Deep partially linear cox model for current status data.

Deep learning has continuously attained huge success in diverse fields, while its application to survival data analysis remains limited and deserves further exploration. For the analysis of current status data, a deep partially linear Cox model is proposed to circumvent the curse of dimensionality. Modeling flexibility is attained by using deep neural networks (DNNs) to accommodate nonlinear covariate effects and monotone splines to approximate the baseline cumulative hazard function. We establish the convergence rate of the proposed maximum likelihood estimators. Moreover, we derive that the finite-dimensional estimator for treatment covariate effects is $\sqrt{n}$-consistent, asymptotically normal, and attains semiparametric efficiency. Finally, we demonstrate the performance of our procedures through extensive simulation studies and application to real-world data on news popularity.

Study on the Effect of Electrolytes on Processing Efficiency and Accuracy of Titanium Alloy Utilizing Laser and Shaped Tube Electrochemical Machining.

Electrochemical machining (ECM) has become more prevalent in titanium alloy processing. However, the presence of the passivation layer on the titanium alloys significantly impacts the performance of ECM. In an attempt to overcome the passivation effects, a high-temperature electrolyte or the addition of halogen ions to the electrolyte has been used. Still, it often results in compromised machining accuracy and surface roughness. This study applied laser and shaped tube electrolytic machining (Laser-STEM) for titanium alloy drilling, where the laser was guided to the machining zone via total internal reflection. The performance of Laser-STEM using different types of electrolytes was compared. Further, the effects of laser power and pulse voltage on the machining side gap, material removal rate (MRR), and surface roughness were experimentally studied while drilling small holes in titanium alloy. The results indicated that the use of passivating electrolytes improved the machining precision, while the MRR decreased with an increase in laser power during Laser-STEM. The MRR showed an increase while using aggressive electrolytes; however, at the same time, the machining precision deteriorated with the increase in laser power. Particularly, the maximum feeding rate of 6.0 mm/min for the tool electrode was achieved using NaCl solution as the electrolyte during Laser-STEM, marking a 100% increase compared to the rate without the use of a laser. Moreover, the model and equivalent circuits were also established to illustrate the material removal mechanisms of Laser-STEM in different electrolytes. Lastly, the processing of deep small holes with a diameter of 1.5 mm, a depth of 38 mm, and a surface roughness of Ra 2 µm was achieved via Laser-STEM without the presence of a recast layer and heat-affected zones. In addition, the cross-inner flow channels in the titanium alloys were effectively processed.

Cloning of CAT genes in Satsuma mandarin and their expression characteristics in response to environmental stress and arbuscular mycorrhizal fungi.

KEY MESSAGE: CitCAT1 and CitCAT2 were cloned and highly expressed in mature leaves. High temperatures up-regulated CitCAT1 expression, while low temperatures and Diversispora versiformis up-regulated CitCAT2 expression, maintaining a low oxidative damage. Catalase (CAT), a tetrameric heme-containing enzyme, removes hydrogen peroxide (H2O2) to maintain low oxidative damage in plants exposed to environmental stress. This study aimed to clone CAT genes from Citrus sinensis cv. "Oita 4" and analyze their expression patterns in response to environmental stress, exogenous abscisic acid (ABA), and arbuscular mycorrhizal fungal inoculation. Two CAT genes, CitCAT1 (NCBI accession: PP067858) and CitCAT2 (NCBI accession: PP061394) were cloned, and the open reading frames of their proteins were 1479 bp and 1539 bp, respectively, each encoding 492 and 512 amino acids predicted to be localized in the peroxisome, with CitCAT1 being a stable hydrophilic protein and CitCAT2 being an unstable hydrophilic protein. The similarity of their amino acid sequences reached 83.24%, and the two genes were distantly related. Both genes were expressed in stems, leaves, flowers, and fruits, accompanied by the highest expression in mature leaves. In addition, CitCAT1 expression was mainly up-regulated by high temperatures (37 °C), exogenous ABA, and PEG stress within a short period of time, whereas CitCAT2 expression was up-regulated by exogenous ABA and low-temperature (4 °C) stress. Low temperatures (0 °C) for 12 h just up-regulated CitCAT2 expression in Diversispora versiformis-inoculated plants, and D. versiformis inoculation up-regulated CitCAT2 expression, along with lower hydrogen peroxide and malondialdehyde levels in mycorrhizal plants at low temperatures. It is concluded that CitCAT2 has an important role in resistance to low temperatures as well as mycorrhizal enhancement of host resistance to low temperatures.

Transient cavity-cavity strong coupling at terahertz frequency on LiNbO3 chips.

Terahertz (THz) microcavities have garnered considerable attention for their ability to localize and confine THz waves, allowing for strong coupling to remarkably enhance the light-matter interaction. These properties hold great promise for advancing THz science and technology, particularly for high-speed integrated THz chips where transient interaction between THz waves and matter is critical. However, experimental study of these transient time-domain processes requires high temporal and spatial resolution since these processes, such as THz strong coupling, occur in several picoseconds and microns. Thus, most literature studies rarely cover temporal and spatial processes at the same time. In this work, we thoroughly investigate the transient cavity-cavity strong-coupling phenomena at THz frequency and find a Rabi-like oscillation in the microcavities, manifested by direct observation of a periodic energy exchange process via a phase-contrast time-resolved imaging system. Our explanation, based on the Jaynes-Cummings model, provides theoretical insight into this transient strong-coupling process. This work provides an opportunity to deeply understand the transient strong-coupling process between THz microcavities, which sheds light on the potential of THz microcavities for high-speed THz sensor and THz chip design.

POLE2 promotes osteosarcoma progression by enhancing the stability of CD44.

Osteosarcoma (OS) is the most prevalent primary malignancy of bone in children and adolescents. It is extremely urgent to develop a new therapy for OS. In this study, the GSE14359 chip from the GEO database was used to screen differentially expressed genes in OS. DNA polymerase epsilon 2 (POLE2) was confirmed to overexpress in OS tissues and cell lines by immunohistochemical staining, qPCR and Western blot. Knockdown of POLE2 inhibited the proliferation and migration of OS cells in vitro, as well as the growth of tumors in vivo, while the apoptosis rate was increased. Bioinformatics analysis revealed that CD44 and Rac signaling pathway were the downstream molecule and pathway of POLE2, which were inhibited by knockdown of POLE2. POLE2 reduced the ubiquitination degradation of CD44 by acting on MDM2. Moreover, knockdown of CD44 inhibited the tumor-promoting effects of POLE2 overexpression on OS cells. In conclusion, POLE2 augmented the expression of CD44 via inhibiting MDM2-mediated ubiquitination, and then activated Rac signaling pathway to influence the progression of OS, indicating that POLE2/CD44 might be potential targets for OS treatment.

Inherited KDM6AA649T facilitates tumor-immune escape and exacerbates colorectal signet-ring cell carcinoma outcomes.

Childhood onset of colorectal signet-ring cell carcinoma (CR-SRCC) is extremely rare and featured as highly malignant with poor prognosis. Here we reported a CR-SRCC case of 11-year-old boy with a novel inherited X-linked KDM6AA694T mutation. The H3K27me3 demethylase KDM6A was frequently mutated in varieties of tumors and acts as a tumor suppressor. In vivo H3K27me3 demethylation assay demonstrated that KDM6AA694T had dampened H3K27me3 demethylase activity. Overexpression of KDM6AA694T in SRCC cell line KATO3 promoted cell proliferation, invasion and migration, which were further confirmed in vivo by constructing orthotopic tumor growth and lung metastasis model. Besides, expression of KDM6AA694T in immune cells suppresses inflammatory macrophage response and effector T cell response. In conclusion, we characterized a novel inherited KDM6AA694T mutant from a childhood-onset SRCC case and demonstrated that the mutant with impaired H3K27me3 demethylase activity could potentiate tumor malignancy and suppress antitumor immunity.

Exploiting the potential of a novel "in-situ latent heat recovery" in hollow-fiber vacuum membrane distillation process for simultaneously improved water production and energy efficiency.

Thermal driven membrane distillation (MD) technology is a promising method for purifying & recovering various salty (especially high salty) or contaminated wastewaters with low-grade heat sources. However, the drawbacks of "high energy consumption" and "high cooling water consumption" pose special challenges for the future development of this technology. In this article, we report an innovative strategy called "in-situ heat transfer", which is based on the jacketed structure composed of hollow fiber membranes and capillary heat exchange tubes, to simplify the migration steps of condensation latent heat in MD heat recovery process. The results indicate that the novel heat recovery strategy exhibits higher growth rates both in the flux and gained output ratio (47.4 % and 173.1 %, respectively), and further reduces the system's dependence on cooling water. In sum, under the control of the "in-situ heat transfer" mechanism, the functional coupling of "vapor condensation (exothermic)" and "feed evaporation (endothermic)" in limited-domain space is an attractive alternative solution, because it eliminates the disadvantages of the imbalance between heat supply and demand in traditional heat recovery methods. Our research may facilitate the development of MD heat recovery modules for industrial applications, which will help to further achieve the goal of energy saving and emission reduction.

Integrated bioinformatics and machine learning analysis identify ACADL as a potent biomarker of reactive mesothelial cells.

Mesothelial cells with reactive hyperplasia are difficult to distinguish from malignant mesothelioma cells on cell morphology. This study aimed to identify and validate potential biomarkers that distinguish mesothelial cells from mesothelioma cells through machine learning combined with immunohistochemistry (IHC) experiments. We integrated the gene expression matrix from three GEO datasets (GSE2549, GSE12345, GSE51024) to analyze the differently expressed gene (DEGs) between normal and mesothelioma tissues. Then three machine learning algorithms, least absolute shrinkage and selection operator (LASSO), support vector machine-recursive feature elimination (SVM-RFE), and random forest (RF) were used to screen and obtain four shared candidate markers, including ACADL, EMP2, GPD1L, HMMR. The receiver operating characteristic curve (ROC) analysis showed that the area under the curve (AUC) for distinguishing normal from mesothelioma was 0.976, 0.943, 0.962, and 0.956, respectively. The expression and diagnostic performance of these candidate genes were validated in another two independent datasets (GSE42977 and GSE112154), indicating that the performances of ACADL, GPD1L, and HMMR were consistent between the training and validation datasets. Finally, the optimal candidate marker ACADL was verified by IHC assay. ACADL was strongly stained in mesothelial cells, especially for reactive hyperplasic mesothelial cells, but was negative in malignant mesothelioma cells. Therefore, ACADL has the potential to be used as a specific marker of reactive hyperplasic mesothelial cells in the differential diagnosis of mesothelioma.

The Endometrial Stem/Progenitor Cells and Their Niches.

Endometrial stem/progenitor cells are a type of stem cells with the ability to self-renew and differentiate into multiple cell types. They exist in the endometrium and form niches with their neighbor cells and extracellular matrix. The interaction between endometrial stem/progenitor cells and niches plays an important role in maintaining, repairing, and regenerating the endometrial structure and function. This review will discuss the characteristics and functions of endometrial stem/progenitor cells and their niches, the mechanisms of their interaction, and their roles in endometrial regeneration and diseases. Finally, the prospects for their applications will also be explored.

A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma.

Background: Immunotherapy has changed the treatment landscape for lung cancer. This study aims to construct a tumor mutation-related model that combines long non-coding RNA (lncRNA) expression levels and tumor mutation levels in tumor genomes to detect the possibilities of the lncRNA signature as an indicator for predicting the prognosis and response to immunotherapy in lung adenocarcinoma (LUAD). Methods: We downloaded the tumor mutation profiles and RNA-seq expression database of LUAD from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were extracted based on the cumulative number of mutations. Cox regression analyses were used to identify the prognostic lncRNA signature, and the prognostic value of the five selected lncRNAs was validated by using survival analysis and the receiver operating characteristic (ROC) curve. We used qPCR to validate the expression of five selected lncRNAs between human lung epithelial and human lung adenocarcinoma cell lines. The ImmuCellAI, immunophenoscore (IPS) scores and Tumor Immune Dysfunction and Exclusion (TIDE) analyses were used to predict the response to immunotherapy for this mutation related lncRNA signature. Results: A total of 162 lncRNAs were detected among the differentially expressed lncRNAs between the Tumor mutational burden (TMB)-high group and the TMB-low group. Then, five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as tumor mutation-related candidates for constructing the prognostic prediction model. Kaplan‒Meier curves showed that the overall survival of the low-risk group was significantly better than that of the high-risk group, and the results of the GSE50081 set were consistent. The expression levels of PD1, PD-L1 and CTLA4 in the low-risk group were higher than those in the high-risk group. The IPS scores and TIDE scores of patients in the low-risk group were significantly higher than those in the high-risk group. Conclusion: Our findings demonstrated that the five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as candidates for constructing the tumor mutation-related model which may serve as an indicator of tumor mutation levels and have important implications for predicting the response to immunotherapy in LUAD.

A triggered DNA nanomachine with enzyme-free for the rapid detection of telomerase activity in a one-step method.

BACKGROUND: Telomerase is considered a biomarker for the early diagnosis and clinical treatment of cancer. The rapid and sensitive detection of telomerase activity is crucial to biological research, clinical diagnosis, and drug development. However, the main obstacles facing the current telomerase activity assay are the cumbersome and time-consuming procedure, the easy degradation of the telomerase RNA template and the need for additional proteases. Therefore, it is necessary to construct a new method for the detection of telomerase activity with easy steps, efficient reaction and strong anti-interference ability. RESULTS: Herein, an efficient, enzyme-free, economical, sensitive, fluorometric detection method for telomerase activity in one-step, named triggered-DNA (T-DNA) nanomachine, was created based on target-triggered DNAzyme-cleavage activity and catalytic molecular beacon (CMB). Telomerase served as a switch and extended few numbers of (TTAGGG)n repeat sequences to initiate the signal amplification in the T-DNA nanomachine, resulting in a strong fluorescent signal. The reaction was a one-step method with a shortened time of 1 h and a constant temperature of 37 °C, without the addition of any protease. It also sensitively distinguished telomerase activity in various cell lines. The T-DNA nanomachine offered a detection limit of 12 HeLa cells µL-1, 9 SK-Hep-1 cells µL-1 and 3 HuH-7 cells µL-1 with a linear correlation detection range of 0.39 × 102-6.25 × 102 HeLa cells µL-1 for telomerase activity. SIGNIFICANCE: In conclusion, our study demonstrated that the triggered-DNA nanomachine fulfills the requirements for rapid detection of telomerase activity in one-step under isothermal and enzyme-free conditions with excellent specificity, and its simple and stable structure makes it ideal for complex systems. These findings indicated the application prospect of DNA nanomachines in clinical diagnostics and provided new insights into the field of DNA nanomachine-based bioanalysis.

An RRM domain protein SOE suppresses transgene silencing in rice.

Gene expression is regulated at multiple levels, including RNA processing and DNA methylation/demethylation. How these regulations are controlled remains unclear. Here, through analysis of a suppressor for the OsEIN2 over-expressor, we identified an RNA recognition motif protein SUPPRESSOR OF EIN2 (SOE). SOE is localized in nuclear speckles and interacts with several components of the spliceosome. We find SOE associates with hundreds of targets and directly binds to a DNA glycosylase gene DNG701 pre-mRNA for efficient splicing and stabilization, allowing for subsequent DNG701-mediated DNA demethylation of the transgene promoter for proper gene expression. The V81M substitution in the suppressor mutant protein mSOE impaired its protein stability and binding activity to DNG701 pre-mRNA, leading to transgene silencing. SOE mutation enhances grain size and yield. Haplotype analysis in c. 3000 rice accessions reveals that the haplotype 1 (Hap 1) promoter is associated with high 1000-grain weight, and most of the japonica accessions, but not indica ones, have the Hap 1 elite allele. Our study discovers a novel mechanism for the regulation of gene expression and provides an elite allele for the promotion of yield potentials in rice.

Plasma metabolites and risk of myocardial infarction: a bidirectional Mendelian randomization study.

BACKGROUND: Myocardial infarction (MI) is a critical cardiovascular event with multifaceted etiology, involving several genetic and environmental factors. It is essential to understand the function of plasma metabolites in the development of MI and unravel its complex pathogenesis. METHODS: This study employed a bidirectional Mendelian randomization (MR) approach to investigate the causal relationships between plasma metabolites and MI risk. We used genetic instruments as proxies for plasma metabolites and MI and conducted MR analyses in both directions to assess the impact of metabolites on MI risk and vice versa. In addition, the large-scale genome-wide association studies datasets was used to identify genetic variants associated with plasma metabolite (1400 metabolites) and MI (20,917 individuals with MI and 440,906 individuals without MI) susceptibility. Inverse variance weighted was the primary method for estimating causal effects. MR estimates are expressed as beta coefficients or odds ratio (OR) with 95% CI. RESULTS: We identified 14 plasma metabolites associated with the occurrence of MI (P < 0.05), among which 8 plasma metabolites [propionylglycine levels (OR = 0.922, 95% CI: 0.881-0.965, P < 0.001), gamma-glutamylglycine levels (OR = 0.903, 95% CI: 0.861-0.948, P < 0.001), hexadecanedioate (C16-DC) levels (OR = 0.941, 95% CI: 0.911-0.973, P < 0.001), pentose acid levels (OR = 0.923, 95% CI: 0.877-0.972, P = 0.002), X-24546 levels (OR = 0.936, 95% CI: 0.902-0.971, P < 0.001), glycine levels (OR = 0.936, 95% CI: 0.909-0.964, P < 0.001), glycine to serine ratio (OR = 0.930, 95% CI: 0.888-0.974, P = 0.002), and mannose to trans-4-hydroxyproline ratio (OR = 0.912, 95% CI: 0.869-0.958, P < 0.001)] were correlated with a decreased risk of MI, whereas the remaining 6 plasma metabolites [1-palmitoyl-2-arachidonoyl-GPE (16:0/20:4) levels (OR = 1.051, 95% CI: 1.018-1.084, P = 0.002), behenoyl dihydrosphingomyelin (d18:0/22:0) levels (OR = 1.076, 95% CI: 1.027-1.128, P = 0.002), 1-stearoyl-2-docosahexaenoyl-GPE (18:0/22:6) levels (OR = 1.067, 95% CI: 1.027-1.109, P = 0.001), alpha-ketobutyrate levels (OR = 1.108, 95% CI: 1.041-1.180, P = 0.001), 5-acetylamino-6-formylamino-3-methyluracil levels (OR = 1.047, 95% CI: 1.019-1.076, P < 0.001), and N-acetylputrescine to (N (1) + N (8))-acetylspermidine ratio (OR = 1.045, 95% CI: 1.018-1.073, P < 0.001)] were associated with an increased risk of MI. Furthermore, we also observed that the mentioned relationships were unaffected by horizontal pleiotropy (P > 0.05). On the contrary, MI did not lead to significant alterations in the levels of the aforementioned 14 plasma metabolites (P > 0.05 for each comparison). CONCLUSIONS: Our bidirectional MR study identified 14 plasma metabolites associated with the occurrence of MI, among which 13 plasma metabolites have not been reported previously. These findings provide valuable insights for the early diagnosis of MI and potential therapeutic targets.

Timing of first abdominal operation in Crohn's disease based on a diagnostic model.

This study aims to develop a clinical diagnostic model for assessing the need for initial abdominal surgery in patients diagnosed with Crohn's disease (CD) and create a nomogram to facilitate clinical decision-making. A total of 164 surgical CD patients and 230 control CD patients were included in this retrospective analysis. Least Absolute Shrinkage and Selection Operator (Lasso) regression and binomial logistic regression were employed to select clinical variables. The 394 CD patients were randomly allocated to a training set and a validation set in a 7:3 ratio. The filtered variables were used to establish a diagnostic model and nomogram in the training set, subsequently validated in the testing set. Decision Curve Analysis (DCA) and clinical impact curve were constructed to validate the clinical applicability of the model. Binomial logistic regression analysis identified seven clinical variables with a p-value less than 0.01, including Biomarker (B), Waist-to-Height Ratio (WHtR), Intestinal obstruction, Albumin (ALB), Crohn's Disease Activity Index (CDAI), Myocardial Flow Index (MFI), and C-reactive protein (CRP). These variables were utilized to establish the diagnostic model. Calibration curves showed good alignment, with a C-index of 0.996 in the training set and 0.990 in the testing set. DCA and clinical impact curve demonstrated that the diagnostic model had good clinical efficiency and could provide clinical benefits. A validated diagnostic model for determining the timing of the first abdominal operation in CD patients was established and evaluated, showing high discriminative ability, calibration, and clinical efficiency. It can be utilized by clinicians to assess the optimal timing for transitioning CD patients from medical treatment to surgical intervention, providing valuable references for individualized treatment decisions for CD patients.

DRAC 2022: A public benchmark for diabetic retinopathy analysis on ultra-wide optical coherence tomography angiography images.

We described a challenge named "DRAC - Diabetic Retinopathy Analysis Challenge" in conjunction with the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2022). Within this challenge, we provided the DRAC datset, an ultra-wide optical coherence tomography angiography (UW-OCTA) dataset (1,103 images), addressing three primary clinical tasks: diabetic retinopathy (DR) lesion segmentation, image quality assessment, and DR grading. The scientific community responded positively to the challenge, with 11, 12, and 13 teams submitting different solutions for these three tasks, respectively. This paper presents a concise summary and analysis of the top-performing solutions and results across all challenge tasks. These solutions could provide practical guidance for developing accurate classification and segmentation models for image quality assessment and DR diagnosis using UW-OCTA images, potentially improving the diagnostic capabilities of healthcare professionals. The dataset has been released to support the development of computer-aided diagnostic systems for DR evaluation.

Pre-Treatment, Extraction Solvent, and Color Stability of Anthocyanins from Purple Sweetpotato.

Purple sweetpotato anthocyanins (PSPA) exhibit significant potential as food colorants with associated health benefits. However, challenges related to browning and instability have hindered the application of PSPA. In this study, various pre-treatments and solvents for PSPA extraction were evaluated based on color, anthocyanin yields, antioxidant capabilities, and brown index. Browning markedly influenced the color and reduced the antioxidant capacity. Optimal results were obtained with the pre-treatment of "steaming of unpeeled whole sweetpotato" and the solvent "1% citric acid-ddH2O". Furthermore, the color stability of purified PSPA solutions was evaluated under pH levels from 1 to 13 at 25 °C and 65 °C. The PSPA solutions showed a color spectrum from magenta, blue/green, and then to yellow across the pH range. The blue/green hues at pH 10-12 rapidly degraded, while the magenta hue at lower pH showed higher color stability. Elevated temperatures significantly accelerated the PSPA degradation. However, PSPA solutions at pH 1-2 exhibited remarkable color stability, with no spectral decay at either 65 °C for 12 h or 25 °C for 32 days. These results provide valid guidance for the extraction, preservation, and application of PSPA in the food industry.

Rapid Detection of Tannin Content in Wine Grapes Using Hyperspectral Technology.

Wine grape quality is influenced by the variety and growing environment, and the quality of the grapes has a significant impact on the quality of the wine. Tannins are a crucial indicator of wine grape quality, and, therefore, rapid and non-destructive methods for detecting tannin content are necessary. This study collected spectral data of Pinot Noir and Chardonnay using a geophysical spectrometer, with a focus on the 500-1800 nm spectrum. The spectra were preprocessed using Savitzky-Golay (SG), first-order differential (1D), standard normal transform (SNV), and their respective combinations. Characteristic bands were extracted through correlation analysis (PCC). Models such as partial least squares (PLS), support vector machine (SVM), random forest (RF), and one-dimensional neural network (1DCNN) were used to model tannin content. The study found that preprocessing the raw spectra improved the models' predictive capacity. The SVM-RF model was the most effective in predicting grape tannin content, with a test set R2 of 0.78, an RMSE of 0.31, and an RE of 10.71%. These results provide a theoretical basis for non-destructive testing of wine grape tannin content.

Oxygen-Bridged Cu Binuclear Sites for Efficient Electrocatalytic CO2 Reduction to Ethanol at Ultralow Overpotential.

Electrocatalytic CO2 reduction (CO2RR) to alcohols offers a promising strategy for converting waste CO2 into valuable fuels/chemicals but usually requires large overpotentials. Herein, we report a catalyst comprising unique oxygen-bridged Cu binuclear sites (CuOCu-N4) with a Cu···Cu distance of 3.0-3.1 Å and concomitant conventional Cu-N4 mononuclear sites on hierarchical nitrogen-doped carbon nanocages (hNCNCs). The catalyst exhibits a state-of-the-art low overpotential of 0.19 V (versus reversible hydrogen electrode) for ethanol and an outstanding ethanol Faradaic efficiency of 56.3% at an ultralow potential of -0.30 V, with high-stable Cu active-site structures during the CO2RR as confirmed by operando X-ray adsorption fine structure characterization. Theoretical simulations reveal that CuOCu-N4 binuclear sites greatly enhance the C-C coupling at low potentials, while Cu-N4 mononuclear sites and the hNCNC support increase the local CO concentration and ethanol production on CuOCu-N4. This study provides a convenient approach to advanced Cu binuclear site catalysts for CO2RR to ethanol with a deep understanding of the mechanism.

Correlation between Heteroatom Coordination and Hydrogen Evolution for Single-site Pt on Carbon-based Nanocages.

The electrocatalytic performance of single-site catalysts (SSCs) is closely correlated with the electronic structure of metal atoms. Herein we construct a series of Pt SSCs on heteroatom-doped hierarchical carbon nanocages, which exhibit increasing hydrogen evolution reaction (HER) activities along S-doped, P-doped, undoped and N-doped supports. Theoretical simulation indicates a multi-H-atom adsorption process on Pt SSCs due to the low coordination, and a reasonable descriptor is figured out to evaluate the HER activities. Relative to C-coordinated Pt, N-coordinated Pt has higher reactivity due to the electron transfer of N-to-Pt, which enriches the density of states of Pt 5d orbital near the Fermi level and facilitates the capturing of protons, just the opposite to the situations for P- and S-coordinated ones. The stable N-coordinated Pt originates from the kinetic stability throughout the multi-H-atom adsorption process. This finding provides a significant guidance for rational design of advanced Pt SSCs on carbon-based supports.

Variation and disparity in awareness of atrial fibrillation in China: A national cross-sectional study.

BACKGROUND: The latest information regarding the awareness of atrial fibrillation (AF) remains limited in China. OBJECTIVES: The present study aimed to understand the variation and disparity in awareness of AF in China. METHODS: The cross-sectional study used data from the 2020 nationwide epidemiology survey on AF among adults aged 18 years or older in mainland China to assess the prevalence of AF awareness. The awareness of AF diagnostic methods and outcomes was also assessed using an interviewer-administered questionnaire. RESULTS: Of the 114,039 adults responding to the survey, 1463 (age-standardized prevalence, 55.3% (95% confidence interval [CI], 47.7-62.9%) and 10,202 (8.2%, 95%CI 5.4-10.9%) were aware of AF in participants with and without AF, respectively. Of these, 36.4% (95%CI 30.0-42.9%) and 6.3% (95%CI 3.6-9.1%) considered electrocardiogram as a method of diagnosing AF, and 30.0% (95% CI 3.2-8.2%) and 5.2% (95%CI 2.7-7.6%) considered stroke as an outcome of AF. The proportion of participants who being aware of AF varied significantly across sociodemographic and cardiovascular disease subgroups, and was almost consistently lower in rural areas than those in urban areas. Overall, lack of AF awareness was associated with rural areas, geographical region, lower education levels, and without history and had no risk factors of cardiovascular disease. CONCLUSIONS: Nearly half of adults with AF, and >90% non-AF population are unaware of AF in China, with significant variation and disparity. Focused public health initiatives are needed to improve awareness and knowledge of AF among high-risk populations.