Socioeconomic impact assessment of China's CO2 emissions peak prior to 2030

China is the largest emitter of carbon emissions in the world. In this paper, we present an Integrated Model of Economy and Climate (IMEC), an optimization model based on the input-output model. The model is designed to assess the tradeoff between emission deceleration and economic growth. Given that China's projected average growth rate will exceed 5% over the next two decades, we find that China may reach its peak CO2 emissions levels by 2026. According to this scenario, China's carbon emissions will peak at 11.20 Gt in 2026 and will then decline to 10.84 Gt in 2030. Accordingly, approximately 22 Gt of CO2 will be removed from 2015 to 2035 relative to the scenario wherein China's CO2 emissions peak in 2030. While this earlier peaking of carbon emissions will result in a decline in China's GDP, several sectors, such as Machinery and Education, will benefit. In order to reach peak CO2 emissions by 2026, China needs to reduce its annual GDP growth rate to less than 4.5% by 2030 and decrease energy and carbon intensity levels by 43% and 45%, respectively, from 2015 to 2030

Identification of subtype-specific metastasis-related genetic signatures in sarcoma

Background: Sarcomas are heterogeneous rare malignancies constituting approximately 1% of all solid cancers in adults and including more than 70 histological and molecular subtypes with different pathological and clinical development characteristics. Method: We identified prognostic biomarkers of sarcomas by integrating clinical information and RNA-seq data from TCGA and GEO databases. In addition, results obtained from cell cycle, cell migration, and invasion assays were used to assess the capacity for Tanespimycin to inhibit the proliferation and metastasis of sarcoma. Results: Sarcoma samples (N = 536) were divided into four pathological subtypes including DL (dedifferentiated liposarcoma), LMS (leiomyosarcoma), UPS (undifferentiated pleomorphic sarcomas), and MFS (myxofibrosarcoma). RNA-seq expression profile data from the TCGA dataset were used to analyze differentially expressed genes (DEGs) within metastatic and non-metastatic samples of these four sarcoma pathological subtypes with DEGs defined as metastatic-related signatures (MRS). Prognostic analysis of MRS identified a group of genes significantly associated with prognosis in three pathological subtypes: DL, LMS, and UPS. ISG15, NUP50, PTTG1, SERPINE1, and TSR1 were found to be more likely associated with adverse prognosis. We also identified Tanespimycin as a drug exerting inhibitory effects on metastatic LMS subtype and therefore can serve a potential treatment for this type of sarcoma. Conclusions: These results provide new insights into the pathogenesis, diagnosis, treatment, and prognosis of sarcomas and provide new directions for further study of sarcoma

A multi-regional input-output table mapping China's economic outputs and interdependencies in 2012.

Multi-regional input-output (MRIO) models are one of the most widely used approaches to analyse the economic interdependence between different regions. We utilised the latest socioeconomic datasets to compile a Chinese MRIO table for 2012 based on the modified gravity model. The MRIO table provides inter-regional and inter-sectoral economic flows among 30 economic sectors in China's 30 regions for 2012. This is the first MRIO table to reflect China's economic development pattern after the 2008 global financial crisis. The Chinese MRIO table can be used to analyse the production and consumption structure of provincial economies and the inter-regional trade pattern within China, as well as function as a tool for both national and regional economic planning. The Chinese MRIO table also provides a foundation for extensive research on environmental impacts by linking industrial and regional output to energy use, carbon emissions, environmental pollutants, and satellite accounts

Factors influencing cognitive function in patients with Huntington's disease from China: A cross-sectional clinical study.

BACKGROUND AND AIM Huntington's disease (HD) is an autosomal dominant inherited neurodegenerative disorder caused by CAG repeats expansion. Cognitive decline contributes to the loss of daily activity in manifest HD. We aimed to examine the cognition status in a Chinese HD cohort and explore factors influencing the diverse cognitive domains. METHODS A total of 205 participants were recruited in the study with the assessment by neuropsychological batteries, including the mini-mental state examination (MMSE), Stroop test, symbol digit modalities test (SDMT), trail making test (TMT), verbal fluency test (VFT), and Hopkins verbal learning test-revised, as well as motor and psychiatric assessment. Pearson correlation and multiple linear regression models were applied to investigate the correlation. RESULTS Only 41.46% of patients had normal global function first come to our center. There was a significantly difference in MMSE, Stroop test, SDMT, TMT, and VFT across each stage of HD patients (p < .05). Apathy of PBA-s was correlated to MMSE, animal VFT and Stroop-interference tests performance. Severity of motor symptoms, functional capacity, age, and age of motor symptom onset were correlated to all neuropsychological scores, whereas education attainment and diagnostic delay were correlated to most neuropsychological scores except TMT. Severity of motor symptoms, functional capacity, and education attainment showed independent predicting effect (p < .05) in diverse cognitive domains. CONCLUSION Cognitive impairment was very common in Chinese HD patients at the first visit and worse in the patients in advanced phase. The severity of motor symptoms and functional capacity were correlated to the diverse cognitive domains

The Designer Antimicrobial Peptide A-hBD-2 Facilitates Skin Wound Healing by Stimulating Keratinocyte Migration and Proliferation

Background/Aims: Antimicrobial peptides are effective promoters of wound healing but are susceptible to degradation. In this study, we replaced the GIGDP unit on the N-terminal of the endogenous human antimicrobial peptide hBD-2 with APKAM to produce A-hBD-2 and analyzed the effect on wound healing both in vitro and in vivo. Methods: The effects of A-hBD-2 and hBD-2 on cytotoxicity and proliferation in keratinocytes were assessed by Cell Counting Kit-8 assay. The structural stability and antimicrobial activity of hBD-2 and A-hBD-2 were evaluated against Staphylococcus aureus. RNA and proteins levels were evaluated by real-time PCR and western blotting, respectively. Cell migration was evaluated using a transwell assay. Cell cycle analysis was performed by flow cytometry. Wound healing was assessed in Sprague-Dawley rats. Epidermal thickness was evaluated by hematoxylin and eosin staining. Results: We found that hBD-2 exhibited cytotoxicity at high concentrations and decreased the structural stability in the presence of high sodium chloride concentrations. A-hBD-2 exhibited increased structural stability and antimicrobial activity, and had lower cytotoxicity in keratinocytes. A-hBD-2 increased the migration and proliferation of keratinocytes via phosphorylation of EGFR and STAT3 and suppressed terminal differentiation of keratinocytes. We also found that A-hBD-2 elicited mobilization of intracellular Ca2+ and stimulated keratinocytes to produce pro- and anti-inflammatory cytokines and chemokines via phospholipase C activation. Furthermore, A-hBD-2 promoted wound healing in vivo. Conclusion: Our data suggest that A-hBD-2 may be a promising candidate therapy for wound healing

Photometric redshift estimation of galaxies in the DESI Legacy Imaging Surveys

The accurate estimation of photometric redshifts plays a crucial role in accomplishing science objectives of the large survey projects. The template-fitting and machine learning are the two main types of methods applied currently. Based on the training set obtained by cross-correlating the DESI Legacy Imaging Surveys DR9 galaxy catalogue and SDSS DR16 galaxy catalogue, the two kinds of methods are used and optimized, such as EAZY for template-fitting approach and CATBOOST for machine learning. Then the created models are tested by the cross-matched samples of the DESI Legacy Imaging SurveysDR9 galaxy catalogue with LAMOST DR7, GAMA DR3 and WiggleZ galaxy catalogues. Moreover three machine learning methods (CATBOOST, Multi-Layer Perceptron and Random Forest) are compared, CATBOOST shows its superiority for our case. By feature selection and optimization of model parameters, CATBOOST can obtain higher accuracy with optical and infrared photometric information, the best performance ($MSE=0.0032$, $\sigma_{NMAD}=0.0156$ and $O=0.88$ per cent) with $g \le 24.0$, $r \le 23.4$ and $z \le 22.5$ is achieved. But EAZY can provide more accurate photometric redshift estimation for high redshift galaxies, especially beyond the redhisft range of training sample. Finally, we finish the redshift estimation of all DESI DR9 galaxies with CATBOOST and EAZY, which will contribute to the further study of galaxies and their properties.Comment: Accepted for publication in MNRAS. 14 pages, 9 figures, 11 table

Origin and Radiative Forcing of Black Carbon Aerosol: Production and Consumption Perspectives.

Air pollution, a threat to air quality and human health, has attracted ever-increasing attention in recent years. In addition to having local influence, air pollutants can also travel the globe via atmospheric circulation and international trade. Black carbon (BC), emitted from incomplete combustion, is a unique but representative particulate pollutant. This study tracked down the BC aerosol and its direct radiative forcing to the emission sources and final consumers using the global chemical transport model (MOZART-4), the rapid radiative transfer model for general circulation simulations (RRTM), and a multiregional input-output analysis (MRIO). BC was physically transported (i.e., atmospheric transport) from western to eastern countries in the midlatitude westerlies, but its magnitude is near an order of magnitude higher if the virtual flow embodied in international trade is considered. The transboundary effects on East and South Asia by other regions increased from about 3% (physical transport only) to 10% when considering both physical and virtual transport. The influence efficiency on East Asia was also large because of the comparatively large emission intensity and emission-intensive exports (e.g., machinery and equipment). The radiative forcing in Africa imposed by consumption from Europe, North America, and East Asia (0.01 Wm-2) was even larger than the total forcing in North America. Understanding the supply chain and incorporating both atmospheric and virtual transport may improve multilateral cooperation on air pollutant mitigation both domestically and internationally

Pattern changes in determinants of Chinese emissions

Chinese economy has been recovering slowly from the global financial crisis, but it cannot achieve the same rapid development of the pre-recession period. Instead, the country has entered a new phase of economic development – a "new normal". We use a structural decomposition analysis (SDA) and environmental input-output analysis (IOA) to estimate the determinants of China's carbon emission changes during 2005-2012. China's imports are linked to a global multi-regional input-output (MRIO) model based on the Global Trade and Analysis Project (GTAP) database to calculate the embodied CO2 emissions in imports. We find that the global financial crisis has affected the drivers of China's carbon emissions growth. From 2007 to 2010, the CO2 emissions induced by China's exports dropped, whereas emissions induced by capital formation grew rapidly. In the "new normal", the strongest factors that offset CO2 emissions have shifted from efficiency gains to structural upgrading. Efficiency was the strongest factor offsetting China's CO2 emissions before 2010 but drove a 1.4% increase in emissions in the period 2010-2012. By contrast, production structure and consumption patterns caused a 2.6% and 1.3% decrease, respectively, in China's carbon emissions from 2010 to 2012. In addition, China tends to shift gradually from an investment to a consumption-driven economy. The proportion of CO2 emissions induced by consumption had a declining trend before 2010 but grew from 28.6% to 29.1% during 2010-2012

Single nucleotide polymorphisms at the TRAF1/C5 locus are associated with rheumatoid arthritis in a Han Chinese population

<p>Abstract</p> <p>Background</p> <p>Genetic variants in <it>TRAF1C5 </it>and <it>PTPN22 </it>genes have been shown to be significantly associated with arthritis rheumatoid in Caucasian populations. This study investigated the association between single nucleotide polymorphisms (SNPs) in <it>TRAF1/C5 </it>and <it>PTPN22 </it>genes and rheumatoid arthritis (RA) in a Han Chinese population. We genotyped SNPs rs3761847 and rs7021206 at the <it>TRAF1/C5 </it>locus and rs2476601 SNP in the <it>PTPN22 </it>gene in a Han Chinese cohort composed of 576 patients with RA and 689 controls. The concentrations of anti-cyclic citrullinated peptide antibodies (CCP) and rheumatoid factor (RF) were determined for all affected patients. The difference between the cases and the controls was compared using <it>χ</it>²analysis.</p> <p>Results</p> <p>Significant differences in SNPs rs3761847 and rs7021206 at <it>TRAF1/C5 </it>were observed between the case and control groups in this cohort; the allelic p-value was 0.0018 with an odds ratio of 1.28 for rs3761847 and 0.005 with an odds ratio of 1.27 for rs7021206. This significant association between rs3761847 and RA was independent of the concentrations of anti-CCP and RF. No polymorphism of rs2476601 was observed in this cohort.</p> <p>Conclusions</p> <p>We first demonstrated that genetic variants at the <it>TRAF1/C5 </it>locus are significantly associated with RA in Han Chinese, suggesting that <it>TRAF1/C5 </it>may play a role in the development of RA in this population, which expands the pathogenesis role of <it>TRAF1/C5 </it>in a different ethnicity.</p