Asymmetrically Coordinated Cu Dual-Atom-Sites Enables Selective CO2 Electroreduction to Ethanol.

Electrochemical reduction of CO2 (CO2RR) to value-added liquid fuels is a highly attractive solution for carbon-neutral recycling, especially for C2+ products. However, the selectivity control to preferable products is a great challenge due to the complex multi-electron proton transfer process. In this work, a series of Cu atomic dispersed catalysts are synthesized by regulating the coordination structures to optimize the CO2RR selectivity. Cu2-SNC catalyst with a uniquely asymmetrical coordinated CuN2-CuNS site shows high ethanol selective with the FE of 62.6% at -0.8 V versus RHE and 60.2% at 0.9 V versus RHE in H-Cell and Flow-Cell test, respectively. Besides, the nest-like structure of Cu2-SNC is beneficial to the mass transfer process and the selection of catalytic products. In situ experiments and theory calculations reveal the reaction mechanisms of such high selectivity of ethanol. The S atoms weaken the bonding ability of the adjacent Cu to the carbon atom, which accelerates the selection from *CHCOH to generate *CHCHOH, resulting in the high selectivity of ethanol. This work indicates a promising strategy in the rational design of asymmetrically coordinated single, dual, or tri-atom catalysts and provides a candidate material for CO2RR to produce ethanol.

Atomic Printing Strategy Achieves Precise Anchoring of Dual-Copper Atoms on C2N Structure for Efficient CO2 Reduction to Ethylene.

Isolated metal sites catalysts (IMSCs) play crucial role in electrochemical CO2 reduction, with potential industrial applications. However, tunable synthesis strategies for IMSCs are limited. Herein, we present an atomic printing strategy that draws inspiration from the ancient Chinese "movable-type printing technology". Selecting customizable combinations of metal atoms as metal precursors form an extensive binuclear metal library. A series of dual-atom catalysts were prepared by utilizing the edge nitrogen atoms in the C2N cavity as anchoring "pincers" to capture metal atoms. To prove utility, the dual atom catalyst Cu2-C2N is investigated as electrocatalytic CO2RR catalyst. The synergistic interaction of dual Cu atoms promotes C-C coupling and guarantees FEC2+ (90.8%) and FEC2H4. (71.7%) at -1.10 V vs RHE. DFT calculations revealed the Cu2 site would be subtly flipped during CO2RR for enhancing *CO adsorption and dimerization. We validate that atomic printing strategies are applicable to wide range of metal combinations, representing a significant advancement in the development of IMSCs.

Low-dose CT image super-resolution with noise suppression based on prior degradation estimator and self-guidance mechanism.

The anatomies in low-dose computer tomography (LDCT) are usually distorted during the zooming-in observation process due to the small amount of quantum. Super-resolution (SR) methods have been proposed to enhance qualities of LDCT images as post-processing approaches without increasing radiation damage to patients, but suffered from incorrect prediction of degradation information and incomplete leverage of internal connections within the 3D CT volume, resulting in the imbalance between noise removal and detail sharpening in the super-resolution results. In this paper, we propose a novel LDCT SR network where the degradation information self-parsed from the LDCT slice and the 3D anatomical information captured from the LDCT volume are integrated to guide the backbone network. The prior degradation estimator (PDE) is proposed following the contrastive learning strategy to estimate the degradation features in the LDCT images without paired low-normal dose CT images. The self-guidance fusion module (SGFM) is designed to capture anatomical features with internal 3D consistencies between the squashed images along the coronal, sagittal, and axial views of the CT volume. Finally, the features representing degradation and anatomical structures are integrated to recover the CT images with higher resolutions. We apply the proposed method to the 2016 NIH-AAPM Mayo Clinic LDCT Grand Challenge dataset and our collected LDCT dataset to evaluate its ability to recover LDCT images. Experimental results illustrate the superiority of our network concerning quantitative metrics and qualitative observations, demonstrating its potential in recovering detail-sharp and noise-free CT images with higher resolutions from the practical LDCT images.

Simultaneously activating molecular oxygen and surface lattice oxygen on Pt/TiO2 for low-temperature CO oxidation.

Developing high-performance Pt-based catalysts with low Pt loading is crucial but challenging for CO oxidation at temperatures below 100 °C. Herein, we report a Pt-based catalyst with only a 0.15 wt% Pt loading, which consists of Pt-Ti intermetallic single-atom alloy (ISAA) and Pt nanoparticles (NP) co-supported on a defective TiO2 support, achieving a record high turnover frequency of 11.59 s-1 at 80 °C and complete conversion of CO at 120 °C. This is because the coexistence of Pt-Ti ISAA and Pt NP significantly alleviates the competitive adsorption of CO and O2, enhancing the activation of O2. Furthermore, Pt single atom sites are stabilized by Pt-Ti ISAA, resulting in distortion of the TiO2 lattice within Pt-Ti ISAA. This distortion activates the neighboring surface lattice oxygen, allowing for the simultaneous occurrence of the Mars-van Krevelen and Langmuir-Hinshelwood reaction paths at low temperatures.

Porous alumina nanosheet-supported asymmetric platinum clusters for efficient diboration of alkynes.

Precisely designing asymmetrical structures is an effective strategy to optimize the performance of metallic catalysts. Asymmetric Pt clusters were attached to defect-rich porous alumina nanosheets (Pt clu/dp-Al2O3) using a pyrolysis technique coupled with wet impregnation. These Pt-functionalized nanosheets feature a high concentration of active sites, demonstrating remarkable cycling performance and catalytic activity in alkyne diboration. The conversion yield and selectivity can reach up to 97% and 95%, correspondingly.

p-d Orbital Hybridization Induced by Asymmetrical FeSn Dual Atom Sites Promotes the Oxygen Reduction Reaction.

With more flexible active sites and intermetal interaction, dual-atom catalysts (DACs) have emerged as a new frontier in various electrocatalytic reactions. Constructing a typical p-d orbital hybridization between p-block and d-block metal atoms may bring new avenues for manipulating the electronic properties and thus boosting the electrocatalytic activities. Herein, we report a distinctive heteronuclear dual-metal atom catalyst with asymmetrical FeSn dual atom sites embedded on a two-dimensional C2N nanosheet (FeSn-C2N), which displays excellent oxygen reduction reaction (ORR) performance with a half-wave potential of 0.914 V in an alkaline electrolyte. Theoretical calculations further unveil the powerful p-d orbital hybridization between p-block stannum and d-block ferrum in FeSn dual atom sites, which triggers electron delocalization and lowers the energy barrier of *OH protonation, consequently enhancing the ORR activity. In addition, the FeSn-C2N-based Zn-air battery provides a high maximum power density (265.5 mW cm-2) and a high specific capacity (754.6 mA h g-1). Consequently, this work validates the immense potential of p-d orbital hybridization along dual-metal atom catalysts and provides new perception into the logical design of heteronuclear DACs.

Induro-RT mediated circRNA-sequencing (IMCR-seq) enables comprehensive profiling of full-length and long circular RNAs from low input total RNA.

Circular RNA (circRNA) has recently gained attention for its emerging biological activities, relevance to disease, potential as biomarkers, and promising an alternative modality for RNA vaccines. Nevertheless, sequencing circRNAs has presented challenges. In this context, we introduce a novel circRNA sequencing method called Induro-RT mediated circRNA-sequencing (IMCR-seq), which relies on a group II intron reverse transcriptase with robust rolling circle reverse transcription activity. The IMCR-seq protocol eliminates the need for conventional circRNA enrichment methods such as rRNA depletion and RNaseR digestion yet achieved the highest circRNA enrichment and detected 6-1000 times more circRNAs for the benchmarked human samples compared to other methods. IMCR-seq is applicable to any organism, capable of detecting circRNAs of longer than 7000 nucleotides, and is effective on samples as small as 10 ng of total RNA. These enhancements render IMCR-seq suitable for clinical samples, including disease tissues and liquid biopsies. We demonstrated the clinical relevance of IMCR-seq by detecting cancer-specific circRNAs as potential biomarkers from IMCR-seq results on lung tumor tissues together with blood plasma samples from both a healthy individual and a lung cancer patient. In summary, IMCR-seq presents an efficient and versatile circRNA sequencing method with high potential for research and clinical applications.

Sulfur-Bridged Asymmetric CuNi Bimetallic Atom Sites for CO2 Reduction with High Efficiency.

Double-atom catalysts (DACs) with asymmetric coordination are crucial for enhancing the benefits of electrochemical carbon dioxide reduction and advancing sustainable development, however, the rational design of DACs is still challenging. Herein, this work synthesizes atomically dispersed catalysts with novel sulfur-bridged Cu-S-Ni sites (named Cu-S-Ni/SNC), utilizing biomass wool keratin as precursor. The plentiful disulfide bonds in wool keratin overcome the limitations of traditional gas-phase S ligand etching process and enable the one-step formation of S-bridged sites. X-ray absorption spectroscopy (XAS) confirms the existence of bimetallic sites with N2Cu-S-NiN2 moiety. In H-cell, Cu-S-Ni/SNC shows high CO Faraday efficiency of 98.1% at -0.65 V versus RHE. Benefiting from the charge tuning effect between the metal site and bridged sulfur atoms, a large current density of 550 mA cm-2 can be achieved at -1.00 V in flow cell. Additionally, in situ XAS, attenuated total reflection surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS), and density functional theory (DFT) calculations show Cu as the main adsorption site is dual-regulated by Ni and S atoms, which enhances CO2 activation and accelerates the formation of *COOH intermediates. This kind of asymmetric bimetallic atom catalysts may open new pathways for precision preparation and performance regulation of atomic materials toward energy applications.

Lattice Strain and Mott-Schottky Effect of the Charge-Asymmetry Pd1Fe Single-Atom Alloy Catalyst for Semi-Hydrogenation of Alkynes with High Efficiency.

The ideal interface design between the metal and substrate is crucial in determining the overall performance of the alkyne semihydrogenation reaction. Single-atom alloys (SAAs) with isolated dispersed active centers are ideal media for the study of reaction effects. Herein, a charge-asymmetry "armor" SAA (named Pd1Fe SAA@PC), which consists of a Pd1Fe alloy core and a semiconducting P-doped C (PC) shell, is rationally designed as an ideal catalyst for the selective hydrogenation of alkynes with high efficiency. Multiple spectroscopic analyses and density functional theory calculations have demonstrated that Pd1Fe SAA@PC is dual-regulated by lattice tensile and Schottky effects, which govern the selectivity and activity of hydrogenation, respectively. (1) The PC shell layer applied an external traction force causing a 1.2% tensile strain inside the Pd1Fe alloy to increase the reaction selectivity. (2) P doping into the C-shell layer realized a transition from a p-type semiconductor to an n-type semiconductor, thereby forming a unique Schottky junction for advancing alkyne semihydrogenation activity. The dual regulation of lattice strain and the Schottky effect ensures the excellent performance of Pd1Fe SAA@PC in the semihydrogenation reaction of phenylethylene, achieving a conversion rate of 99.9% and a selectivity of 98.9% at 4 min. These well-defined interface modulation strategies offer a practical approach for the rational design and performance optimization of semihydrogenation catalysts.

Continuous warming drives the colonization dynamics of periphytic ciliate fauna in marine environments.

In order to evaluate the influence of global warming on the ecosystem processes in marine environments, the changes in colonization dynamics of periphytic microbiota were studied using the periphytic ciliate communities as the test organism fauna under a continuous warming gradient of 22℃ (control), 25℃, 28℃, 31℃, and 34 ℃. The results demonstrated that (1) the test ciliate communities generally showed a similar temporal pattern in within the colonization process under the water temperatures from 22 up to 28℃; however, (2) the colonization dynamics were significantly changed, and the fitness of colonization curves to the MacArthur-Wilson model equation was failed under the temperature increased by 6 ℃, and (3) the loading or assimilative capacity of the test aquatic ecosystem was decreased with the increase of water temperature. Therefore, this study suggests that continuous warming may significantly drive the colonization dynamics of periphytic ciliates in marine ecosystems.

Sulfur Modified Carbon-Based Single-Atom Catalysts for Electrocatalytic Reactions.

Efficient and sustainable energy development is a powerful tool for addressing the energy and environmental crises. Single-atom catalysts (SACs) have received high attention for their extremely high atom utilization efficiency and excellent catalytic activity, and have broad application prospects in energy development and chemical production. M-N4 is an active center model with clear catalytic activity, but its catalytic properties such as catalytic activity, selectivity, and durability need to be further improved. Adjustment of the coordination environment of the central metal by incorporating heteroatoms (e.g., sulfur) is an effective and feasible modification method. This paper describes the precise synthetic methods for introducing sulfur atoms into M-N4 and controlling whether they are directly coordinated with the central metal to form a specific coordination configuration, the application of sulfur-doped carbon-based single-atom catalysts in electrocatalytic reactions such as ORR, CO2RR, HER, OER, and other electrocatalytic reaction are systematically reviewed. Meanwhile, the effect of the tuning of the electronic structure and ligand configuration parameters of the active center due to doped sulfur atoms with the improvement of catalytic performance is introduced by combining different characterization and testing methods. Finally, several opinions on development of sulfur-doped carbon-based SACs are put forward.

Identification and validation of hub genes expressed in ulcerative colitis with metabolic dysfunction-associated steatotic liver disease.

Objective: Ulcerative colitis (UC) and metabolic dysfunction-associated steatotic liver disease (MASLD) are closely intertwined; however, the precise molecular mechanisms governing their coexistence remain unclear. Methods: We obtained UC (GSE75214) and MASLD (GSE151158) datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were acquired by the 'edgeR' and 'limma' packages of R. We then performed functional enrichment analysis of common DEGs. Hub genes were selected using the cytoHubba plugin and validated using GSE87466 for UC and GSE33814 for MASLD. Immunohistochemistry was employed to validate the hub genes' expression in clinical samples. Immune infiltration and gene set enrichment analyses of the hub genes were performed. Finally, we estimated the Spearman's correlation coefficients for the clinical correlation of the core genes. Results: Within a cohort of 26 differentially regulated genes in both UC and MASLD, pathways involving cytokine-mediated signaling, cell chemotaxis, and leukocyte migration were enriched. After further validation, CXCR4, THY1, CCL20, and CD2 were identified as the hub genes. Analysis of immune infiltration patterns highlighted an association between elevated pivotal gene expression and M1 macrophage activation. Immunohistochemical staining revealed widespread expression of pivotal genes in UC- and MASLD-affected tissues. Furthermore, significant correlations were observed between the increased expression of hub genes and biochemical markers, such as albumin and prothrombin time. Conclusion: This bioinformatics analysis highlights CXCR4, THY1, CCL20, and CD2 as crucial genes involved in the co-occurrence of UC and MASLD, providing insights into the underlying mechanisms of these two conditions.

Sensitive remote homology search by local alignment of small positional embeddings from protein language models.

Accurately detecting distant evolutionary relationships between proteins remains an ongoing challenge in bioinformatics. Search methods based on primary sequence struggle to accurately detect homology between sequences with less than 20% amino acid identity. Profile- and structure-based strategies extend sensitive search capabilities into this twilight zone of sequence similarity but require slow pre-processing steps. Recently, whole-protein and positional embeddings from deep neural networks have shown promise for providing sensitive sequence comparison and annotation at long evolutionary distances. Embeddings are generally faster to compute than profiles and predicted structures but still suffer several drawbacks related to the ability of whole-protein embeddings to discriminate domain-level homology, and the database size and search speed of methods using positional embeddings. In this work, we show that low-dimensionality positional embeddings can be used directly in speed-optimized local search algorithms. As a proof of concept, we use the ESM2 3B model to convert primary sequences directly into the 3D interaction (3Di) alphabet or amino acid profiles and use these embeddings as input to the highly optimized Foldseek, HMMER3, and HH-suite search algorithms. Our results suggest that positional embeddings as small as a single byte can provide sufficient information for dramatically improved sensitivity over amino acid sequence searches without sacrificing search speed.

Cascade Dual Sites Modulate Local CO Coverage and Hydrogen-Binding Strength to Boost CO2 Electroreduction to Ethylene.

Rationally modulating the binding strength of reaction intermediates on surface sites of copper-based catalysts could facilitate C-C coupling to generate multicarbon products in an electrochemical CO2 reduction reaction. Herein, theoretical calculations reveal that cascade Ag-Cu dual sites could synergistically increase local CO coverage and lower the kinetic barrier for CO protonation, leading to enhanced asymmetric C-C coupling to generate C2H4. As a proof of concept, the Cu3N-Ag nanocubes (NCs) with Ag located in partial Cu sites and a Cu3N unit center are successfully synthesized. The Faraday efficiency and partial current density of C2H4 over Cu3N-Ag NCs are 7.8 and 9.0 times those of Cu3N NCs, respectively. In situ spectroscopies combined with theoretical calculations confirm that Ag sites produce CO and Cu sites promote asymmetric C-C coupling to *COCHO, significantly enhancing the generation of C2H4. Our work provides new insights into the cascade catalysis strategy at the atomic scale for boosting CO2 to multicarbon products.

Discovery of cytosine deaminases enables base-resolution methylome mapping using a single enzyme.

Deaminases have important uses in modification detection and genome editing. However, the range of applications is limited by the small number of characterized enzymes. To expand the toolkit of deaminases, we developed an in vitro approach that bypasses a major hurdle with their toxicity in cells. We assayed 175 putative cytosine deaminases on a variety of substrates and found a broad range of activity on double- and single-stranded DNA in various sequence contexts, including CpG-specific deaminases and enzymes without sequence preference. We also characterized enzyme selectivity across six DNA modifications and reported enzymes that do not deaminate modified cytosines. The detailed analysis of diverse deaminases opens new avenues for biotechnological and medical applications. As a demonstration, we developed SEM-seq, a non-destructive single-enzyme methylation sequencing method using a modification-sensitive double-stranded DNA deaminase. The streamlined protocol enables accurate, base-resolution methylome mapping of scarce biological material, including cell-free DNA and 10 pg input DNA.

A Hybrid Framework of Dual-Domain Signal Restoration and Multi-depth Feature Reinforcement for Low-Dose Lung CT Denoising.

Low-dose computer tomography (LDCT) has been widely used in medical diagnosis. Various denoising methods have been presented to remove noise in LDCT scans. However, existing methods cannot achieve satisfactory results due to the difficulties in (1) distinguishing the characteristics of structures, textures, and noise confused in the image domain, and (2) representing local details and global semantics in the hierarchical features. In this paper, we propose a novel denoising method consisting of (1) a 2D dual-domain restoration framework to reconstruct noise-free structure and texture signals separately, and (2) a 3D multi-depth reinforcement U-Net model to further recover image details with enhanced hierarchical features. In the 2D dual-domain restoration framework, the convolutional neural networks are adopted in both the image domain where the image structures are well preserved through the spatial continuity, and the sinogram domain where the textures and noise are separately represented by different wavelet coefficients and processed adaptively. In the 3D multi-depth reinforcement U-Net model, the hierarchical features from the 3D U-Net are enhanced by the cross-resolution attention module (CRAM) and dual-branch graph convolution module (DBGCM). The CRAM preserves local details by integrating adjacent low-level features with different resolutions, while the DBGCM enhances global semantics by building graphs for high-level features in intra-feature and inter-feature dimensions. Experimental results on the LUNA16 dataset and 2016 NIH-AAPM-Mayo Clinic LDCT Grand Challenge dataset illustrate the proposed method outperforms the state-of-the-art methods on removing noise from LDCT images with clear structures and textures, proving its potential in clinical practice.

Low-Dose CT Image Super-resolution Network with Noise Inhibition Based on Feedback Feature Distillation Mechanism.

Low-dose computed tomography (LDCT) has been widely used in medical diagnosis. In practice, doctors often zoom in on LDCT slices for clearer lesions and issues, while, a simple zooming operation fails to suppress low-dose artifacts, leading to distorted details. Therefore, numerous LDCT super-resolution (SR) methods have been proposed to promote the quality of zooming without the increase of the dose in CT scanning. However, there are still some drawbacks that need to be addressed in existing methods. First, the region of interest (ROI) is not emphasized due to the lack of guidance in the reconstruction process. Second, the convolutional blocks extracting fix-resolution features fail to concentrate on the essential multi-scale features. Third, a single SR head cannot suppress the residual artifacts. To address these issues, we propose an LDCT CT joint SR and denoising reconstruction network. Our proposed network consists of global dual-guidance attention fusion modules (GDAFMs) and multi-scale anastomosis blocks (MABs). The GDAFM directs the network to focus on ROI by fusing the extra mask guidance and average CT image guidance, while the MAB introduces hierarchical features through anastomosis connections to leverage multi-scale features and promote the feature representation ability. To suppress radial residual artifacts, we optimize our network using the feedback feature distillation mechanism (FFDM) which shares the backbone to learn features corresponding to the denoising task. We apply the proposed method to the 3D-IRCADB and PANCREAS datasets to evaluate its ability on LDCT image SR reconstruction. The experimental results compared with state-of-the-art methods illustrate the superiority of our approach with respect to peak signal-to-noise (PSNR), structural similarity (SSIM), and qualitative observations. Our proposed LDCT joint SR and denoising reconstruction network has been extensively evaluated through ablation, quantitative, and qualitative experiments. The results demonstrate that our method can recover noise-free and detail-sharp images, resulting in better reconstruction results. Code is available at https://github.com/neu-szy/ldct_sr_dn_w_ffdm .

Single-cell landscape of the cellular microenvironment in three different colonic polyp subtypes in children.

BACKGROUND: The understanding of the heterogeneous cellular microenvironment of colonic polyps in paediatric patients with solitary juvenile polyps (SJPs), polyposis syndrome (PJS) and Peutz-Jeghers syndrome (PJS) remains limited. METHODS: We conducted single-cell RNA sequencing and multiplexed immunohistochemistry (mIHC) analyses on both normal colonic tissue and different types of colonic polyps obtained from paediatric patients. RESULTS: We identified both shared and disease-specific cell subsets and expression patterns that played important roles in shaping the unique cellular microenvironments observed in each polyp subtype. As such, increased myeloid, endothelial and epithelial cells were the most prominent features of SJP, JPS and PJS polyps, respectively. Noticeably, memory B cells were increased, and a cluster of epithelial-mesenchymal transition (EMT)-like colonocytes existed across all polyp subtypes. Abundant neutrophil infiltration was observed in SJP polyps, while CX3CR1hi CD8+ T cells and regulatory T cells (Tregs) were predominant in SJP and JPS polyps, while GZMAhi natural killer T cells were predominant in PJS polyps. Compared with normal colonic tissues, myeloid cells exhibited specific induction of genes involved in chemotaxis and interferon-related pathways in SJP polyps, whereas fibroblasts in JPS polyps had upregulation of myofiber-associated genes and epithelial cells in PJS polyps exhibited induction of a series of nutrient absorption-related genes. In addition, the TNF-α response was uniformly upregulated in most cell subsets across all polyp subtypes, while endothelial cells and fibroblasts separately showed upregulated cell adhesion and EMT signalling in SJP and JPS polyps. Cell-cell interaction network analysis showed markedly enhanced intercellular communication, such as TNF, VEGF, CXCL and collagen signalling networks, among most cell subsets in polyps, especially SJP and JPS polyps. CONCLUSION: These findings strengthen our understanding of the heterogeneous cellular microenvironment of polyp subtypes and identify potential therapeutic approaches to reduce the recurrence of polyps in children.

Microplastics drive community dynamics of periphytic protozoan fauna in marine environments.

The pollution of microplastics (MPs) to the marine environment has become a widespread focus of attention. To assess MP-induced ecotoxicity on marine ecosystems, periphytic protozoan communities were used as test organisms and exposed to five concentrations of MPs: 0, 1, 5, 25, and 125 mg l-1. Protozoan samples were collected using microscope slides from coastal waters of the Yellow Sea, northern China. A total of 13 protozoan species were identified and represented different tolerance to MP-induced ecotoxicity. Inhibition effects of MPs on the test protozoan communities were clearly shown in terms of both the species richness and individual abundance and followed linear relationships to MP concentrations. The community patterns were driven by MPs and significantly shifted at concentrations over 5 mg l-1. Our findings demonstrated that MPs may induce the community-level ecotoxic response of periphytic protozoan fauna and followed significant community dynamics. Thus, it is suggested that periphytic protozoan fauna may be used as useful community-based test model organisms for evaluating MP-induced ecotoxicity in marine environments.

Integrating Host Design and Tailored Electronic Effects of Yolk-Shell Zn-Mn Diatomic Sites for Efficient CO2 Electroreduction.

Modulating the surface and spatial structure of the host is associated with the reactivity of the active site, and also enhances the mass transfer effect of the CO2 electroreduction process (CO2 RR). Herein, we describe the development of two-step ligand etch-pyrolysis to access an asymmetric dual-atomic-site catalyst (DASC) composed of a yolk-shell carbon framework (Zn1 Mn1 -SNC) derived from S,N-coordinated Zn-Mn dimers anchored on a metal-organic framework (MOF). In Zn1 Mn1 -SNC, the electronic effects of the S/N-Zn-Mn-S/N configuration are tailored by strong interactions between Zn-Mn dual sites and co-coordination with S/N atoms, rendering structural stability and atomic distribution. In an H-cell, the Zn1 Mn1 -SNC DASC shows a low onset overpotential of 50 mV and high CO Faraday efficiency of 97 % with a low applied overpotential of 343 mV, thus outperforming counterparts, and in a flow cell, it also reaches a high current density of 500 mA cm-2 at -0.85 V, benefitting from the high structure accessibility and active dual sites. DFT simulations showed that the S,N-coordinated Zn-Mn diatomic site with optimal adsorption strength of COOH* lowers the reaction energy barrier, thus boosting the intrinsic CO2 RR activity on DASC. The structure-property correlation found in this study suggests new ideas for the development of highly accessible atomic catalysts.