Determination of parabens in human urine by optimal ultrasound-assisted emulsification microextraction and on-line acetylation gas chromatography-mass spectrometry.

An effective and solvent-less method for the rapid determination of four commonly detected parabens (methyl-, ethyl-, propyl- and butyl-) in human urine samples is described. This method employed ultrasound-assisted emulsification microextraction (USAEME) before identification and quantitation of the parabens via on-line acetylation gas chromatography-mass spectrometry (GC-MS). Urine samples were enzymatically de-conjugated with ß-glucuronidase and then extracted by an optimal USAEME procedure for the measurement of total concentrations of target analytes. The optimal USAEME parameters for one mL of urine sample (containing 0.1-g of sodium chloride), according to the Box-Behnken design method, are thus described: extractant of 200-µL of ethyl acetate, and ultrasonication for 1.0min and centrifugation at 7000rpm (3min). The supernatant was collected and evaporated until dry. Then the residue was re-dissolved in methanol (100-µL), and the extract was subjected to on-line acetylation GC-MS analysis. The limits of quantitation (LOQs) were less than 0.06ng/mL. Precisions for both intra- and inter-day analysis were calculated, and were less than 8%. Mean extraction recovery (known as trueness) was between 83 and 101% on three concentration levels. In human urine, the total concentrations of the four selected parabens, according to preliminary results, range from 0.3 to 124.5ng/mL for male, and from 27.2 to 246.3ng/mL for female. Female urine samples showed higher concentrations for the target parabens, which may indicate higher exposure due to lifestyle. This method permits accurate and high-throughput analysis of parabens for epidemiological studies.

Molecular Mechanism of the Cell Death Induced by the Histone Deacetylase Pan Inhibitor LBH589 (Panobinostat) in Wilms Tumor Cells.

BACKGROUND: Wilms tumor (WT) is an embryonic kidney cancer, for which histone acetylation might be a therapeutic target. LBH589, a novel targeted agent, suppresses histone deacetylases in many tumors. This study investigated the antitumor activity of LBH589 in SK-NEP-1 and G401 cells. METHODS: SK-NEP-1 and G401 cell growth was assessed by CCK-8 and in nude mice experiments. Annexin V/propidium iodide staining followed by flow cytometry detected apoptosis in cell culture. Gene expressions of LBH589-treated tumor cells were analyzed using an Arraystar Human LncRNA Array. The Multi Experiment View cluster software analyzed the expression data. Differentially expressed genes from the cluster analyses were imported into the Ingenuity Pathway Analysis tool. RESULTS: LBH589 inhibited cell proliferation of SK-NEP-1 and G401 cells in a dose-dependent manner. Annexin V, TUNEL and Hochest 33342 staining analysis showed that LBH589-treated cells showed more apoptotic features compared with the control. LBH589 treatment inhibited the growth of SK-NEP-1 xenograft tumors in nude mice. Arraystar Human LncRNA Array analysis of genes and lncRNAs regulated by LBH589 identified 6653 mRNAs and 8135 lncRNAs in LBH589-treated SK-NEP-1 cells. The most enriched gene ontology terms were those involved in nucleosome assembly. KEGG pathway analysis identified cell cycle proteins, including CCNA2, CCNB2, CCND1, CCND2, CDK4, CDKN1B and HDAC2, etc. Ingenuity Pathway Analysis identified important upstream molecules: HIST2H3C, HIST1H4A, HIST1A, HIST1C, HIST1D, histone H1, histone H3, RPRM, HSP70 and MYC. CONCLUSIONS: LBH589 treatment caused apoptosis and inhibition of cell proliferation of SK-NEP-1and G401 cells. LBH589 had a significant effect and few side effects on SK-NEP-1 xenograft tumors. Expression profiling, and GO, KEGG and IPA analyses identified new targets and a new "network" of genes responding to LBH589 treatment in SK-NEP-1 cells. RPRM, HSP70 and MYC may be important regulators during LBH589 treatment. Our results provide new clues to the proapoptotic mechanism of LBH589.

Feature analysis of superficial soft tissue interface based on wave numbers / 南方医科大学学报

Based on a simple deconvolution model of multi-layer interfaces, the reasons of wave number variation of the interfacial echo signal were analyzed to explore a method for feature recognition of the superficial soft tissue interfaces. The interfacial echo signal data were decomposed and reconstructed by Mallat multisolution analysis, with the number of the reconstructed interface signal as the feature. The results showed that the deconvolution model was effective for extracting the interface echo signal features in the superficial soft tissue and allowed identification and location of tissue defects.