Integration of Single-Cell RNA Sequencing and Bulk RNA Sequencing to Identify an Immunogenic Cell Death-Related 5-Gene Prognostic Signature in Hepatocellular Carcinoma.

Introduction: Immunogenic cell death (ICD) can enhance the potency of immunotherapy in cancer treatment. Nevertheless, it is ambiguous how ICD-related genes (ICDRGs) contribute to hepatocellular carcinoma (HCC). Methods: Single-cell RNA sequencing (scRNA-seq) data were used to distinguish malignant cells from normal cells in the HCC tumor microenvironment(TME). Bulk RNA sequencing data was employed to acquire the landscape of the 33 ICDRGs. Unsupervised clustering identified two ICD molecular subtypes. The cellular infiltration characteristics and biological behavior in different subtypes were analyzed by ssGSEA. Subsequently, differentially expressed genes (DEGs) between the two subtypes were determined, based on which patients were classified into three gene clusters. Then, the prognostic model was constructed by Lasso-Cox analysis. Finally, we investigated the expression of risk genes in cancer cell line encyclopedia (CCLE) and validated the function of NKX3-2 in vitro experiments. Results: ICD scores and ICDRGs expression in malignant cells were significantly lower than in normal cells by scRNA-seq analysis. ICD-high subtype was characterized by ICD-related gene overexpression and high levels of immune infiltration abundance and immune checkpoints; Three DEGs-related gene clusters were likewise strongly linked to stromal and immunological activation. In the ICD-related prognostic model consisting of NKX3-2, CHODL, MMP1, NR0B1, and CTSV, the low-risk group patients had a better endpoint and displayed increased susceptibility to immunotherapy and chemotherapeutic drugs like 5-Fluorouracil, afatinib, bortezomib, cediratinib, lapatinib, dasatinib, gefitinib and crizotinib. Moreover, NKX3-2 amplification in HCC samples has been verified by experiments, and its disruption suppressed the proliferation and invasion of tumor cells. Conclusion: Our study highlighted the potential of the ICDRGs risk score as a prognostic indicator to aid in the accurate diagnosis and immunotherapy sensitivity of HCC.

Subsidizing Grid-Based Electrolytic Hydrogen Will Increase Greenhouse Gas Emissions in Coal Dominated Power Systems.

Clean hydrogen has the potential to serve as an energy carrier and feedstock in decarbonizing energy systems, especially in "hard-to-abate" sectors. Although many countries have implemented policies to promote electrolytic hydrogen development, the impact of these measures on costs of production and greenhouse gas emissions remains unclear. Our study conducts an integrated analysis of provincial levelized costs and life cycle greenhouse gas emissions for all hydrogen production types in China. We find that subsidies are critical to accelerate low carbon electrolytic hydrogen development. Subsidies on renewable-based hydrogen provide cost-effective carbon dioxide equivalent (CO2e) emission reductions. However, subsidies on grid-based hydrogen increase CO2e emissions even compared with coal-based hydrogen because grid electricity in China still relies heavily on coal power and likely will beyond 2030. In fact, CO2e emissions from grid-based hydrogen may increase further if China continues to approve new coal power plants. The levelized costs of renewable energy-based electrolytic hydrogen vary among provinces. Transporting renewable-based hydrogen through pipelines from low- to high-cost production regions reduces the national average levelized cost of renewables-based hydrogen but may increase the risk of hydrogen leakage and the resulting indirect warming effects. Our findings emphasize that policy and economic support for nonfossil electrolytic hydrogen is critical to avoid an increase in CO2e emissions as hydrogen use rises during a clean energy transition.

OTUB1 accelerates hepatocellular carcinoma by stabilizing RACK1 via its non-canonical ubiquitination.

BACKGROUND: Dysregulated ubiquitination modification occupies a pivotal role in hepatocellular carcinoma (HCC) tumorigenesis and progression. The ubiquitin aldehyde binding 1 (OTUB1) was aberrantly upregulated and exhibited the pro-tumorigenic function in HCC. However, the underlying mechanisms and responsible targets of OTUB1 remain unclear. METHODS: First, bioinformatics analysis, western blot and immunohistochemistry staining were applied to analyze OTUB1 expression in HCC specimens. Then, immunoprecipitation assay-tandem mass spectrometry (MS) combined with the gene set enrichment analysis (GSEA) was used to explore the downstream target of OTUB1. Co-immunoprecipitation and ubiquitination assays were used to identify the mechanisms involved. Finally, we explored the regulatory effect of MAZ on OTUB1 through ChIP-qPCR and dual-luciferase reporter assay. RESULTS: OTUB1 was broadly elevated in HCC tissues and promoted the proliferation and metastasis of HCC in vitro and in vivo. The receptor for activated C kinase 1 (RACK1) performed as a functional partner of OTUB1 and its hyperactivation was associated with aggressive development and other malignant features in HCC by activating oncogenes transcription. Mechanistically, OTUB1 directly bound to RACK1 at its C-terminal domain and decreased the K48-linked ubiquitination of RACK1 through its non-canonical suppression of ubiquitination activity, which stabilized RACK1 protein levels in HCC cells. Therefore, OTUB1 significantly increased multiple oncogenes expression and activated PI3K/AKT and FAK/ERK signaling in a RACK1-dependent manner in HCC. Moreover, the transcription factor MAZ upregulated OTUB1 expression through identifying a putative response element of OTUB1 promoter area. CONCLUSIONS: Our findings might provide a new therapeutic strategy for HCC by modifying the MAZ-OTUB1-RACK1 axis.

Deploying green hydrogen to decarbonize China's coal chemical sector.

China's coal chemical sector uses coal as both a fuel and feedstock and its increasing greenhouse gas (GHG) emissions are hard to abate by electrification alone. Here we explore the GHG mitigation potential and costs for onsite deployment of green H2 and O2 in China's coal chemical sector, using a life-cycle assessment and techno-economic analyses. We estimate that China's coal chemical production resulted in GHG emissions of 1.1 gigaton CO2 equivalent (GtCO2eq) in 2020, equal to 9% of national emissions. We project GHG emissions from China's coal chemical production in 2030 to be 1.3 GtCO2eq, ~50% of which can be reduced by using solar or wind power-based electrolytic H2 and O2 to replace coal-based H2 and air separation-based O2 at a cost of 10 or 153 Chinese Yuan (CNY)/tCO2eq, respectively. We suggest that provincial regions determine whether to use solar or wind power for water electrolysis based on lowest cost options, which collectively reduce 53% of the 2030 baseline GHG emissions at a cost of 9 CNY/tCO2eq. Inner Mongolia, Shaanxi, Ningxia, and Xinjiang collectively account for 52% of total GHG mitigation with net cost reductions. These regions are well suited for pilot policies to advance demonstration projects.

Heterogeneous effects of battery storage deployment strategies on decarbonization of provincial power systems in China.

Battery storage is critical for integrating variable renewable generation, yet how the location, scale, and timing of storage deployment affect system costs and carbon dioxide (CO2) emissions is uncertain. We improve a power system model, SWITCH-China, to examine three nationally uniform battery deployment strategies (Renewable-connected, Grid-connected, and Demand-side) and a heterogeneous battery deployment strategy where each province is allowed to utilize any of the three battery strategies. Here, we find that the heterogeneous strategy always provides the lowest system costs among all four strategies, where provinces with abundant renewable resources dominantly adopt Renewable-connected batteries while those with limited renewables dominantly adopt Demand-side batteries. However, which strategy achieves the lowest CO2 emissions depends on carbon prices. The Renewable-connected strategy achieves the lowest CO2 emissions when carbon prices are relatively low, and the heterogeneous strategy results in the lowest CO2 emissions only at extremely high carbon prices.

Exploring the Successions in Microbial Community and Flavor of Daqu during Fermentation Produced by Different Pressing Patterns.

Daqu can be divided into artificially pressed daqu (A-Daqu) and mechanically pressed daqu (M-Daqu) based on pressing patterns. Here, we compared the discrepancies in physicochemical properties, volatile metabolites, and microbiota features between A-Daqu and M-Daqu during fermentation and further investigated the factors causing those differences. A-Daqu microbiota was characterized by six genera (e.g., Bacillus and Thermoactinomyces), while five genera (e.g., Bacillus and Thermomyces) dominated in M-Daqu. The flavor compounds analysis revealed that no obvious difference was observed in the type of esters between the two types of daqu, and M-Daqu was enriched with more alcohols. The factors related to differences between the two types of daqu were five genera (e.g., Hyphopichia). The functional prediction of microbial communities revealed that the functional discrepancies between the two types of daqu were mainly related to ethanol metabolism and 2,3-butanediol metabolism. This study provided a theoretical basis for understanding the heterogeneity of daqu due to the different pressing patterns.

Carbon Mitigation and Environmental Co-Benefits of a Clean Energy Transition in China's Industrial Parks.

Industrial parks are emerging priorities for carbon mitigation. Here we analyze air quality, human health, and freshwater conservation co-benefits of decarbonizing the energy supply of 850 China's industrial parks. We examine a clean energy transition including early retirement of coal-fired facilities and subsequent replacement with grid electricity and onsite energy alternatives (municipal solid waste-to-energy, rooftop photovoltaic, and distributed wind power). We find that such a transition would reduce greenhouse gas emissions by 41% (equal to 7% of 2014 national CO2 equivalent emissions); emissions of SO2 by 41%, NOx by 32%, and PM2.5 by 43% and freshwater consumption by 20%, relative to a 2030 baseline scenario. Based on modeled air pollutant concentrations, we estimate such a clean energy transition will result in ∼42,000 avoided premature deaths annually due to reduced ambient PM2.5 and ozone exposure. Costs and benefits are monetized including technical costs of changes in equipment and energy use and societal benefits resulting from improvements in human health and reductions of climate impacts. We find that decarbonizing industrial parks brings annual economic benefits of US$30-156 billion in 2030. A clean energy transition in China's industrial parks thus provides both environmental and economic benefits.

Reduced rural residential emissions in the Northern China Plain from 2015 to 2021.

China's rapid economic growth over the past few decades has been fueled by the fossil-fuel dominated energy system. In Northern China, coal and biomass are important fuel types for household cooking and heating. The use of coal and biomass not only contributes to CO2 emissions, but also worsens the ambient air quality and further causes adverse health outcomes. Since 2016, action plans have been implemented annually to promote the substitution of solid fuel use in the rural households of the Beijing-Tianjin-Hebei and surrounding region ("2 + 26" region). However, a comprehensive evaluation of the emission reductions by the control policies is still lacking. In this study, we built a rural residential emission inventory in the "2 + 26" region based on two-phase national household surveys in 2010 and 2015. We evaluated the air pollutant and CO2 reduction benefits of various control measures from 2015 to 2021 and discussed the opportunities for the synergistical control of air pollutant and CO2 emissions. We estimated that, in 2015, the coal and biomass fuel consumption from rural households in the "2 + 26" region was 28.7 Mt. and 30.6 Mt., respectively, which resulted in 93.8 Mt., 416.5kt, 402.5kt, 80.1kt, 268.0kt, and 6122.2kt of CO2, PM2.5, SO2, NOx, VOCs, and CO emissions. With the implementation of household solid fuel substitution policies, air pollutant emissions were estimated to decrease by 53- 74 % from 2015 to 2021, while the percentage reduction of CO2 was only 39 % due to additional emissions from the alternative clean energy sources. If biomass was treated as carbon-neutral fuel, the CO2 reducing potential was even lower. Building a clean and sustainable rural energy system is a multi-win option for China to achieve the "Beautiful China", "Healthy China" and carbon-neutrality goals.

Medication non-adherence and associated factors among older adult stroke survivors in China.

Aim: Medication non-adherence has remained a common and costly global health issue of growing importance among older adults. This study aims to determine the prevalence and associated factors related to medication non-adherence among older adult stroke survivors in China. Methods and results: In this cross-sectional study, a total of 402 older adult stroke survivors were recruited from three tertiary hospitals in China. The results of the survey showed that 61.4% exhibited medication non-adherence. The chances of medication non-adherence among older adult stroke survivors who had primary school or less educational levels were higher than those who had senior secondary and junior college educational levels [OR (95% CI) = 0.440(0.249, 0.778)] as well as those who had a bachelor's degree or above educational levels [OR (95%CI) = 0.367(0.202, 0.667)]. Moreover, the probability of medication non-adherence with 4-5 and ≥6 types of total prescription medications per day increased by 1.993 times [OR (95% CI) = 1.993(1.190, 3.339))] and 2.233 times [OR (95%CI) = 2.233(1.159, 4.300)], respectively, as compared to when there were ≤3 types. Furthermore, medication non-adherence decreased with the increase in health literacy scores (ß = -0.641 (95% CI; (0.913, 0.965)) and BMQ specific-necessity scores (ß = -0.131 (95% CI; 0.806, 0.995)). On the other hand, when the BMQ specific-concerns score increased by one unit, medication non-adherence increased by 11.1% [OR (95% CI) = 1.111(1.044, 1.182)]. Conclusion: The present study found that patient medication adherence among older adult stroke survivors in China is problematic and associated with educational levels, total prescribed drugs per day, beliefs about medication, and health literacy scores. This indicates that measures should be taken to enhance medication adherence among such higher-risk populations.

Understanding the complexity of existing fossil fuel power plant decarbonization.

Growing national decarbonization commitments require rapid and deep reductions of carbon dioxide emissions from existing fossil-fuel power plants. Although retrofitting existing plants with carbon capture and storage or biomass has been discussed extensively, yet such options have failed to provide evident emission reductions at a global scale so far. Assessments of decarbonization technologies tend to focus on one specific option but omit its interactions with competing technologies and related sectors (e.g., water, food, and land use). Energy system models could mimic such inter-technological and inter-sectoral competition but often aggregate plant-level parameters without validation, as well as fleet-level inputs with large variability and uncertainty. To enhance the accuracy and reliability of top-down optimization models, bottom-up plant-level experience accumulation is of vital importance. Identifying sweet spots for plant-level pilot projects, overcoming the technical, financial, and social obstacles of early large-scale demonstration projects, incorporating equity into the transition, propagating the plant-level potential to generate fleet-level impacts represent some key complexity of existing fossil-fuel power plant decarbonization challenges that imposes the need for a serious re-evaluation of existing fossil fuel power plant abatement in energy transition.

A Take-Over Performance Evaluation Model for Automated Vehicles from Automated to Manual Driving.

The evaluation of take-over performance and take-over safety performance is critical to improving the take-over performance of conditionally automated driving, and few studies have attempted to evaluate take-over safety performance. This study applied a binary logistic model to construct a take-over safety performance evaluation model. A take-over driving simulator was established, and a take-over simulation experiment was carried out. In the experiment, data were collected from 15 participants who took over the vehicle and performed emergency evasive maneuvers while performing non-driving-related task (NDRT). Then, to calibrate the abnormal trajectory, the Kalman filter is adopted to filter the disturbed vehicle positioning data and the belief rule-based (BRB) method is proposed to warn irregular driving behavior. The results revealed that the accident rate of male participants is higher than that of female participants in the three frequency take-over experiment, and the overall driving performance of female participants is higher than that of male participants. Meanwhile, medium and high take-over frequencies have a significant effect on the prevention of vehicle collisions. In the take-over safety performance evaluation model, the minimum time to collision (TTC) of 2.3 s is taken as the boundary between the dangerous group and the safety group, and the model prediction accuracy rate is 87.7%. In sum, this study enriches existing research on the safety performance evaluation of conditionally automated driving take-over and provides important implications for the design of driving simulators and the performance and safety evaluation of human-machine take-over.

A Double-Layered Belief Rule Base Model for Driving Anger Detection Using Human, Vehicle, and Environment Characteristics: A Naturalistic Experimental Study.

"Road rage," namely, driving anger, has been becoming increasingly common in auto era. As "road rage" has serious negative impact on road safety, it has attracted great concern to relevant scholar, practitioner, and governor. This study aims to propose a model to effectively and efficiently detect driving anger states with different intensities for taking targeted intervening measures in intelligent connected vehicles. Forty-two private car drivers were enrolled to conduct naturalistic experiments on a predetermined and busy route in Wuhan, China, where drivers' anger can be induced by various incentive events like weaving/cutting in line, jaywalking, and traffic congestion. Then, a data-driven model based on double-layered belief rule base is proposed according to the accumulation of the naturalistic experiments data. The proposed model can be used to effectively detect different driving anger states as a function of driver characteristics, vehicle motion, and driving environments. The study results indicate that average accuracy of the proposed model is 82.52% for all four-intensity driving anger states (none, low, medium, and high), which is 1.15%, 1.52%, 3.53%, 5.75%, and 7.42%, higher than C4.5, BPNN, NBC, SVM, and kNN, respectively. Moreover, the runtime ratio of the proposed model is superior to that of those models except for C4.5. Hence, the proposed model can be implemented in connected intelligent vehicle for detecting driving anger states in real time.

Cross-Regional Customized Bus Route Planning Considering Staggered Commuting During the COVID-19.

In order to solve the problem of cross-regional customized bus (CB) route planning during the COVID-19, we develop a CB route planning method based on an improved Q-learning algorithm. First, we design a sub-regional route planning approach considering commuters' time windows of pick-up stops and drop-off stops. Second, for the CB route with the optimal social total travel cost, we improve the traditional Q-learning algorithm, including state-action pair, reward function and update rule of Q value table. Then, a setup method of CB stops is designed and the path impedance function is constructed to obtain the optimal operating path between each of the two stops. Finally, we take three CB lines in Beijing as examples for numerical experiment, the theoretical and numerical results show that (i) compared with the current situation, although the actual operating cost of optimized route increases slightly, it is covered by the reduction of travel cost of passengers and the transmission risk of COVID-19 has also dropped significantly; (ii) the improved Q-learning algorithm can solve the problem of data transmission lag effectively and reduce the social total travel cost obviously.

Identification of Vitamin D-related gene signature to predict colorectal cancer prognosis.

Colorectal cancer (CRC) is one of the most common malignant carcinomas worldwide with poor prognosis, imposing an increasingly heavy burden on patients. Previous experiments and epidemiological studies have shown that vitamin D and vitamin D-related genes play a vital role in CRC. Therefore, we aimed to construct a vitamin D-related gene signature to predict prognosis in CRC. The CRC data from The Cancer Genome Atlas (TCGA) was performed as the training set. A total of 173 vitamin D-related genes in the TCGA CRC dataset were screened, and 17 genes associated with CRC prognosis were identified from them. Then, a vitamin D-related gene signature consisting of those 17 genes was established by univariate and multivariate Cox analyses. Moreover, four external datasets (GSE17536, GSE103479, GSE39582, and GSE17537) were used as testing set to validate the stability of this signature. The high-risk group presented a significantly poorer overall survival than low-risk group in both of training set and testing sets. Besides, the areas under the curve (AUCs) for signature on OS in training set at 1, 3, and 5 years were 0.710, 0.708, 0.710 respectively. The AUCs of the ROC curve in GSE17536 for 1, 3, and 5 years were 0.649, 0.654, and 0.694. These results indicated the vitamin D-related gene signature model could effectively predict the survival status of CRC patients. This vitamin D-related gene signature was also correlated with TNM stage in CRC clinical parameters, and the higher risk score from this model was companied with higher clinical stage. Furthermore, the high accuracy of this prognostic signature was validated and confirmed by nomogram model. In conclusion, we have proposed a novel vitamin D-related gene model to predict the prognosis of CRC, which will help provide new therapeutic targets and act as potential prognostic biomarkers for CRC.

Inequality of household consumption and air pollution-related deaths in China.

Substantial quantities of air pollution and related health impacts are ultimately attributable to household consumption. However, how consumption pattern affects air pollution impacts remains unclear. Here we show, of the 1.08 (0.74-1.42) million premature deaths due to anthropogenic PM2.5 exposure in China in 2012, 20% are related to household direct emissions through fuel use and 24% are related to household indirect emissions embodied in consumption of goods and services. Income is strongly associated with air pollution-related deaths for urban residents in which health impacts are dominated by indirect emissions. Despite a larger and wealthier urban population, the number of deaths related to rural consumption is higher than that related to urban consumption, largely due to direct emissions from solid fuel combustion in rural China. Our results provide quantitative insight to consumption-based accounting of air pollution and related deaths and may inform more effective and equitable clean air policies in China.

cAMP induction by ouabain promotes endothelin-1 secretion via MAPK/ERK signaling in beating rabbit atria.

Adenosine 3',5'-cyclic monophosphate (cAMP) participates in the regulation of numerous cellular functions, including the Na(+)-K(+)-ATPase (sodium pump). Ouabain, used in the treatment of several heart diseases, is known to increase cAMP levels but its effects on the atrium are not understood. The aim of the present study was to examine the effect of ouabain on the regulation of atrial cAMP production and its roles in atrial endothelin-1 (ET-1) secretion in isolated perfused beating rabbit atria. Our results showed that ouabain (3.0 µmol/L) significantly increased atrial dynamics and cAMP levels during recovery period. The ouabain-increased atrial dynamics was blocked by KB-R7943 (3.0 µmol/L), an inhibitor for reverse mode of Na(+)-Ca(2+) exchangers (NCX), but did not by L-type Ca(2+) channel blocker nifedipine (1.0 µmol/L) or protein kinase A (PKA) selective inhibitor H-89 (3.0 µmol/L). Ouabain also enhanced atrial intracellular cAMP production in response to forskolin and theophyline (100.0 µmol/L), an inhibitor of phosphodiesterase, potentiated the ouabain-induced increase in cAMP. Ouabain and 8-Bromo-cAMP (0.5 µmol/L) markedly increased atrial ET-1 secretion, which was blocked by H-89 and by PD98059 (30 µmol/L), an inhibitor of extracellular-signal-regulated kinase (ERK) without changing ouabain-induced atrial dynamics. Our results demonstrated that ouabain increases atrial cAMP levels and promotes atrial ET-1 secretion via the mitogen-activated protein kinase (MAPK)/ERK signaling pathway. These findings may explain the development of cardiac hypertrophy in response to digitalis-like compounds.

Revealing the hidden health costs embodied in Chinese exports.

China emits a considerable amount of air pollutants when producing goods for export. Previous efforts have emphasized the magnitude of export-related emissions; however, their health consequences on the Chinese population have not been quantified. Here, we present an interdisciplinary study to estimate the health impact of export-related air pollution. The results show that export-related emissions elevated the annual mean population weighted PM2.5 by 8.3 µg/m(3) (15% of the total) in 2007, causing 157,000 deaths and accounting for 12% of the total mortality attributable to PM2.5-related air pollution. Compared to the eastern coastal provinces, the inner regions experience much larger export-related health losses relative to their economic production gains, owing to huge inter-regional disparities in export structures and technology levels. A shift away from emission-intensive production structure and export patterns, especially in inner regions, could significantly help improve national exports while alleviating the inter-regional cost-benefit inequality. Our results provide the first quantification of health consequences from air pollution related to Chinese exports. The proposed policy recommendations, based on health burden, economic production gains, and emission analysis, would be helpful to develop more sustainable and effective national and regional export strategies.