The Diagnostic Value of Serum miR-129 in Breast Cancer Patients with Bone Metastasis.

BACKGROUND: The current study aims to investigate the expression of serum miR-129 in breast cancer patients with bone metastasis and to further study its diagnostic role. METHODS: Serum samples of 60 patients with bone metastasis of breast cancer and 60 patients with non-bone metastasis of breast cancer were collected. The expression of serum miR-129 in breast cancer patients was detected by real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). The relationship between miR-129 and bone metastasis or bone pain in breast cancer patients with bone metastasis was analyzed. Receiver operating characteristic (ROC) curve was performed to analyze the diagnostic role of serum miR-129 expression in breast cancer patients with bone metastasis. RESULTS: The expression of miR-129 in serum of breast cancer patients with bone metastasis was significantly lower than that of non-bone metastasis patients. Furthermore, the lower the expression level of serum miR-129 was, the higher the degree of bone metastasis and bone pain was found in breast cancer patients. The ROC curve showed that the area under the curve (AUC) of miR-129 expression in serum for diagnosis of bone metastasis of breast cancer was 0.941 (95% CI: 0.891 - 0.991) with the sensitivity and specificity of 87.5% and 91.7%, respectively. CONCLUSIONS: In summary, decreased serum miR-129 in breast cancer patients can be used as a potential diagnostic marker of bone metastasis in breast cancer patients.

Rapid and non-destructive analysis for the identification of multi-grain rice seeds with near-infrared spectroscopy.

The rapid and non-destructive discriminant analysis of rice seeds has great significance for large-scale agriculture. Using near-infrared (NIR) diffuse-reflectance spectroscopy with partial least squares-discriminant analysis (PLS-DA), a variety identification method of multi-grain rice seeds was developed. The equidistant combination method was adopted for large-range wavelength screening. A step-by-step phase-out method was proposed to eliminate interference wavelengths and improve the predicted effect. The optimal wavelength model was a combination of 54 wavelengths within 808-974 nm of the short-NIR region. One type of pure rice variety (Y Liangyou 900) was used for identification (negative). Positive samples included the other four pure varieties and contamination of Y Liangyou 900 by the above four varieties. The recognition-accuracy rates for positive, negative and total validation samples reached 93.1%, 95.1%, and 94.3%, respectively. In the long-NIR region, the local optimal wavelength model was a combination of 49 wavelengths within 1188-1650 nm, and the recognition-accuracy rates for positive, negative and total validation samples were 90.3%, 94.1%, and 92.5%, respectively. Results confirmed the feasibility of NIR spectroscopy for variety identification of multi-grain rice seeds. The proposed two discrete-wavelength models located in the short- and long-NIR regions can provide valuable reference to a dedicated spectrometer.