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MicroRNAs(miRNAs) are emerging as important regulators in tumorigenesis. Increasing evidences have indicated microRNA-7(miR-7) to be a potential tumor suppressor in several human cancers. However, only a limited number of target genes have been identified so far and its biological function in Non-Small Cell Lung Cancer (NSCLC) remains to be further elucidated. In the present study, we observed a reduction of miR-7 level in NSCLC cell lines. Overexpression of miR-7 not only suppressed NSCLC A549 cells proliferation, induced cell apoptosis and inhibited cell migration in vitro, but also reduced tumorigenicity in vivo. Bioinformatics predictions revealed a potential binding site of miR-7 on 3'UTR of BCL-2 and it was further confirmed by luciferase assay. Moreover, subsequent experiments showed that BCL-2 was downregulated by miR-7 at both transcriptional and translational levels. These results suggest that miR-7 regulates the expression of BCL-2 through direct 3'UTR interactions. Therefore, we postulate BCL-2 to be a novel target possibly involved in miR-7-mediated growth suppression and apoptosis of A549 cells. These findings may provide a basic rationale for the use of miR-7 in the treatment of NSCLC.

Compositional data on the sterol and alcohol fractions isolated from deep-sea marine sediments from the Okinawa Trough were obtained to determine the relative contribution from marine and terrestrial inputs. Following extraction, the total saponified neutral fraction was derivatized witn BSTFA and then analysed by capillary GC and GC-MS. A suite of C26–C29 stenols and stanols and C30–C32 keto-alcohols were identified in the sediments. Major sterols included 27-nor-24-methylcholesta-5,22E-dien-3s-ol and cholest-5-en-3s-ol, which are most likely from marine fauna, and the C28 sterols 24-methylcholesta-5,22E-dien-3s-ol and 24-methylcholesta-5,24(28)-dien-3s-ol, both of which are common in diatoms. C29 sterols were dominated by sterols with 24-ethyl substitution of higher plant origin, but 23,24-dimethyl sterols which are found in some marine phytoplankton were also quite abundant. The major 4-methyl sterol was 4α,23,24-trimethyl-5α-cholest-22E-en-3s-ol which is considered a common indicator of dinoflagellates. Each sterol co-occurred with the corresponding 5α-stanol. Other indicators of terrestrial input such as α- and s-amyrin were also identified. The sediments also contained significant amounts of the C30 keto-alcohol triacontan-15-one-1-ol, as well as smaller amounts of C31 and C32 keto-alcohols. These unusual lipids are found in many marine sediments, and they may be formed by the oxidation of the corresponding C30–C32 alkyl diols found in some marine microalgae. The thermal stability of the compounds in these sediments was studied by heating portions of the surface sediment in glass tubes for 16 h at temperatures ranging from 100°C to 200°C. The C27 stanol/stenol ratio increased with increasing temperatures up to 140°C, as did the corresponding C28 and C29 stanol/stenol ratios. The keto-alcohols were more stable than sterols under these conditions.

Examination of solvent-extractable lipids in sediments from Beibu Gulf, South China Sea by capillary gas chromatography (GC) and capillary gas chromatography-mass spectrometry (GC-MS) resulted in the first identifications of β, γ-carotanes and their C19 to C31 homologs in the modern sediments from the China Seas. Distributional features of these (mainly triterpenoid and steroid hydrocarbons) biomarkers are discussed and the possibility of using these compounds as indicators of source of materials, diagenesis and depositional conditions is explored. It was found that the biomarkers in this region are mixtures of allochthonous (terrigenous and/or crude oil leak or pollution) and antochthonous (marine) organic components. The biomarders have proved to be of value for understanding sedimentation.

Test Selection in DFT (design for test) is known to be a NP-complete problem. Applying particle swarm optimization algorithm to test selection is firstly proposed in this paper. By analyzing characteristics of test selection, it constructs particles and velocities of BPSO (binary particle swarm optimization); It optimizes the particles using the fitness, which includes the indexes of test selection, and adds multiform inertial weight to BPSO according to its characteristic of getting into local optimal easily. The experimental results show that the proposed algorithm can earlier achieve higher fault detection rate, isolation rate and more compact test sets when compared to other similar test selection algorithms.