The paper aims to investigate the influencing factors that drive the temporal and spatial differences of CO
2
emissions for the transportation sector in China. For this purpose, this study adopts a ...Logistic Mean Division Index (LMDI) model to explore the driving forces of the changes for the transport sector’s CO
2
emissions from a temporal perspective during 2000–2017 and identifies the key factors of differences in the transport sector’s CO
2
emissions of China’s 15 cities in four key years (i.e., 2000, 2005, 2010, and 2017) using a multi-regional spatial decomposition model (M-R). Based on the empirical results, it was found that the main forces for affecting CO
2
emissions of the transport sector are not the same as those from temporal and spatial perspectives. Temporal decomposition results show that the income effect is the dominant factor inducing the increase of CO
2
emissions in the transport sector, while the transportation intensity effect is the main factor for curbing the CO
2
emissions. Spatial decomposition results demonstrate that income effect, energy intensity effect, transportation intensity effect, and transportation structure effect are important factors which result in enlarging the differences in city-level CO
2
emissions. In addition, the less-developed cities and lower energy efficiency cities have greater potential to reduce CO
2
emissions of the transport sector. Understanding the feature of CO
2
emissions and the influencing factors of cities is critical for formulating city-level mitigation strategies of the transport sector in China. Overall, it is expected that the level of economic development is the main factor leading to the differences in CO
2
emissions from a spatial-temporal perspective
.
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•Inkjet system used to renew a liquid electrode surface.•Low-viscosity carbon fluid prepared with spherical graphite powder.•First trial of inkjet polarography.
A single nozzle ...piezoelectric inkjet device was introduced for polarography using a dropping carbon fluid electrode (DCFE). The viscosity of the carbon fluid prepared by mixing a spherical graphite powder and a perfluoroalkane oil was low enough for it to be ejected by the inkjet system. The periodic renewal of the DCFE was achieved at a frequency of 1 Hz with a constant droplet size (about 2 mm). A polarogram of ferrocenecarboxylate with a limiting current was observed.
Selenium levels can regulate the function of T cells, macrophages, B cells, natural killer cells and other immune cells. However, the effect of selenium on the immune function of dendritic cells ...(DCs) isolated from selenium-supplemented mice is unknown. In this study, C57BL/6J mice were randomly divided into three groups and fed diets containing low (0.08 ppm), medium (0.25 ppm) or high (1 ppm) selenium levels for 8 weeks. Immature (imDCs) and mature (mDCs) dendritic cells were then isolated from the bone marrow. Next, the migration, phagocytic capacity and mixed lymphocyte reaction (MLR) for imDCs and mDCs were detected by transwell and flow cytometry. The levels of C-C chemokine receptor type 7 (CCR7), major histocompatibility complex II (MHCII) and reactive oxygen species (ROS) were assayed by flow cytometry. F-actin and superoxide dismutase (SOD) activity was detected by fluorescence microscopy and SOD assay kit, respectively. In addition, the extracellular signal-regulated kinase (ERK), Akt, Ras homolog gene family member A/Rho-associated protein kinase (RhoA/ROCK) signalling, selenoprotein K (SELENOK) and glutathione peroxidase 1 (GPX1) levels were measured by western blot analysis. The results indicated that selenium deficiency enhanced the migration of imDCs by ROS and SELENOK-mediated ERK, Akt and RhoA/ROCK pathways but impaired the antigen uptake of imDCs. Although a high selenium level inhibited the migration of imDCs, it had no effect on phagocytic capacity. For mDCs, low selenium levels impaired free migration, and high levels inhibited the chemotactic migration involved in F-actin and CCR7, respectively. Low and high selenium levels impaired the MLR by inhibiting MHCII surface localisation, which might be related to ROS- and SELENOK-mediated ERK, Akt and RhoA/ROCK signalling pathways. In summary, selenium may regulate the immune function of mouse DCs through the ROS- and SELENOK-mediated ERK, Akt and RhoA/ROCK signalling.
Selenium is an essential trace element that can regulate the function of immnue cells via selenoproteins. However, the effects of selenium on human dendritic cell (DCs) remain unclear. Thus, ...selenoprotein levels in monocytes, immature DCs (imDCs) and mature DCs (mDCs) treated with or without Na
2
SeO
3
were evaluated using RT-PCR, and then the immune function of imDCs and mDCs was detected by flow cytometry, cell counting and the CCK8 assay. In addition, the effects of Se on cytokine and surface marker expression were investigated by RT-PCR. The results revealed different expression levels of selenoprotein in monocytes, imDCs and mDCs, and selenoproeins could be regulated by Se. Moreover, it was indicated that anti-phagocytic activity was improved by 0.1 µM Se, whereas it was suppressed by 0.2 µM Se in imDCs; The migration of imDCs and mDCs was improved by 0.1 µM Se, whereas their migration was inhibited by treatment with 0.05 or 0.2 µM Se; The mixed lymphocyte reaction of mDCs was improved by 0.1 µM Se, and it was inhibited by 0.05 and 0.2 µM Se. In addition, 0.1 µM Se improved the immune function of DCs through the regulation of
CD80
,
CD86
,
IL12-p35
and
IL12-p40
. Wheres 0.05 and 0.2 µM Se impaired immune function of DCs by up-regulation of interleukin (
IL-10
) in imDCs and down-regulation of
CD80
,
CD86
,
IL12-p35
and
IL12-p40
in mDCs. In conclusion, 0.1 µM Se might improve the immune function of human DCs through selenoproteins.
Dendritic cells (DCs) are the most potent antigen-presenting cells. Upon maturation, DCs express costimulatory molecules and migrate to the lymph nodes to present antigens to T cells. The actin ...cytoskeleton plays key roles in multiple aspects of DC functions. However, little is known about the mechanisms and identities of actin-binding proteins that control DC maturation and maturation-associated functional changes. Tropomodulin1 (Tmod1), an actin-capping protein, controls actin depolymerization and nucleation. We found that Tmod1 was expressed in bone marrow-derived immature DCs and was significantly upregulated upon lipopolysaccharide (LPS)-induced DC maturation. By characterizing LPS-induced mature DCs (mDCs) from Tmod1 knockout mice, we found that compared with
mDCs, Tmod1-deficient mDCs exhibited lower surface expression of costimulatory molecules and chemokine receptors and reduced secretion of inflammatory cytokines, suggesting that Tmod1 deficiency retarded DC maturation. Tmod1-deficient mDCs also showed impaired random and chemotactic migration, deteriorated T-cell stimulatory ability, and reduced F-actin content and cell stiffness. Furthermore, Tmod1-deficient mDCs secreted high levels of IFN-β and IL-10 and induced immune tolerance in an experimental autoimmune encephalomyelitis (EAE) mouse model. Mechanistically, Tmod1 deficiency affected TLR4 signaling transduction, resulting in the decreased activity of MyD88-dependent NFκB and MAPK pathways but the increased activity of the TRIF/IRF3 pathway. Rescue with exogenous Tmod1 reversed the effect of Tmod1 deficiency on TLR4 signaling. Therefore, Tmod1 is critical in regulating DC maturation and immune functions by regulating TLR4 signaling and the actin cytoskeleton. Tmod1 may be a potential target for modulating DC functions, a strategy that would be beneficial for immunotherapy for several diseases.
Interlukin-10 (IL-10) is an immunomodulatory cytokine which predominantly induces immune-tolerance. It has been also identified as a major cytokine in the tumor microenvironment that markedly ...mediates tumor immune escape. Previous studies on the roles of IL-10 in tumor immunosuppression mainly focus on its biochemical effects. But the effects of IL-10 on the biophysical characteristics of immune cells are ill-defined. Dendritic cells (DCs) are the most potent antigen-presenting cells and play a key role in the anti-tumor immune response. IL-10 can affect the immune regulatory functions of DCs in various ways. In this study, we aim to explore the effects of IL-10 on the biophysical functions of mature DCs (mDCs). mDCs were treated with different concentrations of IL-10 and their biophysical characteristics were identified. The results showed that the biophysical properties of mDCs, including electrophoresis mobility, osmotic fragility and deformability, as well as their motilities, were impaired by IL-10. Meanwhile, the cytoskeleton (F-actin) of mDCs was reorganized by IL-10. IL-10 caused the alternations in the expressions of fasin1 and profilin1 as well as the phosphorylation of cofilin1 in a concentration-dependent fashion. Moreover, Fourier transformed infrared resonance data showed that IL-10 made the status of gene transcription and metabolic turnover of mDCs more active. These results demonstrate a new aspect of IL-10's actions on the immune system and represent one of the mechanisms for immune escape of tumors. It may provide a valuable clue to optimize and improve the efficiency of DC-based immunotherapy against cancer.
The explosive increase in the number of images on the Internet has brought with it the great challenge of how to effectively index, retrieve, and organize these resources. Assigning proper tags to ...the visual content is key to the success of many applications such as image retrieval and content mining. Although recent years have witnessed many advances in image tagging, these methods have limitations when applied to high-quality and large-scale training data that are expensive to obtain. In this paper, we propose a novel semantic neighbor learning method based on user-contributed social image datasets that can be acquired from the Web＇s inexhaustible social image content. In contrast to existing image tagging approaches that rely on high-quality image-tag supervision, we acquire weak supervision of our neighbor learning method by progressive neighborhood retrieval from noisy and diverse user-contributed image collections. The retrieved neighbor images are not only visually alike and partially correlated but also semantically related. We offer a step-by-step and easy-to-use implementation for the proposed method. Extensive experimentation on several datasets demonstrates that the performance of the proposed method significantly outperforms others.
The transport sector is the fourth largest industrial CO
2
emitter in China, next to power sector, iron and steel industries, and nonmetallic mineral product industry, and plays an important role in ...reducing China’s CO
2
emissions. In this study, a temporal decomposition analysis model, i.e., Logistic Mean Division Index (LMDI), is developed to analyze the influencing factors of CO
2
emissions in China’s transport sector during 2000–2015. Then, a multi-regional spatial decomposition model is employed to identify the key factors to induce the differences in CO
2
emissions of China’s 30 regional transport sectors in 2000, 2005, 2010, and 2015. Based on the empirical results, we find that both in the temporal and spatial perspectives, the main factors that affect CO
2
emissions in the transport sector are the same ones. From the temporal perspective, the income effect is the dominant factor increasing CO
2
emissions of transport sector, while energy intensity effect and transportation structure effect are the key influencing factors that curb the CO
2
emissions of China’s transport sector, during the whole study period. From the spatial perspective, the income effect, energy intensity effect, and transportation structure effect are the key influencing factors that enlarge the gap of CO
2
emissions of various transport sectors in the key study years. More importantly, the less-developed regions and high energy intensity regions (i.e., the lower energy efficiency regions) are identified to have the great potential to reduce CO
2
emissions of transport sector. Therefore, differentiated mitigation measures and interregional collaborations are encouraged to reduce transport sector’s CO
2
emissions in China.
Mitigation pathways play a vital role in realizing carbon neutrality. However, the complex relationships within the social system remain unclear, particularly the economic and energy effects on a ...macroeconomic level and the critical sectors. This study assesses the economic cost and energy transition effects of different policy scenarios based on an improved dynamic computable general equilibrium (CGE) model. The results show that (1) energy structure optimization (E2) and integrated policy scenarios could achieve the carbon neutrality target. In addition, carbon sink is another critical factor that can offset the remaining emissions. (2) Projected GDP losses in 2060 fluctuate from 0.7% in the carbon trading scenario (C1) to 4.92% in E2. Energy structure optimization and energy technology scenarios exert greater impacts on the power and iron and steel sectors. (3) The energy structure optimization scenario (high renewable HR: 9.23 billion tce) has the most significant impact on energy consumption, whereas the energy technology policy scenario (E2: 9.48 billion tce) has the smallest effect on energy consumption. (4) One integrated policy scenario (HRC4E2: 7.1 × 104 tons) has the most prominent air pollutant reduction potential, followed by LRC2E2 (25.0 × 104 tons) and HRC3E1 (10.1 × 104 tons).
•An improved CGE model framework was developed.•Analyze economic cost, energy transition and pollutant effect towards carbon neutrality.•The integrated policy scenarios are crucial in achieving carbon neutrality.•The CCS technology helps long-term CO2 emissions reduction in China.
To formulate efficient emission reduction policies, we explore the driving forces of CO2 emissions from the transport sector of four municipalities in China during 2000–2017 based on the ...temporal-spatial decomposition analysis model. The key factors causing the differences in CO2 emissions will be investigated in important years (i.e., 2000, 2005, 2010, and 2017). Two main results are found: (1) Energy intensity, as well as transportation intensity, is the dominant restraining factor confronting the transport sector’s CO2 emissions, while the income effect is reversed. (2) The results of the analysis further show what drives different emission levels (e.g., income effect, energy structure, and transportation structure) and four municipalities have greater potential in the reduction of CO2 emissions. We further discuss the root causes of the spatial-temporal differences in carbon emissions in the transport sector and analyse their future trends in detail. Based on this, we propose to pay attention to strengthen coordinated emission reduction, optimize the transportation mode, adjust the energy consumption structure, and select emission reduction strategies according to local conditions. In addition, emission reductions in the transportation sector are also affected by various factors such as social systems and transformation costs, and further research is needed in the future.
•A spatial-temporal analysis is conducted to study China's transport emissions.•Bilateral–regional spatial decomposition model to decompose factors are used.•Intensities of energy and transport are crucial factors restraining CO2 emissions.•The income effect is the main contributor to increase CO2 emissions.•Municipalities have greater potential in the reduction of CO2 emissions.
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