Investigating net primary production in climate regions of Khuzestan Province, Iran using CASA model.

This study aimed to investigate the vegetation production changes in Khuzestan province, Iran using MODIS data production, meteorological data, vegetation maps as well as topographic and field monitoring data in CASA model. The study area was divided into different climatic classes based on multivariate statistical method, so the vegetation of each climatic region was examined separately for changes in NPP values. Production changes due to degradation were calculated using the Miami model and subsequently, the rain use efficiency (RUE) and the light use efficiency (LUE) and correlation indices between the CASA model and ground data were determined. The results of this study (R2) showed that the accuracy of this model varies depending on the type of climatic regions (R2 = 0.80 to R2 = 0.15). In different climatic regions, the rate of NPP changes (very humid 68 gC/m2 to ultra-dry 15 gC/m2) varies in rangeland types. The highest rate of vegetation production is observed seasonally in May. Degradation conditions also reduced RUE and LUE. However, in hyper-arid regions, adaptations of plants in some different species (Hammada Spp.) increase their efficiency compared to other vegetation types. The results showed the importance of vegetation and climate classification in vegetation production studies.

Precise GDP Spatialization and Analysis in Built-Up Area by Combining the NPP-VIIRS-like Dataset and Sentinel-2 Images.

Spatialization and analysis of the gross domestic product of second and tertiary industries (GDP23) can effectively depict the socioeconomic status of regional development. However, existing studies mainly conduct GDP spatialization using nighttime light data; few studies specifically concentrated on the spatialization and analysis of GDP23 in a built-up area by combining multi-source remote sensing images. In this study, the NPP-VIIRS-like dataset and Sentinel-2 multi-spectral remote sensing images in six years were combined to precisely spatialize and analyze the variation patterns of the GDP23 in the built-up area of Zibo city, China. Sentinel-2 images and the random forest (RF) classification method based on PIE-Engine cloud platform were employed to extract built-up areas, in which the NPP-VIIRS-like dataset and comprehensive nighttime light index were used to indicate the nighttime light magnitudes to construct models to spatialize GDP23 and analyze their change patterns during the study period. The results found that (1) the RF classification method can accurately extract the built-up area with an overall accuracy higher than 0.90; the change patterns of built-up areas varied among districts and counties, with Yiyuan county being the only administrative region with an annual expansion rate of more than 1%. (2) The comprehensive nighttime light index is a viable indicator of GDP23 in the built-up area; the fitted model exhibited an R2 value of 0.82, and the overall relative errors of simulated GDP23 and statistical GDP23 were below 1%. (3) The year 2018 marked a significant turning point in the trajectory of GDP23 development in the study area; in 2018, Zhoucun district had the largest decrease in GDP23 at -52.36%. (4) GDP23 gradation results found that Zhangdian district exhibited the highest proportion of high GDP23 (>9%), while the proportions of low GDP23 regions in the remaining seven districts and counties all exceeded 60%. The innovation of this study is that the GDP23 in built-up areas were first precisely spatialized and analyzed using the NPP-VIIRS-like dataset and Sentinel-2 images. The findings of this study can serve as references for formulating improved city planning strategies and sustainable development policies.

Impacts of urbanization on ecosystem carbon cycle: a case study of land use change in Tianjin metropolitan area.

For the sustainable development of the city, in a study of Tianjin's rapid urbanization, we explore the complex interplay between land use change and the ecosystem carbon cycle from 2000 to 2020. Spatial analysis and profit-loss matrix calculations reveal contrasting ecological impacts: expansion of woodlands and grasslands enhances Net Primary Productivity (NPP) and reduces carbon emissions, while urban construction shows the opposite effect. Over 20 years, Tianjin's urban transformation led to a 16.91 GgC decline in NPP amidst a construction boom. However, post-2015 ecological policy shifts resulted in a significant net carbon uptake of 0.85 Gt, demonstrating the potential of policy interventions in mitigating environmental impacts of urbanization. This study underscores the importance of sustainable urban planning and ecological conservation strategies in highly urbanized settings.

Inactivation of Sufu in cementoblasts accelerates external tooth root resorption.

Cementum has been empirically regarded as an antiresorptive barrier against tooth roots. However, little is known about the factors of homeostasis and resistant mechanisms of tooth roots against resorption. Here, we investigated cementum factors and their interaction against resorption using transgenic mice exhibiting external cervical root resorption (ECRR). Ectopically thickened cervical cementum caused by functional inactivation of ectonucleotide pyrophosphotase/phosphodiesterase 1 (Enpp1) was susceptible to ECRR with aging. In addition, the inactivation of the suppressor of fused (Sufu), a Hedgehog signaling inhibitor, in cementoblasts led to ECRR. Interestingly, concurrent inactivation of Sufu and Enpp1 in cementoblasts remarkably exacerbated ECRR with higher Rankl expression. Cellular and molecular analyses using cementoblasts and bone marrow-derived macrophages indicated that Dickkopf-related protein 1 (Dkk1) induced by the inactivation of Sufu in cementoblasts has roles in the acceleration of ECRR triggered by Enpp1 inactivation. Using compound mutant mice for concurrent Wntless and Enpp1 inactivation, this synergistic cooperation of Dkk1 and Npp1 for resorption found in double mutant Sufu and Enpp1 mice was confirmed by the reproduction of amplified ECRR. On the basis of these findings, we conclude that proper Npp1 function and sustained Wnt activity in the cervical cementum are essential for the homeostasis of tooth roots against resorption in a physiological state.

NPP1 and TNAP hydrolyze ATP synergistically during biomineralization.

Matrix vesicles (MVs) are a special class of extracellular vesicles released by mineralizing cells during bone and tooth mineralization that initiate the precipitation of apatitic minerals by regulating the extracellular ratio between inorganic phosphate (Pi), a calcification promoter, and pyrophosphate (PPi), a calcification inhibitor. The Pi/PPi ratio is thought to be controlled by two ecto-phosphatases present on the outer leaflet of the MVs' membrane: ectonucleotide pyrophosphatase/phosphodiesterase 1 (NPP1) that produces PPi as well as Pi from ATP and tissue-nonspecific alkaline phosphatase (TNAP) that hydrolyzes both ATP and PPi to generate Pi. However, if and how these enzymes act in concert in MVs are still unclear. Herein, we investigated the role of NPP1 and TNAP in ATP hydrolysis during MV-mediated biomineralization using proteoliposomes as a biomimetic model for MVs. Proteoliposomes composed by 1,2-dipalmitoylphosphatidylcholine (DPPC) and harboring NPP1 alone, TNAP alone, or both together at different molar ratios (1:1, 10:1, and 1:10) were fabricated. After 48 h of incubation with ATP, TNAP-containing proteoliposomes consumed more ATP than NPP1-containing vesicles (270 and 210 nmol, respectively). Both types of vesicles comparatively formed ADP (205 and 201 nmol, respectively), while NPP1-containing vesicles hydrolyzed AMP less efficiently than TNAP-containing proteoliposomes (10 and 25 nmol, respectively). In vitro mineralization assays showed that in the presence of ATP, TNAP-harboring proteoliposomes mineralized through a sigmoidal single-step process, while NPP1-harboring vesicles displayed a two-step mineralization process. ATR-FTIR analyses showed that the minerals produced by TNAP-harboring proteoliposomes were structurally more similar to hydroxyapatite than those produced by NPP1-harboring vesicles. Our results with proteoliposomes indicate that the pyrophosphohydrolase function of NPP1 and the phosphohydrolase activity of TNAP act synergistically to produce a Pi/PPi ratio conducive to mineralization and the synergism is maximal when the two enzymes are present at equimolar concentrations. The significance of these findings for hypophosphatasia is discussed.

Preclinical evaluation of bozepinib in bladder cancer cell lines: modulation of the NPP1 enzyme.

Bladder cancer (BC) is the most common cancer of the urinary tract. Bozepinib (BZP), a purine-derived molecule, is a potential compound for the treatment of cancer. Purinergic signaling consists of the activity of nucleosides and nucleotides present in the extracellular environment, modulating a variety of biological actions. In cancer, this signaling is mainly controlled by the enzymatic cascade involving the NTPDase/E-NPP family and ecto-5'-nucleotidase/CD73, which hydrolyze extracellular adenosine triphosphate (ATP) to adenosine (ADO). The aim of this work is to evaluate the activity of BZP in the purinergic system in BC cell lines and to compare its in vitro antitumor activity with cisplatin, a chemotherapeutic drug widely used in the treatment of BC. In this study, two different BC cell lines, grade 1 RT4 and the more aggressive grade 3 T24, were used along with a human fibroblast cell line MRC-5, a cell used to predict the selectivity index (SI). BZP shows strong antitumor activity, with notable IC50 values (8.7 ± 0.9 µM for RT4; 6.7 ± 0.7 µM for T24), far from the SI for cisplatin (SI for BZP: 19.7 and 25.7 for RT4 and T24, respectively; SI for cisplatin: 1.7 for T24). BZP arrests T24 cells in the G2/M phase of the cell cycle, inducing early apoptosis. Moreover, BZP increases ATP and ADP hydrolysis and gene/protein expression of the NPP1 enzyme in the T24 cell line. In conclusion, BZP shows superior activity compared to cisplatin against BC cell lines in vitro.

Use of iRNA in the post-transcriptional gene silencing of necrosis-inducing Phytophthora protein 1(NPP1) in Phytophthora cinnamomi.

BACKGROUND: Phytophthora cinnamomi is an Oomycetes associated with soil, this Oomycete is one of the most destructive species of Phytophthora, being responsible for the decline of more than 5000 ornamental, forest, or fruit plants. It can secrete a class of protein NPP1 (Phytophthora necrosis inducing protein 1), responsible for inducing necrosis in leaves and roots of plants, leading to their death. OBJECTIVE: This work will report the characterization of the Phytophthora cinnamomi NPP1 gene responsible for the infection of Castanea sativa roots and will characterize the mechanisms of interaction between Phytophthora cinnamomi and Castanea sativa, by gene silencing NPP1 from Phytophthora cinnamomi mediated by RNAi. METHODS AND RESULTS: For silencing a part of the coding region of the NPP1 gene, was placed in the sense and antisense directions between an intron and ligated to the integrative vector pTH210. Cassette integration was confirmed by PCR and sequencing on the hygromycin-resistant Phytophthora cinnamomi transformants. Transformants obtained with the silenced gene was used to infect Castanea sativa. CONCLUSIONS: Plants infected with these transformants showed a great reduction in disease symptoms, confirming iRNA as a potential alternative biological tool in the study of molecular factors, and in the control and management of Phytophthora cinnamomi.

Refined assessment of space-time changes, influencing factors and socio-economic impacts of the terrestrial ecosystem quality: A case study of the GBA.

The terrestrial ecosystem is the cradle of energy and material basis for human survival and development. However, there are large research deficits in accurately and finely depicting the quality of the terrestrial ecosystem (QTE) and assessing its changing triggers' contribution. Here, we summarized three major principles for selecting image sources in remote sensing data fusion. A continuous 30-m net vegetation productivity (NPP) dataset during 2000-2019 for the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was derived by using the Carnegie-Ames-Stanford approach model and pre-fused normalized difference vegetation index. The factors' contributions to the QTE changes were quantitatively assessed. The role of the QTE in affecting the socio-economic and its behind mechanisms was quantitatively investigated. The results showed that: (1) High-quality images sources are the preference for spatio-temporal fusion of remote sensing data. Images with close month, the same season and year, and sensors should be then selected. Images of different sensors with similar spectral bandwidth, the ones from adjacent years and seasons, can be alternately considered. (2) Fine-resolution NPP has higher accuracy than coarse-resolution NPP and has marked advantages in finely characterizing the QTE. In the past 20 years, the QTE in the GBA has shown a fluctuating increasing trend (0.20 Tg C/yr). (3) Human activities contributed 54.19% of the QTE changes in the GBA, and dominates the QTE changes in the central rapidly urbanizing areas. Residual factors accounted for an overall contribution ratio of 35.71%. Climate change dominants the peripheral forest variations in the GBA. (4) In the GBA, the improvement of QTE has a significant positive socio-economic impact, it contributes to the GDP increment firstly then the GDP aggregate indirectly. Our results highlight that it is of great urgent to estimate long-term continuous NPP with high spatio-temporal resolution globally. Controlling strategies should be implemented to reduce factitious impacts on QTE. High level of ecological and environmental protection promotes the sustainable development.

Machine learning-based prediction and assessment of recent dynamics of forest net primary productivity in Romania.

While the analysis of spatio-temporal changes in the net primary productivity (NPP) of forests can provide critical information on carbon cycle and climate change, these ecological trends have remained unclear in many countries worldwide, including Romania. By using complex (satellite, forest and climate) data, many sophisticated (machine learning) algorithms and some widely applied (the Mann-Kendall test and Sen's slope estimator) statistical procedures, this study investigates, for the first time, recent forest NPP trends (1987-2018) that occurred in Romania, in relation to climate change that affected the country over the past decades. Following the modelling, mapping and assessment of NPP dynamics, results showed almost exclusively positive trends for this ecological parameter, which accounts for ∼99% of all forest NPP changes that occurred throughout the country, after 1987. Interestingly, almost three quarters (∼73%) of all NPP increasing trends are statistically significant, which indicates that Romania's forests have recently experienced a large-scale improvement in carbon fluxes and stocks. Investigations of eco-climatic relationships suggest that climate change has partially contributed to these surprising NPP dynamics observed in recent decades. All these findings can provide valuable information for forest management and for many stakeholders and policymakers who operate in the forestry and climate fields in Romania.

Cumulative effects of drought have an impact on net primary productivity stability in Central Asian grasslands.

Global warming has exacerbated the threat of drought in Central Asia, amplifying its ecological implications within the region's grassland ecosystems. This has become an increasingly prominent issue that requires attention and action. The temporal link between grassland development and drought is asymmetric. However, a quantitative assessment of the temporal effects of multiscale drought on Central Asian grasslands has yet to be explored. Based on correlation analysis and the coefficient of variation method, this study analysed the cumulative and lag effects of multitimescale drought on grassland NPP (net primary productivity) under different climatic zones, altitudes and water availabilities in Central Asia from 1982 to 2018, and discussed the impact of temporal effects on grassland NPP stability. Our results on the cumulative effects of drought on grasslands indicate the 6.72 months preceding NPP measurement was the duration for which, on average, drought was most strongly correlated with NPP. Additionally, we found a mean lagged effect of 5.36 months, meaning that the monthly drought 5.36 months prior to NPP measurement was, on average, most strongly correlated with NPP. The degree to which grassland NPP was affected by cumulative drought at a given level of water availability was inversely proportional to the number of cumulative drought months. Under different water availabilities, the lagged effect of grassland NPP was stronger in dry areas than in wet areas, and the number of lag months tended to decrease and then increase as the water availability increased. The percentage of areas where grassland NPP was dominated by the cumulative and lagging effects of drought was 30.02% and 69.98%, respectively. The stability of grassland NPP was adversely affected by the drought accumulation effect. The findings of this study contribute to a deeper understanding of the long-term effects of drought on grassland ecosystems. Additionally, it will aid in the development of strategies for mitigating and adapting to drought events, thereby minimizing their negative impacts on agriculture, livestock, and ecosystems.

Contributions of climate change and human activities to grassland degradation and improvement from 2001 to 2020 in Zhaosu County, China.

Grassland degradation poses a serious threat to biodiversity, ecosystem services, and human well-being. In this study, we investigated grassland degradation in Zhaosu County, China, between 2001 and 2020, and analyzed the impacts of climate change and human activities using the Miami model. The actual net primary productivity (ANPP) obtained with CASA (Carnegie-Ames-Stanford Approach) modeling, showed a decreasing trend, reflecting the significant degradation that the grasslands in Zhaosu County have experienced in the past 20 years. Grassland degradation was found to be highest in 2018, while the degraded area continuously decreased in the last 3 years (2018-2020). Climatic factors for found to be the dominant factor affecting grassland degradation, particularly the decrease in precipitation. On the other hand, human activities were found to be the main factor affecting improvement of grasslands, especially in recent years. This finding profoundly elucidates the underlying causes of grassland degradation and improvement and helps implement ecological conservation and restoration measures. From a practical perspective, the research results provide an important reference for the formulation of policies and management strategies for sustainable land use.

Identification of factors influencing net primary productivity of terrestrial ecosystems based on interpretable machine learning --evidence from the county-level administrative districts in China.

Global climate change is rooted in the imbalance between carbon sources and sinks, and net-zero greenhouse gas emissions should focus not only on the source-side drivers but also on the sink-side influencing factors. Taking the county-level administrative districts in China as the sample, this study uses machine learning models to fit the relationship between socioeconomic development (SED) and net primary productivity (NPP) of terrestrial ecosystems. Moreover, it identifies key influencing factors and their effects based on the SHapley Additive exPlanations (SHAP) algorithm. The results show that the districts with low terrestrial NPP show the characteristics of agglomeration distribution. The eight key factors, in order, are as follows: agricultural development level, latitude, population size, longitude, animal husbandry development level, economic scale, time trend and industrialization level. In this study, via SHAP interaction plots, we found that the effects of population, economic growth, and industrialization on terrestrial NPP are regionally heterogeneous; via cluster analysis, we found the stage characteristics of the mode of SED affecting terrestrial NPP. Therefore, the conservation of terrestrial NPP needs to be combined with the stage changes of SED, as well as inter-regional differences, to develop a regionally coordinated and time-coherent ecological carbon sink conservation plan.

Contribution of soil algae to the global carbon cycle.

Soil photoautotrophic prokaryotes and micro-eukaryotes - known as soil algae - are, together with heterotrophic microorganisms, a constitutive part of the microbiome in surface soils. Similar to plants, they fix atmospheric carbon (C) through photosynthesis for their own growth, yet their contribution to global and regional biogeochemical C cycling still remains quantitatively elusive. Here, we compiled an extensive dataset on soil algae to generate a better understanding of their distribution across biomes and predict their productivity at a global scale by means of machine learning modelling. We found that, on average, (5.5 ± 3.4) × 106 algae inhabit each gram of surface soil. Soil algal abundance especially peaked in acidic, moist and vegetated soils. We estimate that, globally, soil algae take up around 3.6 Pg C per year, which corresponds to c. 6% of the net primary production of terrestrial vegetation. We demonstrate that the C fixed by soil algae is crucial to the global C cycle and should be integrated into land-based efforts to mitigate C emissions.

Land use intensification increasingly drives the spatiotemporal patterns of the global human appropriation of net primary production in the last century.

Land use has greatly transformed Earth's surface. While spatial reconstructions of how the extent of land cover and land-use types have changed during the last century are available, much less information exists about changes in land-use intensity. In particular, global reconstructions that consistently cover land-use intensity across land-use types and ecosystems are missing. We, therefore, lack understanding of how changes in land-use intensity interfere with the natural processes in land systems. To address this research gap, we map land-cover and land-use intensity changes between 1910 and 2010 for 9 points in time. We rely on the indicator framework of human appropriation of net primary production (HANPP) to quantify and map land-use-induced alterations of the carbon flows in ecosystems. We find that, while at the global aggregate level HANPP growth slowed down during the century, the spatial dynamics of changes in HANPP were increasing, with the highest change rates observed in the most recent past. Across all biomes, the importance of changes in land-use areas has declined, with the exception of the tropical biomes. In contrast, increases in land-use intensity became the most important driver of HANPP across all biomes and settings. We conducted uncertainty analyses by modulating input data and assumptions, which indicate that the spatial patterns of land use and potential net primary production are the most critical factors, while spatial allocation rules and uncertainties in overall harvest values play a smaller role. Highlighting the increasing role of land-use intensity compared to changes in the areal extent of land uses, our study supports calls for better integration of the intensity dimension into global analyses and models. On top of that, we provide important empirical input for further analyses of the sustainability of the global land system.

Baseline assessment of marine actinobacterial diversity around the nuclear power plant sites, India and its application to uranium remediation.

Baseline assessments of marine microbial studies are very limited around ecologically sensitive areas of the Nuclear Power Plant (NPP) site with respect to their occurrence, distribution, role in adaptation, and their potential remediation process. The distribution and diversity of marine microbes are largely dependent on the physicochemical parameters relating to a specific area, especially spore-producing marine actinobacteria are a source for indigenous bioremediation agents. Marine actinobacterial diversity with conventional and 16 S rRNA gene analysis was done with different pre-treatment conditions and selective media. Totally, 170 different strains are identified in genera level and it belongs to 18 genera with dominant by Streptomyces sp. (75species) followed by Nocardiposis sp, (18species) Rhodococcus sp. (14species). Multiple k-dominance plots simplified the perception of marine actinobacteria according to genera level influence to standard stock. This is the first kind of study in India and the results could act as baseline inventory in terms of microbial diversity around NPP sites. Further, a potential strain of Actinomadura sp. (T5S13) produced 243.7 mg/L of EPS and remediate the Uranium radionuclides. The functional group shifting and adsorption nature were also confirmed by SEM with EDS analysis.

Enzymology of extracellular NAD metabolism.

Extracellular NAD represents a key signaling molecule in different physiological and pathological conditions. It exerts such function both directly, through the activation of specific purinergic receptors, or indirectly, serving as substrate of ectoenzymes, such as CD73, nucleotide pyrophosphatase/phosphodiesterase 1, CD38 and its paralog CD157, and ecto ADP ribosyltransferases. By hydrolyzing NAD, these enzymes dictate extracellular NAD availability, thus regulating its direct signaling role. In addition, they can generate from NAD smaller signaling molecules, like the immunomodulator adenosine, or they can use NAD to ADP-ribosylate various extracellular proteins and membrane receptors, with significant impact on the control of immunity, inflammatory response, tumorigenesis, and other diseases. Besides, they release from NAD several pyridine metabolites that can be taken up by the cell for the intracellular regeneration of NAD itself. The extracellular environment also hosts nicotinamide phosphoribosyltransferase and nicotinic acid phosphoribosyltransferase, which inside the cell catalyze key reactions in NAD salvaging pathways. The extracellular forms of these enzymes behave as cytokines, with pro-inflammatory functions. This review summarizes the current knowledge on the extracellular NAD metabolome and describes the major biochemical properties of the enzymes involved in extracellular NAD metabolism, focusing on the contribution of their catalytic activities to the biological function. By uncovering the controversies and gaps in their characterization, further research directions are suggested, also to better exploit the great potential of these enzymes as therapeutic targets in various human diseases.

Modelling Fagus sylvatica stem growth along a wide thermal gradient in Italy by incorporating dendroclimatic classification and land surface phenology metrics.

Calibrating land surface phenology (LSP) with tree rings is important to model spatio-temporal variations in forest productivity. We used MODIS (resolution: 250 m) NDVI, WDRVI and EVI series 2000-2014 to derive LSP metrics quantifying phenophase timing and canopy photosynthetic rates of 26 European beech forests covering a large thermal gradient (5-16 °C) in Italy. Average phenophase timing changed greatly with site temperature (e.g. growing season 70 days longer at low- than high-elevation); average VI values were affected by precipitation. An annual temperature about 12 °C (c. 1100 m asl) represented a bioclimatic threshold dividing warm from cold beech forests, distinguished by different phenology-BAI (basal area increment) relationships and LSP trends. Cold forests showed decreasing VI values (browning) and delayed phenophases and had negative BAI slopes. Warmer forests tended to increase VI (greening), and positive BAI slopes. NDVI peak, commonly used in global trend assessments, changed with elevation in agreement with changes in wood production. A cross-validation modelling approach demonstrated the ability of LSP to predict average BAI and its interannual variability. Merging sites into bioclimatic groups improved models by amplifying the signal in growth or LSP. NDVI had highest performances when informing on BAI trends; WDRVI and EVI were mostly selected for modelling mean and interannual BAI. WDRVI association with tree rings, tested in this study for the first time, showed that this VI is highly promising for studying forest dynamics. MODIS LSP can quantify forest functioning changes across landscapes and model interannual spatial variations and trends in productivity dynamics under climate change.

Assessment of ecological restoration projects under water limits: Finding a balance between nature and human needs.

Revegetation has significantly contributed to improvements in ecosystem services, such as carbon sequestration and soil retention. Yet, vegetation expansion in water-limited regions may generate conflict of water demand between nature and humans. Present studies are still lacking when it comes to identifying the permissible vegetation capacity, i.e. net primary productivity (NPP) threshold, based on the local water resources limits, and further proposing adjustment and optimization strategies to keep water use balanced in anthropogenic-biological systems. Under such a circumstance, this study assesses the difference between the actual NPP and NPP thresholds at regional and ecosystem scales in China. The results show that 8 out of 31 provinces have their provincial actual NPP above the regional NPP thresholds, mainly concentrated in northern China between 400 and 800 mm iso-precipitation line, i.e. North China Plain (Beijing-Tianjin-Hebei), the middle reaches of the Yellow River Basin (Shaanxi and Henan provinces), and the Northeast China (Heilongjiang, Jilin and Liaoning). Forest ecosystems dominate the difference between the actual total woodland and grassland ecosystems NPP and the permissible NPP thresholds in these regions, ranging from 67% (Beijing) to 99% (Tianjin). If the current vegetation intensity in these regions remains unchanged, the areas of woodland and grassland ecosystems should be optimized 0-48% and 0-100% of their present areas to balance the water demand between the ecosystems and humans, without considering the potential consequence of climate change and soil erosion. Although 23 provinces have their regional actual NPP below their permissible NPP thresholds, 6 out of 23 provinces still have their woodland and grassland ecosystems NPP above the corresponding NPP thresholds, mainly focusing on the Northwestern China north over the 400 mm iso-precipitation line, including Inner Mongolia, Qinghai, Hainan, Shanxi, Gansu and Xinjiang. Forest ecosystems also dominate the negative NPP differences in these regions, ranging from 91% (Inner Mongolia) to 46% (Gansu). These reveal the hidden and potential pressure in the 6 provinces to balance limited water resources in the local anthropogenic-biological system. This study provides a method to assess the water-resources permissible NPP threshold and further proposes the specific adjustment and optimization plans for the areas with actual NPP above the corresponding NPP thresholds, which can provide guidance for ecological restoration program implementations in a more sustainable way.

Spatial and temporal distribution characteristics of carbon emissions and their drivers in shrinking cities in China: Empirical evidence based on the NPP/VIIRS nighttime lighting index.

Shrinking cities are a category of cities characterized by population loss, and the environmental problems of these cities are often neglected. Using panel data from 2012 to 2019, this paper investigates the spatial and temporal distribution characteristics of carbon emissions in shrinking cities in China and the driving factors. The results find that: (1) From 2012 to 2019, carbon emissions tend to increase in shrinking cities and decrease in non-shrinking cities. Due to earlier industrial development and ecological neglect, shrinking cities in Northeast China have higher carbon emissions than other regions. (2) Population size, industrial structure and public services promote the growth of carbon emissions in shrinking cities. The influence of living environment on carbon emissions in shrinking cities is not significant. There is an environmental Kuznets curve (EKC) relationship between economic level and carbon emission. (3) In shrinking cities, the increase in commuting time and distance due to spatial expansion promotes the growth of carbon emissions. Foreign investment decreases with the loss of population, which reduces carbon emissions. Technological progress gradually declines as investment in science and technology decreases, which makes carbon emissions grow. This paper clarifies the driving factors of carbon emissions in shrinking cities in China, and therefore, the findings of this paper have important reference value for the formulation of carbon reduction policies in shrinking cities in developing countries.

Sulfated Polysaccharides from Macroalgae Are Potent Dual Inhibitors of Human ATP-Hydrolyzing Ectonucleotidases NPP1 and CD39.

Extracellular ATP mediates proinflammatory and antiproliferative effects via activation of P2 nucleotide receptors. In contrast, its metabolite, the nucleoside adenosine, is strongly immunosuppressive and enhances tumor proliferation and metastasis. The conversion of ATP to adenosine is catalyzed by ectonucleotidases, which are expressed on immune cells and typically upregulated on tumor cells. In the present study, we identified sulfopolysaccharides from brown and red sea algae to act as potent dual inhibitors of the main ATP-hydrolyzing ectoenzymes, ectonucleotide pyrophosphatase/phosphodiesterase-1 (NPP1) and ecto-nucleoside triphosphate diphosphohydrolase-1 (NTPDase1, CD39), showing nano- to picomolar potency and displaying a non-competitive mechanism of inhibition. We showed that one of the sulfopolysaccharides tested as a representative example reduced adenosine formation at the surface of the human glioblastoma cell line U87 in a concentration-dependent manner. These natural products represent the most potent inhibitors of extracellular ATP hydrolysis known to date and have potential as novel therapeutics for the immunotherapy of cancer.