The use of formic acid (FA) to produce molecular H2 is a promising means of efficient energy storage in a fuel‐cell‐based hydrogen economy. To date, there has been a lack of heterogeneous catalyst ...systems that are sufficiently active, selective, and stable for clean H2 production by FA decomposition at room temperature. For the first time, we report that flexible pyridinic‐N‐doped carbon hybrids as support materials can significantly boost the efficiency of palladium nanoparticle for H2 generation; this is due to prominent surface electronic modulation. Under mild conditions, the optimized engineered Pd/CN0.25 catalyst exhibited high performance in both FA dehydrogenation (achieving almost full conversion, and a turnover frequency of 5530 h−1 at 25 °C) and the reversible process of CO2 hydrogenation into FA. This system can lead to a full carbon‐neutral energy cycle.
Pyridinic‐N‐tuned catalysis: An electron‐rich pyridinic‐N dopant modulates the electronic interactions between the active sites of palladium nanoparticles and the carbon support. Formic acid dehydrogenation at room temperature is significantly boosted by the pyridinic‐N‐doped palladium catalyst, presenting an efficient and reliable route to clean H2 generation and sustainable energy storage.
•Establish an inter-provincial emissions trading model of China.•The economic performance of carbon emission trading in China is modelled.•Total abatement cost could be reduced by 23.67% with the ...unified emissions trading market.•The emissions trading market may result in a carbon price of 53yuan/tCO2 for the 2020 target.
Chinese government has committed to reduce its carbon intensity by 40–45% over the period 2005–2020 at the 2009 Copenhagen Summit. To achieve the target in a cost-effective way, China is signaling strong intentions to establish emissions trading scheme, and presently seven pilots have been established. This paper focuses on the cost-saving effects of carbon emissions trading in China for the 2020 target. First, an interprovincial emissions trading model is constructed. Then, three kinds of policy scenarios, including no carbon emissions trading among provinces (NETS), the carbon emissions trading only covering the pilots (PETS), and the unified carbon emissions trading market (CETS), have been designed. The results show that China needs to reduce its emissions by 819 MtCO2 for achieving the 42.5% reduction in carbon intensity over the period 2005–2020. The PETS and the CETS, which may result in a carbon price of 99yuan/tCO2 and 53yuan/tCO2, could reduce the total abatement costs by 4.50% and 23.67%, respectively. This paper also finds that the carbon emissions trading could yield different impacts on different provinces, and the cost-saving effects of the eastern and western provinces are more pronounced than the central provinces. Necessary sensitivity analysis is also provided at the end of the research. These findings may be useful for promoting the development of carbon emissions trading in China.
Abstract
We perform a profile analysis of the combined H
i
data cube of the Large Magellanic Cloud (LMC) from observations with the Australia Telescope Compact Array and the Parkes radio telescope. ...For the profile analysis, we use a newly developed algorithm that decomposes individual line profiles into an optimal number of Gaussian components based on a Bayesian nested sampling. The decomposed Gaussian components are then classified into
kinematically
cold, warm, and hot gas components based on their velocity dispersion. The estimated masses of the kinematically cold, warm, and hot gas components are ∼12.2%, ∼58.3%, and ∼29.5% of the total H
i
mass of the LMC, respectively. Our analysis reveals the highly complex H
i
structure and kinematics of the LMC that are seen in previous studies but in a more quantitative manner. We also extract the undisturbed H
i
gas bulk motions and derive new H
i
gas bulk rotation curves of the LMC by applying a 2D tilted-ring analysis. In contrast to previously derived H
i
rotation curves, the newly derived bulk rotation curves are much more consistent with the carbon star kinematics, with rotation velocity linearly increasing in the inner part and reaching a maximum of ∼60 km s
−1
at the outermost measured radius. By comparing the lower bulk rotation curves with previous studies, we conclude that there is a lower dynamical contribution of dark matter in the central part of the LMC.
The formate‐based rechargeable hydrogen battery (RHB) promises high reversible capacity to meet the need for safe, reliable, and sustainable H2 storage used in fuel cell applications. Described ...herein is an additive‐free RHB which is based on repetitive cycles operated between aqueous formate dehydrogenation (discharging) and bicarbonate hydrogenation (charging). Key to this truly efficient and durable H2 handling system is the use of highly strained Pd nanoparticles anchored on graphite oxide nanosheets as a robust and efficient solid catalyst, which can facilitate both the discharging and charging processes in a reversible and highly facile manner. Up to six repeated discharging/charging cycles can be performed without noticeable degradation in the storage capacity.
The formate/bicarbonate pair: A rechargeable hydrogen battery based on repetitive formate/bicarbonate interconversion in aqueous solution was developed. A hybrid material of Pd nanoparticles and reduced graphite oxide serves as the robust and efficient catalyst for both steps. Multiple charging and discharging cycles were performed with comparable storage/release efficiency and the resulting H2 gas is free of CO and CO2.
Background Human urine-derived stem cells (USCs)-derived exosomes (USC-Exo) could improve kidney ischemia/reperfusion injury (IRI), while the underlying mechanisms of this protective effect remain ...unclear. Methods Human USCs and USC-Exo were isolated and verified by morphology and specific biomarkers. The effects of USC-Exo on ferroptosis and kidney injury were detected in the IRI-induced acute kidney injury (AKI) model in C57BL/6 mice. The effects of USC-Exo on ferroptosis and lncRNA taurine-upregulated gene 1 (TUG1) were detected in hypoxia/reoxygenation (H/R)-treated human proximal tubular epithelial cells (HK-2). The interaction of SRSF1 and TUG1, ACSL4 was checked via RNA pull-down/RIP and RNA stability assays. The effects of LncRNA TUG1 on SRSF1/ACSL4-mediated ferroptosis were verified in H/R-treated HK-2 cells and the IRI-induced AKI mouse models. Results USC-Exo treatment improved kidney injury and ameliorated ferroptosis in IRI-induced AKI mouse models. USC-Exo were rich in lncRNA TUG1, which suppressed ferroptosis in HK-2 cells exposed to H/R. Mechanistically, lncRNA TUG1 regulates the stability of ACSL4 mRNA by interacting with RNA-binding protein SRSF1. In addition, SRSF1 upregulation or ACSL4 downregulation partially reversed the protective effect of lncRNA TUG1 on ferroptosis in H/R-treated HK-2 cells. Further, ACSL4 upregulation partially reversed TUG1's repression on kidney injury and ferroptosis in IRI-induced AKI mice. Conclusion Collectively, lncRNA TUG1 carried by USC-Exo regulated ASCL4-mediated ferroptosis by interacting with SRSF1 and then protected IRI-induced AKI. Potentially, USC-Exo rich in lncRNA TUG1 can serve as a promising therapeutic method for IRI-AKI. Keywords: LncRNA TUG1, Urine-derived stem cells, Exosomes, Ferroptosis, Ischemia/reperfusion injury, Acute kidney injury
Although the roles of earthworms and soil collembolans in the transport of microplastics have been studied previously, the effects of the soil biota at different trophic levels and interspecific ...relationships remain poorly understood. Here, we examine three soil microarthropod species to explore their effects on the transport of microplastics. The selected Folsomia candida and Hypoaspis aculeifer are extensively used model organisms, and Damaeus exspinosus is a common and abundant indigenous species in China. A model food chain (prey-collembolan and predator-mite) was structured to test the role of the predator-prey relationship in the transport of microplastics. Commercial Polyvinyl chloride (PVC) particles (Diameter: 80–250 μm) were selected as the test microplastics, because large amounts of PVC have persisted and accumulated in the environment. Synchronized soil microarthropods were held in plates for seven days to determine the movement of microplastics. The 5000 microplastic particles were carefully placed in the center of each plate prior to the introduction of the animals. Our results clearly show that all three microarthropod species moved and dispersed the microplastics in the plates. The 0.54%, 1.8% and 4.6% of the added microplastic particles were moved by collembolan, predatory mite and oribatid mite, respectively. Soil microarthropods (<0.2 cm) transported microplastic particles up to 9 cm. The avoidance behavior was observed in the collembolans in respect of the microplastics. The predatory -prey relationship did promote the transport of microplastics in the plates, increasing transport by 40% compared with the effects of adding single species (P < .05). Soil microarthropods commonly occur in surface soils (0–5 cm) and, due to their small body size, they can enter soil pores. Our results therefore suggest that the movement of microplastics by soil microarthropods may influence the exposure of other soil biota to microplastics and change the physical properties of soils.
Display omitted
•Predator-prey relationship increased movement of MPs by modifying animal activity.•The oribatid mite had the greatest ability to transport MPs.•F. candida, H. aculeifer and oribatid mite transported MPs up to 9 cm.•Avoidance of PVC particles by F. candida was observed in video recordings.
Predator-prey interactions in food chains can promote the transport of microplastics in soil ecosystems.
Objective
The purpose of this study was to compare the clinical and radiological efficacy of autologous adipose-derived stromal vascular fraction (SVF) versus hyaluronic acid in patients with ...bilateral knee osteoarthritis.
Methods
Sixteen patients with bilateral symptomatic knee osteoarthritis (K-L grade II to III; initial pain evaluated at four or greater on a ten-point VAS score) were enrolled in this study, which were randomized into two groups. Each patient received 4-ml autologous adipose-derived SVF treatment (group test,
n
= 16) in one side of knee joints and a single dose of 4-ml hyaluronic acid treatment (group control,
n
= 16) in the other side. The clinical evaluations were performed pre-operatively and post-operatively at one month, three months, six months, and 12-months follow-up visit, using the ten-point visual analog scale (VAS), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and the knee range of motion (ROM). The whole-organ assessment of the knees was performed with whole-organ magnetic resonance imaging score (WORMS) based on MRI at baseline, six months and 12-months follow-up. The articular repair tissue was assessed quantitatively and qualitatively by magnetic resonance observation of cartilage repair tissue (MOCART) score based on follow-up MRI at six months and 12 months.
Results
No significant baseline differences were found between two groups. Safety was confirmed with no severe adverse events observed during 12-months follow-up. The SVF-treated knees showed significantly improvement in the mean VAS, WOMAC scores, and ROM at 12-months follow-up visit compared with the baseline. In contrast, the mean VAS, WOMAC scores, and ROM of the control group became even worse but not significant from baseline to the last follow-up visit. WORMS and MOCART measurements revealed a significant improvement of articular cartilage repair in SVF-treated knees compared with hyaluronic acid-treated knees.
Conclusion
The results of this study suggest that autologous adipose-derived SVF treatment is safe and can effectively relief pain, improve function, and repair cartilage defects in patients with knee osteoarthritis.
In this work, we investigated the expression pattern and regulatory function of long noncoding RNA (lncRNA) KCNQ1 opposite strand/antisense transcript 1 (KCNQ1OT1) in breast cancer. We found that ...KCNQ1OT1 was significantly upregulated in breast cancer cell lines. In lentiviral-transduced BT-549 and HCC1599 cells, KCNQ1OT1 knockdown impaired cancer cell functions, including in vitro proliferation and migration, and in vivo transplant growth. The possible sponging target of KCNQ1OT1, human microRNA-107 (hsa-miR-107), was confirmed to be bound by KCNQ1OT1, and was upregulated in breast cancer cells with KCNQ1OT1 downregulation. Further, hsa-miR-107 knockdown in KCNQ1OT1-downregulated cancer cells reversed its impairing effects on cancer cell proliferation and migration in vitro. Thus, loss of KCNQ1OT1 is associated with functional impairment in breast cancer cells, likely through inverse regulation of its sponging target, hsa-miR-107.
This study aimed at establishing more accurate predictive models based on novel machine learning algorithms, with the overarching goal of providing clinicians with effective decision-making ...assistance. We retrospectively analyzed the breast cancer patients recorded in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2016. Multivariable logistic regression analyses were used to identify risk factors for bone metastases in breast cancer, whereas Cox proportional hazards regression analyses were used to identify prognostic factors for breast cancer with bone metastasis (BCBM). Based on the identified risk and prognostic factors, we developed diagnostic and prognostic models that incorporate six machine learning classifiers. We then used the area under the receiver operating characteristic (ROC) curve (AUC), learning curve, precision curve, calibration plot, and decision curve analysis to evaluate performance of the machine learning models. Univariable and multivariable logistic regression analyses showed that bone metastases were significantly associated with age, race, sex, grade, T stage, N stage, surgery, radiotherapy, chemotherapy, tumor size, brain metastasis, liver metastasis, lung metastasis, breast subtype, and PR. Univariate and multivariate Cox regression analyses revealed that age, race, marital status, grade, surgery, radiotherapy, chemotherapy, brain metastasis, liver metastasis, lung metastasis, breast subtype, ER, and PR were closely associated with the prognosis of BCBM. Among the six machine learning models, the XGBoost algorithm predicted the most accurate results (Diagnostic model AUC = 0.98; Prognostic model AUC = 0.88). According to the Shapley additive explanations (SHAP), the most critical feature of the diagnostic model was surgery, followed by N stage. Interestingly, surgery was also the most critical feature of prognostic model, followed by liver metastasis. Based on the XGBoost algorithm, we could effectively predict the diagnosis and survival of bone metastasis in breast cancer and provide targeted references for the treatment of BCBM patients.
