MiRNA-506 presents multiple tumor suppressor activities by targeting EZH2 in nasopharyngeal carcinoma.

OBJECTIVE: MiR-506 has been reported to be associated with multiple malignancies, but its roles in nasopharyngeal cancer (NPC) are not fully understood. Our objective is to demonstrate its effects on NPC and the underlying mechanisms. METHODS: Totally fifteen pairs of NPC and adjacent non-tumorous tissues were collected for the detection of miR-506 and enhancer of zeste homolog 2 (EZH2) expression. Dual luciferase reporter assay was employed for verifying the relationship between miR-506 and EZH2. The flow cytometry and MTT assays were employed to explore the effects of miR-506 and EZH2 on the cell apoptosis and proliferation, respectively. Wound closure and transwell assays were used to evaluate the cell migration and invasion abilities. Western blotting or RT-qPCR assays were applied to detect the alterations of miR-506, EZH2 and epithelial-mesenchymal transition (EMT)-related markers. Morphological changes of cells with EMT were assessed by light microscopy. RESULTS: MiR-506 was significantly decreased and EZH2 was obviously increased in NPC tissues. Overexpression of miR-506 decreased the EZH2 level, promoted apoptosis, inhibited proliferation, invasion and migration of NPC cells. Accordingly, miR-506 overexpression attenuated EMT process of NPC cells as demonstrated by the alterations of EMT-related markers and the morphological changes. In addition, the luciferase assay proved that miR-506 directly targeted EZH2. Furthermore, the overexpression of EZH2 reversed the tumor-suppressive effects induced by miR-506 mimics. CONCLUSION: MiR-506 acted as a tumor suppressor to promote apoptosis and inhibit invasion and migration via directly targeting EZH2. MiR-506 can be a candidate target for gene therapy against NPC.

Two-Dimensional Excitonic Metal-Organic Framework: Design, Synthesis, Regulation, and Properties.

A family of two-dimensional (2D) Zn-based metal-organic frameworks (MOFs) with exitonic emission have been successfully synthesized under hydrothermal conditions. When isophthalic acid ligands with different substitutions are introduced, the crystal structures and fluorescence properties are significantly changed. Hirshfeld surface calculation is used to study the nuances of diverse substitutions during the construction of all of the crystals. The solid fluorescence results indicate that there are obvious two-channel emissions, including intralayer excimers and interlayer trapped excitons, both in 1 and 2 with a double-layer structure and in 3 with a single-layer structure, mainly exhibiting intralayer emission. Furthermore, the fluorescence changes on morphology transformations are explored after mechanical exfoliation consisting of grinding and ultrasonicaation of MOFs 1-3. The regulation and control of crystal structure and morphology can suppress emission based on interlayer excitons, achieving adjustment of the overall emitting color. To the best of our knowledge, this is the first report of 2D bilayer MOFs with dual-channel emissions, which provides a new structural model for synthesizing new exciton materials.

[Hyperspectral Technique for Estimating the Shelf-Lives of Fresh Spinach Leaves Covered with Film].

In order to prolong the shelf-life of fruits and vegetables, plastic films have been covered on them to improve water retention and keep external bacteria away. It is of great significance to estimate the quality of packaged fruits and vegetables accurately by predicting the shelf-life of them. In this research, hyperspectral technology combined with chemometric methods were employed to estimate the shelf-life of fresh spinach leaves in the same environment. Hyperspectral data covering the range of Vis-NIR (380～1 030 nm) and NIR (874～1 734 nm) were acquired from 300 spinach leaves (75 dishs) which were stored in 4 ℃ among 5 periods (0 d, 2 d, 4 d, 6 d, 8 d). Meanwhile, the chlorophyll contents of all spinach leaves were determined. The mean spectra of 300 spinach leaves (200 leaves in training set and 100 leaves in prediction set) were extracted. And then, principal component analysis (PCA) on the training set of 200 spectra from 5 periods of shelf-life displayed apparent cluster. Partial least-squares discriminant analysis (PLS-DA) models were established according to spectral datas and the virtual levels that we ascribed to the different storage periods previously. The total discriminant accuracy rates of prediction set were 83% (VIS-NIR) and 81% (NIR), respectively. The result indicated that the classification and prediction on the shelf-life of fresh spinach can be realized with hyperspectral technology combined with chemometric methods, which offered a theoretical guidance to evaluate the quality of packaged spinach for consumers, and provided technical supports for the development of instruments used for testing the shelf-life of fruits and vegetables in further study.

[Discriminate the Rape Sclerotinia at Early Stage Based on Confocal Raman Spectroscopy].

Oilseed rape(Brassica napus L. ) is a principal source of edible oil for human consumption and it feeds livestock as a by product with high energy and protein. However, oilseed plants often suffer from the invasion of various diseases, which could affect the yield and quality of the rapeseeds. Rape sclerotinia rot caused by the fungus sclerotinia sclerotiorum (Lib. ) de Bary may severely affect the growth of oilseed rape. Therefore, searching non-invasive detection methods of detection plant disease at early stage is crucial for monitoring growing conditions of crops. Confocal Raman spectroscopy in the region of 500～2 000 cm(-1) coupled with chemometrics methods were employed to discriminate the rape sclerotinia disease at early stage on the oilseed rape leaves. A total of 60 samples(30 healthy plant leaves and 30 infected leaves) were used to acquire the Raman spectra and wavelet transform was applied to remove the fluorescence background. Regression coefficients of the partial least squares-discriminant analysis(PLS-DA) were used to select the 8 characteristic peaks based on the whole Raman spectra. 983，1 001, 1 205, 1 521, 1 527, 1 658, 1 670 and 1 758 cm(-1) were employed to establish PLS-DA discriminate models and recognition accuracy was 100%. The results showed Raman spectra combined with chemometrics method is promising for detecting rape sclerotinia infection in the oilseed rape leaves at early stage. This study provided a theoretical reference for researching the interaction between the fungus and plants and early detecting of disease infection.

Detection of Fungus Infection on Petals of Rapeseed (Brassica napus L.) Using NIR Hyperspectral Imaging.

Infected petals are often regarded as the source for the spread of fungi Sclerotinia sclerotiorum in all growing process of rapeseed (Brassica napus L.) plants. This research aimed to detect fungal infection of rapeseed petals by applying hyperspectral imaging in the spectral region of 874-1734 nm coupled with chemometrics. Reflectance was extracted from regions of interest (ROIs) in the hyperspectral image of each sample. Firstly, principal component analysis (PCA) was applied to conduct a cluster analysis with the first several principal components (PCs). Then, two methods including X-loadings of PCA and random frog (RF) algorithm were used and compared for optimizing wavebands selection. Least squares-support vector machine (LS-SVM) methodology was employed to establish discriminative models based on the optimal and full wavebands. Finally, area under the receiver operating characteristics curve (AUC) was utilized to evaluate classification performance of these LS-SVM models. It was found that LS-SVM based on the combination of all optimal wavebands had the best performance with AUC of 0.929. These results were promising and demonstrated the potential of applying hyperspectral imaging in fungus infection detection on rapeseed petals.

[Study on the Visualization of the Biomass of Chlorella sp., Isochrysis galbana, and Spirulina sp. Based on Hyperspectral Imaging Technique].

Effective cultivation of the microalgae is the key issue for microalgal bio-energy utilization. In nutrient rich culture conditions, the microalge have a fast growth rate, but they are more susceptible to environmental pollution and influence. So to monitor the the growth process of microalgae is significant during cultivating. Hyperspectral imaging has the advantages of both spectra and image analysis. The spectra contain abundant material quality signal and the image contains abundant spatial information of the material about the chemical distribution. It can achieve the rapid information acquisition and access a large amount of data. In this paper, the authors collected the hyperspectral images of forty-five samples of Chlorella sp., Isochrysis galbana, and Spirulina sp., respectively. The average spectra of the region of interest (ROI) were extracted. After applying successive projection algorithm (SPA), the authors established the multiple linear regression (MLR) model with the spectra and corresponding biomass of 30 samples, 15 samples were used as the prediction set. For Chlorella sp., Isochrysis galbana, and Spirulina sp., the correlation coefficient of prediction (r(pre)) are 0.950, 0.969 and 0.961, the root mean square error of prediction (RMSEP) for 0.010 2, 0.010 7 and 0.007 1, respectively. Finally, the authors used the MLR model to predict biomass for each pixel in the images of prediction set; images displayed in different colors for visualization based on pseudo-color images with the help of a Matlab program. The results show that using hyperspectral imaging technique to predict the biomass of Chlorella sp. and Spirulina sp. were better, but for the Isochrysis galbana visualization needs to be further improved. This research set the basis for rapidly detecting the growth of microalgae and using the microalgae as the bio-energy.

[Study on Soil Elements Detection with Laser-Induced Breakdown Spectroscopy: A Review].

Laser-induced breakdown spectroscopy (LIBS), as a kind of atomic emission spectroscopy, has been considered to be a future new tool for chemical analysis due to its unique features, such as no need of sample preparation, stand-off or remote analysis. What's more it can achieve fast and multi-element analysis. Therefore, LIBS technology is regarded as a future "SurperStar" in the field of chemical analysis and green analytical techniques. At present, rapid and accurate detection and prevention of soil contamination (mainly in pollutants of heavy metals and organic matter) is deemed to be a concerned and serious central issue in modern agriculture and agricultural sustainable development. In this paper, the reseach achievements and trends of soil elements detection based on LIBS technology were being reviewed. The structural composition and foundmental of LIBS system is first briefly introduced. And the paper offers a review of on LIBS applications and fruits including the detection and analysis of major element, nutrient element and heavy metal element. Simultaneously, some studies on soil related metials and fields are briefly stated. The research tendency and developing prospects of LIBS in soil detection are presented at last.

Laser-Induced Breakdown Spectroscopy Coupled with Multivariate Chemometrics for Variety Discrimination of Soil.

The aim of this work was to analyze the variety of soil by laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics methods. 6 certified reference materials (CRMs) of soil samples were selected and their LIBS spectra were captured. Characteristic emission lines of main elements were identified based on the LIBS curves and corresponding contents. From the identified emission lines, LIBS spectra in 7 lines with high signal-to-noise ratio (SNR) were chosen for further analysis. Principal component analysis (PCA) was carried out using the LIBS spectra at 7 selected lines and an obvious cluster of 6 soils was observed. Soft independent modeling of class analogy (SIMCA) and least-squares support vector machine (LS-SVM) were introduced to establish discriminant models for classifying the 6 types of soils, and they offered the correct discrimination rates of 90% and 100%, respectively. Receiver operating characteristic (ROC) curve was used to evaluate the performance of models and the results demonstrated that the LS-SVM model was promising. Lastly, 8 types of soils from different places were gathered to conduct the same experiments for verifying the selected 7 emission lines and LS-SVM model. The research revealed that LIBS technology coupled with chemometrics could conduct the variety discrimination of soil.

Hyperspectral Imaging for Determining Pigment Contents in Cucumber Leaves in Response to Angular Leaf Spot Disease.

Hyperspectral imaging technique was employed to determine spatial distributions of chlorophyll (Chl), and carotenoid (Car) contents in cucumber leaves in response to angular leaf spot (ALS). Altogether, 196 hyperspectral images of cucumber leaves with five infection severities of ALS were captured by a hyperspectral imaging system in the range of 380-1,030 nm covering 512 wavebands. Mean spectrum were extracted from regions of interest (ROIs) in the hyperspectral images. Partial least square regression (PLSR) models were used to develop quantitative analysis between the spectra and the pigment contents measured by biochemical analyses. In addition, regression coefficients (RCs) in PLSR models were employed to select important wavelengths (IWs) for modelling. It was found that the PLSR models developed by the IWs provided the optimal measurement results with correlation coefficient (R) of prediction of 0.871 and 0.876 for Chl and Car contents, respectively. Finally, Chl and Car distributions in cucumber leaves with the ALS infection were mapped by applying the optimal models pixel-wise to the hyperspectral images. The results proved the feasibility of hyperspectral imaging for visualizing the pigment distributions in cucumber leaves in response to ALS.

The effect of temperature on the biodegradation properties of municipal solid waste.

The aim of this study is to analyse the effect of temperature on the biodegradation and settlement properties of municipal solid waste by using bioreactors. Three kinds of controlled temperature were performed during the biodegradation test; the variation of weight, leachate and biogas production were carefully monitored. The degradation test indicated that more leachate leaked out owing to the external compression and polymer hydrolysis reaction in the aerobic phase, which could lead to the decrease of biodegradation rate in the anaerobic phase. A proper temperature range in favour of enhancing biodegradation of refuse was obtained, which ranged from 22 °C to 45 °C. Finally, an empirical equation of biodegradation ratio was proposed, which incorporated the temperature effect. In the end, the validation of this proposed model is verified, and is proved to be reasonable for predicting degradation velocity in landfills.