Three-dimensional Structure Research Articles

CoFe Hydroxide Nanospheres for Enhanced Alkaline Water Splitting and Seawater Oxidation:Anion Doping Effects of Fluorine and Carbonate.

Green hydrogen production can be achieved through electrolysis of fresh water or the use of renewable energy to electrolyze seawater. However, due to the low activity and poor stability of oxygen evolution reaction catalysts, direct electrolysis of alkaline seawater faces significant challenges. Herein, The catalyst F-CoFe(OH)-CO3/NF with three-dimensional nanosphere structure was prepared, The introduction of CO3 2- into the intermediate layer of CoFe hydroxide improves the corrosion resistance of alkaline electrolyte and the doping of F- is to design three-dimensional layered nanostructures, increase the active site, and accelerate the diffusion of the electrolyte. By in situ Raman analysis, partial oxidation of CoFe hydroxide to CoFe (oxy)hydroxide as the active center can accelerating the adsorption of oxygen-related intermediates. In 1 M KOH, it requires overpotentials of 210 mV and 251 mV to drive current densities of 10 and 100 mA cm-2, respectively. And it remained stable at the current density of 100 mA cm-2 for 120 h in 1 M KOH. F-CoFe(OH)-CO3/NF can also catalyzes the decomposition of electrolytic seawater. Compared with hydroxide, anion-doped carbonate hydroxide is more efficient and stable in electrolyte solution, which is of great importance for the development of a new stable electrocatalyst for water decomposition.

Abstract B034: Engineering the tumor microenvironment: Patient-specific microphysiological systems of the head and neck cancer tumor microenvironment

Abstract Introduction: Survival rates in advanced head and neck cancer (HNC) remain poor with no clinically approved biomarkers to predict treatment efficacy. HNC is a highly heterogenous disease and the lack of available models that capture patient heterogeneity and the complexity of the tumor microenvironment (TME) contributes to these poor patient outcomes. Microphysiological systems (MPS) are complex multicellular in vitro models that can recapitulate three-dimensional organ structure and function. The low cell number requirements for MPS permits the creation of patient-specific TME models, where all the cell types can be isolated from a single piece of tumor tissue. These patient-specific MPS represent a promising strategy for elucidating the contribution of the TME to treatment resistance, predicting the best treatment for each patient and improving patient outcomes in HNC. Here, we report a patient-specific MPS that contains multiple TME compartments and recapitulates patient heterogeneity. Methods: Tumor tissue was collected from patients with oral cavity carcinoma undergoing standard of care surgery followed by radiation or chemoradiation. Tissue from each patient was digested and tumor infiltrating leukocytes (TIL) were isolated using CD45 magnetic beads, while epithelial cells and fibroblasts were expanded in culture using specific media formulations. Tissue was also snap frozen for single cell RNA sequencing analysis. To build the MPS, a custom designed microfluidic device was filled with a hydrogel matrix containing patient-matched TIL, fibroblasts and epithelial spheroids to mimic the solid tumor. Lumens molded from the hydrogel were seeded with blood or lymphatic endothelial cells to create vasculature. Multiple replicate MPS can be built from each patient, which are cultured in an optimized media formulation to support the multiple primary cell types. Patient-specific MPS were treated with radiation or cisplatin + radiation to mimic the treatment the patient received. Multiple orthogonal endpoints were measured including tumor cell migration and viability, cytokine secretion and angiogenesis. Single cell sequencing was also performed on the original tumor tissue and matched MPS. Results: We have successfully created patient-specific models of the HNC TME. Single cell RNA sequencing analysis of the MPS suggests that cellular heterogeneity is being retained. Patient characteristics varied between MPS with some patient TME MPS showing highly migratory tumor cells or angiogenic responses. Treatment responses were measured for each patient-specific MPS and ongoing work will characterize the contributions of the TME to treatment resistance. These data demonstrate the feasibility of using patient-specific MPS to investigate the contribution of the TME to treatment response and resistance and lays important groundwork for using MPS to identify patient treatment responses. Citation Format: Adeel Ahmed, Marcos Lares, Fauzan Ahmed, Adam R. Burr, Paul M. Harari, David J. Beebe, Sheena C. Kerr. Engineering the tumor microenvironment: Patient-specific microphysiological systems of the head and neck cancer tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B034.

Synthesis of β-cyclodextrin magnetic-graphene-oxide pyrenyl (β-mGOP) gels for high-throughput enrichment and detection of various trace mycotoxins in food using UHPLC-cIMS

In this research, β-cyclodextrin magnetic-graphene-oxide pyrenyl gel composite (β-mGOP) was employed to remove trace mycotoxins from food products. The β-mGOP gels exhibited a three-dimensional macroporous structure that facilitated the rapid diffusion of target molecules into the nanoporous structure of the covalent organic frameworks embedded within the gel. The adsorption process of mycotoxins onto the β-mGOP gels conformed to the pseudo-second-order kinetics and the Freundlich adsorption model. These findings demonstrated exceptional rapid adsorption kinetics without pore collapse, making the material suitable as fillers for solid-phase extraction adsorbents. Additionally, a novel screening technique utilizing β-mGOP gels in conjunction with cyclic ion mobility mass spectrometry was developed to illustrate the efficacy of β-mGOP gels in capturing various trace substances in food and enhancing detection resolution. The versatile, uncomplicated, and scalable characteristics of β-mGOP gels indicate their promising potential for future applications in high-throughput analysis of trace contaminants in food.

Operationalising weather surveillance radar data for use in ecological research

Global biodiversity declines require a step change in monitoring frameworks to properly track and diagnose population trends. National weather surveillance radar (WSR) networks offer high spatial (ca. 1-10 km) and temporal (5–10 min) resolution data collected over regional and decadal scales, with well-supported infrastructure that holds great promise for the study of biodiversity. However, WSR datasets pose new challenges for ecologists due to their format, volume, and three-dimensional spatial structure. Here, we define a novel approach to the processing of WSR data to produce a product that can be used to interrogate trends in aerial biodiversity (abundance or diversity) at and across individual ground-level sites. From the full volume of WSR data collected approximately every six minutes we extract vertical columns of WSR observations above sites to compare against standardised nocturnal macro-moth monitoring data at ground level. The results show that there is strong agreement between the WSR-derived proxy of biodiversity in the air column and ground-level measurements of abundance and diversity in nocturnal moth communities. The columnar product operates on a biologically relevant scale with a diameter of 5 km, although column dimensions can easily be customised, and can be deployed at any site within a WSR's observable range. These findings have the potential to unlock past and present WSR observations for widespread application to existing and novel ecological questions and can be applied to weather radar networks around the world.

Exploration of the Subsurface Three-Dimensional Structure in Rare Earth Ore Areas Using Electrical Resistivity Tomography: A Case Study in Changting, Fujian, China

The development of fracture zones (broken zones) and underground karst rivers in underlying granite can significantly reduce the recovery rate of ion-adsorption-type rare earth ores. Additionally, leaching solutions flowing along unfavorable geological formations can lead to environmental pollution. Therefore, investigating the development of fracture zones (leakage channels) in granite basements is of great significance. In Changting, Fujian, China, several methods have been used in exploration areas (C1 and C2) to study the characteristics of rare ores. This study has focused on the stratigraphic and structural characteristics of the C2 exploration area. Twelve exploration profiles were designed to collect data using electrical resistivity tomography, and a deep electrical structure model of the study area was obtained through inverse calculations. The results indicated that the exploration profiles effectively delineated the thickness of the weathered granite layer and the spatial distribution characteristics of the deep-seated fault structures, which were consistent with the drilling results within the study area. These findings provide important reference materials for the assessment of ion-adsorption-type rare earth ore reserves, blocking leakage channels, and the layout of recovery tunnels.

Loop Extrusion Machinery Impairments in Models and Disease.

Structural maintenance of chromosomes (SMC) complexes play a crucial role in organizing the three-dimensional structure of chromatin, facilitating key processes such as gene regulation, DNA repair, and chromosome segregation. This review explores the molecular mechanisms and biological significance of SMC-mediated loop extrusion complexes, including cohesin, condensins, and SMC5/6, focusing on their structure, their dynamic function during the cell cycle, and their impact on chromatin architecture. We discuss the implications of impairments in loop extrusion machinery as observed in experimental models and human diseases. Mutations affecting these complexes are linked to various developmental disorders and cancer, highlighting their importance in genome stability and transcriptional regulation. Advances in model systems and genomic techniques have provided deeper insights into the pathological roles of SMC complex dysfunction, offering potential therapeutic avenues for associated diseases.

Three-dimensional velocity structure of the MS 6.0 Luxian earthquake source region and adjacent areas based on a dense seismic array

On September 16, 2021, an MS 6.0 earthquake struck Luxian County in the Sichuan basin. To investigate the regional velocity structure and its relationship with seismic activity, we gathered seismic phase data from permanent stations for events occurring between January 2009 and April 2021 as well as data from a dense mobile seismic array that operated from April 2021 to July 2023. Utilizing Double-Difference tomography, we have determined well-constrained earthquake relocations and have derived a detailed 3D velocity structure. Many of the earthquakes exhibit linear clustering patterns, with an average depth of 4.3 km and a NE-SW orientation. Approximately 96 % of the seismic events occurred within a depth range of 0–7 km. The early aftershock sequence of the Luxian event also displayed a linear trend, with a length of 6 km but with an ESE orientation. The mainshock occurred at a depth of 6.2 km, located at the northwestern end of the aftershock sequence. The aftershock sequence along with other linear seismic clusters, predominantly occurred within regions characterized by high seismic velocities and low Poisson's ratios, both within the sedimentary cover above the crystalline basement. The heterogeneity of the velocity structure likely plays a significant role in controlling the occurrence of moderate-to-strong earthquakes in the deeper parts of the study region, which deepens the existing understanding from previous research: pre-existing faults, their scales, and their slip-tendencies under the present-day regional and reservoir-scale stress fields are also controlling factors for induced earthquakes, especially larger ones. We have identified five areas where moderate-to-strong earthquakes are speculated to have a higher likelihood of occurrence. These findings hold considerable importance for local seismic hazard assessments.

Topology and size optimization of viscous dampers with discrete design variables by outer approximation

This article proposes a novel seismic retrofitting approach for the topology and size optimization of fluid viscous dampers using discrete design variables. The design variables are the damping coefficients of the dampers, and they are chosen from catalogues, leading to practical optimal design solutions. The optimization problems considered are formulated as 0–1 nonlinear programming problems. An algorithm based on outer approximation and that relies on first-order information is proposed to find optimized designs with modest computational resources and time. The effectiveness of the proposed approach is demonstrated through optimal seismic retrofitting of three-dimensional irregular frame structures. In the optimization problem formulation, the retrofitted structures are subjected to realistic seismic ground acceleration records with constraints on inter-storey drifts and total storey accelerations.

Bioinformatics analysis to design a multi-epitope mRNA vaccine against S. agalactiae exploiting pathogenic proteins

Antibiotic resistance in bacterial pathogen infections is a growing global issue that occurs due to their adaptation to changing environmental conditions. Therefore, producing an efficient vaccine as an alternative approach can improve the immune system, eradicate related pathogens, and overcome this growing problem. Streptococcus agalactiae belongs to group B Streptococcus (GBS). Colonization of GBS during pregnancy is a significant risk factor for infants and young children. S. agalactiae infected population exhibits resistance to beta-lactams, including penicillin and the second-line antibiotics erythromycin and clindamycin. On the other hand, there are currently no commercial vaccines against this pathogen. Vaccination of pregnant women is a highly effective method to protect newborns and infants from S. agalactiae infection, and it has been identified as an urgent demand by the World Health Organization. This study employed various immunoinformatic tools to develop an effective vaccine that could trigger both humoral and cell-mediated immunity and prevent disease. For this purpose, three conserved antigenic proteins of the main pathogenic strains of S. agalactiae were utilized to predict CTL, HTL, and B-cell epitopes for producing an mRNA vaccine against different strains of S. agalactiae. The selected epitopes were fused using proper linkers. The Resuscitation promoting factor E (RpfE) sequence was incorporated in the designed vaccine construct as an adjuvant to boost its immune response. Different physicochemical characteristics of the final designed vaccine, modeling of the three-dimensional structure, molecular docking, molecular dynamics simulation, and immunological response simulation were screened following vaccine administration in an in vivo model. Computational immune simulation data identified that IgG1, IgM, INF γ, IL-2, T helper, and B-cell populations increased significantly after vaccination. These findings suggested that the vaccine candidate may provide good protection against S. agalactiae infection. However, experimental and animal model studies are required for additional validation and implementation in human vaccination programs.

Structural Insights into Cold-Active Lipase from Glaciozyma antarctica PI12: Alphafold2 Prediction and Molecular Dynamics Simulation.

Cold-active enzymes have recently gained popularity because of their high activity at lower temperatures than their mesophilic and thermophilic counterparts, enabling them to withstand harsh reaction conditions and enhance industrial processes. Cold-active lipases are enzymes produced by psychrophiles that live and thrive in extremely cold conditions. Cold-active lipase applications are now growing in the detergency, synthesis of fine chemicals, food processing, bioremediation, and pharmaceutical industries. The cold adaptation mechanisms exhibited by these enzymes are yet to be fully understood. Using phylogenetic analysis, and advanced deep learning-based protein structure prediction tool Alphafold2, we identified an evolutionary processes in which a conserved cold-active-like motif is presence in a distinct subclade of the tree and further predicted and simulated the three-dimensional structure of a putative cold-active lipase with the cold active motif, Glalip03, from Glaciozyma antarctica PI12. Molecular dynamics at low temperatures have revealed global stability over a wide range of temperatures, flexibility, and the ability to cope with changes in water and solvent entropy. Therefore, the knowledge we uncover here will be crucial for future research into how these low-temperature-adapted enzymes maintain their overall flexibility and function at lower temperatures.

Stabilization mechanism of emulsion gels of crude oil with low asphaltene, resin, and wax contents

The generation of semi-solid emulsion gels was observed in crude oil with low asphaltene, resin, and wax contents. The semi-solid emulsion gels were very stable and could not be effectively demulsified by conventional demulsifiers. To solve the problem of demulsification, crude oil component analysis, high-temperature gas chromatography, element analysis, Fourier transform infrared spectroscopy, oil–water interfacial tension measurement, and viscoelastic analysis of interface film were used to conduct a detailed study on the stability mechanism of the emulsion gels. The results show that crude oil has a low resin/asphaltene mass ratio and poor asphaltene solvation; thus, resin and asphaltene mainly exist as colloids at the oil–water interface. Meanwhile, the resin and asphaltene in the crude oil have high oxygen content and low acid number, indicating the existence of many phenolic hydroxyl groups. Therefore, strong hydrogen bonding between phenolic hydroxyl groups further enhances the structural strength of resin/asphaltene aggregates. In addition, the long carbon-chain wax in crude oil has poor solubility and is easy to precipitate when the temperature decreases. The long carbon chains easily form a three-dimensional network structure. Resin/asphaltene aggregates are adsorbed on the surface of water droplets, and their alkyl parts interact with the wax in crude oil to form a tight, three-dimensional network structure, which binds the water droplets. The water droplets aggregate without coalescing, resulting in crude oil emulsion gels and causing difficulties in demulsification.

Protein Design by Integrating Machine Learning and Quantum-Encoded Optimization

The protein design problem involves finding polypeptide sequences folding into a given three-dimensional structure. Its rigorous algorithmic solution is computationally demanding, involving a nested search in sequence and structure spaces. Structure searches can now be bypassed thanks to recent machine-learning breakthroughs, which have enabled accurate and rapid structure predictions. Similarly, sequence searches might be entirely transformed by the advent of quantum annealing machines and by the required new encodings of the search problem, which could be performative even on classical machines. In this work, we introduce a general protein design scheme where algorithmic and technological advancements in machine learning and quantum-inspired algorithms can be integrated, and an optimal physics-based scoring function is iteratively learned. In this first proof-of-concept application, we apply the iterative method to a lattice protein model amenable to exhaustive benchmarks, finding that it can rapidly learn a physics-based scoring function and achieve promising design performances. Strikingly, our quantum-inspired reformulation outperforms conventional sequence optimization even when adopted on classical machines. The scheme is general and can be extended, e.g., to encompass off-lattice models, and it can integrate progress on various computational platforms, thus representing a new paradigm approach for protein design. Published by the American Physical Society 2024

Hydrogel dressing in diabetic wound healing

Abstract. With the intensification of social ageing, the number of geriatric patients continues to increase. Among them, the problem of diabetic patients whose wounds cannot heal for a long time and even cause amputation has received widespread attention. Excessive inflammation caused by adverse exogenous and endogenous factors that interfere with the regulation of wound inflammation is the main factor in the failure of the wound to heal according to standard procedures. As a polymer with a three-dimensional structure, the hydrogel is expected to be a new type of chronic wound dressing with good potential due to its good biocompatibility and drug loading. Summarizing the advantages of new functional hydrogel dressings and the progress of research in diabetic wounds, it is expected to provide some new ideas for clinical research and functional improvement of hydrogels.

Achieving enhanced thermal conductivity and low dielectric constants using double-oriented fluorinated graphene skeleton in silicone gel composites

The dielectric properties and thermal conductivity of composites are often contradictory. To improve the thermal conductivity, the filler content needs to be increased, which often contributes to the high dielectric constant of the material. Inspired by the layout of community buildings, in this study, silicone gel/double-oriented fluorinated graphene skeleton composites were prepared, which solved the difficulty in assembling fluorinated graphene in situ into a three-dimensional continuous network structure. This greatly improved the thermal conductivity and reduced the dielectric constant of the silicone gel while maintaining a low filler content and the insulating properties. In addition, based on the reconstruction of a real three-dimensional body, the mechanism by which the skeleton improved the material performance was analyzed using finite element simulation. The vertical and horizontal thermal conductivity of the silicone gel/double-oriented fluorinated graphene skeleton composites reached 3.34 W/(m·K) and 2.65 W/(m·K), respectively, and the dielectric constant dropped to 80 % of that of pure silicone gel. This provided a new way to synergistically improve the dielectric properties and thermal conductivity of insulating materials, and has great application potential as a thermal interface material in next-generation electronic devices.

RNA sample optimization for cryo-EM analysis.

RNAs play critical roles in most biological processes. Although the three-dimensional (3D) structures of RNAs primarily determine their functions, it remains challenging to experimentally determine these 3D structures due to their conformational heterogeneity and intrinsic dynamics. Cryogenic electron microscopy (cryo-EM) has recently played an emerging role in resolving dynamic conformational changes and understanding structure-function relationships of RNAs including ribozymes, riboswitches and bacterial and viral noncoding RNAs. A variety of methods and pipelines have been developed to facilitate cryo-EM structure determination of challenging RNA targets with small molecular weights at subnanometer to near-atomic resolutions. While a wide range of conditions have been used to prepare RNAs for cryo-EM analysis, correlations between the variables in these conditions and cryo-EM visualizations and reconstructions remain underexplored, which continue to hinder optimizations of RNA samples for high-resolution cryo-EM structure determination. Here we present a protocol that describes rigorous screenings and iterative optimizations of RNA preparation conditions that facilitate cryo-EM structure determination, supplemented by cryo-EM data processing pipelines that resolve RNA dynamics and conformational changes and RNA modeling algorithms that generate atomic coordinates based on moderate- to high-resolution cryo-EM density maps. The current protocol is designed for users with basic skills and experience in RNA biochemistry, cryo-EM and RNA modeling. The expected time to carry out this protocol may range from 3 days to more than 3 weeks, depending on the many variables described in the protocol. For particularly challenging RNA targets, this protocol could also serve as a starting point for further optimizations.

Drug Discovery in the Age of Artificial Intelligence: Transformative Target-Based Approaches.

The complexities inherent in drug development are multi-faceted and often hamper accuracy, speed and efficiency, thereby limiting success. This review explores how recent developments in machine learning (ML) are significantly impacting target-based drug discovery, particularly in small-molecule approaches. The Simplified Molecular Input Line Entry System (SMILES), which translates a chemical compound's three-dimensional structure into a string of symbols, is now widely used in drug design, mining, and repurposing. Utilizing ML and natural language processing techniques, SMILES has revolutionized lead identification, high-throughput screening and virtual screening. ML models enhance the accuracy of predicting binding affinity and selectivity, reducing the need for extensive experimental screening. Additionally, deep learning, with its strengths in analyzing spatial and sequential data through convolutional neural networks (CNNs) and recurrent neural networks (RNNs), shows promise for virtual screening, target identification, and de novo drug design. Fragment-based approaches also benefit from ML algorithms and techniques like generative adversarial networks (GANs), which predict fragment properties and binding affinities, aiding in hit selection and design optimization. Structure-based drug design, which relies on high-resolution protein structures, leverages ML models for accurate predictions of binding interactions. While challenges such as interpretability and data quality remain, ML's transformative impact accelerates target-based drug discovery, increasing efficiency and innovation. Its potential to deliver new and improved treatments for various diseases is significant.

Three-dimensional numerical calculation and case application of IP five-directional well logging

Abstract Conventional well logging can effectively detect the vertical distribution range of ore bodies near the well by placing detectors in the well. However, its detection capability for the horizontal extension of ore bodies is limited. Therefore, starting from the differential equations satisfied by the point source in three-dimensional structures, this paper deduced the variational problem satisfied by the total potential under three-dimensional complex conditions. By focusing on well logging, tetrahedral cross-grid partitioning technology was employed to achieve high-precision three-dimensional finite element forward modeling. Simulations were carried out for different forms of ore bodies using the induced polarization five-direction observation method, considering the presence of ore bodies near the well and the case where the measurement well passes through the ore body. The paper analyzed and summarized the induced polarization anomaly patterns formed by ore bodies with low resistance and high polarization in different horizontal extension directions under induced polarization five-direction logging with power supply measurements from different directions. Based on this, a human-computer interaction system was constructed to perform forward fitting and inversion interpretation of the measured induced polarization data, resulting in a good application effect.

Robust Brewed Tea Waste/Reduced Graphene Oxide Hydrogel for High Performance Flexible Supercapacitors.

Tea waste contains various substances with phenolic hydroxyl groups, including lignin, tannins, tea polyphenols, etc., which are rarely utilized. In this study, tea waste was directly dispersed with graphene oxide to prepare tea waste/reduced graphene oxide (TW/rGO) hydrogel through a one-step hydrothermal method. The prepared hydrogel presented a continuous three-dimensional porous structure and exhibited good mechanical properties with a compressive strength of 53.4 ± 4.0 kPa. It also showed excellent electrochemical performance as an electrode material. Its specific capacitance reached 434.7 F g-1 at a current density of 1 A g-1, and its capacitance retention was 55.8% when the current density was increased to 100 A g-1. In addition, an TW/rGO assembled all-solid-state supercapacitor demonstrated a superior specific capacitance of 372.8 F g-1 and a competitive energy density of 12.9 Wh kg-1 at 1 A g-1.

Boosting ion uptake and electron transport through bridging Na2MnSiO4 with acidified carbon nanotubes for enhanced hybrid capacitance deionization

The enhancement of ion uptake capacity and electron transport process in the hybrid capacitive deionization (HCDI) Faraday electrode material is achieved by bridging Na2MnSiO4 (NMS) with acidified carbon nanotubes (HCNT). Herein, NMS@HCNT composites with three-dimensional conductive network structure were synthesized by the sol–gel method and subsequent thermal treatment. The NMS@HCNT Faraday electrode material displayed a high desalination capacity of 52.84 mg/g and a satisfactory mean salt adsorption rate of 6.89 mg/g/min, which are significantly higher than the desalination capacity (30.06 mg/g) and mean salt adsorption rate (4.35 mg/g/min) of NMS. This excellent desalination performance is mainly attributed to the fact that HCNT in the NMS@HCNT material not only acts as a highway for electron transport, but also increases the specific surface area of the material, which provide more ion-accessible surfaces and active sites to facilitate charge transfer and ion uptake capacity during desalination, thus effectively enhancing the HCDI performance of the electrode material. This study offers valuable insights into the design of HCDI electrode materials for high-efficiency desalination.

Construction of directional electron transfer from Pt to MoO2-x in macroporous structure for efficient hydrogen oxidation

Hydrogen oxidation reaction (HOR) as the anode reaction in proton exchange membrane fuel cell, usually suffers from the high loading of platinum (Pt) and subsequent CO poisoning especially by using industrial crude hydrogen as fuel. In this work, we propose a directional electron transfer route from Pt to MoO2-x in the macroporous structure to significantly enhance the HOR activity as well as the CO tolerance, which is constructed by interface engineering and defect strategy to anchor highly dispersed Pt nanoparticles onto the three-dimensional MoO2-x-C framework. The optimized 2Pt-MoO2-x-C with 1.02 wt% Pt demonstrates higher HOR peak current density (3.57 mA cm−2) and nearly 25 times higher mass activity than 20 wt% Pt/C. The excellent HOR performance is attributed to the synergistic effect between Pt and MoO2-x species, in which the charge transfer from Pt to MoO2-x improves H2 adsorption ability of Pt and accelerates the activation of H2 due to the reduced hydrogen binding energy of MoO2-x caused by Pt-O construction, leading to the release of H* thereby the enhancement of HOR activity. The construction of three-dimensional macroporous structure enhances the HOR dynamics by promoting the conductivity, mass transfer and the exposure of active sites. Moreover, the formed Mo-OH in Pt-MoO2-x-C can effectively react with CO species to remove the CO poisoning of Pt, endowing the excellent CO tolerance.