An analysis of neurovascular disease markers in the hippocampus of Tupaia chinensis at different growth stages

IntroductionIt is considered that Tupaia chinensis can replace laboratory primates in the study of nervous system diseases. To date, however, protein expression in the brain of Tupaia chinensis has not been fully understood.MethodThree age groups of T. chinensis-15 days, 3 months and 1.5 years—were selected to study their hippocampal protein expression profiles.ResultsA significant difference was observed between the 15-day group and the other two age groups, where as there were no significant differences between the 3-month and 1.5-year age groups. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that differentially expressed proteins could be enriched in several pathways related to neurovascular diseases, such as metabolic pathways for Alzheimer's disease (AD), Huntington's disease, Parkinson's disease, and other diseases. The KEGG enrichment also showed that relevant protein involved in oxidative phosphorylation in the hippocampus of T. chinensis for 15days were downregulated, and ribosomal proteins (RPs) were upregulated, compared to those in the hippocampus of the other two age groups.DiscussionIt was suggested that when the hippocampus of T. chinensis developed from day 15 to 3 months, the expression of oxidatively phosphorylated proteins and RPs would vary over time. Meanwhile, the hippocamppal protein expression profile of T. chinensis after 3 months had become stable. Moreover, the study underlines that, during the early development of the hippocampus of T. chinensis, energy demand increases while protein synthesis decreases. The mitochondria of T. chinensis changes with age, and the oxidative phosphorylation metabolic pathway of mitochondria is closely related to neurovascular diseases, such as stroke and cerebral ischemia

Evaluation of Machine Learning Approaches to Predict Soil Organic Matter and pH Using vis-NIR Spectra

Soil organic matter (SOM) and pH are essential soil fertility indictors of paddy soil in the middle-lower Yangtze Plain. Rapid, non-destructive and accurate determination of SOM and pH is vital to preventing soil degradation caused by inappropriate land management practices. Visible-near infrared (vis-NIR) spectroscopy with multivariate calibration can be used to effectively estimate soil properties. In this study, 523 soil samples were collected from paddy fields in the Yangtze Plain, China. Four machine learning approaches—partial least squares regression (PLSR), least squares-support vector machines (LS-SVM), extreme learning machines (ELM) and the Cubist regression model (Cubist)—were used to compare the prediction accuracy based on vis-NIR full bands and bands reduced using the genetic algorithm (GA). The coefficient of determination (R2), root mean square error (RMSE), and ratio of performance to inter-quartile distance (RPIQ) were used to assess the prediction accuracy. The ELM with GA reduced bands was the best model for SOM (SOM: R2 = 0.81, RMSE = 5.17, RPIQ = 2.87) and pH (R2 = 0.76, RMSE = 0.43, RPIQ = 2.15). The performance of the LS-SVM for pH prediction did not differ significantly between the model with GA (R2 = 0.75, RMSE = 0.44, RPIQ = 2.08) and without GA (R2 = 0.74, RMSE = 0.45, RPIQ = 2.07). Although a slight increase was observed when ELM were used for prediction of SOM and pH using reduced bands (SOM: R2 = 0.81, RMSE = 5.17, RPIQ = 2.87; pH: R2 = 0.76, RMSE = 0.43, RPIQ = 2.15) compared with full bands (R2 = 0.81, RMSE = 5.18, RPIQ = 2.83; pH: R2 = 0.76, RMSE = 0.45, RPIQ = 2.07), the number of wavelengths was greatly reduced (SOM: 201 to 44; pH: 201 to 32). Thus, the ELM coupled with reduced bands by GA is recommended for prediction of properties of paddy soil (SOM and pH) in the middle-lower Yangtze Plain

Potential of VIS-NIR-SWIR Spectroscopy from the Chinese Soil Spectral Library for Assessment of Nitrogen Fertilization Rates in the Paddy-Rice Region, China

To meet growing food demand with limited land and reduced environmental impact, soil testing and formulated fertilization methods have been widely adopted around the world. However, conventional technology for investigating nitrogen fertilization rates (NFR) is time consuming and expensive. Here, we evaluated the use of visible near-infrared shortwave-infrared (VIS-NIR-SWIR: 400–2500 nm) spectroscopy for the assessment of NFR to provide necessary information for fast, cost-effective and precise fertilization rating. Over 2000 samples were collected from paddy-rice fields in 10 Chinese provinces; samples were added to the Chinese Soil Spectral Library (CSSL). Two kinds of modeling strategies for NFR, quantitative estimation of soil N prior to classification and qualitative by classification, were employed using partial least squares regression (PLSR), locally weighted regression (LWR), and support vector machine discriminant analogy (SVMDA). Overall, both LWR and SVMDA had moderate accuracies with Cohen’s kappa coefficients of 0.47 and 0.48, respectively, while PLSR had fair accuracy (0.37). We conclude that VIS-NIR-SWIR spectroscopy coupled with the CSSL appears to be a viable, rapid means for the assessment of NFR in paddy-rice soil. Based on qualitative classification of soil spectral data only, it is recommended that the SVMDA be adopted for rapid implementation

Soil classification of multi-horizontal profiles using support vector machines and vis-NIR spectroscopy

The need for rapid and inexpensive techniques for high-resolution soil information has led to improvements over traditional methods, and in particular those based on visible near-infrared (vis–NIR) spectroscopy. While vis–NIR has been used for soil classification for some preliminary studies, how to combine spectral information from soil profiles remains a substantial challenge. This study was undertaken to investigate the potential of vis–NIR to discriminate soil classes on profiles containing various soil horizons. We took 130 soil profiles at Zhejiang province, of which were classified in the field at suborder level according to Chinese Soil Taxonomy (5 soil orders and 10 suborders). Subsoil samples were taken by diagnosis layers (A, B and C). Support vector machine (SVM) algorithm was used to determine the soil classes, by analyzing quantitatively their diffuse reflectance spectra in the vis– NIR range. For SVM is a binary classification algorithm, the qualitative analysis was conducted by combining the votes of each sample from the same profile and the class got most votes in one profile was defined as their predicted soil class. Readily available variables (soil color) and well-predicted properties (soil organic matter, soil texture and pH) using vis-NIR spectra were added as auxiliary information. Using synthesized model (spectra plus auxiliary soil information), SVM produced better clas- sification performances at soil order level and suborder level (accuracy were 68.29% and 63.51% respectively) than spectra independently (accuracy were 60.69% and 58.54% respectively). They suggest that vis–NIR spectroscopy combining votes gained from SVM could make an essential contribution to the identification of soil classes in an effective approach of soil classification even when profiles contain various soil horizons

Down-regulation of miR-210-3p encourages chemotherapy resistance of renal cell carcinoma via modulating ABCC1

Abstract Background ATP-binding cassette transporter super-family including ABCC1 and MDR-1 were involved in multi-drug resistance (MDR) of renal cell carcinoma (RCC) patients. Several miRNAs were confirmed to promote the MDR and the survival of tumor cells. Methods The RCC cell lines Caki-2 with vinblastine-resistant (Caki-2/VBL) or doxorubicin-resistant (Caki-2/DOX) were constructed, respectively. The expressions of miR-210-3p, ABCC1 and MDR-1 protein were determined by qRT-PCR and Western blot assays. The viability of RCC cells was assessed by MTT assay. The regulatory relationship between miR-210-3p and ABCC1 was analyzed by Dual Luciferase assay. The effect of miR-210-3p in vivo was investigated with a tumor xenograft model in mice. Results MiR-210-3p expression was observed to significantly decrease in Caki-2/VBL and Caki-2/DOX cells. Meanwhile, ABCC1 and MDR-1 were significantly increased in Caki-2/VBL and Caki-2/DOX cells. ABCC1 was a novel target of miR-210-3p and negatively regulated by miR-210-3p. And miR-210-3p improved drug-sensitivity of RCC cells. Down-regulation of ABCC1 could reverse the effect of miR-210-3p knockdown on the drug-resistance and the level of MDR-1 in drug-sensitive RCC cells. Conclusion We confirmed that down-regulation of miR-210-3p increased ABCC1 expression, thereby enhancing the MRP-1-mediated multidrug resistance of RCC cells

Heavy Metal Pollution Delineation Based on Uncertainty in a Coastal Industrial City in the Yangtze River Delta, China

Assessing heavy metal pollution and delineating pollution are the bases for evaluating pollution and determining a cost-effective remediation plan. Most existing studies are based on the spatial distribution of pollutants but ignore related uncertainty. In this study, eight heavy-metal concentrations (Cr, Pb, Cd, Hg, Zn, Cu, Ni, and Zn) were collected at 1040 sampling sites in a coastal industrial city in the Yangtze River Delta, China. The single pollution index (PI) and Nemerow integrated pollution index (NIPI) were calculated for every surface sample (0–20 cm) to assess the degree of heavy metal pollution. Ordinary kriging (OK) was used to map the spatial distribution of heavy metals content and NIPI. Then, we delineated composite heavy metal contamination based on the uncertainty produced by indicator kriging (IK). The results showed that mean values of all PIs and NIPIs were at safe levels. Heavy metals were most accumulated in the central portion of the study area. Based on IK, the spatial probability of composite heavy metal pollution was computed. The probability of composite contamination in the central core urban area was highest. A probability of 0.6 was found as the optimum probability threshold to delineate polluted areas from unpolluted areas for integrative heavy metal contamination. Results of pollution delineation based on uncertainty showed the proportion of false negative error areas was 6.34%, while the proportion of false positive error areas was 0.86%. The accuracy of the classification was 92.80%. This indicated the method we developed is a valuable tool for delineating heavy metal pollution

The Airflow Field Characteristics of the Unmanned Agricultural Aerial System on Oilseed Rape (Brassica napus) Canopy for Supplementary Pollination

Pollination success is essential for hybrid oilseed rape (OSR, Brassica napus) seed production, but traditional pollination methods are not efficient. The unmanned agricultural aerial system (UAAS) has developed rapidly and has been widely used in China. When flying, the wind field generated by the rotors overcomes the UAAS gravity, and it blows and disturbs the crops below, which helps the pollen spread. In order to investigate the distribution law of the three-dimensional (direction x, y, z) airflow field, experiments involving three levels of flight speed (FS) at 4.0, 5.0, and 6.0 m/s, and three levels of flight height (FH) at 1.5, 2.0, and 2.5 m were conducted in the OSR field by using an electric four-rotor UAAS P20. The effects of FS and FH on airflow velocities (vx, vy, vz) were analyzed. High-speed dynamic camera (HSDC) technology was used to capture the swings of OSR plants under airflow field disturbance. OSR pollen samples were collected during the experiments. The results showed that the airflow field in the direction x was mainly concentrated on the center of the flight path (S3), and the maximum wind velocity of direction x was 8.01 m/s (T1, S3). The direction x airflow field width was distributed almost symmetrically, but the center position shifted easily, due to crosswind. The airflow field in the direction y was distributed on both sides of the center flight path, and the velocity was generally larger, with the maximum at 7.91 m/s (T1, S2). The airflow field in the direction z was distributed irregularly, and the velocity was small. The FH had highly significant impacts on  vx (p < 0.01), and the interaction of FS and FH had significant impacts on  vx (0.01 < p < 0.05), while the FS had no significant impact on vx (p = 0.70804 > 0.05). The FS, FH, and interaction of FS and FH all had highly significant impacts on vy (p < 0.01). The swings of the OSR plant captured by the HSDC proved that the UAAS airflow field could effectively blow the OSR plant. The swing amplitude changes showed a positive correlation with airflow velocities (vx) in general. Although the observed OSR plant swung forward and backward repeatedly, there was a law of first forward, and then backward, and forward again at the beginning of each swing. The pollen collected on the sampler verified that the UAAS airflow field could help with pollen spread. The research results provide technical support for UAAS application on supplementary pollination for hybrid OSR seed production

A meta-analysis of the Timing of Chest Radiotherapy in Patients with Limited-stage Small Cell Lung Cancer

Background and objective Although evidence for a significant survival benefit of chest radiotherapy has been proven, no conclusion could be drawn regarding the optimal timing of chest radiation. The aim of this study is to explore whether the timing of chest radiation may influence the survival of the patients with limited-stage small-cell lung cancer (LSSCLC) by performing a literature-based meta-analysis. Methods By searching Medline, CENTRAL (the Cochrane central register of controlled trials), CBM, and CNKI, et al, we collected both domestic and overseas published documents about randomized trials comparing different timing chest radiotherapy in patients with LS-SCLC. Early chest radiation was regarded as beginning within 30 days after the start of chemotherapy. Random or fixed effect models were applied to conduct meta-analysis on the trials. The combined odds ratio (OR) and the 95% confidence interval (CI) were calculated to estimate the mortality in 2 or 3 years and toxicity of the two treatments. The statistical heterogeneity was determined by cochran’s Chi-square test (Q test). The Begg’ test was used to determine the publication bias. Results Six trials that included a total of 1 189 patients were analyzed in the meta-analysis 587 patients were in the early radiation group and 602 patients were in the late radiation group. Considering all 6 eligible trials, the overall survival at 2/3 years was not significantly different between early and late chest radiation (OR=0.78, 95%CI: 0.55-1.05, Z=1.68, P=0.093). For the toxicity, no obvious difference was observed for early chest radiotherapy compared with late irradiation in pneumonitis (OR=1.93, 95%CI: 0.97-3.86, P=0.797), esophagitis (OR=1.43, 95%CI: 0.95-2.13, P=0.572) and thrombocytopenia (OR=1.23, 95%CI: 0.88-1.77, P=0.746), respectively. Conclusion No statistical difference was observed in 2/3 years survival and toxicity, including pneumonitis, esophagitis and thrombocytopenia, between early radiation and late radiotherapy in LS-SCLC