Clonal integration of stress signal induces morphological and physiological response of root within clonal network.

Clonal integration of defense or stress signal induced systemic resistance in leaf of interconnected ramets. However, similar effects of stress signal in root are poorly understood within clonal network. Clonal fragments of Centella asiaticas with first-young, second-mature, third-old and fourth-oldest ramets were used to investigate transportation or sharing of stress signal among interconnected ramets suffering from low water availability. Compared with control, oxidative stress in root of the first-young, second-mature and third-old ramets was significantly alleviated by exogenous ABA application to the fourth-oldest ramets as well as enhancement of antioxidant enzyme (SOD, POD, CAT and APX) activities and osmoregulation ability. Surface area and volume in root of the first-young ramets were significantly increased and total length in root of the third-old ramets was significantly decreased. POD activity in root of the fourth-oldest and third-old ramets was significantly enhanced by exogenous ABA application to the first-young ramets. Meanwhile, total length and surface area in root of the fourth-oldest and third-old ramets were significantly decreased. Ratio of belowground to aboveground biomass in the whole clonal fragments was significantly increased by exogenous ABA application to the fourth-oldest or first-young ramets. It is suggested that transportation or sharing of stress signal may induce systemic resistance in root of interconnected ramets. Specially, transportation or sharing of stress signal against phloem flow was observed in the experiment. Possible explanation is that rapid recovery of foliar photosynthesis in first-young ramets subjected to exogenous ABA application can partially reverse phloem flow within clonal network. Thus, our experiment provides insight into ecological implication on clonal integration of stress signal.

Global, regional, and national burden of kidney dysfunction from 1990 to 2019: a systematic analysis from the global burden of disease study 2019.

OBJECTIVE: We aim to explore the prevalence and temporal trends of the burden of kidney dysfunction (KD) in global, regional and national level, since a lack of related studies. DESIGN: Cross-sectional study. MATERIALS: The data of this research was obtained from Global Burden of Diseases Study 2019. The estimation of the prevalence, which was measured by the summary exposure value (SEV), and attributable burden of KD was performed by DisMod-MR 2.1, a Bayesian meta-regression tool. The Spearman rank order correlation method was adopted to perform correlation analysis. The temporal trends were represented by the estimated annual percentage change (EAPC). RESULTS: In 2019, there were total 3.16 million deaths and 76.5 million disability-adjusted life years (DALYs) attributable to KD, increased by 101.1% and 81.7% compared with that in 1990, respectively. From 1990 to 2019, the prevalence of KD has increased in worldwide, but decreased in High-income Asia Pacific. Nearly 48.5% of countries globally, such as South Africa, Egypt and Mexico had increased mortality rates of KD from 1990 to 2019 while 44.6% for disability rate. Countries with lower socio-demographic index (SDI) are facing a higher prevalence as well as mortality and disability rate compared with those with higher SDI. Compared with females, the prevalence of KD was lower in males, however the attributable mortality and disability rate were higher in all years from 1990 to 2019. CONCLUSION: With the progress of senescent, we will face more severe challenges of reducing the prevalence and attributable burden of KD, especially in regions with lower SDI. Effective measures are urgently required to alleviate the prevalence and burden of KD.

Collagen I-DDR1 signaling promotes hepatocellular carcinoma cell stemness via Hippo signaling repression.

Cancer stem cells (CSCs) are a minority population of cancer cells with stemness and multiple differentiation potentials, leading to cancer progression and therapeutic resistance. However, the concrete mechanism of CSCs in hepatocellular carcinoma (HCC) remains obscure. We found that in advanced HCC tissues, collagen I was upregulated, which is consistent with the expression of its receptor DDR1. Accordingly, high collagen I levels accompanied by high DDR1 expression are associated with poor prognoses in patients with HCC. Collagen I-induced DDR1 activation enhanced HCC cell stemness in vitro and in vivo. Mechanistically, DDR1 interacts with CD44, which acts as a co-receptor that amplifies collagen I-induced DDR1 signaling, and collagen I-DDR1 signaling antagonized Hippo signaling by facilitating the recruitment of PP2AA to MST1, leading to exaggerated YAP activation. The combined inhibition of DDR1 and YAP synergistically abrogated HCC cell stemness in vitro and tumorigenesis in vivo. A radiomic model based on T2 weighted images can noninvasively predict collagen I expression. These findings reveal the molecular basis of collagen I-DDR1 signaling inhibiting Hippo signaling and highlight the role of CD44/DDR1/YAP axis in promoting cancer cell stemness, suggesting that DDR1 and YAP may serve as novel prognostic biomarkers and therapeutic targets in HCC.

Effects of nutrient supply on leaf stoichiometry and relative growth rate of three stoloniferous alien plants.

Different nutrient supply brings about changes in leaf stoichiometry, which may affect growth rate and primary production of plants. Invasion of alien plants is a severe threat to biodiversity and ecosystem worldwide. A pot experiment was conducted by using three stoloniferous alien plants Wedelia trilobata, Alternanther philoxeroides and Hydrocotyle vulgaris to investigate effects of nutrient supply on their leaf stoichiometry and relative growth rate. Different nitrogen or phosphorus supply was applied in the experiment (N1:1 mmol L-1, N2:4 mmol L-1, and N3:8 mmol L-1, P1:0.15 mmol L-1, P2:0.6 mmol L-1 and P3:1.2 mmol L-1). Nitrogen and phosphorus concentrations in leaves of the three alien plants significantly increased with increase of nitrogen supply. With increase of phosphorus supply, nitrogen or phosphorus concentration of leaf was complex among the three alien plants. N:P ratio in leaf of the three alien plants subjected to different levels of nutrient supply was various. A positive correlation between relative growth rate and N:P ratio of the leaf is observed in W. trilobata and A. philoxeroides suffering from N-limitation. A similar pattern was not observed in Hydrocotyle vulgaris. We tentatively concluded that correlations between relative growth rate and N: P ratio of the leaf could be affected by species as well as nutrient supply. It is suggested that human activities, invasive history, local abundance of species et al maybe play an important role in the invasion of alien plants as well as relative growth rate.

Comprehensive Analysis of the Effect of 20(R)-Ginsenoside Rg3 on Stroke Recovery in Rats via the Integrative miRNA-mRNA Regulatory Network.

MicroRNAs (miRNAs) are a class of small, endogenous, noncoding RNAs. Recent research has proven that miRNAs play an essential role in the occurrence and development of ischemic stroke. Our previous studies confirmed that 20(R)-ginsenosideRg3 [20(R)-Rg3] exerts beneficial effects on cerebral ischemia-reperfusion injury (CIRI), but its molecular mechanism has not been elucidated. In this study, we used high-throughput sequencing to investigate the differentially expressed miRNA and mRNA expression profiles of 20(R)-Rg3 preconditioning to ameliorate CIRI injury in rats and to reveal its potential neuroprotective molecular mechanism. The results show that 20(R)-Rg3 alleviated neurobehavioral dysfunction in MCAO/R-treated rats. Among these mRNAs, 953 mRNAs were significantly upregulated and 2602 mRNAs were downregulated in the model group versus the sham group, whereas 437 mRNAs were significantly upregulated and 35 mRNAs were downregulated in the 20(R)-Rg3 group in contrast with those in the model group. Meanwhile, the expression profile of the miRNAs showed that a total of 283 differentially expressed miRNAs were identified, of which 142 miRNAs were significantly upregulated and 141 miRNAs were downregulated in the model group compared with the sham group, whereas 34 miRNAs were differentially expressed in the 20(R)-Rg3 treatment group compared with the model group, with 28 miRNAs being significantly upregulated and six miRNAs being significantly downregulated. Furthermore, 415 (391 upregulated and 24 downregulated) differentially expressed mRNAs and 22 (17 upregulated and 5 downregulated) differentially expressed miRNAs were identified to be related to 20(R)-Rg3's neuroprotective effect on stroke recovery. The Kyoto Encyclopedia of Genes and Genomes (KEGG) results showed that 20(R)-Rg3 could modulate multiple signaling pathways related to these differential miRNAs, such as the cGMP-PKG, cAMP and MAPK signaling pathways. This study provides new insights into the protective mechanism of 20(R)-Rg3 against CIRI, and the mechanism may be partly associated with the regulation of brain miRNA expression and its target signaling pathways.

miR­378a­3p inhibits cellular proliferation and migration in glioblastoma multiforme by targeting tetraspanin 17.

Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor and patients with this disease tend to have poor clinical outcome. MicroRNAs (miRs) are important regulators of a number of key pathways implicated in tumor pathogenesis. Recently, the expression of miR­378 was shown to be dysregulated in several different types of cancer, including gastric cancer, colorectal cancer and oral carcinoma. Additional studies have demonstrated that miR­378 may serve as a potential therapeutic target against human breast cancer. However, the underlying mechanisms and potential targets of miR­378a­3p involved in GBM remain unknown. The aim of the present of was to determine the effects of miR­378a­3p and its potential targets. Tetraspanin 17 (TSPAN17) is involved in the neoplastic events in GBM and is a member of the tetraspanin family of proteins. The tetraspanins are involved in the regulation of cell growth, migration and invasion of several different types of cancer cell lines, and may potentially act as an oncogene associated with GBM pathology. The results of the present study showed that high miR­378a­3p and low TSPAN17 expression levels were associated with improved survival in patients with GBM. Additionally, high levels of TSPAN17 were linked to the poor prognosis of patients with GBM aged 50­60, larger tumor sizes (≥5 cm) and an advanced World Health Organization stage. TSPAN17 was identified and confirmed as a direct target of miR­378a­3p using a luciferase reporter assay in human glioma cell lines. Overexpression of miR­378a­3p in either of U87MG or MT­330 cells decreased the expression of TSPAN17, promoted apoptosis and decreased proliferation, migration and invasion. Overexpression of TSPAN17 attenuated the aforementioned effects induced by miR­378a­3p overexpression. The present study indicated that miR­378a­3p suppresses the progression of GBM by reducing TSPAN17 expression, and may thus serve as a potential therapeutic target for treating patients with GBM.

Combination of Droplet Extraction and Pico-ESI-MS Allows the Identification of Metabolites from Single Cancer Cells.

We have combined droplet extraction and a pulsed direct current electrospray ionization mass spectrometry method (Pico-ESI-MS) to obtain information-rich metabolite profiling from single cells. We studied normal human astrocyte cells and glioblastoma cancer cells. Over 600 tandem mass spectra (MS2) of metabolites from a single cell were recorded, allowing the successful identification of more than 300 phospholipids. We found the ratios of unsaturated phosphatidylcholines (PCs) to saturated PCs were significantly higher in glioblastoma cells compared to normal cells. In addition, both isomeric PC (17:1) and (phosphatidylethanolamine) PE (20:1) were found in glioblastoma cells, whereas only PC (17:1) was observed in astrocyte cells. Our method paves the way to characterize the chemical contents of single cells, providing rich metabolome information. We suggest that this technique is general and can be applied to other life science studies such as differentiation and drug resistance of individual cells.

Integrated Droplet-Based Microextraction with ESI-MS for Removal of Matrix Interference in Single-Cell Analysis.

Integrating droplet-based microfluidics with mass spectrometry is essential to high-throughput and multiple analysis of single cells. Nevertheless, matrix effects such as the interference of culture medium and intracellular components influence the sensitivity and the accuracy of results in single-cell analysis. To resolve this problem, we developed a method that integrated droplet-based microextraction with single-cell mass spectrometry. Specific extraction solvent was used to selectively obtain intracellular components of interest and remove interference of other components. Using this method, UDP-Glc-NAc, GSH, GSSG, AMP, ADP and ATP were successfully detected in single MCF-7 cells. We also applied the method to study the change of unicellular metabolites in the biological process of dysfunctional oxidative phosphorylation. The method could not only realize matrix-free, selective and sensitive detection of metabolites in single cells, but also have the capability for reliable and high-throughput single-cell analysis.

[Research on fast detecting tomato seedlings nitrogen content based on NIR characteristic spectrum selection].

In order to improve the accuracy and robustness of detecting tomato seedlings nitrogen content based on near-infrared spectroscopy (NIR), 4 kinds of characteristic spectrum selecting methods were studied in the present paper, i. e. competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variables elimination (MCUVE), backward interval partial least squares (BiPLS) and synergy interval partial least squares (SiPLS). There were totally 60 tomato seedlings cultivated at 10 different nitrogen-treatment levels (urea concentration from 0 to 120 mg . L-1), with 6 samples at each nitrogen-treatment level. They are in different degrees of over nitrogen, moderate nitrogen, lack of nitrogen and no nitrogen status. Each sample leaves were collected to scan near-infrared spectroscopy from 12 500 to 3 600 cm-1. The quantitative models based on the above 4 methods were established. According to the experimental result, the calibration model based on CARS and MCUVE selecting methods show better performance than those based on BiPLS and SiPLS selecting methods, but their prediction ability is much lower than that of the latter. Among them, the model built by BiPLS has the best prediction performance. The correlation coefficient (r), root mean square error of prediction (RMSEP) and ratio of performance to standard derivate (RPD) is 0. 952 7, 0. 118 3 and 3. 291, respectively. Therefore, NIR technology combined with characteristic spectrum selecting methods can improve the model performance. But the characteristic spectrum selecting methods are not universal. For the built model based or single wavelength variables selection is more sensitive, it is more suitable for the uniform object. While the anti-interference ability of the model built based on wavelength interval selection is much stronger, it is more suitable for the uneven and poor reproducibility object. Therefore, the characteristic spectrum selection will only play a better role in building model, combined with the consideration of sample state and the model indexes.

[Research on development and experiment of NIR wheat quality quick detection system].

In order to detect wheat quality rapidly and nondestructively, NIR wheat quality quick detection system was developed on the base of grating technology. To test accuracy, repeatability and stability of this self-made system, Bruker MPA spectroscopy was selected as target analyzer and 56 wheat samples were analyzed by building and validating PLS calibration models. In the 4 models of the self-made system, the coefficient of determination R2 is 92.38%, 93.48%, 93.16% and 94.44%; root mean square error of cross validation RMSECV = 0.405, 0.374, 0.383, 0.346; ratio of performance to standard deviate RPD = 3.62, 3.39, 3.82, 4.24, respectively. And evaluating indicators of validating results in the 4 models are as follows: R2 = 96.97%, 94.22%, 96.62% and 96.34%; Root mean square error of prediction RMSEP = 0.221, 0.305, 0.233 and 0.243 respectively. The model of MPA spectroscopy gave an R2 of 95.99%, a RMSECV of 0.293, RPD of 5 and validation results are R2 of 98.31%, RMSEP of 0.165, respectively. The results show that the models of self-made instrument have good prediction performance, stability and repeatability, and wavelength and absorbance of the obtained spectra have a good repeatability. The prediction effect of single spectrum is not ideal, but it can be improved by using average spectrum of repeated acquisition. NIR wheat quality quick detection system can detect wheat quality with good performance.

[Study on quality detection of milk powder based on near infrared spectroscopy (NIR)].

The traditional NIR model was usually built according to various parameters of an individual type of milk powder so that it's really time-consuming. To simplify the application of NIR in real-time quality detection of milk powder, it was proposed in the present paper to build NIR models for a sample set composed of different types of milk powder. With 70 samples provided by one manufacturer, 6 NIR models including acidity, fat, lactose, sucrose, protein and ash, were built by optimizing algorithms. The results indicated that these NIR models except the acidity model have good stability and high prediction ability (RSD<10%, RPD>3).

[Spectrum analysis of crop and weeds at seedling].

The infestation information on field weeds is the basis of variable spraying herbicides. It was found that the method using the spectral characteristics of plant is superior in real-time respect. The Fourier transform infrared spectrum technique was applied to measure the reflectance of wheat and weeds in the range from 700 to 1100 nm. The discrimination analysis was done using the SPSS software. Firstly, the source spectrum data were compressed and normalized. Secondly, the characteristic wavelengths were selected by using stepwise method. Thirdly, the discrimination model was set up to use the selected wavelengths as the variables for detecting wheat and weeds. It was shown by the result of discrimination analysis that the correct classification rate of wheat and weeds detection with the selected wavelength points achieved 97%. In addition, the selected wavelength points were marked in the "red edge" of reflectance within some range, and the rate of correct classification increased with the increase in the numbers of the selected wavelength points. According to the selected wavelength points, the proper filters were chosen to perform the multi-spectral images captured and processed with the machine vision system.