SLUG is activated by nuclear factor kappa B and confers human alveolar epithelial A549 cells resistance to tumor necrosis factor-alpha-induced apoptosis

BACKGROUND: The role of tumor necrosis factor alpha (TNF-α) in cancer is complex with both apoptotic and anti-apoptotic roles proposed. However the mechanism is not clear. In the study, we designed to investigate the effect of TNF-α on the activation and expression of nuclear factor kappa B (NF-κB)/p65/SLUG/PUMA/Bcl-2 levels in human lung cancer A549 cell line, and in conditions of TNF-α-induced apoptosis. METHODS: We have engineered three A549 cell lines that were transiently transfected with PUMA siRNA, SLUG siRNA and Bcl-2 siRNA, respectively. We have measured the in vitro effects of siRNA on apoptosis, and sensitivity to 20 ng/ml of TNF-α treatment for 24–48 h. RESULTS: We found the NF-κB activity and PUMA mRNA/protein was significantly increased after treatment of TNF-α for 24 h in untreated A549 cells, and led to a significant increase in TNF-α-induced apoptosis, no significant increase of SLUG and Bcl-2 level was shown. However, after treatment of TNF-α for 48 h in untreated A549 cells, SLUG and Bcl-2 level was significant increased, and PUMA level was significant decreased, and TNF-α-induced apoptosis was significantly decreased compared to the apoptosis level after treatment of TNF-α for 24 h. Inhibition of the NF-κB activity could effectively decrease the PUMA level and increase the SLUG and Bcl-2 level. PUMA silencing by siRNA led to a significant decrease in TNF-α-induced apoptosis after treatment of TNF-α for 24 h. Bcl-2 and SLUG silencing by siRNA led to a significant increase in TNF-α-induced apoptosis for 48 h. Furthermore, SLUG silencing increased PUMA level and decreased Bcl-2 level. CONCLUSIONS: The findings suggested that TNF-α treatment promoted apoptosis via the NF-κB-dependent PUMA pathway. The anti-apoptotic role of TNF-α was via NF-κB-dependent SLUG and Bcl-2 pathway at a later time

Urbanization affects spatial variation and species similarity of bird diversity distribution

Although cities are human-dominated systems, they provide habitat for many other species. Because of the lack of long-term observation data, it is challenging to assess the impacts of rapid urbanization on biodiversity in Global South countries. Using multisource data, we provided the first analysis of the impacts of urbanization on bird distribution at the continental scale and found that the distributional hot spots of threatened birds overlapped greatly with urbanized areas, with only 3.90% of the threatened birds’ preferred land cover type in urban built-up areas. Bird ranges are being reshaped differently because of their different adaptations to urbanization. While green infrastructure can improve local bird diversity, the homogeneous urban environment also leads to species compositions being more similar across regions. More attention should be paid to narrow-range species for the formulation of biodiversity conservation strategies, and conservation actions should be further coordinated among cities from a global perspective

Model Reduction and Nonlinear Model Predictive Control of Large-Scale Distributed Parameter Systems with Applications in Solid Sorbent-Based CO2 Capture

<p>This dissertation deals with some computational and analytic challenges for dynamic process operations using first-principles models. For processes with significant spatial variations, spatially distributed first-principles models can provide accurate physical descriptions, which are crucial for offline dynamic simulation and optimization. However, the large amount of time required to solve these detailed models limits their use for online applications such as nonlinear model predictive control (NMPC). To cope with the computational challenge, we develop computationally efficient and accurate dynamic reduced order models which are tractable for NMPC using temporal and spatial model reduction techniques. Then we introduce an input and state blocking strategy for NMPC to further enhance computational efficiency. To improve the overall economic performance of process systems, one promising solution is to use economic NMPC which directly optimizes the economic performance based on first-principles dynamic models. However, complex process models bring challenges for the analysis and design of stable economic NMPC controllers. To solve this issue, we develop a simple and less conservative regularization strategy with focuses on a reduced set of states to design stable economic NMPC controllers. In this thesis, we study the operation problems of a solid sorbent-based CO2 capture system with bubbling fluidized bed (BFB) reactors as key components, which are described by a large-scale nonlinear system of partial-differential algebraic equations. By integrating dynamic reduced models and blocking strategy, the computational cost of NMPC can be reduced by an order of magnitude, with almost no compromise in control performance. In addition, a sensitivity based fast NMPC algorithm is utilized to enable the online control of the BFB reactor. For economic NMPC study, compared with full space regularization, the reduced regularization strategy is simpler to implement and lead to less conservative regularization weights. We analyze the stability properties of the reduced regularization strategy and demonstrate its performance in the economic NMPC case study for the CO2 capture system.</p

BMSCs-Seeded Interpenetrating Network GelMA/SF Composite Hydrogel for Articular Cartilage Repair

Because of limited self-healing ability, the treatment of articular cartilage defects is still an important clinical challenge. Hydrogel-based biomaterials have broad application prospects in articular cartilage repair. In this study, gelatin methacrylate (GelMA)and silk fibroin (SF) were combined to form a composite hydrogel with an interpenetrating network (IPN) structure under ultraviolet irradiation and ethanol treatment. Introducing silk fibroin into GelMA hydrogel significantly increased mechanical strength as compressive modulus reached 300 kPa in a GelMA/SF-5 (50 mg/mL silk fibroin) group. Moreover, composite IPN hydrogels demonstrated reduced swelling ratios and favorable biocompatibility and supported chondrogenesis of bone mesenchymal stem cells (BMSCs) at day 7 and day 14. Additionally, significantly higher gene expressions of Col-2, Acan, and Sox-9 (p < 0.01) were found in IPN hydrogel groups when compared with the GelMA group. An in vivo study was performed to confirm that the GelMA-SF IPN hydrogel could promote cartilage regeneration. The results showed partial regeneration of cartilage in groups treated with hydrogels only and satisfactory cartilage repair in groups of cell-seeded hydrogels, indicating the necessity of additional seeding cells in hydro-gel-based cartilage treatment. Therefore, our results suggest that the GelMA/SF IPN hydrogels may be a potential functional material in cartilage repair and regeneration

Vegetation Landscape Changes and Driving Factors of Typical Karst Region in the Anthropocene

Vegetation degeneration has become a serious ecological problem for karst regions in the Anthropocene. According to the deficiency of long serial and high-resolution analysis of karst vegetation, this paper reconstructed the variation of vegetation landscape changes from 1987 to 2020 in a typical karst region of China. Using Landsat time series data, the dynamic changes and driving factors of natural karst vegetation were identified at the landscape scale. On the premise of considering the time-lag effect, the main climatic factors that influence vegetation growth were presented at the interannual timescale. Then, the approach of residual analysis was adopted to distinguish the dominant factors affecting vegetation growth. Results of trend analysis revealed that 21.5% of the forestland showed an overall significant decline in vegetation growth, while only 1.5% showed an increase in vegetation growth during the study period. Precipitation and radiation were the dominant meteorological factors influencing vegetation at the interannual timescale, as opposed to temperature. More than 70% of the natural vegetation growth was dominated by climatic factors. The area percentage of negative human impact has increased gradually since 2009 and reached 18.5% in 2020, indicating the currently serious situation of vegetation protection; fortunately, in recent years, human disturbances on vegetation have been mitigated in karst areas with the promotion of ecological conservation and restoration projects

Evaluating the Relationship between Field Aerodynamic Roughness and the MODIS BRDF, NDVI, and Wind Speed over Grassland

Aerodynamic roughness (AR) is an important parameter that influences the momentum and energy exchange between the earth’s surface and the atmosphere. In this study, profile wind data observed during the vegetation growing period (April–September) in 2013 and 2014 at the A’rou grassland station, which is in the upstream of the Heihe River Basin (HRB), were used to determine the relationship between the field AR and the Moderate-resolution Imaging Spectroradiometer (MODIS) near-infrared (NIR) bi-directional reflectance distribution function (BRDF) R index, the normalized difference vegetation index (NDVI), and a combination of these indices. In addition, the relationship between the average wind speed at a height of 1 m and the field AR is also presented. The results indicate that the MODIS NIR BRDF_R index and the NDVI are both sensitive indicators of the AR over grassland (R2: 0.5228 for NIR BRDF_R; R2: 0.579 for NDVI). Moreover, the combined index shows a significantly increased R2 value of 0.721, which is close to the result inferred from the wind speed (R2: 0.7411). The proposed remote sensing-based combination index (CI) has the potential for use in evaluations of the AR over grasslands during growing season and its sensitivity can reach levels that are comparable to considering the effects of wind speed, which usually requires ground-based observations

Spatiotemporal Analysis of Actual Evapotranspiration and Its Causes in the Hai Basin

Evapotranspiration (ET) is an important component of the eco-hydrological process. Comprehensive analyses of ET change at different spatial and temporal scales can enhance the understanding of hydrological processes and improve water resource management. In this study, monthly ET data and meteorological data from 57 meteorological stations between 2000 and 2014 were used to study the spatiotemporal changes in actual ET and the associated causes in the Hai Basin. A spatial analysis was performed in GIS to explore the spatial pattern of ET in the basin, while parametric t-test and nonparametric Mann-Kendall test methods were used to analyze the temporal characteristics of interannual and annual ET. The primary causes of the spatiotemporal variations were partly explained by detrended fluctuation analysis. The results were as follows: (i) generally, ET increased from northwest to southeast across the basin, with significant differences in ET due to the heterogeneous landscape. Notably, the ET of water bodies was highest, followed by those of paddy fields, forests, cropland, brush, grassland and settlement; (ii) from 2000 to 2014, annual ET exhibited an increasing trend of 3.7 mm per year across the basin, implying that the excessive utilization of water resources had not been alleviated and the water resource crisis worsened; (iii) changes in vegetation coverage, wind speed and air pressure were the major factors that influenced interannual ET trends. Temperature and NDVI largely explained the increases in ET in 2014 and can be used as indicators to evaluate annual ET and provide early warning for associated issues

The Impacts of Vegetation and Meteorological Factors on Aerodynamic Roughness Length at Different Time Scales

The aerodynamic roughness length (z0m) is a crucial parameter for reliably simulating turbulent exchanges between the land surface and the atmosphere. Due to the large number of input variables related to vegetation growth and aerodynamic conditions near the surface, estimating z0m precisely is difficult and, to date, no universal model has been established. Understanding the z0m changes in time series data and the relative contributions of vegetation indices and meteorological factors is important to providing a basis for modelling z0m. In this paper, the main meteorological factors that influence z0m in different seasons are presented based on data from three automatic weather stations (AWSs) that represent various land surface patterns in the Heihe river basin. A correlation analysis identified the dominant factors that influence z0m changes at half-hour and daily scales; then, a factor analysis was performed to identify the different contributions of vegetation indices and meteorological factors to z0m at different time scales. The results show that meteorological factors (wind speed, wind direction and atmospheric stability) are the main driving factors for z0m at the Arou and Guantan sites, which are situated in grassland and forest mountain areas, respectively, and that the vegetation indices have no impact on the z0m variations in these areas. In contrast, for the Daman site, situated in flat farmland, the vegetation indices are the primary driving factors, while meteorological factors such as wind speed and atmospheric stability are secondary factors, and wind direction has no significant influence. Finally, a detailed analysis was conducted to detect the relationships between half-hourly z0m measurements and three dominant meteorological factors

Crop Condition Assessment with Adjusted NDVI Using the Uncropped Arable Land Ratio

Crop condition assessment in the early growing stage is essential for crop monitoring and crop yield prediction. A normalized difference vegetation index (NDVI)-based method is employed to evaluate crop condition by inter-annual comparisons of both spatial variability (using NDVI images) and seasonal dynamics (based on crop condition profiles). Since this type of method will generate false information if there are changes in crop rotation, cropping area or crop phenology, information on cropped/uncropped arable land is integrated to improve the accuracy of crop condition monitoring. The study proposes a new method to retrieve adjusted NDVI for cropped arable land during the growing season of winter crops by integrating 16-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance data at 250-m resolution with a cropped and uncropped arable land map derived from the multi-temporal China Environmental Satellite (Huan Jing Satellite) charge-coupled device (HJ-1 CCD) images at 30-m resolution. Using the land map’s data on cropped and uncropped arable land, a pixel-based uncropped arable land ratio (UALR) at 250-m resolution was generated. Next, the UALR-adjusted NDVI was produced by assuming that the MODIS reflectance value for each pixel is a linear mixed signal composed of the proportional reflectance of cropped and uncropped arable land. When UALR-adjusted NDVI data are used for crop condition assessment, results are expected to be more accurate, because: (i) pixels with only uncropped arable land are not included in the assessment; and (ii) the adjusted NDVI corrects for interannual variation in cropping area. On the provincial level, crop growing profiles based on the two kinds of NDVI data illustrate the difference between the regular and the adjusted NDVI, with the difference depending on the total area of uncropped arable land in the region. The results suggested that the proposed method can be used to improve the assessment of early crop condition, but additional evaluation in other major crop producing regions is needed to better assess the method’s application in other regions and agricultural systems