Label-free cell phenotypic profiling of histamine H4R receptor and discovery of non-competitive H4R antagonist from natural products.

Histamine 4 receptor (H4R), the most recently identified subtype of histamine receptor, primarily induces inflammatory reactions upon activation. Several H4R antagonists have been developed for the treatment of inflammatory bowel disease (IBD) and atopic dermatitis (AD), but their use has been limited by adverse side effects, such as a short half-life and toxicity. Natural products, as an important source of anti-inflammatory agents, offer minimal side effects and reduced toxicity. This work aimed to identify novel H4R antagonists from natural products. An H4R target-pathway model deconvoluted downstream Gi and MAPK signaling pathways was established utilizing cellular label-free integrative pharmacology (CLIP), on which 148 natural products were screened. Cryptotanshinone was identified as selective H4R antagonist, with an IC50 value of 11.68 ± 1.30 µM, which was verified with Fluorescence Imaging Plate Reader (FLIPR) and Cellular Thermal Shift (CTS) assays. The kinetic binding profile revealed the noncompetitive antagonistic property of cryptotanshinone. Two allosteric binding sites of H4R were predicted using SiteMap, Fpocket and CavityPlus. Subsequent molecular docking and dynamics simulation indicated that cryptotanshinone interacts with H4R at a pocket formed by the outward interfaces between TM3/4/5, potentially representing a new allosteric binding site for H4R. Overall, this study introduced cryptotanshinone as a novel H4R antagonist, offering promise as a new hit for drug design of H4R antagonist. Additionally, this study provided a novel screening model for the discovery of H4R antagonists.

Toward Smart Sensing by MXene.

The Internet of Things era has promoted enormous research on sensors, communications, data fusion, and actuators. Among them, sensors are a prerequisite for acquiring the environmental information for delivering to an artificial data center to make decisions. The MXene-based sensors have aroused tremendous interest because of their extraordinary performances. In this review, the electrical, electronic, and optical properties of MXenes are first introduced. Next, the MXene-based sensors are discussed according to the sensing mechanisms such as electronic, electrochemical, and optical methods. Initially, biosensors are introduced based on chemiresistors and field-effect transistors. Besides, the wearable pressure sensor is demonstrated with piezoresistive devices. Third, the electrochemical methods include amperometry and electrochemiluminescence as examples. In addition, the optical approaches refer to surface plasmonic resonance and fluorescence resonance energy transfer. Moreover, the prospects are delivered of multimodal data fusion toward complicated human-like senses. Eventually, future opportunities for MXene research are conveyed in the new material discovery, structure design, and proof-of-concept devices.

Hydroxyapatite-Derived Heterogeneous Ru-Ru2 P Electrocatalyst and Environmentally-Friendly Membrane Electrode toward Efficient Alkaline Electrolyzer.

Alkaline membrane water electrolysis is a promising production technology, and advanced electrocatalyst and membrane electrode design have always been the core technology. Herein, an ion-exchange method and an environmentally friendly in situ green phosphating strategy are successively employed to fabricate Ru-Ru2 P heterogeneous nanoparticles by using hydroxyapatite (HAP) as a phosphorus source, which is an exceptionally active electrocatalyst for hydrogen evolution reaction (HER). Density functional theory calculation results reveal that strong electronic redistribution occurs at the heterointerface of Ru-Ru2 P, which modulates the electronic structure to achieve an optimized hydrogen adsorption strength. The obtained Ru-Ru2 P possesses excellent HER performance (24 mV at 10 mA cm-2 ) and robust stability (1000 mA cm-2 for 120 h) in alkaline media. Furthermore, an environmentally friendly membrane electrode with a sandwich structure is assembled by HAP nanowires as an alkaline membrane, Ru-Ru2 P as a cathodic catalyst, and NiFe-LDH as an anodic catalyst, respectively. The voltage of (-) Ru-Ru2 P || NiFe-LDH/CNTs (+) (1.53 V at 10 mA cm-2 ) is lower than that of (-) 20 wt% Pt/C || RuO2 (+) (1.60 V at 10 mA cm-2 ) for overall water splitting. Overall, the studies not only design an efficient catalyst but also provide a new route to achieve a high-stability electrolyzer for industrial H2 production.

Chemical profiling of Ziziphi spinosae semen using on-line comprehensive two-dimensional liquid chromatography-mass spectrometry based on a novel phthalic anhydride bonded stationary phase.

Ziziphi spinosae semen has been widely used to treat insomnia and anxiety. To profile its chemical components, an online comprehensive two-dimensional liquid chromatography-mass spectrometry was developed. In this two-dimensional liquid chromatography system, a novel phthalic anhydride-bonded stationary phase column was combined with a C18 column. As a result, this new stationary phase exhibited remarkable differences in separation selectivity from C18, achieving a good orthogonality of 83.3%. Moreover, this new stationary phase with weaker hydrophobicity than C18 realized solvent compatibility in the online configuration. Coupled with tandem MS, 154 compounds were identified, including 51 unreported compounds. Compared with one-dimensional liquid chromatography-mass spectrometry, this online two-dimensional liquid chromatography-mass spectrometry system exhibited a much higher resolving power in isomer separation. This work provided an effective separation and characterization method for the material basis of Ziziphi spinosae semen. This strategy provides ideas for the material basis research of other traditional Chinese medicines.

Enhanced Hydrogen Evolution Reaction over Co Nanoparticles Embedded N-Doped Carbon Nanotubes Electrocatalyst with Zn as an Accelerant.

The rational design for transition metals-based carbon nano-materials as efficient electrocatalysts still remains a crucial challenge for economical electrochemical hydrogen production. Carbon nanotubes (CNTs) as attractive electrocatalysts are typically activated by non-metal dopant to promote catalytic performance. Metals doping or metal/non-metal co-doping of CNTs, however, are rarely explored. Herein, this work rationally designs bimetal oxide templates of ZnCo2 O4 for heterogeneously doping Zn and N into Co nanoparticles embedded carbon nanotubes (Co@Zn-N-CNTs). During the formation of CNTs, Zn atoms volatilize from ZnCo2 O4 and in situ dope into the carbon skeleton. In particular, owing to the low electronegativity of Zn, the electrons aptly transfer from Zn to carbon atoms, which generate a high electron density for the carbon layers and offer more preponderant catalytic sites for hydrogen reduction. The Co@Zn-N-CNTs catalyst exhibits enhanced hydrogen evolution reaction activity in 0.5 m H2 SO4 electrolyte, with a low onset potential of -20 mV versus RHE at 1 mA cm-2 , an overpotential of 67 mV at 10 mA cm-2 , a small Tafel slope of 52.1 mV dec-1 , and persistent long-term stability. This study provides brand-new insights into the utilization of Zn as electronic regulator and activity promoter toward the design of high-efficiency electrocatalysts.

Stemness Maintenance and Massproduction of Neural Stem Cells on Poly L-Lactic Acid Nanofibrous Membrane Based on Piezoelectriceffect.

Neural stem cells (NSCs) therapy is promising for treating neurodegenerative disorders and neural injuries. However, the limited in vitro expansion, spontaneous differentiation, and decrease in stemness obstruct the acquisition of high quantities of NSCs, restricting the clinical application of cell-based therapies and tissue engineering. This article reports a facile method of promoting NSCs expansion and maintaining stemness using wireless electrical stimulation triggered by piezoelectric nanomaterials. A nanofibrous membrane of poly L-lactic acid (PLLA) is prepared by electrostatic spinning, and the favorable piezoelectric property of PLLA facilitates the freeing of electrons after transformation. These self-powered electric signals generated by PLLA significantly enhance NSCs proliferation. Further, an undifferentiated cellular state is maintained in the NSCs cultured on the surfaces of PLLA nanofibers exposed to ultrasonic vibration. In addition, the neural differentiation potencies and functions of NSCs expanded by piezoelectric-driven localized electricity are not attenuated. Moreover, cell stemness can be maintained by wireless electric stimulation. Taken together, the electronic signals mediated by PLLA nanofibers facilitate NSCs proliferation. This efficient and simple strategy can maintain the stemness of NSCs during proliferation, which is essential for their clinical application, and opens up opportunities for the mass production of NSCs for use in cell therapy.

An effective formaldehyde gas sensor based on oxygen-rich three-dimensional graphene.

Three-dimensional (3D) graphene with a high specific surface area and excellent electrical conductivity holds extraordinary potential for molecular gas sensing. Gas molecules adsorbed onto graphene serve as electron donors, leading to an increase in conductivity. However, several challenges remain for 3D graphene-based gas sensors, such as slow response and long recovery time. Therefore, research interest remains in the promotion of the sensitivity of molecular gas detection. In this study, we fabricate oxygen plasma-treated 3D graphene for the high-performance gas sensing of formaldehyde. We synthesize large-area, high-quality, 3D graphene over Ni foam by chemical vapor deposition and obtain freestanding 3D graphene foam after Ni etching. We compare three types of strategies-non-treatment, oxygen plasma, and etching in HNO3solution-for the posttreatment of 3D graphene. Eventually, the strategy for oxygen plasma-treated 3D graphene exceeds expectations, which may highlight the general gas sensing based on chemiresistors.

Chemical profiling of Qingfei Paidu Decoction by triplex off-line two-dimensional liquid chromatography coupled with quadrupole time-of-flight mass spectrometry.

Qingfei Paidu Decoction is a Chinese medicine formula that has been proved effective in the treatment of coronavirus disease 2019. However, the comprehensive separation and characterization of Qingfei Paidu Decoction are of a great challenge due to the diversity of chemical components in a wide range of polarity. In this study, a triplex off-line two-dimensional liquid chromatography coupled with quadrupole time-of-flight mass spectrometry is developed for the analysis of Qingfei Paidu Decoction. One reversed-phase liquid chromatography×hydrophilic interaction liquid chromatography system and two reversed-phase liquid chromatography×reversed phase liquid chromatography systems were constructed to separate polar components and weak-polar components in Qingfei Paidu Decoction, respectively. Benefiting from the good orthogonality of two-dimensional liquid chromatography and high sensitivity of quadrupole time-of-flight MS, chemical components with different polarities and content were discovered. A total of 749 peaks were detected in positive and negative ionization mode and presented as a four-dimensional data plot. Meanwhile, 498 compounds belonging to 14 categories were tentatively identified. These results provide good supplementary to elucidate the material basis of Qingfei Paidu Decoction. The triplex off-line two-dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry strategy can be a powerful and efficient tool for the separation and characterization of chemical substances in traditional Chinese medicine formulas.

Laser ablative TiO2 and tremella-like CuInS2 nanocomposites for robust and ultrasensitive photoelectrochemical sensing of let-7a.

A photoelectrochemical (PEC) biosensor based on a multiple signal amplification strategy was established for highly sensitive detection of microRNA (miRNA). TiO2 was prepared on the surface of titanium sheet by laser etching to improve its stability and photoelectrical properties, and CuInS2-sensitized TiO2 was used to form a superior photoelectrical layer, which realized the initial signal amplification. The electron donor dopamine (DA) was modified to H2 as a signal regulator, which effectively increased the photocurrent signal. To further amplify the signal, an enzyme-free hybridization reaction was implemented. When target let-7a and fuel-DNA (F-DNA) were present, the base of H1 specifically recognized let-7a and forced dopamine@AuNPs-H2 away from the electrode surface. Subsequently, the end base of H1 specifically recognized F-DNA, and let-7a was replaced and recycled to participate in the next cycle. Enzyme-free circulation, as a multifunctional amplification method, ensured the recycling of target molecules. This PEC sensor for let-7a detection showed an excellent linear response from 0.5 to 1000 pM with a detection limit of 0.12 pM. The intra-batch RSD was 3.8% and the recovery was 87.74-108.1%. The sensor was further used for clinical biomolecular monitoring of miRNA, showing excellent quantitative detection capability.

Integration of Two-Dimensional Liquid Chromatography-Mass Spectrometry and Molecular Docking to Characterize and Predict Polar Active Compounds in Curcuma kwangsiensis.

Curcuma kwangsiensis, one species of Curcumae zedoaria Ros. c, is a commonly used traditional Chinese medicine (TCM) for treating cardiovascular disease, cancer, asthma and inflammation. Polar compounds are abundant in water decoction, which would be responsible for critical pharmacological effects. However, current research on polar compounds in Curcumae zedoaria Ros. c remains scarce. In this study, the polar fraction from Curcuma kwangsiensis was firstly profiled on G protein-coupled receptor 109A (GPR109A), ß2-adrenergic receptor (ß2-AR), neurotensin receptor (NTSR), muscarinic-3 acetylcholine receptor (M3) and G protein-coupled receptor 35 (GPR35), which were involved in its clinical indications and exhibited excellent ß2-AR and GPR109A receptor activities. Then, an offline two-dimensional reversed-phase liquid chromatography (RPLC) coupled with the hydrophilic interaction chromatography (HILIC) method was developed to separate polar compounds. By the combination of a polar-copolymerized XAqua C18 column and an amide-bonded XAmide column, an orthogonality of 47.6% was achieved. As a result of coupling with the mass spectrometry (MS), a four-dimensional data plot was presented in which 373 mass peaks were detected and 22 polar compounds tentatively identified, including the GPR109A agonist niacin. Finally, molecular docking of these 22 identified compounds to ß2-AR, M3, GPR35 and GPR109A receptors was performed to predict potential active ingredients, and compound 9 was predicted to have a similar interaction to the ß2-AR partial agonist salmeterol. These results were supplementary to the material basis of Curcuma kwangsiensis and facilitated the bioactivity research of polar compounds. The integration of RPLC×HILIC-MS and molecular docking can be a powerful tool for characterizing and predicting polar active components in TCM.

A Plane Extraction Approach in Inverse Depth Images Based on Region-Growing.

Planar surfaces are prevalent components of man-made indoor scenes, and plane extraction plays a vital role in practical applications of computer vision and robotics, such as scene understanding, and mobile manipulation. Nowadays, most plane extraction methods are based on reconstruction of the scene. In this paper, plane representation is formulated in inverse-depth images. Based on this representation, we explored the potential to extract planes in images directly. A fast plane extraction approach, which employs the region growing algorithm in inverse-depth images, is presented. This approach consists of two main components: seeding, and region growing. In the seeding component, seeds are carefully selected locally in grid cells to improve exploration efficiency. After seeding, each seed begins to grow into a continuous plane in succession. Both greedy policy and a normal coherence check are employed to find boundaries accurately. During growth, neighbor coplanar planes are checked and merged to overcome the over-segmentation problem. Through experiments on public datasets and generated saw-tooth images, the proposed approach achieves 80.2% CDR (Correct Detection Rate) on the ABW SegComp Dataset, which has proven that it has comparable performance with the state-of-the-art. The proposed approach runs at 5 Hz on typical 680 × 480 images, which has shown its potential in real-time practical applications in computer vision and robotics with further improvement.

Highly Morphology-Controllable and Highly Sensitive Capacitive Tactile Sensor Based on Epidermis-Dermis-Inspired Interlocked Asymmetric-Nanocone Arrays for Detection of Tiny Pressure.

The tactile sensor lies at the heart of electronic skin and is of great importance in the development of flexible electronic devices. To date, it still remains a critical challenge to develop a large-scale capacitive tactile sensor with high sensitivity and controllable morphology in an economical way. Inspired by the interlocked microridges between the epidermis and dermis, herein, a highly sensitive capacitive tactile sensor by creating interlocked asymmetric-nanocones in poly(vinylidenefluoride-co-trifluoroethylene) film is proposed. Particularly, a facile method based on cone-shaped nanoporous anodized aluminum oxide templates is proposed to cost-effectively fabricate the highly ordered nanocones in a controllable manner and on a large scale. Finite-element analysis reveals that under vertical forces, the strain/stress can be highly strengthened and localized at the contact apexes, resulting in an amplified variation of film permittivity and thickness. Benefiting from this, the developed tactile sensor presents several conspicuous features, including the maximum sensitivity (6.583 kPa-1 ) in the low pressure region (0-100 Pa), ultralow detection limit (≈3 Pa), rapid response/recovery time (48/36 ms), excellent stability and reproducibility (10 000 cycles). These salient merits enable the sensor to be successfully applied in a variety of applications including sign language gesture detection, spatial pressure mapping, Braille recognition, and physiological signal monitoring.

Phosphorus-Doped Iron Nitride Nanoparticles Encapsulated by Nitrogen-Doped Carbon Nanosheets on Iron Foam In Situ Derived from Saccharomycetes Cerevisiae for Electrocatalytic Overall Water Splitting.

It is vitally essential to propose a novel, economical, and safe preparation method to design highly efficient electrocatalysts. Herein, phosphorus-doped iron nitride nanoparticles encapsulated by nitrogen-doped carbon nanosheets are grown directly on the iron foam substrate (P-Fe3 N@NC NSs/IF) by in situ deriving from Saccharomycetes cerevisiae (S. cerevisiae), where anion elements of C, N, and P all from S. cerevisiae replace the hazardous CH4 , NH3 , and H3 P. The diffusion pattern of N, P in S. cerevisiae and contact form between metal and S. cerevisiae observably affect the composition and phase of the product during high-temperature calcination. The obtained P-Fe3 N@NC NSs/IF demonstrates superior electrocatalytic performance for the hydrogen evolution reaction and oxygen evolution reaction, also satisfying durability. Theoretical calculation confirms that Fe sites of P-Fe3 N serve as the active center, and N sites and P doping regulate the hydrogen binding strength to enhance catalytic ability. Additionally, the two-electrode electrolyzer assembled by P-Fe3 N@NC NSs/IF as both anode and cathode electrodes needs only 1.61 V to reach 10 mA cm-2 for overall water splitting with a superb stability. The S. cerevisiae-based process presents a feasible approach for synthesis of nitrides, carbides, phosphides, and electrocatalytic applications.

Application of two-dimensional liquid chromatography in the separation of traditional Chinese medicine.

Traditional Chinese medicines have been widely used to prevent and cure diseases for thousands of years. For the purpose of better understanding the extremely complicated traditional Chinese medicines, powerful separation techniques are essential. Two-dimensional liquid chromatography has been proven to be more powerful for the separation of complex traditional Chinese medicines due to its enhanced peak capacity and resolution compared with one-dimensional liquid chromatography. Enormous efforts have been made on the coupling of independent separation mechanisms to improve the resolving power for complex traditional Chinese medicine samples, including the development and introduction of novel stationary phases. This review aims to give an overview on the applications of two-dimensional liquid chromatography in traditional Chinese medicine research since 2008, including comprehensive two-dimensional liquid chromatography, heart-cutting two-dimensional liquid chromatography both in on-line, and off-line mode. Different couplings of separation modes were respectively discussed based on specific studies, with emphasis on the applications of novel stationary phases in the two-dimensional liquid chromatography.

Characterization of tropane and cinnamamide alkaloids from Scopolia tangutica by high-performance liquid chromatography with quadrupole time-of-flight tandem mass spectrometry.

Scopolia tangutica is a traditional Chinese medicine used for antispasmodic, anesthesia, analgesia, and sedation. Its medicinal activity is associated to alkaloid constituents, including tropane and cinnamamide types. Low content of alkaloids in plant makes them difficult to be isolated and identified. The present work developed an effective method to quickly characterize alkaloids from Scopolia tangutica by high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry. Thirteen reference compounds were studied for their fragmentation pathways, including five tropane alkaloids and eight cinnamamide ones. Alkaloid constituent was analyzed by an optimized high-performance liquid chromatography method and mass spectrometry analysis to achieve systematic characterization of alkaloids from Scopolia tangutica. As a result, 53 compounds were identified, including 21 tropane alkaloids (eight new ones), 18 caffeoyl ones (ten new ones) and 14 dicaffeoyl ones (seven new ones). It was important to provide rich information in phytochemical study and structure-guided isolation of important compounds from this plant.

DeepHMap++: Combined Projection Grouping and Correspondence Learning for Full DoF Pose Estimation.

In recent years, estimating the 6D pose of object instances with convolutional neural network (CNN) has received considerable attention. Depending on whether intermediate cues are used, the relevant literature can be roughly divided into two broad categories: direct methods and two-stage pipelines. For the latter, intermediate cues, such as 3D object coordinates, semantic keypoints, or virtual control points instead of pose parameters are regressed by CNN in the first stage. Object pose can then be solved by correspondence constraints constructed with these intermediate cues. In this paper, we focus on the postprocessing of a two-stage pipeline and propose to combine two learning concepts for estimating object pose under challenging scenes: projection grouping on one side, and correspondence learning on the other. We firstly employ a local-patch based method to predict projection heatmaps which denote the confidence distribution of projection of 3D bounding box's corners. A projection grouping module is then proposed to remove redundant local maxima from each layer of heatmaps. Instead of directly feeding 2D⁻3D correspondences to the perspective-n-point (PnP) algorithm, multiple correspondence hypotheses are sampled from local maxima and its corresponding neighborhood and ranked by a correspondence⁻evaluation network. Finally, correspondences with higher confidence are selected to determine object pose. Extensive experiments on three public datasets demonstrate that the proposed framework outperforms several state of the art methods.

Synthesis and chromatographic evaluation of phenyl/tetrazole bonded stationary phase based on thiol-epoxy ring opening reaction.

A silica-based reversed-phase stationary phase bonding with phenyl and tetrazole groups was synthesized by thiol-epoxy ring opening reaction. The bonded groups could not only provide hydrophobic interaction, but also π-π, hydrogen bonding, electrostatic interactions, and so on. The results of characterization with elemental analysis and solid-state 13 C cross-polarization magic-angle-spinning NMR spectroscopy indicated the successful preparation of phenyl/tetrazole sulfoether bonded stationary phase. Chromatographic evaluation revealed that phenyl/tetrazole sulfoether bonded stationary phase behaved well under the reversed-phase mode. The column parameters (H, S*, A, B, and C) showed different selectivity compared with some typical commercial columns, and it was validated by the separation of estrogen, ginsenoside, alkaloid samples. Based on the different selectivity between phenyl/tetrazole sulfoether bonded stationary phase and C18 columns, phenyl/tetrazole sulfoether bonded stationary phase also showed potential to construct a 2D reversed-phase liquid chromatography system with C18. And it was verified by the separation of corydalis tuber and curcuma zedoary extracts.

An Occlusion-Aware Framework for Real-Time 3D Pose Tracking.

Random forest-based methods for 3D temporal tracking over an image sequence have gained increasing prominence in recent years. They do not require object's texture and only use the raw depth images and previous pose as input, which makes them especially suitable for textureless objects. These methods learn a built-in occlusion handling from predetermined occlusion patterns, which are not always able to model the real case. Besides, the input of random forest is mixed with more and more outliers as the occlusion deepens. In this paper, we propose an occlusion-aware framework capable of real-time and robust 3D pose tracking from RGB-D images. To this end, the proposed framework is anchored in the random forest-based learning strategy, referred to as RFtracker. We aim to enhance its performance from two aspects: integrated local refinement of random forest on one side, and online rendering based occlusion handling on the other. In order to eliminate the inconsistency between learning and prediction of RFtracker, a local refinement step is embedded to guide random forest towards the optimal regression. Furthermore, we present an online rendering-based occlusion handling to improve the robustness against dynamic occlusion. Meanwhile, a lightweight convolutional neural network-based motion-compensated (CMC) module is designed to cope with fast motion and inevitable physical delay caused by imaging frequency and data transmission. Finally, experiments show that our proposed framework can cope better with heavily-occluded scenes than RFtracker and preserve the real-time performance.

Metal-Carbon Hybrid Electrocatalysts Derived from Ion-Exchange Resin Containing Heavy Metals for Efficient Hydrogen Evolution Reaction.

Transition metal-carbon hybrids have been proposed as efficient electrocatalysts for hydrogen evolution reaction (HER) in acidic media. Herein, effective HER electrocatalysts based on metal-carbon composites are prepared by controlled pyrolysis of resin containing a variety of heavy metals. For the first time, Cr2 O3 nanoparticles of 3-6 nm in diameter homogeneously dispersed in the resulting porous carbon framework (Cr-C hybrid) is synthesized as efficient HER electrocatalyst. Electrochemical measurements show that Cr-C hybrids display a high HER activity with an onset potential of -49 mV (vs reversible hydrogen electrode), a Tafel slope of 90 mV dec(-1) , a large catalytic current density of 10 mA cm(-2) at -123 mV, and the prominent electrochemical durability. X-ray photoelectron spectroscopic measurements confirm that electron transfer occurs from Cr2 O3 into carbon, which is consistent with the reported metal@carbon systems. The obtained correlation between metals and HER activities may be exploited as a rational guideline in the design and engineering of HER electrocatalysts.

Graphene-Supported Mesoporous Carbons Prepared with Thermally Removable Templates as Efficient Catalysts for Oxygen Electroreduction.

Graphene-supported mesoporous carbons with rich nitrogen self-doped active sites (N-MC/rGO) are prepared by direct pyrolysis of a graphene-oxide-supported polymer composite embedded with massive, evenly distributed amorphous FeOOH that serve as efficient thermally removable templates. The resulting N-MC/rGO catalysts exhibit high surface areas and apparent electrocatalytic activity for oxygen reduction reaction in alkaline media. Among the series, the sample prepared at 800 °C displays the best performance with a more positive onset potential, higher limiting currents, much higher stability, and stronger poison resistance than commercial Pt/C. This is ascribed to the synergetic functions of the highly conductive graphene support and the mesoporous N-doped carbons that effectively impede the restacking of the graphene sheets and enhance the exposure of the rich nitrogen self-doped active sites.