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With the appearance of potential risks and benefits brought about by environmental, social, and governance factors, various industries are aware of the importance of sustainable investment. Undeniably, sustainable investing has become an important force for change in different industries, especially in financial markets. However, the current state of research in this field remains unexplored, with the specific research focus and the role of countries in economic globalization and sustainable development remaining undocumented. To address this issue, this article presents a bibliometric analysis of sustainable investments in financial markets using data extracted from the Scopus database. The study explores the current state of research on sustainable investing in financial markets and identifies potential directions for future research by analysing a total of 1,794 academic articles published in leading finance and sustainability journals between 1982 and April 2023. This analysis further examines the relationship between national academic collaboration and key research themes. Analysis of the results shows that the United States, China and the United Kingdom rank among the top three in the number of publications in the field of sustainable investment research. Developing countries such as China and India are also gradually increasing their attention in this field and gradually assuming corresponding responsibilities. The keyword co-occurrence analysis further highlights the vital role of the core concepts of “Investment”, “Commerce”, “Costs” and “Climate Change” and “Energy policy” in sustainable investment research and practice. The findings of this quantitative bibliographic analysis will be of significant value to researchers, policymakers and practitioners interested in sustainable investing and its role in shaping the future of finance. [ABSTRACT FROM AUTHOR]

Global climate change and land use change are the two main factors influencing the hydrological cycle. Under future climate change conditions, the consequential change of hydrological extremes and design flood values of basins will directly influence the operation and dispatch of cascade reservoirs. Therefore, studying the impact of climate change on design flood values is crucial for flood defense and hydropower output increment. Annual maximum (AM) sampling was employed to obtain the annual maximum daily flood series of the Xiaodeshi station in the future (up to the year 2100) based on soil and water assessment tool (SWAT) modeling of daily runoff. Then, a time-varying moment model with time and meteorological factors taken as the covariates was developed, and the parameters were optimized based on the particle swarm optimization (PSO) algorithm. Subsequently, the design flood values with different frequencies were calculated, varying annually from 2022 to 2100. To align with the present reservoir operation protocol, a new method was developed based on the equivalent reliability (ER) principle to calculate the unique design flood values based on the dynamic outputs. The results indicate that, compared with using time as the covariate, the time-varying moment model with meteorological factors as covariates is physically more significant and yields more reasonable results. Under future climate change conditions, the design values decrease slightly under the representative concentration pathways (RCP)2.6 and RCP4.5 concentration path for the low frequencies (exceedance probability of 0.1% and 0.2%), with increases for other frequencies (Yan et al. 2017). They increase under the RCP8.5 concentration paths for all, especially medium, frequencies (exceedance probability of 5% and 10%). By combining the time-varying moment model with the equal reliability method, more reliable design flood values can be obtained. Global climate change is the main driving factor influencing the hydrological cycle and water resource allocation. The Yalong River Basin is an important hydropower base in China, with a total planned installed capacity of 30 million kilowatts, raising the question of whether the cascade reservoirs will be operated safely under the dispatching rules set based on the historical flow regime. In this study, the authors analyzed and evaluated the situation of flood defense at the selected representative station. The authors developed a new method to cope with the challenge of flood defense risk evaluation under future climate change conditions based on special methods and principles. The results indicate that the frequency of floods in the Yalong River basin will increase owing to future climate change, leading to a greater risk on flood control. Therefore, a modification on the operation and management rules of cascade hydropower stations in the basin is unavoidable. [ABSTRACT FROM AUTHOR]

China is the largest CO2 emitter in the world and announced that carbon peak and neutral targets will be achieved before 2030 and 2060, respectively. A retrospective analysis of past CO2 emissions and their drivers is important for the actions of peaking CO2 emissions before 2030 in China. CO2 emissions from energy use (coal, oil, and natural gas) and cement production from 2000 to 2020 were calculated first, and their drivers were decomposed into economic and population growth, energy intensity, and emission coefficient by logarithmic mean Divisa index (LMDI) analysis in this study. China's CO2 emissions increased nearly threefold from 3385 in 2000 to 10,788 million tonnes (Mt) in 2020, with a decline from 2013 to 2016. Coal was the major emission sector contributing more than 70% in most years, while natural gas emissions increased nearly 13 times from 53 to 723 Mt in the two decades, although its contribution only accounted for 6.7% in 2020. Economic growth was the major positive driver, while energy intensity reduction was the major negative driver of the emission increments by year and by the Five Year Plan (FYP). Emission coefficient reduction gradually became important due to its negative effect, especially in the 13th FYP, which offset ~ 30% of the emissions induced by economic growth. The projections of CO2 emissions in 2025, 2030, and 2035 could be 11,596 ± 582, 11,774 ± 621, and 11,401 ± 672 Mt, respectively, suggesting that China's carbon emissions could peak around 2030 with an increment of ~ 1000 Mt on the 2020 levels. Under the sustainable growth of the economy and population, it is possible to reduce the carbon peak value or achieve peak time earlier through the additional reduction of energy intensity and emission coefficient by technological progress and energy alternatives such as non-fossil fuels. [ABSTRACT FROM AUTHOR]

While the reduction in anthropogenic emissions due to Coronavirus disease 2019 (COVID‐19) lockdown in China and its impact on air quality have been reported extensively, its impact on ambient carbon dioxide (CO2) concentrations is still yet to be assessed. In this study, the impact of emission reductions on spatiotemporal changes of CO2 concentrations during the COVID‐19 pandemic was quantified in the Yangtze River Delta region (YRD), using high‐resolution dynamic emission inventory and the Weather Research and Forecasting model coupled with the Vegetation Photosynthesis and Respiration Model (WRF‐VPRM). The simulated CO2 concentrations from dynamic emission inventory shows a better agreement with surface observations compared with the Open‐source Data Inventory for Anthropogenic CO2 and Emission Database for Global Atmospheric Research emission, providing confidence in the quantification of CO2 concentrations variations. Our results show that emission reductions during the COVID‐19 pandemic lead to a CO2 decrease by 4.6 ppmv (−1.1%) in Shanghai and 3.1 ppmv (−0.7%) in YRD region. For the column‐averaged CO2 concentrations (denoted as XCO2), it also decreases by 0.20 ppmv (−0.05%) in Shanghai and 0.15 ppmv (−0.04%) in YRD region. Furthermore, emission reductions from transportation and industry are major contributors to the decline in CO2 concentrations at the near surface, accounting for 45.8% (41.1%) and 34.9% (41.0%) in Shanghai (YRD). Our study deepens the understanding of the response of CO2 concentrations to different sectors, which is helpful for emission management and climate adaption policies. Plain Language Summary: Carbon dioxide (CO2) is the most important greenhouse gas in the atmosphere and has a profound impact on global climate change. It kept increasing over the last decades. Although previous studies have investigated the sources and sinks of air pollutants, the variations of CO2 concentrations at regional to national scales remains poorly understood owing to a lack of long‐term observations and limited modeling studies. High‐resolution CO2 emission inventory is in high demand in accurate CO2 simulations. This work integrates a high‐resolution dynamic emission inventory with WRF‐VPRM model to quantify the influence of reduced emissions from different sectors on the spatiotemporal changes of CO2 concentrations during the COVID‐19 pandemic. This modeling system can help to understand the response of CO2 concentrations to emissions and serves as a basis for atmospheric inversion of CO2 emissions. Key Points: High‐resolution CO2 dynamic emission inventory greatly improves CO2 simulations compared with Open‐source Data Inventory for Anthropogenic CO2 and Emission Database for Global Atmospheric ResearchAnthropogenic emission reductions cause CO2 concentrations decrease by 4.6 (3.1) ppmv in Shanghai (Yangtze River Delta) during the COVID‐19 pandemicIndustrial and transportation emissions mainly dominate the reduction in CO2 concentrations at the near surface and vertical altitude [ABSTRACT FROM AUTHOR]

The spatiotemporal characteristics of ozone pollution and increased human health risks in Central China were investigated using a long time series of ozone concentrations from 2014 to 2020. We found a gradual increase in ozone pollution, with the highest concentrations observed in the northeastern region. The spatial distribution of population density showed distinct patterns, with the northeastern and east-central regions coinciding with areas of high ozone concentrations. The study found an overall increasing trend in MDA8 ozone concentrations, with a regional average increase of 3.5 (μg m−3) per year, corresponding to a 4.4% annual increase. We observed a significant clustering of areas at a higher risk of premature mortality associated with long-term ozone exposure, particularly in the northeastern region. Estimated premature mortality due to ozone pollution in Central China between 2014 and 2020 shows an increasing trend from 2014 to 2019 and a decreasing trend in 2020 due to the occurrence of extreme ozone pollution and the subsequent recovery of ozone concentrations after the closures due to COVID-19. Premature mortality due to ozone exposure is affected by both ozone levels and the exposed population, with high correlation coefficients exceeding 0.95. The high total population (more than 220 million per year) and increasing ozone levels exacerbate the problem of premature mortality due to ozone pollution. This study improves our understanding of the impact of ozone pollution on human health and emphasizes the dynamic nature of ozone pollution and its impacts on human health over time. It underscores the need for further study and comprehensive action to mitigate these health risks. [ABSTRACT FROM AUTHOR]

With rapid economic development, extensive human activity has changed landscape patterns (LPs) dramatically, which has further influenced hydrological processes. However, the effects of LPs changes on hydrological processes, especially for the streamflow–sediment relationship in the subtropical monsoon climate zone, have not been reported. In our study, 10 watersheds with different sizes in the subtropical monsoon climate zone of southeastern China were chosen as the study area, and the effect of the 14 most commonly used landscape metrics (LMs) on 4 typical hydrological indices (water yields (WY), the runoff coefficient (RC), the soil erosion modulus (SEM), and the suspended sediment concentration (SSC)) were analyzed based on land use maps and hydrological data from 1990 to 2019. The results reveal that the LP characteristics within the study area have changed significantly. The number of patches and landscape shape indices were significantly positively correlated with watershed size (p < 0.01). For most watersheds, the largest patch index was negatively correlated with WY, RC, and SEM, and the perimeter area fractal dimension was positively correlated with WY, RC, SEM, and SSC. The effects of several LMs on the hydrological indices had scale effects. WY/RC and the interspersion and juxtaposition index were negatively correlated in most larger watersheds but were positively correlated in most smaller watersheds. Similar results were found for Shannon's diversity/evenness index and SEM. In general, an increase in a small patch of landscape and in landscape diversity would increase WY, the fragmentation of LPs would result in more soil erosion, and LPs would affect the relationship between streamflow and sediment yield. As a result, a proper decrease in landscape fragmentation and physical connectivity in the subtropical monsoon climate zone of southeastern China would benefit soil erosion prevention. These results enhance the knowledge about the relationship between LPs and hydrological processes in the subtropical monsoon climate zone of southeastern China and benefit local water and soil conservation efforts. [ABSTRACT FROM AUTHOR]

Background: This study aimed to better characterize the clinicopathologic characteristics, outcomes, and prognostic factors of AITL in China. Methods: We retrospectively analyzed 312 patients with AITL enrolled between January 2011 and December 2020 from five institutions in China. Results: The median age was 65 years, with 92.6% advanced stage, 59.7% elevated LDH, 46.1% anemia, and 44.0% hypergammaglobulinemia. The majority of patients (84.9%) received anthracycline‐based regimens with or without etoposide, and only 6.1% underwent autologous stem cell transplantation following first remission. The 5‐year OS and PFS estimates were 43.4% and 25.0% with no significant improvement of survival between patients treated during 2011–2015 and 2016–2020, respectively. Both the International Prognostic Index (IPI) and the prognostic index for PTCL, not otherwise specified (PIT), were predictive for OS. In multivariate analysis, age >70 years, elevated LDH, and albumin level <35 g/L were independent prognostic factors for OS. Combining these three factors, a novel prognostic model (the Chinese AITL score) was constructed, which stratified patients into low‐, intermediate‐, and high‐risk groups, with 5‐year OS rates of 69.0%, 41.5%, and 23.7%, respectively. This new model was successfully validated in an independent cohort. Conclusions: Patients with AITL were mainly treated with anthracycline‐based regimens, and the outcomes were still unsatisfactory in China. Our novel prognostic model may improve our ability to identify patients at different risks for alternative therapies. [ABSTRACT FROM AUTHOR]

The existing contradictory findings on the contribution of trading volume to volatility forecasting prompt us to seek new solutions to test the sequential information arrival hypothesis (SIAH). Departing from other empirical analyses that mainly focus on sophisticated testing methods, this research offers new insights into the volume‐volatility nexus by decomposing and reconstructing the trading activity into short‐run components that typically represent irregular information flow and long‐run components that denote extreme information flow in the stock market. We are the first to attempt at incorporating an improved empirical mode decomposition (EMD) method to investigate the volatility forecasting ability of trading volume along with the Heterogeneous Autoregressive (HAR) model. Previous trading volume is used to obtain the decompositions to forecast the future volatility to ensure an ex ante forecast, and both the decomposition and forecasting processes are carried out by the rolling window scheme. Rather than trading volume by itself, the results show that the reconstructed components are also able to significantly improve out‐of‐sample realized volatility (RV) forecasts. This finding is robust both in one‐step ahead and multiple‐step ahead forecasting horizons under different estimation windows. We thus fill the gap in studies by (1) extending the literature on the volume‐volatility linkage to EMD‐HAR analysis and (2) providing a clear view on how trading volume helps improve RV forecasting accuracy. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) and methane (CH4) are the two major radiative forcing factors of greenhouse gases. In this study, surface and column mole fractions of CO2 and CH4 were first measured at a desert site in Dunhuang, west China. The average column mole fractions of CO2 (XCO2) and CH4 (XCH4) were 413.00 ± 1.09 ppm and 1876 ± 6 ppb, respectively, which were 0.90 ppm and 72 ppb lower than their surface values. Diurnal XCO2 showed a sinusoidal mode, while XCH4 appeared as a unimodal distribution. Ground observed XCO2 and XCH4 were compared with international satellites, such as GOSAT, GOSAT-2, OCO-2, OCO-3, and Sentinel-5P. The differences between satellites and EM27/SUN observations were 0.26% for XCO2 and −0.38% for XCH4, suggesting a good consistency between different satellites and ground observations in desert regions in China. Hourly XCO2 was close to surface CO2 mole fractions, but XCH4 appeared to have a large gap with CH4, probably because of the additional chemical removals of CH4 in the upper atmosphere. It is necessary to carry out a long-term observation of column mole fractions of greenhouse gases in the future to obtain their temporal distributions as well as the differences between satellites and ground observations. [ABSTRACT FROM AUTHOR]

This research investigates the role of trading volume and data frequency in volatility forecasting by evaluating the performance of Generalized Autoregressive Conditional Heteroskedasticity Mixed‐Data Sampling (GARCH‐MIDAS), traditional GARCH, and intraday GARCH models. We take trading volume as the proxy for information flow and examine whether the Sequential Information Arrival Hypothesis (SIAH) is supported in the China stock market. The contributions of this study are as follows. (1) We provide a more consistent comparison to evaluate the forecasting ability of the MIDAS approach. (2) We extend the literature on the forecasting performance of trading volume to the GARCH‐MIDAS approach. (3) We present clear evidence to support that forecasting ability strongly relies upon data frequency. The empirical results show that: (1) GARCH‐MIDAS is not able to beat the traditional GARCH method when both are estimated by the same predictor sampled at different frequencies; (2) there is a positive relation between trading volume and volatility, but no clear evidence appears that SIAH holds in the China stock market; and (3) high‐frequency data are highly recommended for daily realized volatility (RV) forecasting, whereas intraday GARCH could significantly outperform traditional GARCH and GARCH‐MIDAS in volatility forecasting. [ABSTRACT FROM AUTHOR]

This research investigates the role of high-frequency data in volatility forecasting of the China stock market by particularly feeding different frequency return series directly into a large number of GARCH versions. The contributions of this research are as follows. 1) We provide clear evidence to support that the superiority of traditional time series models in volatility forecasting remains by taking advantage of high-frequency data. 2) We incorporate different distribution assumptions in GARCH models to capture the stylized facts of high-frequency data. The result shows that: 1) data frequency in GARCH application substantially influence the accuracy of volatility forecasting, as the higher the frequency is of the return series, the better are the forecasts provided; 2) non-normal distributions such as skewed student-t and generalized error distribution are more capable at reproducing the stylized facts of both intraday and daily return series than normal distribution; and 3) GARCH estimated by 5-min returns not only outperforms other GARCH alternatives, but also considerably beats RV-based models such as HAR and ARFIMA at volatility forecasting. [ABSTRACT FROM AUTHOR]

• The characteristics of rainfall erosivity in the Huaihe River Basin were analyzed. • 87% rainfall erosivity concentrated during May – September in the Huaihe River Basin. • Rainfall erosivity in the Huaihe River Basin was highest in the upper basin. • Climatic indexes were correlated with rainfall erosivity with different lag times. • Some advice was provide for local human activities based on soil erosion prevention. Rainfall erosivity (RE) is an important factor in the soil erosion process, which cannot be altered by human intervention alone. The Huaihe River Basin (HRB) is a large agricultural watershed, suffering severe water erosion, investigating the spatio-temporal variation of RE is essential for local soil erosion prevention. The linear regression, Yue-Pilon method, and the Hurst exponent were used in analyzing the spatio-temporal variation within the HRB during 1960–2018. The slip correlation analysis and F-test were applied to obtain the correlation between climatic indices [the Arctic Oscillation (AO), the Southern Oscillation (SOI), the North Pacific Index (NPI), and the Niño 4SST index (SST)] and RE in the HRB. Results revealed that the annual average RE were 4280, 5061, 4068, 4886, and 4089 MJ mm hm−2 h−1 within the HRB, upper-HRB, middle-HRB, lower-HRB, and the Yishusi River Watershed, respectively. The annual average RE will increase within the upper-HRB and lower-HRB and decrease within the middle-HRB and the Yishusi River Watershed in the future. The seasonal average RE was ranked as summer > autumn = spring > winter in the HRB. The spatiotemporal difference was significant in the HRB, and different sub-regions exhibited a different trend in seasonal RE, except for the winter RE that increased significantly in all sub-regions (p < 0.05). The highest monthly RE occurred in July, with RE during May–September accounting for approximately 87% of the annual RE in the HRB. The AO and NPI had significant correlations with RE (p < 0.05) both on the annual and monthly scales with different lag times. The monthly AO, SOI, SST, and NPI were significantly correlated with RE in the long term with different lag times in different months (p < 0.05). These findings could provide potential predictive factors for RE prediction and help prevent soil erosion within the HRB. [ABSTRACT FROM AUTHOR]

Urban road dusts are carriers of polycyclic aromatic compounds (PACs) and are therefore considered to be a major source of contamination of other environmental compartments and a source of exposure to PACs for urban populations. We determined the occurrence, composition pattern and sources of several PACs (29 alkyl- and parent-PAHs, 15 oxygenated-PAHs (OPAHs), 4 azaarenes (AZAs), and 11 nitrated-PAHs (NPAHs)) in twenty urban road dusts and six suburban surface soils (0–5 cm) from Xi’an, central China. The average concentrations of ∑29PAHs, ∑4AZAs, ∑15OPAHs, and ∑11NPAHs were 15 767, 673, 4754, and 885 ng g −1 in road dusts and 2067, 784, 854, and 118 ng g −1 in surface soils, respectively. The concentrations of most individual PACs were higher in street dusts than suburban soils, particularly for PACs with molecular weight >192 g mol −1 . The enrichment factors of individual PACs were significantly positively correlated with log K OA and log K OW , indicating an increasing deposition and co-sorption of the PACs in urban dusts with decreasing volatility and increasing hydrophobicity. Significant correlations between the concentrations of individual and sum of PACs, carbon fractions (soot and char), and source-characteristic PACs (combustion-derived PAHs and retene, etc.), indicated that PAHs, OPAHs and AZAs were mostly directly emitted from combustion activities and had similar post-emission fates, but NPAHs were possibly more intensely photolyzed after deposition as well as being emitted from vehicle exhaust sources. The incremental lifetime cancer risk (ILCR) resulting from exposure to urban dust bound-PACs was higher than 10 −6 , indicating a non-negligible cancer risk to residents of Xi’an. [ABSTRACT FROM AUTHOR]

Natural hydrological processes have been changed under the combined influences of climate change and intensive human activities in the Huangbaihe River Basin, where large-scale phosphate mining has been taking place. Therefore, evaluating the impact of climate change and intensive human activities on runoff variation and detecting the main driving factor leading to the variation are important for more efficient water resource management and more sustainable development of the regional economy. Despite numerous studies having been performed on this topic, little research focused on the impact of mining on runoff variation. The non-parametric Mann-Kendall (MK) trend test and accumulative anomaly methods were applied to identifying basic trends and change points of the hydro-meteorological elements over the period from 1978 to 2016. Then, the Soil Water and Assessment Tool (SWAT) and the Slope Changing Ratio of Accumulative Quantity (SCRAQ) were both used to quantify the contributions of climate change and anthropogenic activities on runoff variation. In this step, the runoff data were restored to their natural state before the construction of Xuanmiaoguan (XMG) dam. Due to the lack of locally observed evapotranspiration data, Global Land Evaporation Amsterdam Model and an empirical equation applied to obtain the evapotranspiration data. The results revealed that the change points are in 1985 and 2006. Therefore, the total period was divided into three periods, that is, the baseline period Ta (1978–1984), change period Tb (1985–2005) and change period Tc (2006–2016). Compared with the baseline period Ta, climate change dominates the runoff variation in the period Tb and is responsible for 60.5 and 74.4% of runoff variation, while human activities contribute the most to runoff variation for the period Tc (79.3 and 86.1%). Furthermore, an analysis of the underlying mechanism of underground phosphate mining indicates that mining can affect overland flow and baseflow simultaneously. This study can provide some information in determining the contributions of climate change and human activities in intensive phosphate mined basins and areas lack of evapotranspiration data. [ABSTRACT FROM AUTHOR]

Polycyclic aromatic compounds (PACs) such as polycyclic aromatic hydrocarbons (PAHs) and their derivatives [oxygenated PAHs (OPAHs), nitrated PAHs (NPAHs), and azaarenes (AZAs)] are toxic and ubiquitous air pollutants. In this study, the concentrations of these PACs were determined in air obtained in spring and autumn of 2012 from urban and rural areas of the Tibetan Plateau, temperate, subtropical, and tropical climate zones in China. Average concentrations (gaseous + particulate) of ∑29PAHs, ∑15OPAHs, ∑11NPAHs, and ∑4AZAs were 928 ± 658, 54 ± 45, 5.3 ± 4.4, 14 ± 11 ng m -3 and 995 ± 635, 67 ± 38, 8.4 ± 6.1, 24 ± 16 ng m -3 in spring and autumn, respectively. Various C fractions and latitude correlated significantly with the concentrations and ratios of PACs. The slopes of the regression of gas-particle partition coefficients (K p ) of PACs on their sub-cooled liquid vapor pressures (P L 0 ), indicated both adsorption and absorption to total suspended particles (TSP) for PAHs, OPAHs, and NPAHs in the four studied climatic zones. This result was further supported by comparing the fractions of PACs in TSP calculated from field data with those predicted by the Junge-Pankow adsorption and K OA absorption models. The concentration ratios of most OPAHs or NPAHs to their parent PAHs and of benzo[e]pyrene/benzo[a]pyrene were higher in autumn than in spring and increased with remoteness from point sources. This suggests enhanced secondary formation of PAH derivatives due to the elevated photochemical activity in autumn and longer ageing of air and associated transformation of PACs during their long-distance transport from source regions (urban sites) to rural sites. Lifetime lung cancer risk estimated from PACs ranged from 0.8 ± 0.6 to 3.1 ± 1.0 (×10 -3 ) recommended by the WHO. Gaseous PACs contributed substantially to the estimated cancer risks and their contributions increased with decreasing latitude in China.- 5 ) recommended by the WHO. Gaseous PACs contributed substantially to the estimated cancer risks and their contributions increased with decreasing latitude in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Objective: To develop a prognostic model for Chinese patients with relapsed diffuse large B-cell lymphoma (DLBCL) after initial R-CHOP therapy., Methods: We retrospectively analyzed the characteristics and survival outcomes of 79 patients with relapsed DLBCL initially treated with R-CHOP at Peking Union Medical College Hospital from February 2012 to September 2016. We used the data to develop a novel prognostic model., Results: The median age at the start of salvage therapy was 59 (17-85) years and median time from diagnosis to relapse was 319 (49-1018) days. Multivariate analysis identified short time to relapse (TTR) and B symptoms as independent prognostic factors for reduced progression-free survival (PFS) and overall survival (OS). We created a new prognostic scoring system including TTR, lactate dehydrogenase, absolute lymphocyte count at relapse, and B symptoms, referred to as the TLLB model, which could separate patients into three risk groups with 2-year PFS and OS rates of 70.7%, 40.0%, and 11.1%, and 87.5%, 53.7%, and 29.4%, respectively., Conclusion: TTR and B symptoms can be used as important predictors of survival in patients with DLBCL. The TLLB system provides a useful prognostic model compared with the previous TTL system.

Carbon dioxide (CO 2 ) and methane (CH 4 ) are the two major greenhouse gases (GHGs) in the atmosphere that contribute to global warming. Vehicle emissions on expressways cannot be neglected in the megacity Shanghai because oil accounts for 41% of the total primary energy consumption, and the expressway network carries 60% of the total traffic volume. The spatial distributions of CO 2 and CH 4 concentrations were monitored in situ on the expressways and in road tunnels using a mobile vehicle. The average CO 2 and CH 4 concentrations were 472.88 ± 34.48 ppm and 2033 ± 54 ppb on the expressways and 1308.92 ± 767.48 ppm and 2182 ± 112 ppb in the road tunnels in Shanghai, respectively. The highest CO 2 and CH 4 concentrations appeared on the Yan'an Elevated Road and the North-South Elevated Road, respectively, while their lowest values both occurred on the Huaxia Elevated Road passing through the suburban area. The hotspots of CO 2 and CH 4 were not consistent, suggesting that they have different sources. Tunnels had a "push-pull effect" on GHGs, and the traffic-congested Yan'an East Road Tunnel showed a dramatically increasing trend of GHG concentration from the entrance to the exit. This traffic-congested tunnel could accumulate a very high concentration of GHGs as well as other pollutants, which could introduce unhealthy conditions for both drivers and passengers. Significant correlations between CO 2 and CH 4 mostly appeared on the expressways and in the tunnels in Shanghai, suggesting the influences of vehicle exhaust. ΔCH 4 /ΔCO 2 (the slope of the linear regression between CH 4 and CO 2 ) and the CH 4 /CO 2 ratio could be used as indicators of vehicle exhaust sources because it increases from sources (e.g., road tunnels) to the observatories in the urban area.

Objective: To determine the prevalence, distribution, and factors associated with bone erosion detectable by ultrasound in patients with gout., Methods: Ultrasound scans were performed in 980 patients with gout, and bone erosion was detected. The prevalence and distribution of bone erosion in gout patients were calculated. Both clinical variables and ultrasound signs were entered into a multivariate logistic regression analysis to clarify the factors associated with bone erosion in patients with gout., Results: Bone erosion was found in 431 (44.0%) of the 980 patients with gout, and in 338 (78.4%) of these patients, the bone erosion was found in the first metatarsophalangeal (MTP) joint. A multivariable logistic regression analysis showed that age, duration of gout, the existence of tophi, ultrasound-detected synovial hypertrophy, and joint effusion were independently associated with bone erosion. A tophus was the most powerful factor associated with bone erosion, with an odds ratio (OR) of 4.218 (95% confidence interval 3.092-5.731). The risk for bone erosion also increased as the number of tophi increased (P < 0.001). However, after stratifying the size of tophi, the ORs did not increase significantly (P = 0.206)., Conclusion: A high percentage of gout patients had bone erosions; the first MTP joint was the most frequently involved site. Age, duration of gout, tophi, and synovial hypertrophy were factors associated with bone erosion in gout patients. The number of tophi, but not their size, was strongly associated with bone erosion in patients with gout., (© 2018, American College of Rheumatology.)

Background: Low education level has been thought an important and specific risk factor for dementia. Therefore, we surveyed dementia in a highly educated population in Tianjin, China., Methods: In total, 1324 old people (aged 55 years and over) in three cluster samples from university communities in Tianjin responded to our survey. Data from psychological tests and dementia questionnaires were analyzed., Results: The prevalence of all-cause dementia, Alzheimer's disease (AD), and vascular dementia (VD) was 4.98%, 2.11%, and 2.27%, respectively. A history of stroke (OR=6.036), lack of fruit (OR=5.489), early parental death (OR=3.102), household financial management (OR=2.638), a history of cardiovascular disease (OR=2.434), a history of hypertension (OR=2.042), physical exercise (OR=2.556), were significantly associated with dementia in a single-factor analysis. Four independent variables were entered in a regression equation: early parental death (OR=6.417), lack of fruit in the diet (OR=3.919), personal stroke history (OR=3.901), and lack of physical exercise (OR=2.220)., Conclusion: The prevalence of dementia was lower in highly educated elderly people in universities in Tianjin than in the general population. Risk factors for dementia included disease history, living habits, and early parental death, so corresponding interventions are required., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Quantifying elemental carbon (EC) content in geological samples is challenging due to interferences of crustal, salt, and organic material. Thermal/optical analysis, combined with acid pretreatment, represents a feasible approach. However, the consistency of various thermal/optical analysis protocols for this type of samples has never been examined. In this study, urban street dust and soil samples from Baoji, China were pretreated with acids and analyzed with four thermal/optical protocols to investigate how analytical conditions and optical correction affect EC measurement. The EC values measured with reflectance correction (ECR) were found always higher and less sensitive to temperature program than the EC values measured with transmittance correction (ECT). A high-temperature method with extended heating times (STN120) showed the highest ECT/ECR ratio (0.86) while a low-temperature protocol (IMPROVE-550), with heating time adjusted for sample loading, showed the lowest (0.53). STN ECT was higher than IMPROVE ECT, in contrast to results from aerosol samples. A higher peak inert-mode temperature and extended heating times can elevate ECT/ECR ratios for pretreated geological samples by promoting pyrolyzed organic carbon (PyOC) removal over EC under trace levels of oxygen. Considering that PyOC within filter increases ECR while decreases ECT from the actual EC levels, simultaneous ECR and ECT measurements would constrain the range of EC loading and provide information on method performance. Further testing with standard reference materials of common environmental matrices supports the findings. Char and soot fractions of EC can be further separated using the IMPROVE protocol. The char/soot ratio was lower in street dusts (2.2 on average) than in soils (5.2 on average), most likely reflecting motor vehicle emissions. The soot concentrations agreed with EC from CTO-375, a pure thermal method.

Three techniques were used to measure black carbon (BC) in samples from Chinese loess-paleosol sequences. The results obtained by (1) chemo-thermal oxidation (CTO, performed two ways), (2) acid dichromate oxidation (Cr2O7), and (3) thermal-optical reflectance (TOR) were intercompared because prior studies have shown that the methods can yield disparate results. BC concentrations did vary among the methods, most likely because they measured different components of the BC continuum, but the high-temperature BC (soot) determined by CTO was correlated with the BC and soot obtained by TOR. The CTO and TOR methods both yielded statistically significant linear relationships for loess and lake sediments that had incremental additions of a standard (SRM-1649a). The results also showed that charred material was more abundant in these test sediments than soot carbon. Data for BC in Luochuan loess generated using TOR showed a trend similar to that of magnetic susceptibility, that is, high BC and large susceptibilities during the last interglacial and low values for both variables in the last glacial. The results thus indicate that the TOR method is well suited for studies of sedimentary materials and that more biomass burned during the last interglacial than in the last glacial., (Copyright © 2012 Elsevier Ltd. All rights reserved.)