Mapping port wine stain in vivo by optical coherence tomography angiography and multi-metric characterization.

Port wine stain (PWS) is a congenital cutaneous capillary malformation composed of ecstatic vessels, while the microstructure of these vessels remains largely unknown. Optical coherence tomography angiography (OCTA) serves as a non-invasive, label-free and high-resolution tool to visualize the 3D tissue microvasculature. However, even as the 3D vessel images of PWS become readily accessible, quantitative analysis algorithms for their organization have mainly remained limited to analysis of 2D images. Especially, 3D orientations of vasculature in PWS have not yet been resolved at a voxel-wise basis. In this study, we employed the inverse signal-to-noise ratio (iSNR)-decorrelation (D) OCTA (ID-OCTA) to acquire 3D blood vessel images in vivo from PWS patients, and used the mean-subtraction method for de-shadowing to correct the tail artifacts. We developed algorithms which mapped blood vessels in spatial-angular hyperspace in a 3D context, and obtained orientation-derived metrics including directional variance and waviness for the characterization of vessel alignment and crimping level, respectively. Combining with thickness and local density measures, our method served as a multi-parametric analysis platform which covered a variety of morphological and organizational characteristics at a voxel-wise basis. We found that blood vessels were thicker, denser and less aligned in lesion skin in contrast to normal skin (symmetrical parts of skin lesions on the cheek), and complementary insights from these metrics led to a classification accuracy of ∼90% in identifying PWS. An improvement in sensitivity of 3D analysis was validated over 2D analysis. Our imaging and analysis system provides a clear picture of the microstructure of blood vessels within PWS tissues, which leads to a better understanding of this capillary malformation disease and facilitates improvements in diagnosis and treatment of PWS.

A tobacco ringspot virus-based vector system for gene and microRNA function studies in cucurbits.

Cucurbits are economically important crops worldwide. The genomic data of many cucurbits are now available. However, functional analyses of cucurbit genes and noncoding RNAs have been impeded because genetic transformation is difficult for many cucurbitaceous plants. Here, we developed a set of tobacco ringspot virus (TRSV)-based vectors for gene and microRNA (miRNA) function studies in cucurbits. A TRSV-based expression vector could simultaneously express GREEN FLUORESCENT PROTEIN (GFP) and heterologous viral suppressors of RNA silencing in TRSV-infected plants, while a TRSV-based gene silencing vector could knock down endogenous genes exemplified by PHYTOENE DESATURASE (PDS) in Cucumis melo, Citrullus lanatus, Cucumis sativus, and Nicotiana benthamiana plants. We also developed a TRSV-based miRNA silencing vector to dissect the functions of endogenous miRNAs. Four representative miRNAs, namely, miR159, miR166, miR172, and miR319, from different cucurbits were inserted into the TRSV vector using a short tandem target mimic strategy and induced characteristic phenotypes in TRSV-miRNA-infected plants. This TRSV-based vector system will facilitate functional genomic studies in cucurbits.

Identification of human ovarian cancer relying on collagen fiber coverage features by quantitative second harmonic generation imaging.

Ovarian cancer has the highest mortality rate among all gynecological cancers, containing complicated heterogeneous histotypes, each with different treatment plans and prognoses. The lack of screening test makes new perspectives for the biomarker of ovarian cancer of great significance. As the main component of extracellular matrix, collagen fibers undergo dynamic remodeling caused by neoplastic activity. Second harmonic generation (SHG) enables label-free, non-destructive imaging of collagen fibers with submicron resolution and deep sectioning. In this study, we developed a new metric named local coverage to quantify morphologically localized distribution of collagen fibers and combined it with overall density to characterize 3D SHG images of collagen fibers from normal, benign and malignant human ovarian biopsies. An overall diagnosis accuracy of 96.3% in distinguishing these tissue types made local and overall density signatures a sensitive biomarker of tumor progression. Quantitative, multi-parametric SHG imaging might serve as a potential screening test tool for ovarian cancer.

Phylogeny analysis from gene-order data with massive duplications.

BACKGROUND: Gene order changes, under rearrangements, insertions, deletions and duplications, have been used as a new type of data source for phylogenetic reconstruction. Because these changes are rare compared to sequence mutations, they allow the inference of phylogeny further back in evolutionary time. There exist many computational methods for the reconstruction of gene-order phylogenies, including widely used maximum parsimonious methods and maximum likelihood methods. However, both methods face challenges in handling large genomes with many duplicated genes, especially in the presence of whole genome duplication. METHODS: In this paper, we present three simple yet powerful methods based on maximum-likelihood (ML) approaches that encode multiplicities of both gene adjacency and gene content information for phylogenetic reconstruction. RESULTS: Extensive experiments on simulated data sets show that our new method achieves the most accurate phylogenies compared to existing approaches. We also evaluate our method on real whole-genome data from eleven mammals. The package is publicly accessible at http://www.geneorder.org . CONCLUSIONS: Our new encoding schemes successfully incorporate the multiplicity information of gene adjacencies and gene content into an ML framework, and show promising results in reconstruct phylogenies for whole-genome data in the presence of massive duplications.

Ancestral Genome Reconstruction on Whole Genome Level.

Comparative genomics, evolutionary biology, and cancer researches require tools to elucidate the evolutionary trajectories and reconstruct the ancestral genomes. Various methods have been developed to infer the genome content and gene ordering of ancestral genomes by using such genomic structural variants. There are mainly two kinds of computational approaches in the ancestral genome reconstruction study. Distance/event-based approaches employ genome evolutionary models and reconstruct the ancestral genomes that minimize the total distance or events over the edges of the given phylogeny. The homology/adjacency-based approaches search for the conserved gene adjacencies and genome structures, and assemble these regions into ancestral genomes along the internal node of the given phylogeny. We review the principles and algorithms of these approaches that can reconstruct the ancestral genomes on the whole genome level. We talk about their advantages and limitations of these approaches in dealing with various genome datasets, evolutionary events, and reconstruction problems. We also talk about the improvements and developments of these approaches in the subsequent researches. We select four most famous and powerful approaches from both distance/event-based and homology/adjacency-based categories to analyze and compare their performances in dealing with different kinds of datasets and evolutionary events. Based on our experiment, GASTS has the best performance in solving the problems with equal genome contents that only have genome rearrangement events. PMAG++ achieves the best performance in solving the problems with unequal genome contents that have all possible complicated evolutionary events.

Atmospheric sulfur hexafluoride in-situ measurements at the Shangdianzi regional background station in China.

We present in-situ measurements of atmospheric sulfur hexafluoride (SF6) conducted by an automated gas chromatograph-electron capture detector system and a gas chromatography/mass spectrometry system at a regional background site, Shangdianzi, in China, from June 2009 to May 2011, using the System for Observation of Greenhouse gases in Europe and Asia and Advanced Global Atmospheric Gases Experiment (AGAGE) techniques. The mean background and polluted mixing ratios for SF6 during the study period were 7.22 × 10⁻¹² (mol/mol, hereinafter) and 8.66 × 10⁻¹², respectively. The averaged SF6 background mixing ratios at Shangdianzi were consistent with those obtained at other AGAGE stations located at similar latitudes (Trinidad Head and Mace Head), but larger than AGAGE stations in the Southern Hemisphere (Cape Grim and Cape Matatula). SF6 background mixing ratios increased rapidly during our study period, with a positive growth rate at 0.30 × 10⁻¹² year⁻¹. The peak to peak amplitude of the seasonal cycle for SF6 background conditions was 0.07 × 10⁻¹², while the seasonal fluctuation of polluted conditions was 2.16 × 10⁻¹². During the study period, peak values of SF6 mixing ratios occurred in autumn when local surface horizontal winds originated from W/WSW/SW/SWS/S sectors, while lower levels of SF6 mixing ratios appeared as winds originated from N/NNE/NE/ENE/E sectors.

A natural substitution of a conserved amino acid in eIF4E confers resistance against multiple potyviruses.

Eukaryotic translation initiation factor 4E (eIF4E), which plays a pivotal role in initiating translation in eukaryotic organisms, is often hijacked by the viral genome-linked protein to facilitate the infection of potyviruses. In this study, we found that the naturally occurring amino acid substitution D71G in eIF4E is widely present in potyvirus-resistant watermelon accessions and disrupts the interaction between watermelon eIF4E and viral genome-linked protein of papaya ringspot virus-watermelon strain, zucchini yellow mosaic virus or watermelon mosaic virus. Multiple sequence alignment and protein modelling showed that the amino acid residue D71 located in the cap-binding pocket of eIF4E is strictly conserved in many plant species. The mutation D71G in watermelon eIF4E conferred resistance against papaya ringspot virus-watermelon strain and zucchini yellow mosaic virus, and the equivalent mutation D55G in tobacco eIF4E conferred resistance to potato virus Y. Therefore, our finding provides a potential precise target for breeding plants resistant to multiple potyviruses.

Restricted intake of sulfur-containing amino acids reversed the hepatic injury induced by excess Desulfovibrio through gut-liver axis.

Diet is a key player in gut-liver axis. However, the effect of different dietary patterns on gut microbiota and liver functions remains unclear. Here, we used rodent standard chow and purified diet to mimic two common human dietary patterns: grain and plant-based diet and refined-food-based diet, respectively and explored their impacts on gut microbiota and liver. Gut microbiota experienced a great shift with notable increase in Desulfovibrio, gut bile acid (BA) levels elevated significantly, and liver inflammation was observed in mice fed with the purified diet. Liver inflammation and elevated gut BA levels also occurred in mice fed with the chow diet after receiving Desulfovibrio desulfuricans ATCC 29,577 (DSV). Restriction of sulfur-containing amino acids (SAAs) prevented liver injury mainly through higher hepatic antioxidant and detoxifying ability and reversed the elevated BA levels due to excess Desulfovibrio. Ex vivo fermentation of human fecal microbiota with primary BAs demonstrated that DSV enhanced production of secondary BAs. Higher concentration of both primary and secondary BAs were found in the gut of germ-free mice after receiving DSV. In conclusion, Restriction of SAAs in diet may become an effective dietary intervention to prevent liver injury associated with excess Desulfovibrio in the gut.

Lactic acid fermentation of goji berries (Lycium barbarum) prevents acute alcohol liver injury and modulates gut microbiota and metabolites in mice.

Juice fermented with lactic acid bacteria (LAB) has received attention due to its health benefits, such as antioxidant and anti-inflammatory. Previous research on LAB-fermented goji juice mainly focused on exploring the changes in the metabolite profile and antioxidant activity in vitro, whereas the liver protection properties of LAB-fermented goji juice in vivo are still unknown. This study aimed to investigate the effects of Lacticaseibacillus paracasei E10-fermented goji juice (E10F), Lactiplantibacillus plantarum M-fermented goji juice (MF), Lacticaseibacillus rhamnosus LGG-fermented goji juice (LGGF) on preventing acute alcoholic liver injury with physiology, gut microbial, and metabolic profiles in mice. Compared with goji juice, E10F, MF, and LGGF enhanced the protective effect against liver injury by reducing serum alanine transaminase (ALT) levels, improving the hepatic glutathione (GSH) antioxidant system, and attenuating inflammation by decreasing the levels of interleukin (IL)-1ß, IL-6, tumor necrosis factor (TNF)-α, and transforming growth factor (TGF)-ß. Furthermore, E10F, MF, and LGGF increased intestinal integrity, restructured the gut microbiota including Bacteroides and Lactobacillus, and altered gut microbial metabolites including kyotorphin, indolelactic acid, and N-methylserotonin. Pretreatment of different LAB-fermented goji juice in mice showed significant differences in gut microbiota and metabolism. The correlation analysis demonstrated that the increase of Lactobacillus, indolelactic acid, and N-methylserotonin by E10F, MF, and LGGF was positively correlated with reduced inflammation and improved liver and gut function. Taken together, E10F, MF, and LGGF all have the potential to be converted into dietary interventions to combat acute alcoholic liver injury. It provided a reference for the study of the hepatoprotective effect of LAB-fermented goji juice.

Stabilizing non-iridium active sites by non-stoichiometric oxide for acidic water oxidation at high current density.

Stabilizing active sites of non-iridium-based oxygen evolution reaction (OER) electrocatalysts is crucial, but remains a big challenge for hydrogen production by acidic water splitting. Here, we report that non-stoichiometric Ti oxides (TiOx) can safeguard the Ru sites through structural-confinement and charge-redistribution, thereby extending the catalyst lifetime in acid by 10 orders of magnitude longer compared to that of the stoichiometric one (Ru/TiO2). By exploiting the redox interaction-engaged strategy, the in situ growth of TiOx on Ti foam and the loading of Ru nanoparticles are realized in one step. The as-synthesized binder-free Ru/TiOx catalyst exhibits low OER overpotentials of 174 and 265 mV at 10 and 500 mA cm-2, respectively. Experimental characterizations and theoretical calculations confirm that TiOx stabilizes the Ru active center, enabling operation at 10 mA cm-2 for over 37 days. This work opens an avenue of using non-stoichiometric compounds as stable and active materials for energy technologies.

Mapping the 3D remodeling of the extracellular matrix in human hypertrophic scar by multi-parametric multiphoton imaging using endogenous contrast.

The hypertrophic scar is an aberrant form of wound healing process, whose clinical efficacy is limited by a lack of understanding of its pathophysiology. Remodeling of collagen and elastin fibers in the extracellular matrix (ECM) is closely associated with scar progression. Herein, we perform label-free multiphoton microscopy (MPM) of both fiber components from human skin specimens and propose a multi-fiber metrics (MFM) analysis model for mapping the structural remodeling of the ECM in hypertrophic scars in a highly-sensitive, three-dimensional (3D) manner. We find that both fiber components become wavier and more disorganized in scar tissues, while content accumulation is observed from elastin fibers only. The 3D MFM analysis can effectively distinguish normal and scar tissues with better than 95% in accuracy and 0.999 in the area under the curve value of the receiver operating characteristic curve. Further, unique organizational features with orderly alignment of both fibers are observed in scar-normal adjacent regions, and an optimized combination of features from 3D MFM analysis enables successful identification of all the boundaries. This imaging and analysis system uncovers the 3D architecture of the ECM in hypertrophic scars and exhibits great translational potential for evaluating scars in vivo and identifying individualized treatment targets.

Low Weight Polysaccharide of Hericium erinaceus Ameliorates Colitis via Inhibiting the NLRP3 Inflammasome Activation in Association with Gut Microbiota Modulation.

Ulcerative colitis (UC), one of the typical inflammatory bowel diseases caused by dysregulated immunity, still requires novel therapeutic medicine with high efficacy and low toxicity. Hericium erinaceus has been widely used to treat different health problems especially gastrointestinal sickness in China for thousands of years. Here, we isolated, purified, and characterized a novel low weight polysaccharide (HEP10, Mw: 9.9 kDa) from the mycelia of H. erinaceus in submerged culture. We explored the therapeutic effect of HEP10 on UC and explored its underlying mechanisms. On one hand, HEP10 suppressed the production of TNF-α, IL-1ß, IL-6, inducible iNOS, and COX-2 in LPS challenged murine macrophage RAW264.7 cells, as well as in colons from DSS-induced colitis mice. On the other hand, HEP10 treatment markedly suppressed the activation of NLRP3 inflammasome, NF-κB, AKT, and MAPK pathways. Moreover, HEP10 reversed DSS-induced alternation of the gut community composition and structure by significantly increasing Akkermansia muciniphila and also promoting functional shifts in gut microbiota. Structural equation modeling also highlighted that HEP10 can change widely through gut microbiota. In conclusion, HEP10 has a better prebiotic effect than the crude polysaccharides of H. erinaceus, which can be used as a novel dietary supplement and prebiotic to ameliorate colitis.

Mapping variation of extracellular matrix in human keloid scar by label-free multiphoton imaging and machine learning.

Significance: Rapid diagnosis and analysis of human keloid scar tissues in an automated manner are essential for understanding pathogenesis and formulating treatment solutions. Aim: Our aim is to resolve the features of the extracellular matrix in human keloid scar tissues automatically for accurate diagnosis with the aid of machine learning. Approach: Multiphoton microscopy was utilized to acquire images of collagen and elastin fibers. Morphological features, histogram, and gray-level co-occurrence matrix-based texture features were obtained to produce a total of 28 features. The minimum redundancy maximum relevancy feature selection approach was implemented to rank these features and establish feature subsets, each of which was employed to build a machine learning model through the tree-based pipeline optimization tool (TPOT). Results: The feature importance ranking was obtained, and 28 feature subsets were acquired by incremental feature selection. The subset with the top 23 features was identified as the most accurate. Then stochastic gradient descent classifier optimized by the TPOT was generated with an accuracy of 96.15% in classifying normal, scar, and adjacent tissues. The area under curve of the classification results (scar versus normal and adjacent, normal versus scar and adjacent, and adjacent versus normal and scar) was 1.0, 1.0, and 0.99, respectively. Conclusions: The proposed approach has great potential for future dermatological clinical diagnosis and analysis and holds promise for the development of computer-aided systems to assist dermatologists in diagnosis and treatment.

Highly accurate, automated quantification of 2D/3D orientation for cerebrovasculature using window optimizing method.

Significance: Deep-imaging of cerebral vessels and accurate organizational characterization are vital to understanding the relationship between tissue structure and function. Aim: We aim at large-depth imaging of the mouse brain vessels based on aggregation-induced emission luminogens (AIEgens), and we create a new algorithm to characterize the spatial orientation adaptively with superior accuracy. Approach: Assisted by AIEgens with near-infrared-II excitation, three-photon fluorescence (3PF) images of large-depth cerebral blood vessels are captured. A window optimizing (WO) method is developed for highly accurate, automated 2D/3D orientation determination. The application of this system is demonstrated by establishing the orientational architecture of mouse cerebrovasculature down to the millimeter-level depth. Results: The WO method is proved to have significantly higher accuracy in both 2D and 3D cases than the method with a fixed window size. Depth- and diameter-dependent orientation information is acquired based on in vivo 3PF imaging and the WO analysis of cerebral vessel images with a penetration depth of 800 µm in mice. Conclusions: We built an imaging and analysis system for cerebrovasculature that is conducive to applications in neuroscience and clinical fields.

Desulfovibrio fairfieldensis-Derived Outer Membrane Vesicles Damage Epithelial Barrier and Induce Inflammation and Pyroptosis in Macrophages.

Sulfate-reducing bacteria Desulfovibrio fairfieldensis is an opportunistic pathogen that widely exists in the human intestine and can cause severe infectious diseases. However, the mechanisms contributing to its pathogenesis remain of great interest. In this study, we aim to investigate the outer membrane vesicles (OMVs) secreted by D. fairfieldensis and their pathogenic effect. The OMVs separated by ultracentrifugation were spherical and displayed a characteristic bilayer lipid structure observed by transmission electron microscopy, with an average hydrodynamic diameter of 75 nm measurement using the particle size analyzer. We identified 1496 and 916 proteins from D. fairfieldensis and its OMVs using label-free non-target quantitative proteomics, respectively. The 560 co-expressed proteins could participate in bacterial life activities by function prediction. The translocation protein TolB, which participates in OMVs biogenesis and transporting toxins was highly expressed in OMVs. The OMVs inhibited the expression of tight junction proteins OCCLUDIN and ZO-1 in human colonic epithelial cells (Caco-2). The OMVs decreased the cell viability of monocyte macrophages (THP-1-Mφ) and activated various inflammatory factors secretion, including interferon-γ (IFN-γ), tumor necrosis factor (TNF-α), and many interleukins. Further, we found the OMVs induced the expression of cleaved-gasdermin D, caspase-1, and c-IL-1ß and caused pyroptosis in THP-1-Mφ cells. Taken together, these data reveal that the D. fairfieldensis OMVs can damage the intestinal epithelial barrier and activate intrinsic inflammation.

Oxygenated functional group-driven spontaneous fabrication of Pd nanoparticles decorated porous carbon nanosheets for electrocatalytic hydrodechlorination of 4-chlorophenol.

Researchers have been committed to reducing the hazardous pollutants by developing efficient catalysts while ignoring the pollution caused by the use of toxic surface capping agents, reductants and/or organic solvents in the catalyst preparation process. To alleviate such problems, we here report a novel one-step oxygenated functional group-driven electroless deposition strategy to synthesize clean and uniformly distributed Pd nanoparticles (NPs) using porous carbon nanosheets (PCN) as both substrates and reducing agents. It is observed that the oxygenated functional groups enriched PCN possesses a low work function and allows the spontaneous reduction of PdCl42- ions to Pd NPs deposited on the PCN support (Pd/PCN). The particle size of Pd NPs can be flexibly modulated by simply controlling the immersing time and thereby their maximum catalytic performances can be achieved. Specifically, the optimal Pd/PCN-08 with a Pd loading of 3.0 wt% shows an excellent activity with a turnover frequency of 0.38 min-1 for electrocatalytic hydrodechlorination (ECH) of 4-chlorophenol (4-CP), superior to the previously reported materials. The stability of Pd/PCN-08 for 4-CP ECH is impressive in repetitive cycles. This work proposes a facile and efficient strategy to synthesize high-performance catalysts for detoxifying the hazardous organic pollutants.

Oxygenated functional group-engaged electroless deposition of ligand-free silver nanoparticles on porous carbon for efficient electrochemical non-enzymatic H2O2 detection.

The construction of metal-carbon nanostructures with enhanced performances using traditional methods, such as pyrolysis, photolysis, impregnation-reduction, etc., generally requires additional energy input, reducing agents and capping ligands, which inevitably increase the manufacturing cost and environmental pollution. Herein, a novel one-step substrate-induced electroless deposition (SIED) strategy is developed to synthesize ligand-free Ag NPs supported on porous carbon (PC) (Ag/PC). The PC matrix enriched with oxygenated functional groups has a low work function and thus a low redox potential compared to that of Ag+ ions, which induces the auto-reduction of Ag+ ions to Ag NPs. The as-synthesized Ag/PC-6 modified electrode can be used as an excellent nonenzymatic H2O2 sensor with a broad linear range of 0.001-20 mM, a low detection limit of 0.729 µM (S/N = 3), and a high response sensitivity of 226.9 µA mM-1 cm-2, outperforming most of the reported sensor materials. Moreover, this electrode can be applied to detect trace amounts of H2O2 in juice and milk samples below the permitted residual level in food packaging and the recovery of H2O2 is 99.6% in blood serum (10%) with good reproducibility. This study proposes an efficient approach for synthesizing a highly active supported Ag electrocatalyst, which shows significant potential for practical applications.

Modulation of defects and electrical behaviors of Cu-doped KNN ceramics by fluorine-oxygen substitution.

The lead-free piezoceramics of K0.5Na0.5Nb0.996Cu0.01O3-xFx (KNCNF-x) were synthesized via a conventional solid sintering process, and the inhibition effects of F-O substitution on the defect structures of oxygen vacancies and defect complexes were investigated. The KNCNF-0 ceramic without F doping has the highest level of oxygen vacancies and defect complexes. However, as the level of F increases, the contents of oxygen vacancies and defect complexes decrease correspondingly, and thus, the evolution of hardening to softening behaviors in the ceramics is observed. As a result, the KNCNF-0 piezoceramic shows extremely hardened electrical behaviors (a completely constricted P-E hysteresis loop, large Ei of 10.7 kV cm-1, kp of 38%, d33 of 83 pC N-1, Qm of 3110, and tan δ of 0.2%), while the ceramic with x = 0.28 exhibits softened ferroelectric and piezoelectric characteristics (a non-shrinking P-E hysteresis loop, declining Ei of 7.5 kV cm-1, enhanced kp of 42%, optimized d33 of 103 pC N-1, reduced Qm of 1031, and increased tan δ of 0.6%). This study provides new insights into the modulation of defects and electrical performance of KNN ceramics.

Flexible Active-Site Engineering of Monometallic Co-Layered Double Hydroxides for Achieving High-Performance Bifunctional Electrocatalyst toward Oxygen Evolution and H2O2 Reduction.

It is highly desirable but challenging to develop a facile and scalable strategy to synthesize efficient bifunctional electrocatalysts for oxygen evolution and H2O2 reduction by engineering the active site of monometallic-layered double hydroxides (LDHs). Herein, we developed a convenient, efficient, and scalable method for the construction of monometallic Co-LDHs with tunable Con+ (n = 2, 3) concentration by a one-pot solvothermal reaction in a short time (e.g., 2 and 4 h) using only cobalt nitrate and hexamine as raw materials. The catalytic performance of Co-LDHs was mainly determined by the Con+ (n = 2, 3) concentration, which could be simply regulated by tuning the solvothermal time. Combining the joint merits of three-dimensional flowerlike architecture (abundant accessible active sites and a fast electron/mass transport), Co-LDHs-4 with abundant Co3+ species exhibited an excellent electrocatalytic activity for oxygen evolution reaction in terms of a low overpotential at 10 mA cm-2 (η10 = 241 mV) and long-term durability for 70 h at 100 mA cm-2, better than the state-of-the-art IrO2 and most of the reported analogues. Besides, Co-LDHs-2 enriched in Co2+ displayed a superior electrochemical activity for H2O2 detection with a broad linear range (0.002-20 mM), a low detection limit (0.002 mM), and a high response sensitivity (272.02 µA mM-1 cm-2). Therefore, this work opens a new horizon for the rational development of a highly active electrocatalyst with tunable concentrations of active components.