Anionic oxyl radical formed on CrVI-oxo anchored on the defect site of the UiO-66 node facilitates methane to methanol conversion.

The direct conversion of methane to methanol has attracted increasing interest due to abundant and low-cost natural gas resources. Herein, by anchoring Cr-oxo/-oxyhydroxides on UiO-66 metal-organic frameworks, we demonstrate that reactive anionic oxyl radicals can be formed by controlling the coordination environment based on the results of density functional theory calculations. The anionic oxyl radicals produced at the completely oxidized CrVI site acted as the active species for facile methane activation. The thermodynamically stable CrVI-oxo/-oxyhydroxides with the anionic oxyl radicals catalyze the activation of the methane C-H bond through a homolytic mechanism. An analysis of the results showed that the catalytic performance of the active oxyl species correlates with the reaction energy of methane activation and H adsorption energies. Following methanol formation, N2O can regenerate the active sites on the most stable CrVI oxyhydroxides, i.e., the Cr(O)4Hf species. The present study demonstrated that the anionic oxyl radicals formed on the anchored CrVI oxyhydroxides by tuning the coordination environment enabled facile methane activation and facilitated methanol production.

The features associated with mammography-occult MRI-detected newly diagnosed breast cancer analysed by comparing machine learning models with a logistic regression model.

PURPOSE: To compare machine learning (ML) models with logistic regression model in order to identify the optimal factors associated with mammography-occult (i.e. false-negative mammographic findings) magnetic resonance imaging (MRI)-detected newly diagnosed breast cancer (BC). MATERIAL AND METHODS: The present single-centre retrospective study included consecutive women with BC who underwent mammography and MRI (no more than 45 days apart) for breast cancer between January 2018 and May 2023. Various ML algorithms and binary logistic regression analysis were utilized to extract features linked to mammography-occult BC. These features were subsequently employed to create different models. The predictive value of these models was assessed using receiver operating characteristic curve analysis. RESULTS: This study included 1957 malignant lesions from 1914 patients, with an average age of 51.64 ± 9.92 years and a range of 20-86 years. Among these lesions, there were 485 mammography-occult BCs. The optimal features of mammography-occult BC included calcification status, tumour size, mammographic density, age, lesion enhancement type on MRI, and histological type. Among the different ML models (ANN, L1-LR, RF, and SVM) and the LR-based combined model, the ANN model with RF features was found to be the optimal model. It demonstrated the best discriminative performance in predicting mammography false- negative findings, with an AUC of 0.912, an accuracy of 86.90%, a sensitivity of 85.85%, and a specificity of 84.18%. CONCLUSION: Mammography-occult MRI-detected breast cancers have features that should be considered when performing breast MRI to improve the detection rate for breast cancer and aid in clinician management.

The breakdown of both strange metal and superconducting states at a pressure-induced quantum critical point in iron-pnictide superconductors.

Here we report the first observation of the concurrent breakdown of the strange metal (SM) normal state and superconductivity at a pressure-induced quantum critical point in Ca10(Pt4As8)((Fe0.97Pt0.03)2As2)5 superconductor. We find that, upon suppressing the superconducting state, the power exponent (α) changes from 1 to 2, and the slope of the temperature-linear resistivity per FeAs layer (A□) gradually diminishes. At a critical pressure, A□ and superconducting transition temperature (Tc) go to zero concurrently, where a quantum phase transition from a superconducting state with a SM normal state to a non-superconducting Fermi liquid state occurs. Scaling analysis reveals that the change of A□ with Tc obeys the relation of Tc ~ (A□)0.5, similar to what is seen in other chemically doped unconventional superconductors. These results suggest that there is a simple but powerful organizational principle of connecting the SM normal state with the high-Tc superconductivity.

In-Depth Serum Proteomics Reveals the Trajectory of Hallmarks of Cancer in Hepatitis B Virus-Related Liver Diseases.

Hepatocellular carcinoma (HCC) is a prevalent cancer in China, with chronic hepatitis B (CHB) and liver cirrhosis (LC) being high-risk factors for developing HCC. Here, we determined the serum proteomes (762 proteins) of 125 healthy controls and Hepatitis B virus-infected CHB, LC, and HCC patients and constructed the first cancerous trajectory of liver diseases. The results not only reveal that the majority of altered biological processes were involved in the hallmarks of cancer (inflammation, metastasis, metabolism, vasculature, and coagulation) but also identify potential therapeutic targets in cancerous pathways (i.e., IL17 signaling pathway). Notably, the biomarker panels for detecting HCC in CHB and LC high-risk populations were further developed using machine learning in two cohorts comprised of 200 samples (discovery cohort = 125 and validation cohort = 75). The protein signatures significantly improved the area under the receiver operating characteristic curve of HCC (CHB discovery and validation cohort = 0.953 and 0.891, respectively; LC discovery and validation cohort = 0.966 and 0.818, respectively) compared to using the traditional biomarker, alpha-fetoprotein, alone. Finally, selected biomarkers were validated with parallel reaction monitoring mass spectrometry in an additional cohort (n = 120). Altogether, our results provide fundamental insights into the continuous changes of cancer biology processes in liver diseases and identify candidate protein targets for early detection and intervention.

Elimination of hepatitis C in a hospital characterized by infectious diseases.

Background: The World Health Organization has proposed to eliminate hepatitis C by 2030, yet there is still a large gap to the goal. Screening for hepatitis C is cost-effective and efficient in medical institutions. The aim of this study was to identify the key populations for HCV antibody screening in hospital characterized by infectious diseases, and provide estimates of the proportion of HCV-infected persons in the Beijing Ditan hospital completing each step along a proposed HCV treatment cascade. Methods: A total of 105,112 patients who underwent HCV antibody testing in Beijing Ditan hospital between 2017 and 2020 were included in this study. HCV antibody and HCV RNA positivity rate were calculated and compared by chi-square test. Results: The positivity rate of HCV antibody was 6.78%. The HCV antibody positivity rate and the proportion of positive patients showed an upward trend along with age in the five groups between 10-59 years. In the contrary, a decreasing trend was observed in the three groups above 60 years. Patients with positive HCV antibody were mainly from the Liver Disease Center (36.53%), the Department of Integrative Medicine (16.10%), the Department of Infectious Diseases (15.93%) and the Department of Obstetrics and Gynecology (9.44%). Among HCV antibody positive patients, 6,129 (85.95%) underwent further HCV RNA testing, of whom 2097 were HCV RNA positive, the positivity rate was 34.21%. Of the patients who were HCV RNA positive, 64.33% did not continue with HCV RNA testing. The cure rate for HCV antibody positive patients was 64.98%. Besides, there was a significant positive correlation between HCV RNA positivity rate and HCV antibody level (r = 0.992, P < 0.001). The detection rate of HCV antibody among inpatients showed an upward trend (Z = 5.567, P < 0.001), while the positivity rate showed a downward trend (Z = 2.2926, P = 0.0219). Conclusions: We found that even in hospitals characterized by infectious diseases, a large proportion of patients did not complete each step along a proposed HCV treatment cascade. Besides, we identified key populations for HCV antibody screening, namely: (1) patients over 40 years of age, especially those aged 50-59 years; (2) the Department of Infectious Diseases and the Department of Obstetrics and Gynecology patients. In addition, HCV RNA testing was highly recommended for patients with HCV antibody levels above 8 S/CO.

S100A11 Promotes Metastasis via AKT and ERK Signaling Pathways and Has a Diagnostic Role in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is the most common and malignant liver tumor worldwide, although the treatment approaches for HCC continue to evolve, metastasis is the main reason for high mortality rates. S100 calcium-binding protein A11 (S100A11), an important member of the S100 family of small calcium-binding proteins, is overexpressed in various cells and regulates tumor development and metastasis. However, few studies report the role and underlying regulatory mechanisms of S100A11 in HCC development and metastasis. Herein, we discovered that S100A11 is overexpressed and associated with poor clinical outcomes in HCC cohorts, and we provided the first demonstration that S100A11 could serve as a novel diagnostic biomarker used in conjunction with AFP for HCC. Further analysis implied that S100A11 outperforms AFP in determining whether HCC patients have hematogenous metastasis or not. Using in vitro cell culture model, we demonstrated that S100A11 is overexpressed in metastatic hepatoma cells, knockdown of S100A11 decreases hepatoma cells proliferation, migration, invasion, and epithelial-mesenchymal transition process by inhibiting AKT and ERK signaling pathways. Altogether, our study provides new sights into the biological function and mechanisms underlying S100A11 in promoting metastasis of HCC and explores a novel target for HCC diagnosis and treatment.

Coupled oxygen desorption and structural reconstruction accompanying reduction of copper oxide.

Understanding structural transformation and phase transition accompanying reactions in a solid as a catalyst or oxygen carrier is important to the design and optimization of many catalytic or chemical looping reaction processes. Herein, we combined density functional theory calculation with the stochastic surface walking global optimization approach to track the structural transformation accompanying the reduction of CuO upon releasing oxygen. We then used machine learning (ML) methods to correlate the structural properties of CuOx with varying x. By decomposing a reduction step into oxygen detachment and structural reconstruction, we identified two types of pathways: (1) uniform reduction with minimal structural changes; (2) segregated reduction with significant reconstruction. The results of ML analysis showed that the most important feature is the radial distribution functions of Cu-O at a percentage of oxygen vacancy [C(OV)] < 50% and Cu-Cu at C(OV) > 50% for CuOx formation. These features reflect the underlying physicochemical origin, i.e., Cu-O breaking and Cu-Cu formation in the respective stage of reduction. Phase diagram analysis indicates that CuO will be reduced to Cu2O under a typical oxygen uncoupling condition. This work demonstrates the complexity of solid structural transformation and the potential of ML methods in studying solid state materials involved in many chemical processes.

Lyophilized mRNA-lipid nanoparticle vaccines with long-term stability and high antigenicity against SARS-CoV-2.

Advanced mRNA vaccines play vital roles against SARS-CoV-2. However, most current mRNA delivery platforms need to be stored at -20 °C or -70 °C due to their poor stability, which severely restricts their availability. Herein, we develop a lyophilization technique to prepare SARS-CoV-2 mRNA-lipid nanoparticle vaccines with long-term thermostability. The physiochemical properties and bioactivities of lyophilized vaccines showed no change at 25 °C over 6 months, and the lyophilized SARS-CoV-2 mRNA vaccines could elicit potent humoral and cellular immunity whether in mice, rabbits, or rhesus macaques. Furthermore, in the human trial, administration of lyophilized Omicron mRNA vaccine as a booster shot also engendered strong immunity without severe adverse events, where the titers of neutralizing antibodies against Omicron BA.1/BA.2/BA.4 were increased by at least 253-fold after a booster shot following two doses of the commercial inactivated vaccine, CoronaVac. This lyophilization platform overcomes the instability of mRNA vaccines without affecting their bioactivity and significantly improves their accessibility, particularly in remote regions.

Intron-capture RNA-seq reveals the landscape of intronic RNAs in Arabidopsis.

Intronic RNAs have been overlooked for a long time: They are functional, but treated as "junk." In this work, we designed a new sequencing strategy to investigate intronic RNAs. By using intron-capture RNA-seq, we systematically analyzed the intronic RNAs in Arabidopsis by zooming into the intronic regions an order of magnitude deeper than in previous work. Our key findings include: (1) Intron-capture RNA-seq is a much more efficient approach to analyze intronic RNAs than total RNA-seq and mRNA-seq. (2) We identified three types of intronic RNAs, and found that the GC pattern differs significantly between the introns with and without intronic RNAs. (3) We detected many hidden elements in introns, including circular RNAs, splice junctions, and transcripts that have previously been overlooked. (4) The expression of these intronic RNAs varies during the time course of pathogen infection, which indicates that an unknown mechanism may exist for these RNAs. (5) We also demonstrated that most of intronic RNAs are detectable in both Arabidopsis and rice, suggesting that these non-coding molecules are conserved. Taken together, this work proposes an efficient strategy to analyze intronic RNAs, and provides an unprecedented view of this essential component in biological pathways.

Ni-Catalyzed Asymmetric Hydrogenation of α-Substituted α,ß-Unsaturated Phosphine Oxides/Phosphonates/Phosphoric Acids.

Efficient Ni/(S,S)-Ph-BPE-catalyzed asymmetric hydrogenation of α-substituted α,ß-unsaturated phosphine oxides/phosphonates/phosphoric acids has been successfully developed, and a wide range of chiral α-substituted phosphines hydrogenation products were obtained in generally high yields with excellent enantioselective control (92%-99% yields, 84%->99% ee). This method features a cheap transition metal nickel catalytic system, high functional group tolerance, wide substrate scope generality, and excellent enantioselectivity. A plausible catalytic cycle was proposed for this asymmetric hydrogenation according to the results of deuterium-labeling experiments.

Respiratory immune status and microbiome in recovered COVID-19 patients revealed by metatranscriptomic analyses.

Coronavirus disease 2019 (COVID-19) is currently a severe threat to global public health, and the immune response to COVID-19 infection has been widely investigated. However, the immune status and microecological changes in the respiratory systems of patients with COVID-19 after recovery have rarely been considered. We selected 72 patients with severe COVID-19 infection, 57 recovered from COVID-19 infection, and 65 with non-COVID-19 pneumonia, for metatranscriptomic sequencing and bioinformatics analysis. Accordingly, the differentially expressed genes between the infected and other groups were enriched in the chemokine signaling pathway, NOD-like receptor signaling pathway, phagosome, TNF signaling pathway, NF-kappa B signaling pathway, Toll-like receptor signaling pathway, and C-type lectin receptor signaling pathway. We speculate that IL17RD, CD74, and TNFSF15 may serve as disease biomarkers in COVID-19. Additionally, principal coordinate analysis revealed significant differences between groups. In particular, frequent co-infections with the genera Streptococcus, Veillonella, Gemella, and Neisseria, among others, were found in COVID-19 patients. Moreover, the random forest prediction model with differential genes showed a mean area under the curve (AUC) of 0.77, and KCNK12, IL17RD, LOC100507412, PTPRT, MYO15A, MPDZ, FLRT2, SPEG, SERPINB3, and KNDC1 were identified as the most important genes distinguishing the infected group from the recovered group. Agrobacterium tumefaciens, Klebsiella michiganensis, Acinetobacter pittii, Bacillus sp. FJAT.14266, Brevundimonas naejangsanensis, Pseudopropionibacterium propionicum, Priestia megaterium, Dialister pneumosintes, Veillonella rodentium, and Pseudomonas protegens were selected as candidate microbial markers for monitoring the recovery of COVID patients. These results will facilitate the diagnosis, treatment, and prognosis of COVID patients recovering from severe illness.

Review on Eco-Environment Research in the Yellow River Basin: A Bibliometric Perspective.

The Yellow River Basin (YRB) is an important economic zone and ecological barrier in China. The analysis of its research characteristics and hotspots has been helpful to grasping the future research direction. This work carried out text mining and analysis on scientific papers related to eco-environment research in the YRB from English and Chinese publications. It showed that: there was a fluctuating upward trend over the past 30 years, which was closely related to major events in the YRB during the same period. Chinese research institutions have a closer cooperation with the USA, Australia and other developed countries. More articles were from high-quality journals in ecology, the environment, and others. Interestingly, research institutions with more Chinese articles were mainly located around Beijing or the YRB. Additionally, from a research object perspective, both the English and Chinese articles have mainly focused on large areas such as the lower Yellow River, the middle reaches of the Yellow River, and the upper reaches of the Yellow River, then turning to small areas such as the Yellow River estuary and the source area of the Yellow River. Eco-environment research in the YRB has involved multiple disciplines, and "water-soil-vegetation-ecological protection" has been widely concerned. From the evolution law of hot topics, it has shown a transformation from quantity to quality, from utilization to management, from macro to micro, from construction to high-quality development. It suggests that future research should focus on water, soil, the ecological environment and local high-quality development in small regions and small watersheds.

The expression of cuproptosis-related genes in hepatocellular carcinoma and their relationships with prognosis.

Background: The mechanism of cuproptosis has recently been reported in lipoylated proteins of the tricarboxylic acid (TCA) cycle. Besides, the role of copper was previously recognized in cancer progression. We evaluated the prognostic value of cuproptosis-related gene expression in hepatocellular carcinoma (HCC). Methods: Remarkable genes were selected both in differential expression analysis and Kaplan-Meier survival analysis from ninety-six cuproptosis-related genes using The Cancer Genome Atlas (TCGA) database. The relationships between clinical characteristics and gene expression were performed with Wilcoxon signed-rank test, Kruskal-Wallis test, and logistic regression. Clinicopathologic factors correlated with overall survival in HCCs conducting univariate and multivariate Cox regression analysis. Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and Human Protein Atlas (HPA) databases were utilized to verify the results. Furthermore, Gene Set Enrichment Analysis (GSEA) identified the potential key pathways that dominate cuproptosis in HCC. Results: Elevated ATP7A, SLC25A3, SCO2, COA6, TMEM199, ATP6AP1, LIPT1, DLAT, PDHA1, MTF1, ACP1, FDX2, NUBP2, CIAPIN1, ISCA2 and NDOR1 expression, as well as declined AOC1, FDX1, MT-CO1, and ACO1 expression were significantly emerged in HCC tumor tissues and were significantly associated with HCCs poor survival. The expressions of screened cuproptosis-related genes were prominently related to clinical features. GSEA analysis reported many key signaling pathways (such as natural killer cell mediated cytotoxicity, TCA cycle, glutathione metabolism, ATP-binding cassette (ABC) transporters, Notch signaling pathway, ErbB signaling pathway, and metabolism of xenobiotics by cytochrome p450) were differentially enriched in HCCs with varying degrees of cuproptosis-related genes expression. Conclusions: The twenty cuproptosis-related genes might be utilized as new candidate prognostic biomarkers for HCC.

Using expression quantitative trait loci data and graph-embedded neural networks to uncover genotype-phenotype interactions.

Motivation: A central goal of current biology is to establish a complete functional link between the genotype and phenotype, known as the so-called genotype-phenotype map. With the continuous development of high-throughput technology and the decline in sequencing costs, multi-omics analysis has become more widely employed. While this gives us new opportunities to uncover the correlation mechanisms between single-nucleotide polymorphism (SNP), genes, and phenotypes, multi-omics still faces certain challenges, specifically: 1) When the sample size is large enough, the number of omics types is often not large enough to meet the requirements of multi-omics analysis; 2) each omics' internal correlations are often unclear, such as the correlation between genes in genomics; 3) when analyzing a large number of traits (p), the sample size (n) is often smaller than p, n << p, hindering the application of machine learning methods in the classification of disease outcomes. Results: To solve these issues with multi-omics and build a robust classification model, we propose a graph-embedded deep neural network (G-EDNN) based on expression quantitative trait loci (eQTL) data, which achieves sparse connectivity between network layers to prevent overfitting. The correlation within each omics is also considered such that the model more closely resembles biological reality. To verify the capabilities of this method, we conducted experimental analysis using the GSE28127 and GSE95496 data sets from the Gene Expression Omnibus (GEO) database, tested various neural network architectures, and used prior data for feature selection and graph embedding. Results show that the proposed method could achieve a high classification accuracy and easy-to-interpret feature selection. This method represents an extended application of genotype-phenotype association analysis in deep learning networks.

MolMiner: You Only Look Once for Chemical Structure Recognition.

Molecular structures are commonly depicted in 2D printed forms in scientific documents such as journal papers and patents. However, these 2D depictions are not machine readable. Due to a backlog of decades and an increasing amount of printed literatures, there is a high demand for translating printed depictions into machine-readable formats, which is known as Optical Chemical Structure Recognition (OCSR). Most OCSR systems developed over the last three decades use a rule-based approach, which vectorizes the depiction based on the interpretation of vectors and nodes as bonds and atoms. Here, we present a practical software called MolMiner, which is primarily built using deep neural networks originally developed for semantic segmentation and object detection to recognize atom and bond elements from documents. These recognized elements can be easily connected as a molecular graph with a distance-based construction algorithm. MolMiner gave state-of-the-art performance on four benchmark data sets and a self-collected external data set from scientific papers. As MolMiner performed similarly well in real-world OCSR tasks with a user-friendly interface, it is a useful and valuable tool for daily applications. The free download links of Mac and Windows versions are available at https://github.com/iipharma/pharmamind-molminer.

The association between several autophagy-related genes and their prognostic values in hepatocellular carcinoma: a study on the foundation of TCGA, GEPIA and HPA databases.

BACKGROUND: The purpose of this study was to investigate the relationship between the expression of autophagy-related genes and prognosis in hepatocellular carcinoma (HCC). METHODS AND RESULTS: We selected three autophagy-related genes (ATG3, ATG7, and ATG9A) from gene expression data of liver cancer patients in The Cancer Genome Atlas (TCGA) database by Kaplan-Meier survival analysis, univariate and multivariate Cox regression analysis, and Gene Set Enrichment Analysis (GSEA). Human Protein Atlas (HPA) and Gene Expression Profiling Interactive Analysis (GEPIA) databases were applied to testify the credibility of our results. The expression levels of ATG3, ATG7, and ATG9A were verified by real-time quantitative PCR (RT-qPCR) in normal liver cells (L02) and three HCC cell lines (HepG2, Hep3b, and Li-7). Data analysis results from TCGA showed high ATG3, ATG7, ATG9A expression in HCC tumor tissues. Kaplan-Meier survival analysis showed that the survival rate of the high expression group of ATG3, ATG7, and ATG9A was all significantly lower than the low expression group. GSEA analysis showed that many signaling pathways (such as the regulation of autophagy, glycine serine and threonine metabolism, pathways in cancer, mitogen-activated protein kinase (MAPK) signaling pathway, mammalian target of rapamycin (mTOR) signaling pathway, as well as P53 signaling pathway) were differentially enriched in HCCs with ATG3, ATG7, and ATG9A expression. GEPIA and RT-qPCR also identified that the mRNA expression level of ATG3, ATG7, and ATG9A in normal liver cells were significantly lower than in HCC cells. High protein expression of ATG3, ATG7, and ATG9A was displayed in HCCs from the HPA database. CONCLUSIONS: The ATG3, ATG7, ATG9A might be utilized as prognostic biomarkers for liver cancer.

Amoxicillin encapsulated in the N-2-hydroxypropyl trimethyl ammonium chloride chitosan and N,O-carboxymethyl chitosan nanoparticles: Preparation, characterization, and antibacterial activity.

This is a report on the encapsulation amoxicillin (AMX) in the N-2-Hydroxypropyl trimethyl ammonium chloride chitosan (N-2-HACC) and N,O-carboxymethyl chitosan (CMCS) nanoparticles (NPs) for biomedical applications. The N-2-HACC/CMCS NPs have broad-spectrum antibacterial properties. In order to achieve sustained and slow drug release, improve drug transport efficiency and bioavailability, prolong drug residence time, and reduce pollution, we synthesized highly efficient, easily absorbed and rapidly degradable nano-formulation veterinary antibiotics in this study. The N-2-HACC/CMCS NPs were used for the encapsulation of AMX, and the cytocompatibility, in vitro release, in vivo drug release kinetics and antimicrobial activity of N-2-HACC/CMCS/AMX NPs were investigated. The NPs displayed a round shape and smooth surface, and the NPs allowed the sustained release of AMX at a much slower rate than that of non-coated AMX. The NPs exhibited excellent cytocompatibility and the antimicrobial activity against Escherichia coli, Acinetobacter baumannii, Streptococcus pneumoniae and Staphylococcus aureus. Moreover, the NPs could store at 4 °C, -20 °C and 25 ± 5 °C for 30 d. These results suggested that the N-2-HACC/CMCS NPs could be availed as a candidate for drug delivery carrier to achieve sustained and slow release, improve bioavailability, prolong residence time at the target site, and reduce the dosage of drug.

Blood-brain barrier Permeable nanoparticles for Alzheimer's disease treatment by selective mitophagy of microglia.

Current treatments for Alzheimer's disease (AD) that focus on inhibition of Aß aggregation failed to show effectiveness in people who already had Alzheimer's symptoms. Strategies that synergistically exert neuroprotection and alleviation of oxidative stress could be a promising approach to correct the pathological brain microenvironment. Based on the key roles of microglia in modulation of AD microenvironment, we describe here the development of Prussian blue/polyamidoamine (PAMAM) dendrimer/Angiopep-2 (PPA) nanoparticles that can regulate the mitophagy of microglia as a potential AD treatment. PPA nanoparticles exhibit superior blood-brain barrier (BBB) permeability and exert synergistic effects of ROS scavenging and restoration of mitochondrial function of microglia. PPA nanoparticles effectively reduce neurotoxic Aß aggregate and rescue the cognitive functions in APP/PS1 model mice. Together, our data suggest that these multifunctional dendrimer nanoparticles exhibit efficient neuroprotection and microglia modulation and can be exploited as a promising approach for the treatment of AD.

Understanding the role of Cu+/Cu0 sites at Cu2O based catalysts in ethanol production from CO2 electroreduction -A DFT study.

Cu2O based electrocatalysts generally exhibit better selectivity for C2 products (ethylene or ethanol) in electrochemical carbon dioxide reduction. The surface characteristic of the mixed Cu+ and Cu0 chemical state is believed to play an essential role that is still unclear. In the present study, density functional theory (DFT) calculations have been performed to understand the role of copper chemical states in selective ethanol formation using a partially reduced Cu2O surface model consisting of adjacent Cu+/Cu0 sites. We mapped out the free energy diagram of the reaction pathway from CO intermediate to ethanol and discussed the relation between the formation of critical reduction intermediates and the configuration of Cu+/Cu0 sites. The results showed that Cu+ sites facilitate the adsorption and stabilization of *CO, as well as its further hydrogenation to *CHO. More importantly, as compared to the high reaction energy (1.23 eV) of the dimerization of two *CO on Cu+/Cu0 sites, the preferable formation of *CHO on the Cu+ site makes the C-C coupling reaction with *CO on the Cu0 site happen under a relatively lower energy barrier of 0.58 eV. Furthermore, the post C-C coupling steps leading to the formation of the key intermediate *OCHCH2 to C2 compound are all thermodynamically favoured. Noteworthily, it is found that *OCHCH2 inclines to the ethanol formation because the coordinatively unsaturated Cu+ site could maintain the C-O bond of *OCHCH2, and the weak binding between *O and Cu+/Cu0 sites helps inhibit the pathway toward ethylene. These findings may provide guidelines for the design of CO and CO2 reduction active sites with enhanced ethanol selectivity.

Testing the impact of first-mover advantage on household energy-related carbon emissions: an exploratory study from six urban agglomerations in China.

The household sector has become the second-largest source of energy consumption and CO2 emissions in China. It is important to understand the trends and changing mechanisms of household energy-related CO2 emissions (HECEs) in different social stages for mitigating the impact of climate change. However, the existing trends in HECEs and whether they are congruent with the expectation that HECEs in later developed areas are lower than those in priority areas under the same economic level are unclear. Here, we compared the per capita HECEs (PHECEs) of urban agglomerations under the same economic standards and analyzed the causes of the comparative results. We find that (1) HECEs increased rapidly from 3.65 × 108 t to 12.42 × 108 t during 1995-2017, with an average annual growth rate of 14.19%; (2) urban agglomerations that developed earlier do not have higher PHECEs. The PHECEs of urban agglomerations with moderate and later development do not decrease under increased social, technological, and cognitive conditions; (3) carbon intensity (CI), energy intensity (EI), and per capita regional gross domestic product (PCG) have a positive impact on PHECEs, and the potential impact of EI on PHECEs reduction is greater; (4) the effects of CI, EI, and PCG on PHECEs in different urban agglomerations are various. However, these effects are similar within urban agglomerations. Our study provides a reference for reducing CO2 emissions in the household sector and for the green development of urban agglomerations and emphasizes that the growth of HECE at a reasonable level is necessary when technology does not meet sufficient constraints.