"Oncogene-induced" and/or stress-induced senescence may occur in the process of multi-step cholangiocarcinogenesis, and overexpression of a polycomb group protein EZH2 may play a role in the escape from, and/or bypassing of, senescence.
<b>Conclusion:</b> The relative balance of reduced trigger and increased substrate underlies a multi-dimensional role of MC-II-157c in modulation of cardiac arrhythmia vulnerability associated with prolonged QT interval.
<b>Purpose:</b> To investigate whether prebiopsy multi-parametric (mp) MRI can help to improve predictive performance in prostate cancer.<b>Experimental Design:</b> Based on a support vector machine (SVM) analysis, we prospectively modeled clinical data (age, PSA, digital rectal examination, transrectal ultrasound, PSA density, and prostate volume) and mp-MRI findings [Prostate Imaging and Reporting and Data System (PI-RADS) score and tumor-node-metastasis stage] in 985 men to predict the risk of prostate cancer.
<b>Purpose:</b> To investigate whether prebiopsy multi-parametric (mp) MRI can help to improve predictive performance in prostate cancer.<b>Experimental Design:</b> Based on a support vector machine (SVM) analysis, we prospectively modeled clinical data (age, PSA, digital rectal examination, transrectal ultrasound, PSA density, and prostate volume) and mp-MRI findings [Prostate Imaging and Reporting and Data System (PI-RADS) score and tumor-node-metastasis stage] in 985 men to predict the risk of prostate cancer.
<b>Purpose:</b> To investigate whether prebiopsy multi-parametric (mp) MRI can help to improve predictive performance in prostate cancer.<b>Experimental Design:</b> Based on a support vector machine (SVM) analysis, we prospectively modeled clinical data (age, PSA, digital rectal examination, transrectal ultrasound, PSA density, and prostate volume) and mp-MRI findings [Prostate Imaging and Reporting and Data System (PI-RADS) score and tumor-node-metastasis stage] in 985 men to predict the risk of prostate cancer.
<b>Purpose:</b> To investigate whether prebiopsy multi-parametric (mp) MRI can help to improve predictive performance in prostate cancer.<b>Experimental Design:</b> Based on a support vector machine (SVM) analysis, we prospectively modeled clinical data (age, PSA, digital rectal examination, transrectal ultrasound, PSA density, and prostate volume) and mp-MRI findings [Prostate Imaging and Reporting and Data System (PI-RADS) score and tumor-node-metastasis stage] in 985 men to predict the risk of prostate cancer.
<b>Purpose:</b> To investigate whether prebiopsy multi-parametric (mp) MRI can help to improve predictive performance in prostate cancer.<b>Experimental Design:</b> Based on a support vector machine (SVM) analysis, we prospectively modeled clinical data (age, PSA, digital rectal examination, transrectal ultrasound, PSA density, and prostate volume) and mp-MRI findings [Prostate Imaging and Reporting and Data System (PI-RADS) score and tumor-node-metastasis stage] in 985 men to predict the risk of prostate cancer.
Multi-locus analyses suggested joint effects between ADCY8 and ST3GAL1 (P = 3.00 x 10(-4)), with at least one copy of the "high risk" allele required at both genes for association with BP, consistent with a jointly dominant-dominant model of action.
Multi-variate analysis revealed that GRB7 protein over-expression was an independent adverse prognostic factor for breast cancer-free interval (hazard ratio 1.69, 95% confidence interval 1.07-2.67; P = 0.024).
Multi-parametric flow cytometry assessment of T cell activation (CD69, HLA-DR, CD38) and Treg frequency (CD25(+)FOXP3(+)) found no differences between genotype groups.
Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks.
Multi-tissue gene expression studies identified variants in our top loci, SERPINA1 and AQP9, as eQTLs and showed that SERPINA1 and AQP9 expression in human blood was associated with metabolites from their corresponding metabolic networks.
Multi-variate Cox regression analysis revealed that annexin II expression level was an independent prognostic parameter for the overall survival rate of NSCLC patients.