Proinflammatory Activation of Monocytes in Patients with Immunoinflammatory Rheumatic Diseases.

The pathogenesis of immunoinflammatory rheumatic diseases (IRDs) is based on chronic inflammation, one of the key mechanisms of which may be abnormal activation of macrophages, leading to further disruption of the immune system. OBJECTIVE: . The objective of this study was to evaluate the proinflammatory activation of circulating monocytes in patients with IRDs. MATERIALS AND METHODS: . The study involved 149 participants (53 patients with rheumatoid arthritis (RA), 45 patients with systemic lupus erythematosus (SLE), 34 patients with systemic scleroderma (SSc), and 17 participants without IRDs) 30 to 65 years old. Basal and lipopolysaccharide (LPS)-stimulated secretion of monocytes was studied in a primary culture of monocytes obtained from blood by immunomagnetic separation. Quantitative assessment of the cytokines tumor necrosis factor α (TNF-α), interleukin 1ß (IL-1ß), as well as the chemokine monocyte chemoattractant protein-1 (MCP-1) was carried out in the culture fluid by ELISA. Proinflammatory activation of monocytes was calculated as the ratio of LPS-stimulated and basal secretions. RESULTS: . It was shown that the basal secretion of all studied cytokines was significantly increased in all groups of patients with IRDs, except for the secretion of IL-1ß in the SLE group, compared to the control. LPS-stimulated secretion of TNF-α was increased and MCP-1 was decreased in patients with IRDs compared to the control group; LPS-stimulated IL-1ß secretion only in the SSc group significantly differed from the control group. In the RA group, monocyte activation was reduced for all cytokines compared to the control; in the SLE group, for TNF-α and MCP-1; in the SSc group, for MCP-1. CONCLUSIONS: . The decrease in proinflammatory activation of monocytes in patients with IRDs is due to a high level of basal secretion of cytokines, which can lead to disruption of the adequate immune response in these diseases and is an important link in the pathogenesis of chronic inflammation.

[The influence of diet therapy and regular physical trainings on monocyte chemoattractant protein-1 (MCP-1) secretion by monocytes among obese patients with coronary heart disease].

Chronic systemic inflammation is one of the leading pathogenetic pathways for the development of atherosclerosis in obese patients. In this regard, it seems promising to evaluate the effect of the diet and physical exertion on the proinflammatory activity of monocytes. The purpose of this research was to evaluate the effect of the diet and regular physical trainings on the secretion of monocyte chemotactic factor 1 (MCP-1) by monocytes in obese patients with coronary artery disease. Material and methods. 27 obese participants (body mass index >30 kg/m2) with a confirmed diagnosis of coronary heart disease were recruited. All participants were prescribed with 12 weeks of a specialized diet with a restriction of simple carbohydrates and salt, a 500-kcal daily energy deficit, and with inclusion of cruciferous (200 g per day), seasonal dark berries (70 g per day) and green tea (200 ml per day). The regular assisted physical trainings were also administered. The body composition, blood biochemical parameters and MCP-1 secretion rates in the primary culture of monocytes isolated from blood samples via the immunomagnetic separation method were assessed before and after the intervention. Results. As a result, after the 12-weeks intervention the reliable body weight loss (-4.0%), waist circumference (-4.2%), visceral fat (-5.4%), total cholesterol (-9.8%), LDL-cholesterol (-16.6%) and triglycerides (-26.0%), an improvement in the results of the 6-minute walk test (+10.33%) was achieved, as well as an LPS-stimulated monocytes secretion of MCP-1 decreased by 2.8 times (p=0.005). Conclusion. Overall, the results suggest that diet and regular physical activity in patients with obesity and coronary heart disease may decrease the functional "proinflammatory" activity of monocytes.

MALDI imaging-based classification of hepatocellular carcinoma and non-malignant lesions in fibrotic liver tissue.

Histopathologic differentiation of nodular lesions in cirrhotic liver is difficult even for experienced hepatopathologists especially regarding diagnosis of hepatocellular carcinoma (HCC) in biopsies. For this reason, new tissue markers are needed to reinforce histopathologic decision-making. With advances in molecular techniques, proteomic analysis may help to confirm the diagnosis of HCC. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful technology which allows to determine and to localize proteins directly in tissue sections. Using MALDI IMS proteomic patterns of cryosections with lesions of HCC (n = 15) and non-malignant fibrotic liver tissue (n = 11) were investigated to establish a classification model of HCC, which was validated in an independent set of tissue to distinguish HCC (n = 10) from regenerative nodules (n = 8). By correlating generated mass spectrometric images with the histology of the tissue sections we found that the expression of 4 proteins as indicated by m/z 6274, m/z 6647, m/z 6222 and m/z 6853 was significantly higher in HCC tissue than in non-tumorous liver tissue. The generated classification model based on the most significant 3 differentially expressed proteins allowed a reliable prediction of benign and malignant lesions in fibrotic liver tissue with a sensitivity and specificity of 90 % in the validation set. The identified MALDI IMS proteomic signature can be diagnostically helpful to allow simplifying the diagnostic process and minimize the risks of delays in establishing the objective final diagnosis and initiating treatment of patients with HCC.

Classification and prediction of HCC tissues by Raman imaging with identification of fatty acids as potential lipid biomarkers.

PURPOSE: Patients with hepatocellular carcinoma (HCC) can only be treated curatively at early stages and then have a favorable prognosis of this often fatal disease. For this reason, an early detection and diagnostic confirmation are crucial. Raman imaging spectroscopy is a promising technology for high-resolution visualization of the spatial distribution of molecular composition in tissue sections. The aim of this study was to investigate molecular information of liver tissue by Raman imaging for classification and diagnostic prediction. METHODS: Unstained cryosections of human hepatic tissues (23 patients) were measured by Raman spectroscope in the regions of HCC (n = 12) and fibrosis (n = 17). The acquired data set was used to generate a random forest classification model with 101 iterations of sevenfold cross-validation. The models obtained during cross-validation were also used to predict regions of tumor margin (n = 8) aside from independent testing. RESULTS: Raman spectra differed between malignant and non-malignant tissue regions. Based on these spectral data, a random forest classification model calculated a prediction accuracy of 86 % (76 % sensitivity and 93 % specificity). The ten most important variables were identified at 2895, 2856, 1439, 1298, 1080, 1063, 1023, 937, 920, and 719 cm(-1). CONCLUSIONS: In this study, Raman imaging spectroscopy was applied successfully for liver tissue to differentiate, classify, and predict with high accuracy malignant and non-malignant tissue regions. Furthermore, the most important differences were identified as the Raman signature of fatty acids. The demonstrated results highlight the enormous potential which vibrational spectroscopy techniques have for the future diagnostics and prognosis estimation of HCC.

Discrimination and classification of liver cancer cells and proliferation states by Raman spectroscopic imaging.

Discrimination of nodular lesions in cirrhotic liver is a challenge in the histopathologic diagnostics. For this reason, there is an urgent need for new detection methods to improve the accuracy of the diagnosis of liver cancer. Raman imaging allows to determine the spatial distribution of a variety of molecules in cells or tissue label-free and to correlate this molecular information with the morphological structures at the same sample location. This study reports investigations of two liver cancer cell lines, - HepG2 and SK-Hep1, - as well as HepG2 cells in different cellular growth phases using Raman micro-spectroscopic imaging. Spectral data of all cells were recorded as a color-coded image and subsequentially analyzed by hierarchical cluster and principal component analysis. A support vector machine-based classification algorithm reliably predicts previously unknown cancer cells and cell cycle phases. By including selectively the Raman spectra of the cytoplasmic lipids in the classifier, the accuracy has been improved. The main spectral differences that were found in the comparative analysis can be attributed to a higher expression of unsaturated fatty acids in the hepatocellular carcinoma cells and during the proliferation phase. This corresponds to the already examined de novo lipogenesis in cells of liver cancer.