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OBJECTIVE: To evaluate the association between serum galectin-3 and all-cause death (ACD) and cardiovascular death (CVD) in patients with chronic heart failure (CHF). METHODS: The PubMed and Embase databases and Clinical Trials Registry (www.clinicaltrials.gov) were searched for studies with data on serum galectin-3 and ACD and CVD in CHF patients. The hazard ratios (HRs) of ACD and CVD were calculated and presented with 95% CIs. HRs were pooled using fixed effects or random effects models when appropriate. Sensitivity analysis, meta-regression and subgroup analysis were applied to find the origin of heterogeneity. Visual inspection of Begg's funnel plot and Egger's test were performed to assess the possibility publication bias. RESULTS: Pooled data included the results from 6,440 patients from 12 studies in the meta-analysis. Higher serum galectin-3 was associated with a higher risk of ACD (HR, 1.38; 95% CI, 1.14-1.67) and CVD (HR, 1.13; 95% CI, 1.02-1.25) in CHF patients. In the subgroup analyses, higher serum galectin-3 was associated with an increased risk of ACD in all subgroups. The pooled HR of the shorter follow-up group (1.78; 95% CI, 1.50-2.11) was significantly higher than the pooled HR of the longer follow-up group (1.15; 95% CI, 1.05-1.25). Sensitivity analysis of eliminating one study in each turn indicated that Koukoui et al.'s study had the largest influence on the risk of all-cause death. All-cause death publication bias was not detected (Pr>|z| = 0.35 for Begg's test and P>|t| = 0.15 for Egger's test). CONCLUSIONS: Serum galectin-3 has prognostic value of both all-cause death and cardiovascular death in CHF. Serum galectin-3 could be useful for risk classification in patients with CHF. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=193399.
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In this paper, we investigated the feasibility of using surface enhanced Raman spectroscopy (SERS) and multivariate analysis method to discriminate liver cancer and nasopharyngeal cancer from healthy volunteers. SERS measurements were performed on serum protein samples from 104 liver cancer patients, 100 nasopharyngeal cancer patients, and 95 healthy volunteers. Two dimensionality reduction methods, principal component analysis (PCA) and partial least square (PLS) were compared, and the results indicated that the performance of PLS is superior to that of PCA. When the number of components was compressed to 3 by PLS, support vector machine (SVM) with a Gaussian radial basis function (RBF) was employed to classify various cancers simultaneously. Based on the PLS-SVM algorithm, high diagnostic accuracies of 95.09% and 90.67% were achieved from the training set and the unknown testing set, respectively. The results of this exploratory work demonstrate that serum protein SERS technology combined with PLS-SVM diagnostic algorithm has great potential for the noninvasive screening of cancer.
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Breast cancer has been one of the most common malignant tumors threatening female health with high incidence. Cell mechanics is becoming an important issue and could serves as a potential indicator for early cancer diagnosis. In this study, atomic force microscopy (AFM) was applied to characterize and compare the surface nanostructure and viscoelasticity of different breast cell lines. Our results show that breast cancerous cells MCF-7 exhibit more disorganized filamentous cytoskeleton structure with increased membrane roughness compared to benign breast cells MCF-10A (P < 0.05). The viscoelastic properties, including elasticity and viscosity, are significantly different between the two cell lines. MCF-7 displays reduced elasticity and viscosity, indicating that breast cancer cells are softer and more fluid than benign counterpart. Our findings provide new insights into the biophysical changes of cells during tumor transformation and suggest it could be used for early cancer detection at single cell level. SCANNING 38:558-563, 2016. © 2016 Wiley Periodicals, Inc.