NMR hyperpolarization techniques of gases

Nuclear spin polarization can be significantly increased through the process of hyperpolarization, leading to an increase in the sensitivity of nuclear magnetic resonance (NMR) experiments by 4–8 orders of magnitude. Hyperpolarized gases, unlike liquids and solids, can often be readily separated and purified from the compounds used to mediate the hyperpolarization processes. These pure hyperpolarized gases enabled many novel MRI applications including the visualization of void spaces, imaging of lung function, and remote detection. Additionally, hyperpolarized gases can be dissolved in liquids and can be used as sensitive molecular probes and reporters. This Minireview covers the fundamentals of the preparation of hyperpolarized gases and focuses on selected applications of interest to biomedicine and materials science

Plasma microRNAs as potential biomarkers for non-small-cell lung cancer

Non-small-cell lung cancer (NSCLC) is the leading cause of cancer-related death. Developing minimally invasive techniques that can diagnose NSCLC, particularly at an early stage, may improve its outcome. Using microarray platforms, we previously identified 12 microRNAs (miRNAs) the aberrant expressions of which in primary lung tumors are associated with early-stage NSCLC. Here, we extend our previous research by investigating whether the miRNAs could be used as potential plasma biomarkers for NSCLC. We initially validated expressions of the miRNAs in paired lung tumor tissues and plasma specimens from 28 stage I NSCLC patients by real-time quantitative reverse transcription PCR, and then evaluated diagnostic value of the plasma miRNAs in a cohort of 58 NSCLC patients and 29 healthy individuals. The altered miRNA expressions were reproducibly confirmed in the tumor tissues. The miRNAs were stably present and reliably measurable in plasma. Of the 12 miRNAs, five displayed significant concordance of the expression levels in plasma and the corresponding tumor tissues (all r>0.850, all P<0.05). A logistic regression model with the best prediction was defined on the basis of the four genes (miRNA-21, -126, -210, and 486-5p), yielding 86.22% sensitivity and 96.55% specificity in distinguishing NSCLC patients from the healthy controls. Furthermore, the panel of miRNAs produced 73.33% sensitivity and 96.55% specificity in identifying stage I NSCLC patients. In addition, the genes have higher sensitivity (91.67%) in diagnosis of lung adenocarcinomas compared with squamous cell carcinomas (82.35%) (P<0.05). Altered expressions of the miRNAs in plasma would provide potential blood-based biomarkers for NSCLC