Exploring the metastasis-related biomarker and carcinogenic mechanism in liver cancer based on single cell technology.

Background: Hepatocellular carcinoma (HCC) is a fatal primary malignancy characterized by high invasion and migration. We aimed to explore the underlying metastasis-related mechanism supporting the development of HCC. Methods: The dataset of single cell RNA-seq (GSE149614) were collected for cell clustering by using the Seurat R package, the FindAllMarkers function was used to find the highly expression and defined the cell cluster. The WebGestaltR package was used for the GO and KEGG function analysis of shared genes, the Gene Set Enrichment Analysis (GSVA) was performed by clusterProfiler R package, the hTFtarget database was used to identify the crucial transcription factors (TFs), the Genomics of Drug Sensitivity in Cancer (GDSC) database was used for the drug sensitivity analysis. Finally, the overexpression and trans-well assay was used for gene function analysis. Results: We obtained 9 cell clusters from the scRNA-seq data, including the nature killer (NK)/T cells, Myeloid cells, Hepatocytes, Epithelial cells, Endothelial cells, Plasma B cells, Smooth muscle cells, B cells, Liver bud hepatic cells. Further cell ecological analysis indicated that the Hepatocytes and Endothelial cell cluster were closely related to the cancer metastasis. Subsequently, the NDUFA4L2-Hepatocyte, GTSE1-Hepatocyte, ENTPD1-Endothelial and NDUFA4L2-Endothelial were defined as metastasis-supporting cell clusters, in which the NDUFA4L2-Hepatocyte cells was closely related to angiogenesis, while the NDUFA4L2-Endothelial was related with the inflammatory response and complement response. The overexpression and trans-well assay displayed that NDUFA4L2 exhibited clearly metastasis-promoting role in HCC progression. Conclusion: We identified and defined 4 metastasis-supporting cell clusters by using the single cell technology, the specify shared gene was observed and played crucial role in promoting cancer progression, our findings were expected to provide new insight in control cancer metastasis.

Exosome-derived ANXA9 functions as an oncogene in breast cancer.

Breast cancer (BCA) is one of the most prevalent cancers among women. Emerging evidence has revealed that Annexin A-9 (ANXA9) plays a crucial function in the development of some cancers. Notably, ANXA9 has been reported to be a new prognostic biomarker for gastric and colorectal cancers. However, its expression and biological function in BCA have not yet been investigated. Using online bioinformatics tools such as TIMER, GEPIA, HPA, and UALCAN, we predicted ANXA9 expression and its correlation with the clinicopathological characteristics of BCA patients. RT-qPCR and western blot were utilized to measure ANXA9 mRNA and ANXA9 protein expression in BCA patient tissues and cells. BCA-derived exosomes were identified by transmission electron microscopy. Functional assays were employed to evaluate the biological role of ANXA9 in BCA cell proliferation, migration, invasion, and apoptosis. A tumor xenograft in vivo model was utilized to assess the role of ANXA9 in tumor growth in mice. Bioinformatics and functional screening analysis revealed that ANXA9 was highly expressed in BCA patient tissues, with median ANXA9 expression 1.5- to 2-fold higher than in normal tissues (p < 0.05). RT-qPCR confirmed that ANXA9 expression in BCA tissues was around 1.5-fold higher than the adjacent normal tissues (p < 0.001). ANXA9 expression in different subtypes of BCA also showed a difference, and ANXA9 was found to be mostly significantly upregulated in luminal BCA relative to normal tissues or other histological subtypes (p < 0.001). Moreover, ANXA9 expression was elevated in different races, ages, clinical stages, node metastasis status, and menopause status groups relative to the normal group (p < 0.001). Furthermore, ANXA9 was found to be secreted by BCA tissue-derived exosomes and its expression was upregulated 1- to 7-fold in BCA cells treated with exosomes (p < 0.001), while its expression in MCF10A cells was not significantly altered by treatment with exosomes (p > 0.05). ANXA9 silencing induced a significant decrease of around 30% in the colony number of BCA cells (p < 0.01). The number of migrated and invaded BCA cells also decreased by around 65 and 68%, respectively, after silencing ANXA9 (p < 0.01). Tumor size was significantly reduced (nearly half) in the LV-sh-ANXA9 group relative to the LV-NC group in the xenograft model (p < 0.01), suggesting that ANXA9 silencing repressed tumor progression in BCA progression in vitro and in vivo. In conclusion, exosome-derived ANXA9 functions as an oncogene that facilitates the proliferation, migration, and invasiveness of BCA cells and enhances tumor growth in BCA development, which may provide a new prognostic and therapeutic biomarker for BCA patients.

Associations of Two Common Polymorphisms in MTHFR Gene with Blood Lipids and Therapeutic Efficacy of Simvastatin.

BACKGROUND: Cardio-cerebrovascular disease is an important public health challenge worldwide, and its complex etiology has not been elucidated fully. The study investigated the relationship between two common polymorphisms, C677T and A1298C in the methylenetetrahydrofolate reductase (MTHFR) gene, baseline lipids and the lipid-lowering efficacy of simvastatin in a Chinese hyperlipidemic population. METHODS: All participants were recruited from Anhui, China. By the extreme sampling method, we selected subjects with a low response (n=108) and high response (n=106) based on their adjusted lipid-lowering response to simvastatin administrated for 8 consecutive weeks. Both MTHFR C677T and A1298C loci were genotyped by the MALDI-TOF MS platform. Serum triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels were measured at baseline and after 8 weeks of oral 20 mg/d tablets of simvastatin. RESULTS: Patients with the 677TT genotype had significantly higher baseline TC, HDL-C, and change in HDL-C (ΔHDL-C) levels after treatment than those with 677CC+CT genotypes (ß = 0.207, P = 0.045; ß = 0.182, P = 0.026; and ß = 0.16, P = 0.002, respectively). Patients with 1298AC+CC genotypes had significantly higher baseline LDL-C and change in LDL-C (ΔLDL-C) levels (ß = 0.276, P =0.043; ß = 0.359, P = 0.025, respectively) than those with 1298AA genotype. We found statistical interactions between the two SNPs in association with baseline HDL-C (P for interaction = 0.034), TC (P for interaction = 0.069), and TG (P for interaction = 0.034). Baseline TC (P = 0.027) and HDL-C (P = 0.046) and change in HDL-C (P = 0.019) were different among those with the MTHFR A-T haplotype compared with A-C. CONCLUSION: Our major findings suggest that both MTHFR C677T and A1298C polymorphisms could be important genetic determinants of lipid traits and drug efficacy of simvastatin. This will contribute to a better understanding of strategies for personalized medication in Chinese patients with dyslipidemia.

Fast online evaluation of vegetable freshness using single turnover chlorophyll fluorescence.

Vegetable freshness evaluation is of great significance to ensure the quality of vegetables and realize fine production. Existing vegetable freshness evaluation methods have difficulty realizing rapid online evaluation and industrial applications due to such disadvantages as being susceptible to subjective factors, complicated operation, large computation, and high hardware cost. To solve the above problems, a rapid online vegetable freshness evaluation method was developed based on the single turnover chlorophyll fluorescence parameters Fo', Fv'/Fm' and σPSII'. A freshness evaluation model for spinach and swamp cabbage was established based on a classification and regression tree algorithm, using Fo', Fv'/Fm' and σPSII' as sample features. The model divided the freshness of spinach and swamp cabbage into three grades: good, medium, and poor, and the leave-one-out cross validation results showed that the freshness evaluation accuracies of spinach and swamp cabbage reached 98.1% and 94.3%, respectively.

Quantitative analysis of pH value in soil using laser-induced breakdown spectroscopy coupled with a multivariate regression method.

The quantitative analyses of pH value in soil have been performed using laser-induced breakdown spectroscopy (LIBS) technology. The aim of this work was to obtain a reliable and accurate method for rapid detection of pH value in soil. Seventy-four samples were used as a calibration set, and 24 samples were used as a prediction set. To eliminate the matrix effect, the multivariate models of partial least-squares regression (PLSR) and least-squares support vector regression (LS-SVR) were used to construct the models. The intensities of nine emission lines of C, Ca, Na, O, H, Mg, Al, and Fe elements were used to fit the models. For the PLSR model, the correlation coefficient was 0.897 and 0.906 for the calibration and prediction set, respectively. Furthermore, the analysis accuracy was improved effectively by the LS-SVR method, and the correlation coefficients for calibration and prediction set were improved to 0.991 and 0.987. The prediction mean absolute error was pH 0.1 units, and the root mean square error of the prediction was only 0.079. The results indicated that the LIBS technique coupled with LS-SVR could be a reliable and accurate method for determining pH value in soil.

Univariate and multivariate analyses of strontium and vanadium in soil by laser-induced breakdown spectroscopy.

Univariate and multivariate analyses of strontium (Sr) and vanadium (V) elements in soil have been performed using laser-induced breakdown spectroscopy technology. Thirty-three samples were used as a calibration set, and 11 samples were used as a prediction set. The results demonstrated that the correlation coefficients of the calibration curves method were poor due to the matrix effect. Then, the multivariate models of partial least-squares regression and least squares support vector regression (LS-SVR) were used to construct models. The analysis accuracy was improved effectively by the LS-SVR method, and the correlation coefficient is 0.999 for Sr and 0.983 for V. The average relative errors for the prediction set are lower than 7.45% and 2.88% for Sr and V, respectively. The results indicated that the LIBS technique coupled with LS-SVR could be a reliable and accurate method in the quantitative determination of elemental Sr and V in complex matrices like soil.

Quantitative Analysis of Elements in Fertilizer Using Laser-Induced Breakdown Spectroscopy Coupled with Support Vector Regression Model.

The rapid detection of the elements nitrogen (N), phosphorus (P), and potassium (K) is beneficial to the control of the compound fertilizer production process, and it is of great significance in the fertilizer industry. The aim of this work was to compare the detection ability of laser-induced breakdown spectroscopy (LIBS) coupled with support vector regression (SVR) and obtain an accurate and reliable method for the rapid detection of all three elements. A total of 58 fertilizer samples were provided by Anhui Huilong Group. The collection of samples was divided into a calibration set (43 samples) and a prediction set (15 samples) by the Kennard-Stone (KS) method. Four different parameter optimization methods were used to construct the SVR calibration models by element concentration and the intensity of characteristic line variables, namely the traditional grid search method (GSM), genetic algorithm (GA), particle swarm optimization (PSO), and least squares (LS). The training time, determination coefficient, and the root-mean-square error for all parameter optimization methods were analyzed. The results indicated that the LIBS technique coupled with the least squares-support vector regression (LS-SVR) method could be a reliable and accurate method in the quantitative determination of N, P, and K elements in complex matrix like compound fertilizers.

Predictive value of positron emission tomography for the prognosis of molecularly targeted therapy in solid tumors.

OBJECTIVE: This study aimed at comprehensively exploring the value applying positron emission tomography (PET) to predict the effect of molecularly targeted therapy in solid tumors. MATERIALS AND METHODS: A systematic search was performed for potentially relevant studies from the time of inception to February 2017. The primary endpoints were progression-free survival (PFS), overall survival (OS), and time to progression (TTP). The results were analyzed by Review Manager version 5.3 (RevMan 5.3) statistical software. Subgroup analyses were implemented based on the type of molecularly targeted agents (monoclonal antibodies arm and small molecular targeted agents arm), mechanism (erlotinib/gefitinib arm and bevacizumab arm), radioactive tracers, type of tumor, and reevaluated PET timing. RESULTS: Twenty-six studies incorporating 865 individuals were eligible. Compared with PET nonresponse group, PET response group displayed a decrease in maximal standard uptake value (SUVmax), which was associated with a significantly prolonged PFS (HR =0.41, 95% CI [0.29, 0.59]; P<0.00001), OS (HR =0.52, 95% CI [0.40, 0.67]; P<0.00001), and TTP (HR =0.30, 95% CI [0.14, 0.66]; P=0.003). Similar results were obtained in the subgroup analyses of PFS in erlotinib/gefitinib arm and small molecular targeted agents arm; and OS in lung cancer arm, erlotinib/gefitinib arm, bevacizumab arm, small molecular targeted agents arm, monoclonal antibodies arm, 18F-fluorodeoxythymidine (18F-FLT) arm, 18F-fluorodeoxyglucose (18F-FDG) arm, and early PET timing arm. CONCLUSION: Our study demonstrated that PET was a favorable approach to predict the prognosis of molecularly targeted therapy for solid tumors. PET assessment within 2 weeks could be useful to predict clinical outcome.

Accurate and rapid detection of soil and fertilizer properties based on visible/near-infrared spectroscopy.

Accurate information of soil macronutrient contents and fertilizer macronutrient contents is the precondition of precision fertilization; however, how to detect soil and fertilizer information rapidly, reliably, and inexpensively remains a great challenge. Visible and near-infrared (VIS/NIR) diffuse reflectance spectroscopy proves to be an effective tool for extensive investigation of soil and fertilizer properties. This study first collected many soil and chemical fertilizer samples and performed both spectral scanning and chemical analysis. During the correlation between the collected VIS/NIR spectra and the measured data, different spectral pretreatment, sample selection, and wavelength optimization methods were applied for improving the accuracy and robustness of the prediction models. After appropriate spectral processing and selection of representative samples, both principal component regression and genetic algorithm (GA) can adequately reduce the number of variables and pick out the characteristic variables, which not only enhanced prediction speed but also greatly improved prediction accuracy. In particular, using GA-based models, organic matter content (OMC), total N and pH value in soil and N, P, and K contents in fertilizer can all be accurately predicted.

[Study on the automatic recognition method of elemental spectra in laser induced breakdown spetroscopy].

According to the spectral line broadening mechanism of laser induced breakdown spectroscopy, the emission lines from the standard spectral database of NIST were simulated, and they were compared with the spectral data of experiment. In the process of comparison similarity measure was used to measure the similarity between the simulative spectra and the experimental spectra. The automatic recognition method of elemental spectra was studied, and the spectral data of soil between 340 and 345 nm was recognized by computing the proportional coefficients of the spectral lines. Using principle of nonlinear least squares, the recognition process was completed. The feasibility and the advantage of the method were proved by the results of experiment.

[Study on measurement of trace heavy metal Ni in water by laser induced breakdown spectroscopy technique].

The spectroscopy emission characteristics and the detection limit of trace heavy metal nickel in water was studied based on laser induced breakdown spectroscopy technique, with a 1,064 nm wavelength Nd : YAG laser as excitation source, and the echelle spectrometer and ICCD detector were used for spectral separation and high sensitive detection with high resolution and wide spectral range. A round flat solid state graphite as matrix was used for element enrichment for reducing water splashing, extending the plasma lifetime and improving the detection sensitivity, and the experimental sample was prepared by titrating a fixed volume of nickel nitrate solution of different concentrations on a fixed area of the graphite matrix. The results show that the better detection delay time is about 700 ns, the spectrum intensity raises with the concentration increase, a good linear relationship is presented at low concentration with a correlation coefficient 0.996 1, and the lower limit of detection of nickel in water with 0.28 mg x L(-1) was retrieved. A measurement method for further study of trace heavy metals in water is provided with laser induced breakdown spectroscopy technique.

[Study on the automatic extraction method of spectral data features in laser induced breakdown spectroscopy].

According to that the spectral line broadening of laser induced breakdown spectroscopy (LIBS) was lorentz nonlinear function model, using Levenberg-Marquardt (L-M) agorithm to optimally estimate the undetermined parameter in the function, the continuum background radiation and peak position and peak intensity were corrected, and the method of data points automatic extraction for fitting was analysed. Automatic fitting and feature parameter extraction for spectral data of LIBS based on L-M algorithm that was hybrid programming with matrixVB and VB were accomplished,and the result was compared with the origin 7.5 data analysis software which was manual and commonly used and verified its stability and reliability.

[Influence of humidity on characteristic of laser-induced soil plasmas].

The soil samples at six different humidities were prepared for studying the influence of soil humidity on laser-induced plasmas. By analyzing the characteristic spectral lines of Pb with the wavelength of 405.78 nm, it was demonstrated that the intensities of spectral line, SNR and RSD are linearly inversely proportional to the soil humidity. Under the approximation of local thermal equilibrium, by analyzing the characteristic spectral lines of Fe within the wavelength range of 400 to 440 nm, the temperature of plasmas was obtained by means of the two-dimensional Boltzmann plane. The experimental results show that the plasma temperature monotonously changes from 11 800 to 7 800 K and the electron density monotonously changes from 3.3 x 10(6) cm(-3) to 2.8 x 10(6) cm(-3), when the humidity increases from 0 to 20%.

[Measurement and analysis of copper in soil using laser-induced breakdown spectroscopy].

The present paper analyzed the characteristics of laser-induced breakdown spectroscopy (LIBS) of metal element Cu in soil using the Nd:YAG (wavelength: 1064 nm) laser as the excitation source, where the spectral signals were detected by the highly resolved and wide spectral echelle spectrograph and intensified charge coupled device (ICCD). The time evolution of the characteristic spectral line of Cu was obtained by changing the delay time of ICCD at the same concentration and the gate of ICCD with wavelength of 329. 396 nm of Cu as the characteristic spectral line, from which the best delay time 1.1 micros was found. By measuring the intensities of the characteristic spectral line with different Cu concentrations, it was demonstrated that the intensities of the spectral line increased with the concentration of Cu under the condition of low concentration From the results the LIBS calibration curve of Cu was obtained, and by fitting calculation the detection limit of Cu in soil at 13. 36 microg x g(-1) was obtained.

[Thrombolysis of rabbit's pulmonary embolism with thrombus-targeted urokinase immune liposome].

OBJECTIVE: To develop thrombus-targeted urokinase immune liposome through incorporating D-dimer monoclonal antibody (DDmAb) to liposome and observe the thrombolytic efficiency in a rabbit pulmonary thromboembolism (PE) model. METHODS: Reverse-phase evaporation method was used to develop targeted urokinase immune liposome by coupling DDmAb to urokinase liposome (liposomal-encapsulated urokinase) with glutaraldehyde. The PE models were induced by injecting 4 autologous emboli (2 mm x 5 mm) through jugular vein catheter into pulmonary arteries. New Zealand white rabbits (n = 32) were randomized into four groups: A group (TBS), B group (150 000 IU/kg UK), C group (30 000 IU/kg urokinase liposome) and D group (30 000 IU/kg urokinase immune liposome). The right ventricular pressure and the emboli size in pulmonary arteries were determined. RESULTS: The right ventricular pressure increased significantly in PE rabbits (P < 0.01), the average value is (6.75 +/- 6.82) mm Hg (1 mm Hg = 0.133 kPa). Eighty minutes post various treatments, right ventricular pressure remained unchanged as post PE in group A [(40.15 +/- 11.22) mm Hg vs. (41.67 +/- 14.23) mm Hg], decreased to baseline level in group B and D [(34.71 +/- 8.67) mm Hg vs. (33.98 +/- 9.32) mm Hg, (30.65 +/- 6.67) mm Hg vs. (30.77 +/- 6.85) mm Hg, all P > 0.05], decreased but not returned to normal value in group C. Residual emboli size remained unchanged in group A and partly reduced in group C and more significantly reduced in group B and D. Hemorrhage of heart, kidney and liver was evidenced in group A but not in other groups. CONCLUSION: Acute PE could be successfully treated by the thrombus-targeted urokinase immune liposome with D-dimer monoclonal antibody.