Increased serum extrachromosomal circular DNA SORBS1circle level is associated with insulin resistance in patients with newly diagnosed type 2 diabetes mellitus.

BACKGROUND: Extrachromosomal circular DNAs (eccDNAs) exist in human blood and somatic cells, and are essential for oncogene plasticity and drug resistance. However, the presence and impact of eccDNAs in type 2 diabetes mellitus (T2DM) remains inadequately understood. METHODS: We purified and sequenced the serum eccDNAs obtained from newly diagnosed T2DM patients and normal control (NC) subjects using Circle-sequencing. We validated the level of a novel circulating eccDNA named sorbin and SH3-domain- containing-1circle97206791-97208025 (SORBS1circle) in 106 newly diagnosed T2DM patients. The relationship between eccDNA SORBS1circle and clinical data was analyzed. Furthermore, we explored the source and expression level of eccDNA SORBS1circle in the high glucose and palmitate (HG/PA)-induced hepatocyte (HepG2 cell) insulin resistance model. RESULTS: A total of 22,543 and 19,195 eccDNAs were found in serum samples obtained from newly diagnosed T2DM patients and NC subjects, respectively. The T2DM patients had a greater distribution of eccDNA on chromosomes 1, 14, 16, 17, 18, 19, 20 and X. Additionally, 598 serum eccDNAs were found to be upregulated, while 856 eccDNAs were downregulated in T2DM patients compared with NC subjects. KEGG analysis demonstrated that the genes carried by eccDNAs were mainly associated with insulin resistance. Moreover, it was validated that the eccDNA SORBS1circle was significantly increased in serum of newly diagnosed T2DM patients (106 T2DM patients vs. 40 NC subjects). The serum eccDNA SORBS1circle content was positively correlated with the levels of glycosylated hemoglobin A1C (HbA1C) and homeostasis model assessment of insulin resistance (HOMA-IR) in T2DM patients. Intracellular eccDNA SORBS1circle expression was significantly enhanced in the high glucose and palmitate (HG/PA)-induced hepatocyte (HepG2 cell) insulin resistance model. Moreover, the upregulation of eccDNA SORBS1circle in the HG/PA-treated HepG2 cells was dependent on generation of apoptotic DNA fragmentation. CONCLUSIONS: These results provide a preliminary understanding of the circulating eccDNA patterns at the early stage of T2DM and suggest that eccDNA SORBS1circle may be involved in the development of insulin resistance.

GCN5L1 regulates pulmonary surfactant production by modulating lamellar body biogenesis and trafficking in mouse alveolar epithelial cells.

BACKGROUND: The pulmonary surfactant that lines the air-liquid surface within alveoli is a protein-lipid mixture essential for gas exchange. Surfactant lipids and proteins are synthesized and stored in the lamellar body (LB) before being secreted from alveolar type II (AT2) cells. The molecular and cellular mechanisms that regulate these processes are incompletely understood. We previously identified an essential role of general control of amino acid synthesis 5 like 1 (GCN5L1) and the biogenesis of lysosome-related organelle complex 1 subunit 1 (BLOS1) in surfactant system development in zebrafish. Here, we explored the role of GCN5L1 in pulmonary surfactant regulation. METHOD: GCN5L1 knockout cell lines were generated with the CRISPR/Cas9 system. Cell viability was analyzed by MTT assay. Released surfactant proteins were measured by ELISA. Released surfactant lipids were measured based on coupled enzymatic reactions. Gene overexpression was mediated through lentivirus. The RNA levels were detected through RNA-sequencing (RNA-seq) and quantitative reverse transcription (qRT)- polymerase chain reaction (PCR). The protein levels were detected through western blotting. The cellular localization was analyzed by immunofluorescence. Morphology of the lamellar body was analyzed through transmission electron microscopy (TEM), Lysotracker staining, and BODIPY phosphatidylcholine labeling. RESULTS: Knocking out GCN5L1 in MLE-12 significantly decreased the release of surfactant proteins and lipids. We detected the downregulation of some surfactant-related genes and misregulation of the ROS-Erk-Foxo1-Cebpα axis in mutant cells. Modulating the activity of the axis or reconstructing the mitochondrial expression of GCN5L1 could partially restore the expression of these surfactant-related genes. We further showed that MLE-12 cells contained many LB-like organelles that were lipid enriched and positive for multiple LB markers. These organelles were smaller in size and accumulated in the absence of GCN5L1, indicating both biogenesis and trafficking defects. Accumulated endogenous surfactant protein (SP)-B or exogenously expressed SP-B/SP-C in adenosine triphosphate-binding cassette transporterA3 (ABCA3)-positive organelles was detected in mutant cells. GCN5L1 localized to the mitochondria and LBs. Reconstruction of mitochondrial GCN5L1 expression rescued the organelle morphology but failed to restore the trafficking defect and surfactant release, indicating specific roles associated with different subcellular localizations. CONCLUSIONS: In summary, our study identified GCN5L1 as a new regulator of pulmonary surfactant that plays a role in the biogenesis and positioning/trafficking of surfactant-containing LBs.

Identifying and Validating a Novel miRNA-mRNA Regulatory Network Associated with Prognosis in Lung Adenocarcinoma.

Objective Many studies have revealed the crucial roles of miRNA in multiple human cancers, including lung adenocarcinoma (LUAD). In this study, we sought to explore new miRNA-mRNA pairs that are associated with LUAD prognosis. Methods A novel miRNA-mRNA regulatory network associated with prognosis in LUAD was identified and validated using the bioinformatic tools including OncomiR database, StarBase, miRnet, GEPIA2, UALCAN. Results Twenty key miRNAs were compiled after the analysis of the expression and prognostic value in OncomiR and StarBase. Targeted mRNAs of these key miRNAs were predicted in miRnet, and the resulting mRNAs were also analyzed for their prognostic values and expression patterns in GEPIA2 and UALCAN, respectively. Further expression correlation analysis was performed in StarBase. Subsequently, a new miRNA-mRNA network was built, of which each RNA pair showed negative expression correlation, opposite expression pattern, and prognostic value. Protein-protein interaction network was under construction for the mRNAs, and 19 hub genes were determined. Enrichment analysis showed that "Cell Cycle, Mitotic" was the most significantly enriched term. Then, a miRNA-hub gene sub-network was built. We selected and validated the regulatory relationship of some miRNA-hub pairs, including hsa-miR-1976/RFC2, hsa-let-7c-5p/RFC2, hsa-let-7c-5p/ESPL1, hsa-let-7c-5p/CDC25A, and hsa-miR-101-3p/KIF2C. Moreover, over-expression of hsa-miR-1976 and hsa-let-7c-5p resulted in significant cell cycle arrest. Conclusions Our results determined new prognosis-associated miRNA-mRNA pairs and might shed further light on the mechanism via which miRNA-mRNA network influences prognosis in LUAD.

LncRNA Dnmt3aos regulates Dnmt3a expression leading to aberrant DNA methylation in macrophage polarization.

Long non-coding RNAs (lncRNAs) play key roles in various biological processes. However, the roles of lncRNAs in macrophage polarization remain largely unexplored. In this study, thousands of lncRNAs were identified that are differentially expressed in distinct polarized bone marrow-derived macrophages. Among them, Dnmt3aos (DNA methyltransferase 3A, opposite strand), as a known lncRNA, locates on the antisense strand of Dnmt3a. Functional experiments further confirmed that Dnmt3aos were highly expressed in M(IL-4) macrophages and participated in the regulation of Dnmt3a expression, and played a key role in macrophage polarization. The DNA methylation profiles between the Dnmt3aos knockdown group and the control group in M(IL-4) macrophages were determined by MeDIP-seq technique for the first time, and the Dnmt3aos-Dnmt3a axis-mediated DNA methylation modification-regulated macrophage polarization- related gene IFN-γ was identified. Our study will help to enrich our knowledge of the mechanism of macrophage polarization.

Lactate induced up-regulation of KLHDC8A (Kelch domain-containing 8A) contributes to the proliferation, migration and apoptosis of human glioma cells.

Glioma is a common type of malignant brain tumour with high mortality and relapse rate. However, the molecular mechanisms of glioma development have not been clarified. Differentially expressed genes in normal brain tissues and glioma tissues, low-grade and high-grade gliomas were screened out with GEO database analysis. We found that KLHDC8A (Kelch domain-containing 8A) expression level was significantly increased in high-grade glioma tissues and that high KLHDC8A expression was closely related with poor prognosis. Function assays indicated that KLHDC8A knockdown inhibited proliferation, migration and invasion, blocked the cell cycle and promoted apoptosis in glioma cells. Mechanistically, KLHDC8A regulated various functions in glioma by directly mediating Bcl2, BAX, p21, CDK2, MMP2 transcription and ERK and P38 MAPK activation. KLHDC8A overexpression enhances glioma tumorgenesis such as cell proliferation, migration and invasion. The ERK and P38 MAPK which activated by KLHDC8A overexpression could be reversed by U0126 and SB203580, respectively. Meanwhile, stimulation of lactate which produced by glycolysis is responsible for induction of KLHDC8A expression. Collectively, we demonstrated that KLHDC8A plays an important role in tumorgenesis of glioma, suggesting that it is a promising prognostic marker and a potential therapy target for the treatment of glioma.

Gene regulation network analysis reveals core genes associated with survival in glioblastoma multiforme.

Glioblastoma multiforme (GBM) is a very serious mortality of central nervous system cancer. The microarray data from GSE2223, GSE4058, GSE4290, GSE13276, GSE68848 and GSE70231 (389 GBM tumour and 67 normal tissues) and the RNA-seq data from TCGA-GBM dataset (169 GBM and five normal samples) were chosen to find differentially expressed genes (DEGs). RRA (Robust rank aggregation) method was used to integrate seven datasets and calculate 133 DEGs (82 up-regulated and 51 down-regulated genes). Subsequently, through the PPI (protein-protein interaction) network and MCODE/ cytoHubba methods, we finally filtered out ten hub genes, including FOXM1, CDK4, TOP2A, RRM2, MYBL2, MCM2, CDC20, CCNB2, MYC and EZH2, from the whole network. Functional enrichment analyses of DEGs were conducted to show that these hub genes were enriched in various cancer-related functions and pathways significantly. We also selected CCNB2, CDC20 and MYBL2 as core biomarkers, and further validated them in CGGA, HPA and CCLE database, suggesting that these three core hub genes may be involved in the origin of GBM. All these potential biomarkers for GBM might be helpful for illustrating the important role of molecular mechanisms of tumorigenesis in the diagnosis, prognosis and targeted therapy of GBM cancer.

Analyzing the lncRNA, miRNA, and mRNA-associated ceRNA networks to reveal potential prognostic biomarkers for glioblastoma multiforme.

BACKGROUND: Glioblastoma multiforme (GBM) is the most seriously brain tumor with extremely poor prognosis. Recent research has demonstrated that competitive endogenous RNA (ceRNA) network which long noncoding RNAs (lncRNAs) act as microRNA (miRNA) sponges to regulate mRNA expression were closely related to tumor development. However, the regulatory mechanisms and functional roles of ceRNA network in the pathogenesis of GBM are remaining poorly understood. METHODS: In this study, we systematically analyzed the expression profiles of lncRNA and mRNA (GSE51146 dataset) and miRNA (GSE65626 dataset) from GEO database. Then, we constructed a ceRNA network with the dysregulated genes by bioinformatics methods. The TCGA and GSE4290 dataset were used to confirm the expression and prognostic value of candidate mRNAs. RESULTS: In total, 3413 differentially expressed lncRNAs and mRNAs, 305 differentially expressed miRNAs were indentified in GBM samples. Then a ceRNA network containing 3 lncRNAs, 5 miRNAs, and 60 mRNAs was constructed. The overall survival analysis of TCGA databases indicated that two mRNAs (C1s and HSD3B7) were remarkly related with the prognosis of GBM. CONCLUSION: The ceRNA network may increase our understanding to the pathogenesis of GBM. In general, the candidate mRNAs from the ceRNA network can be predicted as new therapeutic targets and prognostic biomarkers for GBM.

Rapid identification of rice species by laser-induced breakdown spectroscopy combined with pattern recognition.

Laser-induced breakdown spectroscopy (LIBS) combined with pattern recognition was proposed to discriminate rice species. LIBS spectra in the range of 210-480 nm wavelength from 11 different rice species were collected and preprocessed. Principal component analysis was applied to extract the characteristic variables from LIBS spectral data. Three pattern recognition methods, discriminant analysis, radial basis function neural network, and multi-layer perceptron neural network (MLP) were performed to compare the precision in identifying rice species. The results showed that the performance of the MLP model was better. The average identification rate of rice species reached 100% and 97.9% in the training and test sets, respectively, with MLP. The highest and lowest percentages for correct identification were 100% for early indica rice, Huai rice 5, Yan japonica 6, Lian japonica 8, Xuhan 1, Lvhan 1, Sheng rice 16, Yang japonica 687, and Fenghan 30, and 77.8% for Wuyu japonica rice in test sets. The overall results demonstrate that LIBS combined with MLP could be utilized to rapidly discriminate rice species.

Identification of Huanglongbing-infected navel oranges based on laser-induced breakdown spectroscopy combined with different chemometric methods.

In order to realize rapid identification of Gannan navel oranges infected by Huanglongbing (HLB), a full optical diagnostic method of laser-induced breakdown spectroscopy (LIBS) was proposed. All navel oranges were collected from Ganzhou, Jiangxi, China, and samples contain healthy and HLB-infected navel oranges. The LIBS spectra of the plasma plume were collected directly from the epidermis of these navel oranges. The navel orange LIBS spectra in the wavelength range of 200-1050 nm were pretreated with smoothing and multiple scatter correction; on the basis of 10×10-fold cross validation, a random forest (RF) model based on continuous wavelet transform (CWT) and principal component analysis (PCA) were analyzed to identify the navel orange of HLB. The results showed that the PCA-RF and CWT-RF models coupled with suitable methods in preprocessing data can identify HLB-infected navel oranges. The average accuracy obtained from the CWT-RF model was 96.86% in the training set and 97.45% in the test set; the average accuracy by the PCA-RF model was 97.64% in the training set and 97.89% in the test set. The overall results demonstrate that LIBS combined with CWT-RF or PCA-RF, as a valuable analytical tool, could be used for HLB-infected navel orange identification.

Detection of heavy metal Cd in polluted fresh leafy vegetables by laser-induced breakdown spectroscopy.

In seeking a novel method with the ability of green analysis in monitoring toxic heavy metals residue in fresh leafy vegetables, laser-induced breakdown spectroscopy (LIBS) was applied to prove its capability in performing this work. The spectra of fresh vegetable samples polluted in the lab were collected by optimized LIBS experimental setup, and the reference concentrations of cadmium (Cd) from samples were obtained by conventional atomic absorption spectroscopy after wet digestion. The direct calibration employing intensity of single Cd line and Cd concentration exposed the weakness of this calibration method. Furthermore, the accuracy of linear calibration can be improved a little by triple Cd lines as characteristic variables, especially after the spectra were pretreated. However, it is not enough in predicting Cd in samples. Therefore, partial least-squares regression (PLSR) was utilized to enhance the robustness of quantitative analysis. The results of the PLSR model showed that the prediction accuracy of the Cd target can meet the requirement of determination in food safety. This investigation presented that LIBS is a promising and emerging method in analyzing toxic compositions in agricultural products, especially combined with suitable chemometrics.

Simultaneous analysis of Cr and Pb in contaminated pork by laser-induced breakdown spectroscopy.

Laser-induced breakdown spectroscopy (LIBS) as a rapid and green method was used to detect heavy metals Cr and Pb in pork contaminated in the lab. The laser-induced plasma was generated by a Q-switched Nd:YAG laser, and the LIBS signal was collected by a spectrometer with a charge-coupled device detector. The traditional calibration curves (CC) and multivariate partial least squares (PLS) algorithm were applied and compared to validate the accuracy in predicting the content of heavy metals in samples. The results demonstrated that the correlation coefficient of CC is poor by the classical univariate calibration method, so the univariate calibration analysis cannot effectively serve the quantitative purpose in analyzing heavy metals' residue in pork with a complex matrix. The analysis accuracy was improved effectively by the PLS method, and the correlation coefficient is 0.9894 for Cr and 0.9908 for Pb. The concentration of Cr and Pb in samples from a prediction set was obtained using the PLS calibration method, and the average relative errors for the 21 samples in the prediction set are lower than 6.53% and 7.82% for Cr and Pb, respectively. The investigated results display that the matrix effect would be reduced effectively during the quantitative analysis of pork by a LIBS-combined PLS model, and the predictive accuracy would be improved greatly compared to traditional univariate analysis.

[Study on the Enhancement Intensity of Cd in Rice with Microwave-Assisted Laser-Induced Breakdown Spectroscopy].

As food safety problem has become the focus of attention all over the world, green detection methods of the contaminants in food is in accordance with the sustainable development of environment. Heavy metal pollutant Cd element in rice was used as the object of study in this work, laser induced breakdown spectroscopy (LIBS) and microwave assisted laser induced breakdown spectroscopy (MA-LIBS) were utilized to detect the blank and laboratory polluted rice samples respectively. The characteristic line of Cd Ⅰ 228.802 nm was employed as analytical line to discuss the enhancement effect of plasmas emission intensity for the analytical line of target element. Meanwhile, the actual concentration of Cd in rice was measured by anodic stripping voltammetry. The result displayed that LIBS can just detect the plasmas signals of the sample which contained 13.69 µg·g-1 cadmium for the laboratory polluted rice samples which concentration range from 2.16 to 13.69 µg·g-1, however, in the same experimental conditions, MA-LIBS can detect the plasmas signals of Cd in all of the contaminated rice samples successfully, and compared with LIBS, the plasmas emission intensity of Cd element was enhanced from 9 to 27 times. The results showed that the plasmas emission intensity of Cd element in rice can be enhanced effectively by MA-LIBS, and the detection sensitivity can be effectively improved.

Evolution of the germline actin gene in hypotrichous ciliates: multiple nonscrambled IESs at extremely conserved locations in two urostylids.

In hypotrichous ciliates, macronuclear chromosomes are gene-sized, and micronuclear genes contain short, noncoding internal eliminated segments (IESs) as well as macronuclear-destined segments (MDSs). In the present study, we characterized the complete macronuclear gene and two to three types of micronuclear actin genes of two urostylid species, i.e. Pseudokeronopsis rubra and Uroleptopsis citrina. Our results show that (1) the gain/loss of IES happens frequently in the subclass Hypotrichia (formerly Stichotrichia), and high fragmentation of germline genes does not imply for gene scrambling; and (2) the micronuclear actin gene is scrambled in the order Sporadotrichida but nonscrambled in the orders Urostylida and Stichotrichida, indicating the independent evolution of MIC-actin gene patterns in different orders of hypotrichs; (3) locations of MDS-IES junctions of micronuclear actin gene in coding regions are conserved among closely related species.

Quantitative analysis of chromium in potatoes by laser-induced breakdown spectroscopy coupled with linear multivariate calibration.

Laser-induced breakdown spectroscopy (LIBS) coupled with the linear multivariate regression method was utilized to analyze chromium (Cr) quantitatively in potatoes. The plasma was generated using a Nd:YAG laser, and the spectra were acquired by an Andor spectrometer integrated with an ICCD detector. The models between intensity of LIBS characteristic line(s) and concentration of Cr were constructed to predict quantitatively the content of target. The unary, binary, ternary, and quaternary variables were chosen for verifying the accuracy of linear regression calibration curves. The intensity of characteristic lines Cr (CrI: 425.43, 427.48, 428.97 nm) and Ca (CaI: 422.67, 428.30, 430.25, 430.77, 431.86 nm) were used as input data for the multivariate calculations. According to the results of linear regression, the model of quaternary linear regression was established better in comparing with the other three models. A good agreement was observed between the actual content provided by atomic absorption spectrometry and the predicted value obtained by the quaternary linear regression model. And the relative error was below 5.5% for validation samples S1 and S2. The result showed that the multivariate approach can obtain better predicted accuracy than the univariate ones. The result also suggested that the LIBS technique coupled with the linear multivariate calibration method could be a great tool to predict heavy metals in farm products in a rapid manner even though samples have similar elemental compositions.

[Determination of Cu in Shell of Preserved Egg by LIBS Coupled with PLS].

In this work, the content of copper in the shell of preserved eggs were determined directly by Laser induced breakdown spectroscopy (LIBS), and the characteristics lines of Cu was obtained. The samples of eggshell were pretreated by acid wet digestion, and the real content of Cu was obtained by atomic absorption spectrophotometer (AAS). Due to the test precision and accuracy of LIBS was influenced by a serious of factors, for example, the complex matrix effect of sample, the enviro nment noise, the system noise of the instrument, the stability of laser energy and so on. And the conventional unvariate linear calibration curve between LIBS intensity and content of element of sample, such as by use of Schiebe G-Lomakin equation, can not meet the requirement of quantitative analysis. In account of that, a kind of multivariate calibration method is needed. In this work, the data of LIBS spectra were processed by partial least squares (PLS), the precision and accuracy of PLS model were compared by different smoothing treatment and five pretreatment methods. The result showed that the correlation coefficient and the accuracy of the PLS model were improved, and the root mean square error and the average relative error were reduced effectively by 11 point smoothing with Multiplicative scatter correction (MSC) pretreatment. The results of the study show that, heavy metal Cu in preserved egg shells can be direct detected accurately by laser induced breakdown spectroscopy, and the next step batch tests will been conducted to find out the relationship of heavy metal Cu content in the preserved egg between the eggshell, egg white and egg yolk. And the goal of the contents of heavy metals in the egg white, egg yolk can be knew through determinate the eggshell by the LIBS can be achieved, to provide new method for rapid non-destructive testing technology for quality and satety of agricultural products.

[Effect of Characteristic Variable Extraction on Accuracy of Cu in Navel Orange Peel by LIBS].

Heavy metals pollution in foodstuffs is more and more serious. It is impossible to satisfy the modern agricultural development by conventional chemical analysis. Laser induced breakdown spectroscopy (LIBS) is an emerging technology with the characteristic of rapid and nondestructive detection. But LIBS' s repeatability, sensitivity and accuracy has much room to improve. In this work, heavy metal Cu in Gannan Navel Orange which is the Jiangxi specialty fruit will be predicted by LIBS. Firstly, the navel orange samples were contaminated in our lab. The spectra of samples were collected by irradiating the peel by optimized LIBS parameters. The laser energy was set as 20 mJ, delay time of Spectral Data Gathering was set as 1.2 micros, the integration time of Spectral data gathering was set as 2 ms. The real concentration in samples was obtained by AAS (atom absorption spectroscopy). The characteristic variables Cu I 324.7 and Cu I 327.4 were extracted. And the calibration model was constructed between LIBS spectra and real concentration about Cu. The results show that relative error of the predicted concentrations of three relational model were 7.01% or less, reached a minimum of 0.02%, 0.01% and 0.02% respectively. The average relative errors were 2.33%, 3.10% and 26.3%. Tests showed that different characteristic variables decided different accuracy. It is very important to choose suitable characteristic variable. At the same time, this work is helpful to explore the distribution of heavy metals between pulp and peel.

[Influence of Spectral Pre-Processing on PLS Quantitative Model of Detecting Cu in Navel Orange by LIBS].

Cu in navel orange was detected rapidly by laser-induced breakdown spectroscopy (LIBS) combined with partial least squares (PLS) for quantitative analysis, then the effect on the detection accuracy of the model with different spectral data ptetreatment methods was explored. Spectral data for the 52 Gannan navel orange samples were pretreated by different data smoothing, mean centralized and standard normal variable transform. Then 319~338 nm wavelength section containing characteristic spectral lines of Cu was selected to build PLS models, the main evaluation indexes of models such as regression coefficient (r), root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were compared and analyzed. Three indicators of PLS model after 13 points smoothing and processing of the mean center were found reaching 0. 992 8, 3. 43 and 3. 4 respectively, the average relative error of prediction model is only 5. 55%, and in one word, the quality of calibration and prediction of this model are the best results. The results show that selecting the appropriate data pre-processing method, the prediction accuracy of PLS quantitative model of fruits and vegetables detected by LIBS can be improved effectively, providing a new method for fast and accurate detection of fruits and vegetables by LIBS.

[Quantitative analysis of Cu in water by collinear DP-LIBS].

The purpose of this research is to study the influence of double pulse laser induced breakdown spectroscopy (DP-LIBS) on the sensitivity of Cu in water. The water solution of Cu was tested by collinear DP-LIBS in this article. The results show that spectral intensity of Cu can be enhanced obviously by DP-LIBS, compared with single pulse laser induced breakdown spectroscopy (SP-LIBS). Besides, the experimental results were significantly impacted by delay time between laser pulse and spectrometer acquisition, delay time of double laser pulse and energy of laser pulse and so on. The paper determined the best conditions for DP-LIBS detecting Cu in water. The optimal acquisition delay time was 1 380 ns. The best laser pulse delay time was 25 ns. The most appropriate energy of double laser pulse was 100 mJ. Characteristic analysis of spectra of Cu at 324.7 and 327.4 nm was done for quantitative analysis. The detection limit was 3.5 microg x mL(-1) at 324.7 nm, and the detection limit was 4.84 microg x mL(-1) at 327.4 nm. The relative standard deviation of the two characteristic spectral lines was within 10%. The calibration curve of characteristic spectral line, established by 327.4 nm, was verified with 500 microg x mL(-1) sample. Concentration of the sample was 446 microg x mL(-1) calculated by the calibration curve. This research shows that the detection sensitivity of Cu in water can be improved by DP-LIBS. At the same time, it had high stability.

[Knockdown of interferon-γ inducible protein 30 (IFI30) inhibits the proliferation, invasion and migration of human glioma U251 cells by activating STAT1 and promotes their apoptosis].

Objective To establish U251 cells with inhibited expression of interferon-γ inducible protein 30 (IFI30), and to investigate the effect of IFI30 on cell biological function as well as its underlying mechanism. Methods Three knockdown sequences which target IFI30 were designed online and 3 small interfering RNAs (siRNA) were synthesized. After transfection, the inhibition efficiency was detected by real-time quantitative PCR. The siRNA sequence with the highest inhibition efficiency was selected to create short hairpin RNA (shRNA) plasmids. The recombinant plasmids and packaging plasmids were co-transfected into HEK293T cells to prepare lentivirus. The glioma U251 cells were transfected with lentivirus, and the positive cells were screened by puromycin. CCK-8 assay, 5-ethyl-2'-deoxyuridine (EdU) and colony formation assays were used to analyze cell proliferation; the flow cytometry was used to analyze cell cycle and apoptosis; the TranswellTM assay was used to detect cell invasion; the wound-healing assay was employed to detect cell migration, and western blot analysis to detect the protein expresison of cyclin D1, B-cell lymphoma factor 2 (Bcl2), epithelial cadherin (E-cadherin), neural cadherin (N-cadherin), signal transducer and activator of transcription 1 (STAT1). Results The sequence which effectively target IFI30 was screened and U251 cell line capable of inhibiting the IFI30 expression was successfully established. When IFI30 expression was knocked down, the proliferation of U251 cells was inhibited, along with increased ratio of cells in the phase G0/G1, the decreased phase S, the increased rate of cell apoptosis. The cell invasion and migration capabilities was also reduced. The decreased expression of cyclin D1, Bcl2 and N-cadherin were observed in U251 cells, and the expression of E-cadherin and the phosphorylation of STAT1 were found increased. Conclusion Knockdown of IFI30 inhibits the proliferation, invasion and migration of human glioma cell U251 and promotes its apoptosis by activating STAT1.

[Analysis of Cr in soil by LIBS based on conical spatial confinement of plasma].

The present study is to improve the sensitivity of detection and reduce the limit of detection in detecting heavy metal of soil by laser induced breakdown spectroscopy (LIBS). The Cr element of national standard soil was regarded as the research object. In the experiment, a conical cavity with small diameter end of 20 mm and large diameter end of 45 mm respectively was installed below the focusing lens near the experiment sample to mainly confine the signal transmitted by plasma and to some extent to confine the plasma itself in the LIBS setup. In detecting Cr I 425.44 nm, the beast delay time gained from experiment is 1.3 micros, and the relative standard deviation is below 10%. Compared with the setup of non-spatial confinement, the spectral intensity of Cr in the soil sample was enhanced more than 7%. Calibration curve was established in the Cr concentration range from 60 to 400 microg x g(-1). Under the condition of spatial confinement, the liner regression coefficient and the limit of detection were 0.997 71 and 18.85 microg x g(-1) respectively, however, the regression coefficient and the limit of detection were 0.991 22 and 36.99 microg x g(-1) without spatial confinement. So, this shows that conical spatial confinement can/improve the sensitivity of detection and enhance the spectral intensity. And it is a good auxiliary function in detecting Cr in the soil by laser induced breakdown spectroscopy.