lymphocytes were not found to be activated. These results suggest that coronary stent implantation induces a different pattern inducing soluble and cellular inflammation markers, and therefore, they should be taken into account in patients undergoing stent implantation to study clinical correlations.     

Botulinum toxin and neuromotor rehabilitation: An integrated approach to idiopathic cervical dystonia.

Currently, the best treatment option for idiopathic cervical dystonia (ICD) is injection of botulinum toxin (BTX) into the affected muscles, whereas rehabilitative approaches have given disappointing results. We evaluated whether the association of an ad hoc rehabilitative program may improve the clinical efficacy of BTX treatment in a single-center, cross-over, controlled study. Forty patients with ICD were randomly assigned to two different treatment groups: (1) BTX type A (BTX-A) plus a specific program of physical therapy (BTX-PT) or (2) BTX-A alone (BTX-0). Patients in the BTX-PT group showed a longer duration of the clinical benefit (118.8 vs. 99.1 days) and needed a lower dose of BTX at reinjection (284.5 vs. 325.5 units). In addition, they showed more marked reductions in their disability in activities of daily living (-9.7 vs. -4.85 points) and subjective pain (-13.35 vs. 6.95 points) scores. Association of BTX-A therapy with a specific program of physical therapy may improve ICD treatment outcome.     

Biochemical changes after a qigong program: lipids, serum enzymes, urea, and creatinine in healthy subjects.

BACKGROUND: The aim of the present study was to analyze the effects of a qigong training program on blood biochemical parameters. MATERIAL/METHODS: Twenty-nine healthy subjects participated in the study of whom 16 were randomly assigned to the experimental group and 13 to the control. The experimental subjects underwent daily qigong training for one month. Blood samples for the quantification of biochemical parameters (total cholesterol, HDL, LDL, triglycerides, phospholipids, GOT, GPT, GGT, urea, creatinine) were taken before and after the training program. As statistical analysis, ANCOVA was performed. RESULTS: Statistically significant differences were found showing that the experimental group had lower serum levels of GOT (glutamic-oxaloacetic transaminase), GPT (glutamic-pyruvic transaminase), and urea and that there was a trend towards significance in GGT (gamma-glutamyltransferase). CONCLUSIONS: This study demonstrates that after practicing qigong for the short period of one month, noteworthy changes in several blood biochemical parameters were induced. While it is tempting to speculate on the relevance and implications of these biochemical variations, further investigation is needed to elucidate the scope of these findings.     

Integrating support vector machines and neural networks.

Support vector machines (SVMs) are a powerful technique developed in the last decade to effectively tackle classification and regression problems. In this paper we describe how support vector machines and artificial neural networks can be integrated in order to classify objects correctly. This technique has been successfully applied to the problem of determining the quality of tiles. Using an optical reader system, some features are automatically extracted, then a subset of the features is determined and the tiles are classified based on this subset.