Biofuel production for circular bioeconomy: Present scenario and future scope.

In recent years, biofuel production has attracted considerable attention, especially given the increasing worldwide demand for energy and emissions of greenhouse gases that threaten this planet. In this case, one possible solution is to convert biomass into green and sustainable biofuel, which can enhance the bioeconomy and contribute to sustainable economic development goals. Due to being in large quantities and containing high organic content, various biomass sources such as food waste, textile waste, microalgal waste, agricultural waste and sewage sludge have gained significant attention for biofuel production. Also, biofuel production technologies, including thermochemical processing, anaerobic digestion, fermentation and bioelectrochemical systems, have been extensively reported, which can achieve waste valorization through producing biofuels and re-utilizing wastes. Nevertheless, the commercial feasibility of biofuel production is still being determined, and it is unclear whether biofuel can compete equally with other existing fuels in the market. The concept of a circular economy in biofuel production can promote the environmentally friendly and sustainable valorization of biomass waste. This review comprehensively discusses the state-of-the-art production of biofuel from various biomass sources and the bioeconomy perspectives associated with it. Biofuel production is evaluated within the framework of the bioeconomy. Further perspectives on possible integration approaches to maximizing waste utilization for biofuel production are discussed, and what this could mean for the circular economy. More research related to pretreatment and machine learning of biofuel production should be conducted to optimize the biofuel production process, increase the biofuel yield and make the biofuel prices competitive.

Assessment of Lung Nodule Detection and Lung CT Screening Reporting and Data System Classification Using Zero Echo Time Pulmonary MRI.

BACKGROUND: The detection rate of lung nodules has increased considerably with CT as the primary method of examination, and the repeated CT examinations at 3 months, 6 months or annually, based on nodule characteristics, have increased the radiation exposure of patients. So, it is urgent to explore a radiation-free MRI examination method that can effectively address the challenges posed by low proton density and magnetic field inhomogeneities. PURPOSE: To evaluate the potential of zero echo time (ZTE) MRI in lung nodule detection and lung CT screening reporting and data system (lung-RADS) classification, and to explore the value of ZTE-MRI in the assessment of lung nodules. STUDY TYPE: Prospective. POPULATION: 54 patients, including 21 men and 33 women. FIELD STRENGTH/SEQUENCE: Chest CT using a 16-slice scanner and ZTE-MRI at 3.0T based on fast gradient echo. ASSESSMENT: Nodule type (ground-glass nodules, part-solid nodules, and solid nodules), lung-RADS classification, and nodule diameter (manual measurement) on CT and ZTE-MRI images were recorded. STATISTICAL TESTS: The percent of concordant cases, Kappa value, intraclass correlation coefficient (ICC), Wilcoxon signed-rank test, Spearman's correlation, and Bland-Altman. The p-value <0.05 is considered significant. RESULTS: A total of 54 patients (age, 54.8 ± 11.9 years; 21 men) with 63 nodules were enrolled. Compared with CT, the total nodule detection rate of ZTE-MRI was 85.7%. The intermodality agreement of ZTE-MRI and CT lung nodules type evaluation was substantial (Kappa = 0.761), and the intermodality agreement of ZTE-MRI and CT lung-RADS classification was moderate (Kappa = 0.592). The diameter measurements between ZTE-MRI and CT showed no significant difference and demonstrated a high degree of interobserver (ICC = 0.997-0.999) and intermodality (ICC = 0.956-0.985) agreements. DATA CONCLUSION: The measurement of nodule diameter by pulmonary ZTE-MRI is similar to that by CT, but the ability of lung-RADS to classify nodes from MRI images still requires further research. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Carbon emission change based on land use in Gansu Province.

Carbon emissions from land use change have become one of the main sources of regional carbon emissions. In order to explore the changes, 87 districts and counties in Gansu Province are taken as research objects. Based on the remote sensing data and statistical data of land use, the carbon emission coefficient method was used to investigate the spatial characteristics of land use carbon emission of each district and county in Gansu Province in recent 20 years from the perspective of carbon ecological support coefficient and per capita carbon footprint. The main results are as follows: (1) the growth of land use carbon emissions in Gansu Province from 2000 to 2020 was significant, but the growth of carbon emissions after 2010 was fast, and the growth of carbon sinks was relatively slow. (2) The ecological support coefficient of carbon emissions at county level in Gansu Province showed a trend of high in the south and low in the north, high in the east and low in the west, and this trend became more and more obvious with the passage of time. (3) Based on carbon emission, county population, and carbon ecological support capacity, the per capita carbon footprint of each county in Gansu Province was analyzed. The results showed that the per capita carbon footprint in Gansu Province was increasing, indicating that the gap between carbon emission and carbon absorption in each county was widening. By the above result, the author divides the counties of Gansu Province into three regions, low-carbon maintenance area, green development area, and ecological optimization area, and puts forward development suggestions for different regions, respectively. Therefore, this paper can also provide a theoretical reference for the formulation of carbon neutral planning measures in inland northwest China.

Characteristics of carbon budget based on energy carbon emissions and vegetation carbon absorption.

How to evaluate the change characteristics of energy carbon emissions (ECE) and vegetation carbon absorption (VCA) by scientific methods is particularly important for achieving carbon peak by 2030 and carbon neutrality by 2060. Based on provincial-level energy consumption data, nighttime light data, and population data, this study realized spatial simulation of energy carbon emissions and analyzed the change characteristics of energy carbon emissions (ECE) and vegetation carbon absorption (VCA) combined with the net primary productivity (NPP)of vegetation. Besides, the relationship between energy carbon emissions, vegetation carbon absorption, and economic development was also analyzed at an urban scale. The results showed that (1) the total ECE increased from 4.34 billion tons in 2000 to 14.43 billion tons in 2019, but the growth rate of ECE decreased from 15.9% during 2000-2010 to 3.1% during 2010-2019. The VCA capacity has been increasing year by year. In 2019, it could absorb 1.56 billion tons more carbon dioxide than in 2000 with an increase of 16.1%. (2) Through the identification of the increasing and decreasing regions of ECE and VCA, it was found that the continuous rise area of ECE accounts for 0.5% of the study area; the area of fluctuating rise accounted for 6.7% of the study area. The area of continuous decline of VCA accounted for 0.2% of the study area; the area of fluctuating decline accounted for 49.6% of the study area. (3) The eastern China accounted for 42% of ECE and 17% of VCA with 11.4% of land, while the western region accounted for 26% of ECE and 55% of VCA with 66.6% of land, which indicated that there were significant differences in the characteristics of carbon budget between the eastern China and the western region. (4) The carbon pressure index (CPI) of most cities was on the rise, but the carbon efficiency index (CEI) was also on the rise, and cities were developing towards the model of low energy consumption and high output value. In a word, the growth rate of ECE is slowing down, and the VCA capacity is increasing. In the process of promoting carbon neutrality, we should be aware of the different resource endowments of different regions, realize the actual role of each region in carbon neutrality and economic development, and allocate carbon neutrality tasks differently.

The dynamic role of technological innovations and energy structure in China's industrial coal consumption growth: a joint production theoretical decomposition analysis.

China's energy-intensive industries utilize the leading proportion of coal to meet the demand for its industrial outputs, while on the other hand, these industries also assure the provision of livelihood to millions of people, and capping the share of coal consumption for these industries can adversely affect the industrial and economic growth of China. Thus, to achieve the Pareto improvement between environmental pollution and industrial output growth, it is essential to comprehend the patterns of coal consumption in these industries. Hence, the present research intended to analyze the potential drivers of coal consumption by applying a joint LMDI, DEA, and the production theoretical decomposition approach. Findings indices that, first, industrial output growth was the crucial driver to simulate the industrial coal consumption, while the potential coal intensity and coal technology changes exhibited the reverse effect. Second, the coal inputs and industrial output efficiency, along with the improvements in technological gaps, were found to be the imperative factors in decelerating coal consumption. Third, the energy industrial group was discovered to have more potentials of coal conversation as compared to the non-energy industrial group. Moreover, results also indicated that coal pure technical efficiency is accelerating coal growth, which revealed that coal can be saved by enhancing coal allocative efficiency. These findings laid the empirical ground to design a feasible coal conservation policy for achieving the imperative goals of environmental protection without compromising industrial output growth.

The causal effect and autonomous buffering mechanisms of large-scale internal migration on carbon emissions: evidence from China.

Large-scale internal migration and unprecedented urbanization have dramatically promoted economic growth in China, resulting in a rapid surge in carbon emissions in urban areas. However, few studies have investigated the causal effect of mass internal migration on carbon emissions or examined the effects of autonomous mitigation mechanisms, such as population agglomeration and technological innovation. This study identifies the causal effect of internal migration on prefectural-level cities' carbon emissions in China by employing an instrumental variable and further investigates the buffering effect of population agglomeration and technological innovation using mediating effect models. The results show that mass internal migration has a substantial impact on increasing carbon emissions in prefectural-level cities. If the proportion of inflowed migrants rises by 1% point, prefectural-level cities' carbon emissions per capita will increase by 1.9%. A series of robustness tests confirms the result. Population migration also promotes population agglomeration and technological innovation in urban areas. Two autonomous mechanisms buffer 11.9% and 5.4% of prefectural-level cities' incremental carbon emissions per capita caused by population migration, respectively. This study highlights the crucial role of population agglomeration and technological innovation in mitigating carbon emissions in cities experiencing significant migrant inflows and provides several implications for formulating relevant policies.

Application of improved GalNAc conjugation in development of cost-effective siRNA therapies targeting cardiovascular diseases.

N-Acetylgalactosamine (GalNAc)-conjugated small interfering RNA (siRNA) therapies have received approval for treating both orphan and prevalent diseases. To improve in vivo efficacy and streamline the chemical synthesis process for efficient and cost-effective manufacturing, we conducted this study to identify better designs of GalNAc-siRNA conjugates for therapeutic development. Here, we present data on redesigned GalNAc-based ligands conjugated with siRNAs against angiopoietin-like 3 (ANGPTL3) and lipoprotein (a) (Lp(a)), two target molecules with the potential to address large unmet medical needs in atherosclerotic cardiovascular diseases. By attaching a novel pyran-derived scaffold to serial monovalent GalNAc units before solid-phase oligonucleotide synthesis, we achieved increased GalNAc-siRNA production efficiency with fewer synthesis steps compared to the standard triantennary GalNAc construct L96. The improved GalNAc-siRNA conjugates demonstrated equivalent or superior in vivo efficacy compared to triantennary GalNAc-conjugated siRNAs.

Carbon emissions and low-carbon development in Olefin industry.

Olefin industry as a vital part in economic development is facing a problem of high CO2 emission. In this work, for the global and China's olefin industry under different development scenario, the carbon emission is predicted after the revealing of carbon footprint in different olefin routes. The results show that the carbon footprint of the natural gas liquids (NGLs)-derived route is highly lower than that of the oil- and coal-derived routes. The carbon emission from the global olefin industry in 2015 is 553 million ton CO2 (MtCO2). In 2030, it will be ranged between 739 and 924 MtCO2 under different scenarios. Under sustainable development scenario, 15% reduction space is existed, whereas 6% growth is observed under the hybrid-development scenario compared to the business-as-usual situation. In the case of China, its carbon emission is 120 MtCO2 in 2015. Its potential carbon emission in 2030 will increase to 264-925 MtCO2, depending on the rest new capacity from low-carbon or high-carbon routes. The large gap implies the significant influence of the development route choice. However, if most new capacity is from the existed planned olefin projects, the carbon emission will be ranged between 390 and 594 MtCO2. Finally, the low-carbon roadmaps as well as polices are proposed for sustainable development of olefin industry.

Assessment of the Diagnostic Performance of Clinical Examinations and High-Frequency Ultrasound in Patients With Pigmented Skin Tumors.

OBJECTIVES: To investigate whether the integration of high-frequency ultrasound (HFUS) to routine clinical examinations could improve diagnostic performance and management decision for pigmented skin tumors. METHODS: Three general practitioners trained previously and a dermatologist independently assessed pigmented skin tumors and rendered management decision based on clinical examinations alone or clinical examinations integrating HFUS. RESULTS: After integrating HFUS, the diagnostic area under the curve (AUC) (0.658-0.693 versus 0.848, all P < .05) and specificity (46.6-58.6% versus 89.7%, all P < .05) for pigmented skin malignancies were improved for general practitioners, meanwhile unnecessary biopsy rate reduced (42.9-53.6% versus 10.7%, P < .001). To the dermatologist, the diagnostic AUC (0.822 versus 0.949, P < .001), sensitivity (81.7% versus 96.7%, P = .012) and specificity (0.828 versus 0.931, P = .031) improved significantly, meanwhile both missed biopsy rate (14.5% versus 4.8%, P = .031) and unnecessary biopsy rate (19.6% versus 7.1%, P = .016) decreased. Additionally, the diagnostic performance of the general practitioner with integrating HFUS could be comparable with the dermatologist based on clinical examinations alone (all P > .05). CONCLUSIONS: As a complementary tool of clinical examinations, HFUS could help physicians differentiate pigmented skin malignancies and manage decision.

Occurrence characteristics and risk assessment of microplastics in agricultural soils in the loess hilly gully area of Yan' an, China.

Large amounts of microplastics accumulated in the soil of agricultural fields with the rapid development of mulch agriculture. The enrichment of microplastics endangered the growth of crops and food security, and it also posed ecological risks. In this study, we investigated microplastics in a typical agriculture area of Yan' an City, in the loess hilly gully area of China. The characteristics of microplastics including their abundances, sizes, and types were measured through laser direct infrared spectrometer. The potential sources of microplastics were analyzed and the risk of soil microplastic pollution was evaluated. It was elaborated that the average abundances of microplastics in soil, water, and fertilizer were 4505 ± 435 n·kg-1, 91 ± 27 n·L-1, and 39,629 ± 10,114 n·kg-1, respectively. Microplastics with particle sizes < 100 µm accounted for >90 %. The smaller the particle size, the higher the content of microplastics. The top three polymers were polyethylene (PE, 37.4 %), polyethylene terephthalate (PET, 15.0 %), and ethylene vinyl acetate (EVA, 8.9 %), respectively. Agricultural mulch, plastic film, domestic waste, surface water irrigation, and organic compost were probably the potential sources of soil microplastics. The ecological risk evaluation showed that overall sampling sites had a minor ecological risk of microplastic pollution based on their abundance, while the polymer type showed a relatively high ecological risk for the investigated agricultural soils. Polyvinylchloride (PVC) and polymethylmethacrylate (PMMA) contribute considerably to the ecological risk, and their inputs to the farmland environment should be strictly limited. There was no significant carcinogenic risk to humans. This study would provide the basic reference for the current situation and risk assessment of farmland soil microplastics pollution in the loess hilly gully area of China.

Assessment of Purity, Stability, and Pharmacokinetics of NGP-1, a Novel Prodrug of GS441254 with Potential Anti-SARS-CoV-2 Activity, Using Liquid Chromatography.

SARS-CoV-2 is a highly contagious and pathogenic virus that first appeared in late December 2019 and caused a global pandemic in a short period. The virus is a single-stranded RNA virus belonging to the Coronaviridae family. Numerous treatments have been developed and tested in response to the pandemic, particularly antiviral drugs. Among them, GS441524 (GS441), a nucleoside antiviral drug, has demonstrated promising results in inhibiting SARS-CoV-2. Nevertheless, the limited oral bioavailability of GS441 restricts its application to patients with the virus. In this study, a novel prodrug of GS441 (NGP-1) with an isobutyl ester and cyclic carbonate structure was designed and synthesized. Its purity and the stability in different artificial digestive juices of NGP-1 was determined with HPLC-DAD methods. The pharmacokinetics of NGP-1 and GS441 were studied in rats via gavage administration. A new LC-MS/MS method was developed to quantitatively analyze GS441 in plasma samples. The results showed that the ka, Cmax, and MRT of converted GS441 from NGP-1 were 5.9, 3, and 2.5 times greater than those of GS441 alone. The Frel of NGP-1 was approximately four-fold that of GS441, with an AUC0-∞ of 9716.3 h·ng mL-1. As a prodrug of GS441, NGP-1 increased its lipophilicity, absorption, and bioavailability, indicating that it holds promise in improving the clinical efficacy of anti-SARS-CoV-2 medications.

Fear of childbirth and its determinants in pregnant women in the third trimester: a cross-sectional study.

BACKGROUND: Fear of childbirth (FOC) is a prevalent issue among pregnant women and significantly relates to adverse outcomes for the mother and child. However, it is not clear the prevalence and risk factors of FOC among pregnant women in a region with a moderate level of economic development in China. The aim of this study was to investigate the prevalence and risk factors of FOC among pregnant women in the third trimester of pregnancy in Lianyungang city, Eastern China. METHODS: A cross-sectional survey was conducted from December 2022 to February 2023 among pregnant women in the third trimester who met the inclusion criteria and visited Lianyungang Maternal and Child Health Hospital in Jiangsu Province, Eastern China. A structured questionnaire including sociodemographic characteristics, clinical characteristics, FOC, family function, doctor-patient communication, social support, general self-efficacy, anxiety, depression, insomnia symptoms, and quality of life was used to collect data. A multiple linear regression model was used to identify predictors of FOC. RESULTS: This study included 535 pregnant women in the third trimester. The mean score of FOC was 30.67 ± 10.18, and the median score was 29.00. The prevalence of FOC was 56.64%. Multiple linear regression analysis revealed that pregnant women with electronic screen exposure time more than 5 h per day (ß = 2.02, 95%CI: 0.50-3.53, P < 0.05), no history of cesarean section (ß = 2.66, 95%CI: 0.61-4.71, P < 0.05), likes sour food or hates greasy food (ß = 1.75, 95%CI: 0.00-3.50, P < 0.05), anxiety (ß = 0.50, 95%CI: 0.21-0.80, P < 0.05) and depression (ß = 0.30, 95%CI: 0.04-0.57, P < 0.05) were more likely to have a greater level of FOC than their counterparts. However, a significantly lower level of FOC was observed in pregnant women who were multipara (ß=-1.64, 95%CI: -3.27-0.01, P < 0.05), not worrying about delivery without family members (ß=-3.75, 95%CI: -5.26-2.25, P < 0.001), had good family function (ß=-0.32, 95%CI: -0.64-0.00, P < 0.05) and doctor-patient communication (ß=-0.33, 95%CI: -0.64-0.02, P < 0.05). CONCLUSIONS: The prevalence of FOC was high in Lianyungang city, Eastern China. FOC is influenced by multiple factors. There is an urgent need to develop interventions to reduce the prevalence of FOC in the third trimester of pregnancy, and to pay attention to pregnant women with risk factors for FOC.

Biosafety and Ecological Assessment of Genetically Engineered and Edited Crops.

Nearly three decades have passed since the first commercial cultivation of genetically engineered (GE) crops [...].

Relationship between multi-slice computed tomography features and pathological risk stratification assessment in gastric gastrointestinal stromal tumors.

BACKGROUND: Computed tomography (CT) imaging features are associated with risk stratification of gastric gastrointestinal stromal tumors (GISTs). AIM: To determine the multi-slice CT imaging features for predicting risk stratification in patients with primary gastric GISTs. METHODS: The clinicopathological and CT imaging data for 147 patients with histologically confirmed primary gastric GISTs were retrospectively analyzed. All patients had received dynamic contrast-enhanced CT (CECT) followed by surgical resection. According to the modified National Institutes of Health criteria, 147 lesions were classified into the low malignant potential group (very low and low risk; 101 lesions) and high malignant potential group (medium and high-risk; 46 lesions). The association between malignant potential and CT characteristic features (including tumor location, size, growth pattern, contour, ulceration, cystic degeneration or necrosis, calcification within the tumor, lymphadenopathy, enhancement patterns, unenhanced CT and CECT attenuation value, and enhancement degree) was analyzed using univariate analysis. Multivariate logistic regression analysis was performed to identify significant predictors of high malignant potential. The receiver operating curve (ROC) was used to evaluate the predictive value of tumor size and the multinomial logistic regression model for risk classification. RESULTS: There were 46 patients with high malignant potential and 101 with low-malignant potential gastric GISTs. Univariate analysis showed no significant differences in age, gender, tumor location, calcification, unenhanced CT and CECT attenuation values, and enhancement degree between the two groups (P > 0.05). However, a significant difference was observed in tumor size (3.14 ± 0.94 vs 6.63 ± 3.26 cm, P < 0.001) between the low-grade and high-grade groups. The univariate analysis further revealed that CT imaging features, including tumor contours, lesion growth patterns, ulceration, cystic degeneration or necrosis, lymphadenopathy, and contrast enhancement patterns, were associated with risk stratification (P < 0.05). According to binary logistic regression analysis, tumor size [P < 0.001; odds ratio (OR) = 26.448; 95% confidence interval (CI): 4.854-144.099)], contours (P = 0.028; OR = 7.750; 95%CI: 1.253-47.955), and mixed growth pattern (P = 0.046; OR = 4.740; 95%CI: 1.029-21.828) were independent predictors for risk stratification of gastric GISTs. ROC curve analysis for the multinomial logistic regression model and tumor size to differentiate high-malignant potential from low-malignant potential GISTs achieved a maximum area under the curve of 0.919 (95%CI: 0.863-0.975) and 0.940 (95%CI: 0.893-0.986), respectively. The tumor size cutoff value between the low and high malignant potential groups was 4.05 cm, and the sensitivity and specificity were 93.5% and 84.2%, respectively. CONCLUSION: CT features, including tumor size, growth patterns, and lesion contours, were predictors of malignant potential for primary gastric GISTs.

Artificial Intelligence-Based PTEN Loss Assessment as an Early Predictor of Prostate Cancer Metastasis After Surgery: A Multicenter Retrospective Study.

Phosphatase and tensin homolog (PTEN) loss is associated with adverse outcomes in prostate cancer and can be measured via immunohistochemistry. The purpose of the study was to establish the clinical application of an in-house developed artificial intelligence (AI) image analysis workflow for automated detection of PTEN loss on digital images for identifying patients at risk of early recurrence and metastasis. Postsurgical tissue microarray sections from the Canary Foundation (n = 1264) stained with anti-PTEN antibody were evaluated independently by pathologist conventional visual scoring (cPTEN) and an automated AI-based image analysis pipeline (AI-PTEN). The relationship of PTEN evaluation methods with cancer recurrence and metastasis was analyzed using multivariable Cox proportional hazard and decision curve models. Both cPTEN scoring by the pathologist and quantification of PTEN loss by AI (high-risk AI-qPTEN) were significantly associated with shorter metastasis-free survival (MFS) in univariable analysis (cPTEN hazard ratio [HR], 1.54; CI, 1.07-2.21; P = .019; AI-qPTEN HR, 2.55; CI, 1.83-3.56; P < .001). In multivariable analyses, AI-qPTEN showed a statistically significant association with shorter MFS (HR, 2.17; CI, 1.49-3.17; P < .001) and recurrence-free survival (HR, 1.36; CI, 1.06-1.75; P = .016) when adjusting for relevant postsurgical clinical nomogram (Cancer of the Prostate Risk Assessment [CAPRA] postsurgical score [CAPRA-S]), whereas cPTEN does not show a statistically significant association (HR, 1.33; CI, 0.89-2; P = .2 and HR, 1.26; CI, 0.99-1.62; P = .063, respectively) when adjusting for CAPRA-S risk stratification. More importantly, AI-qPTEN was associated with shorter MFS in patients with favorable pathological stage and negative surgical margins (HR, 2.72; CI, 1.46-5.06; P = .002). Workflow also demonstrated enhanced clinical utility in decision curve analysis, more accurately identifying men who might benefit from adjuvant therapy postsurgery. This study demonstrates the clinical value of an affordable and fully automated AI-powered PTEN assessment for evaluating the risk of developing metastasis or disease recurrence after radical prostatectomy. Adding the AI-qPTEN assessment workflow to clinical variables may affect postoperative surveillance or management options, particularly in low-risk patients.

[Health Risk Assessment and Environmental Benchmark of Heavy Metals in Cultivated Land in Wanjiang Economic Zone].

Focusing on the cultivated land in Wanjiang Economic Zone, 338 sets of soil samples of rice, wheat, and their roots were collected; the concentrations of five heavy metals (As, Cd, Cr, Hg, and Pb) were determined; the soil-crop pollution characteristics were evaluated using the method of geo-accumulation index and comprehensive evaluation; the human health risk of ingesting heavy metals from crops was assessed; and the soil environmental reference value of the regional cultivated land was inverted based on the species sensitive distribution model (SSD). The results showed that in the study area, the soil of rice and wheat was polluted by heavy metals (As, Cd, Cr, Hg, and Pb) in varying degrees, among which Cd was the primary pollution factor of rice, with the over-standard rate of 13.33%, and Cr was the main over-standard factor of wheat, with the over-standard rate of 11.32%. The cumulative index showed that the percentage of Cd pollution in rice was 80.7%, and that in wheat was 35.85%. Contrary to the high pollution level of soil heavy metals, only 17.19% and 7.55% of Cd in rice and wheat exceeded the national food safety limit, and the accumulation capacity of the heavy metal Cd was rice>wheat. The health risk assessment indicated that heavy metals had high non-carcinogenic risk and unacceptable carcinogenic risk to adults and children in this study. The carcinogenic risk of rice intake was higher than that of wheat, and the health risk of children was higher than that of adults. SSD inversion showed that the reference values of As, Cd, Cr, Hg, and Pb in paddy soil in the study area were an HC5 of 6.24, 0.13, 258.27, 0.12, and 53.61 mg·kg-1 and an HC95 of 68.81, 5.71, 1068.92, 0.80, and 174.22 mg·kg-1, respectively. The reference values of As, Cd, Cr, Hg, and Pb in wheat soil HC5 were 32.99, 0.04, 271.14, 0.09, and 47.53 mg·kg-1, and the values of HC95 were 225.28, 0.71, 998.58, 1.43, and 241.99 mg·kg-1, respectively. The reverse analysis showed that the HC5 of heavy metals in rice and wheat were lower than the soil risk screening values in the current standard to varying degrees. The current soil standard had loosened for the evaluation results of this region.

Assessment of plasma soluble Tie-2 level to distinguish moyamoya disease from atherosclerotic cerebrovascular disease and predict postoperative neovascularization.

OBJECTIVE: Moyamoya disease (MMD) is a chronic steno-occlusive cerebrovascular disease and features the formation of hazy collateral vessels at the base of the brain. Angiopoietin (Ang)-1 and -2, their receptor Tie-2, and vascular endothelial growth factor (VEGF) that regulate angiogenesis might be important in MMD pathophysiology and postoperative collateral formation. The goal of this study was to determine whether levels of these angiogenic factors could predict collateralization in patients with MMD. METHODS: A total of 196 patients with MMD and 57 with atherosclerotic cerebrovascular disease serving as controls were enrolled. Ang-1, Ang-2, Tie-2, and VEGF mRNA levels were analyzed in middle cerebral artery (MCA) arterial wall specimens by using real-time quantitative polymerase chain reaction. MCA and peripheral plasma concentrations of Ang-1, Ang-2, soluble Tie-2 (sTie-2), and VEGF were examined by enzyme-linked immunosorbent assay. Cerebral arteriography was performed 6 months after bypass surgery to assess the postoperative collateralization. RESULTS: In MCA specimens, patients with MMD exhibited higher expression levels of Ang-1 and Ang-2 but lowered VEGF expression. The patients with MMD had significantly higher concentrations of Ang-1 and Ang-2 but lower levels of VEGF in MCA plasma. Peripheral plasma concentrations of these growth factors were not changed. MCA and peripheral plasma sTie-2 levels were both reduced in patients with MMD. The 6-month follow-up showed that patients with good collateral formation had lower sTie-2 levels in both MCA and peripheral plasma. Furthermore, the Suzuki stage and peripheral plasma sTie-2 level were significantly correlated with good postoperative collateral formation on multivariate analysis. CONCLUSIONS: Ang-1, Ang-2, Tie-2, and VEGF are involved in MMD pathogenesis. The peripheral plasma level of sTie-2 can differentiate MMD from atherosclerotic cerebrovascular disease and serve as a novel biomarker to predict postoperative collateral formation.

Safety assessment of subchronic feeding of insect-resistant and herbicide-resistant transgenic soybeans to juvenile channel catfish (Ictalurus punctatus).

Transgenic soybean is one of the most planted crops for human food and animal feed. The channel catfish (Ictalurus punctatus) is an important aquatic organism cultured worldwide. In this study, the effect of six different soybean diets containing: two transgenic soybeans expressing different types of cp4-epsps, Vip3Aa and pat genes (DBN9004 and DBN8002), their non-transgenic parent JACK, and three conventional soybean varieties (Dongsheng3, Dongsheng7, and Dongsheng9) was investigated in juvenile channel catfish for eight weeks, and a safety assessment was performed. During the experiment, no difference in survival rate was observed in six groups. The hepatosomatic index (HSI) and condition factor (CF) showed no significant difference. Moreover, comparable feed conversion (FC), feeding rate (FR), and feed conversion ratio (FCR) were found between transgenic soybean and JACK groups. Assessment of growth performance showed that the weight gain rate (WGR) and specific growth rate (SGR) of channel catfish were consistent. In addition, there were no changes in enzyme activity indexes (lactate dehydrogenase (LDH), total antioxidant capacity (T-AOC), aspartate aminotransferase (AST) and alanine aminotransferase (ALT)) in channel catfish among treatments. The research provided an experimental basis for the aquaculture feed industry to employ transgenic soybean DBN9004 and DBN8002 for commercial purposes.

High-speed rail and firms' environmental performance: empirical evidence from China.

Developing countries are struggling to balance the economic development and environment protection. This paper examines the impact of high-speed rail (HSR) on firm-level environmental performance in China. Using the staggered expansion of China's passenger-dedicated HSR and the panel data of Chinese manufacturing firm-level data from 2002 to 2012, we find that firms exhibit a lower level of chemical oxygen demand (COD) emissions after the opening of HSR. The average geographical slope of city is used as an instrumental variable to address the potential endogeneity problem of the HSR variable. Furthermore, the reduction effect of HSR introduction on firms' COD emission intensity is more pronounced for firms that located in eastern regions as well as technology-intensive and labor-intensive firms. Agglomeration economies, scale effects, and technological innovation are three plausible channels that allow HSR to promote firm environmental performance. Our paper provides new insights into the impacts of introduction of HSR on firm environmental performance and the development of green city.