MiR-296-3p may affect the proliferation and migration of non-small cell lung cancer cells via regulating RABL3.

OBJECTIVE: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related death worldwide. The pathogenesis of NSCLC has not yet been fully understood, and the therapeutic efficacy of current anti-NSCLC medication remains unsatisfactory. Previous studies indicated that miR-296-3p was down-regulated in NSCLC, suggesting that miR-296-3p may participate in the pathogenesis of NSCLC; however, the specific mechanisms still need to be further explored. The aim of this work is to investigate the roles of miR-296-3p in NSCLC and the related mechanism. PATIENTS AND METHODS: Thirty NSCLC tissue and paired adjacent tissue were collected, and Real Time-quantitative Polymerase Chain Reaction (RT-qPCR) was performed to examine the expression of miR-296-3p in cancer tissue and the adjacent tissue. Next, A549 cells were cultured and transfected with miR-296-3p mimics, and cell migration and invasion were determined using scratch wound-healing and transwell assays. Moreover, Western blot assay was performed to determine the effect of miR-296-3p on the expression of Rab-like 3 (RABL3), Matrix metallopeptidase (MMP)-2, Janus kinase (JAK) and Signal transducer and activator of transcription 3 (STAT3); next, Dual-Luciferase reporter assay has been conducted to prove the direct targeting relationship between miR-296-3p and RABL3. Finally, the cells of different treatments were subcutaneously implanted into nude mice to investigate the effect of miR-296-3p mimics in the xenograft mice tumor models. RESULTS: Our data indicated that miR-296-3p was significantly down-regulated and RABL3 was markedly up-regulated in NSCLC tissue compared with the adjacent tissue. Moreover, transient over-expression of miR-296-3p in A549 cells induced a significant decrease in the proliferation and invasion ability of A549 cells, as well as decreased expression of RABL3, MMP-2, JAK and STAT3. Furthermore, the Dual-Luciferase reporter assay confirmed that RABL3 is a direct target of miR-296-3p. Finally, the results of animal studies indicated that miR-296-3p can regulate the tumorigenesis of A549 cells in vivo. CONCLUSIONS: Our findings proved that miR-296-3p may play a role as a tumor suppressor in NSCLC both in vitro and in vivo, and we first reported that miR-296-3p can regulate the migration and invasion of A549 cells via targeting RABL3. Our data suggested that miR-296-3p may serve as a potential therapeutic target for treating NSCLC.

[Changes in QT interval of electrocardiogram under +Gz acceleration and its significance].

OBJECTIVE: To define whether QT interval could be used to predict the response of pilots to +Gz stress. METHOD: 37 pilots underwent +4 Gz acceleration on a human centrifuge. According to their responses to +Gz stress, subjects were divided into group A (good reaction group, n=18), group B (hyperfunction reaction group, n=14) and group C (inhibition reaction group, n=1). QT and RR interval were measured pre-, during and post-G. The data of 33 subjects (89.2%) whose QT interval could be measured were analyzed statistically. RESULT: During +Gz, QT and RR interval were shortened and sensitivity of QT interval to RR interval was augmented significantly (vs. pre-G, P<0.001); group B had higher sensitivity of QT interval to RR interval during +Gz (P<0.001, as compared with group A); discrimination functions established by QT and RR interval during +Gz were efficient and their accurate judgement rate was 81.8%. CONCLUSION: The changes in QT interval of ECG were related to autonomic nervous imbalance under +Gz; QT interval and RR interval could be used to predict the response of pilots to +Gz stress. These suggested that the parameters and method in this study might be used in G-LOC warning system.

QTL mapping for grain filling rate and yield-related traits in RILs of the Chinese winter wheat population Heshangmai x Yu8679.

A set of 142 winter wheat recombinant inbred lines (RILs) deriving from the cross Heshangmai x Yu8679 were tried in four ecological environments during the seasons 2006 and 2007. Nine agronomic traits comprising mean grain filling rate (GFR(mean)), maximum grain filling rate (GFR(max)), grain filling duration (GFD), grain number per ear (GNE), grain weight per ear (GWE), flowering time (FT), maturation time (MT), plant height (PHT) and thousand grain weight (TGW) were evaluated in Beijing (2006 and 2007), Chengdu (2007) and Hefei (2007). A genetic map comprising 173 SSR markers and two EST markers was generated. Based on the genetic map and phenotypic data, quantitative trait loci (QTL) were mapped for these agronomic traits. A total of 99 putative QTLs were identified for the nine traits over four environments except GFD, PHT and MT, measured in two environments (BJ07 and CD07), respectively. Of the QTL detected, 17 for GFR(mean), 16 for GFR(max), 21 for TGW and 10 for GWE involving the chromosomes 1A, 1B, 2A, 2D, 3A, 3B, 3D, 4A, 4D, 5A, 5B, 6D and 7D were identified. Moreover, 13 genomic regions showing pleiotropic effects were detected in chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 4B, 4D, 5B, 6D and 7D; these QTL revealing pleiotropic effects may be informative for a better understanding of the genetic basis of grain filling rate and other yield-related traits, and represent potential targets for multi-trait marker aided selection in wheat.

An estimation of the minimum number of SSR alleles needed to reveal genetic relationships in wheat varieties. I. Information from large-scale planted varieties and cornerstone breeding parents in Chinese wheat improvement and production.

The genetic relationships of 43 wheat varieties were analyzed with SSR markers. The materials employed included 14 cornerstone breeding parents used before 1980 and another 29 other large-scale planted varieties currently in use in China. A total of 501 different alleles were amplified, including 166 alleles of the A genome, 174 of the B genome and 161 of the D genome. Data obtained were used to estimate genetic similarity using the DICE coefficient, and dendrograms were constructed using the UPGMA method. The dendrogram with 501 alleles successfully differentiated all the cornerstone breeding parents and the large-scale planted varieties, and the dendogram tree was basically consistent with the pedigrees of these varieties. The correlation coefficient between the genetic distance matrix of 501 alleles and that of 450 was 0.99. Correlation coefficients among random samples of alleles suggested that 350 to 400 alleles were needed to detect genetic relationships among common wheat varieties. Correlation coefficients of a genetic similarity matrix based on 580, and those of 501 and 400, random alleles were 0.96 and 0.94, respectively. However, there were marked differences between the matrix based on the 501 alleles and those based on markers located on the A-, B- or D-genome independently. The correlation coefficients between the genetic distance matrix of 501 alleles and alleles within A, B or D genomes were 0.77, 0.76 and 0.67. The estimation of genetic similarity should be based on data from all genomes rather than any one genome.