BACKGROUND.Methylation patterns may be useful biomarkers of cancer detection and risk assessment.METHODS.The methylation status of 6 genes, including a candidate tumor suppressor gene (BLU), the cadherin 13 gene (CDH13), the fragile histidine triad gene (FHIT), the cell cycle control gene p16, the retinoic acid receptor β gene (RARβ), and the Ras association domain family 1 gene (RASSF1A), was examined in plasma samples, corresponding tumor tissues, and normal lung tissues from a group of 63 patients with lung cancer and in plasma samples from 36 cancer‐free individuals. The detection rate of the p16 gene was validated in a test group of 20 patients with lung cancer.RESULTS.The concordance of methylation in tumor tissues and plasma samples was 86%, 87%, 80%, 75%, 76%, and 84% for the BLU, CDH13, FHIT, p16, RARβ, and RASSF1A genes, respectively. The test group showed a similar concordance for p16 methylation detection. Multiple logistic regression analysis showed that the odds ratio for having lung cancer was 10.204 for individuals with p16 methylation (P = .013) and 9.952 for individuals with RASSFIA methylation (P = .019). After several trial tests, the authors established that methylation for ≥2 of the 6 markers met the criterion for an elevated risk of cancer. Comparisons yielded a sensitivity of 73%, a specificity of 82%, and a concordance of 75% between the methylation patterns in tumor tissues and in corresponding plasma samples. The detection rate was relatively high in cigarette smokers with advanced squamous cell lung cancer.CONCLUSIONS.The current results indicated that multiple epigenetic markers in the plasma, especially the p16 and RASSF1A genes, can be used for lung cancer detection. This methylation marker panel should improve the detection of cancer or the risk assessment for lung cancer in combination with conventional diagnostic tools. Cancer 2007. © 2007 American Cancer Society.

Background As Traditional Chinese Medicine (TCM) drugs, Huangqi and Danshen are always applied in combination for spinal cord injury (SCI) treatment based on the compatibility theory of TCM. Astragalus Polysaccharidesis (APS) and Tanshinone IIA (TSIIA) are the main active ingredients of Huangqi and Danshen, and they both possess neuroprotective effects through antioxidant activities. However, low solubility and poor bioavailability have greatly limited their application. In recent years, selenium nanoparticles (SeNPs) have drawn enormous attention as potential delivery carrier for antioxidant drugs. Results In this study, TCM active ingredients-based SeNPs surface decorated with APS and loaded with TSIIA (TSIIA@SeNPs-APS) were successfully synthesized under the guidance of the compatibility theory of TCM. Such design improved the bioavailability of APS and TSIIA with the benefits of high stability, efficient delivery and highly therapeutic efficacy for SCI treatment illustrated by an improvement of the antioxidant protective effects of APS and TSIIA. The in vivo experiments indicated that TSIIA@SeNPs-APS displayed high efficiency of cellular uptake and long retention time in PC12 cells. Furthermore, TSIIA@SeNPs-APS had a satisfactory protective effect against oxidative stress-induced cytotoxicity in PC12 cells by inhibiting excessive reactive oxygen species (ROS) production, so as to alleviate mitochondrial dysfunction to reduce cell apoptosis and S phase cell cycle arrest, and finally promote cell survival. The in vivo experiments indicated that TSIIA@SeNPs-APS can protect spinal cord neurons of SCI rats by enhancing GSH-Px activity and decreasing MDA content, which was possibly via the metabolism of TSIIA@SeNPs-APS to SeCys2 and regulating antioxidant selenoproteins to resist oxidative stress-induced damage. Conclusions TSIIA@SeNPs-APS exhibited promising therapeutic effects in the anti-oxidation therapy of SCI, which paved the way for developing the synergistic effect of TCM active ingredients by nanotechnology to improve the efficacy as well as establishing novel treatments for oxidative stress-related diseases associated with Se metabolism and selenoproteins regulation.

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Night-time fruit-picking technology is important to picking robots. This paper proposes a method of night-time detection and picking-point positioning for green grape-picking robots to solve the difficult problem of green grape detection and picking in night-time conditions with artificial lighting systems. Taking a representative green grape named Centennial Seedless as the research object, daytime and night-time grape images were captured by a custom-designed visual system. Detection was conducted employing the following steps: (1) The RGB (red, green and blue). Color model was determined for night-time green grape detection through analysis of color features of grape images under daytime natural light and night-time artificial lighting. The R component of the RGB color model was rotated and the image resolution was compressed; (2) The improved Chan–Vese (C–V) level set model and morphological processing method were used to remove the background of the image, leaving out the grape fruit; (3) Based on the character of grape vertical suspension, combining the principle of the minimum circumscribed rectangle of fruit and the Hough straight line detection method, straight-line fitting for the fruit stem was conducted and the picking point was calculated using the stem with an angle of fitting line and vertical line less than 15°. The visual detection experiment results showed that the accuracy of grape fruit detection was 91.67% and the average running time of the proposed algorithm was 0.46 s. The picking-point calculation experiment results showed that the highest accuracy for the picking-point calculation was 92.5%, while the lowest was 80%. The results demonstrate that the proposed method of night-time green grape detection and picking-point calculation can provide technical support to the grape-picking robots.