Biochemical Characterization of Hyaluronate Lyase CpHly8 from an Intestinal Microorganism Clostridium perfringens G1121.

Hyaluronic acid (HA) is an important component of extracellular matrices (ECM) and a linear polysaccharide involved in various physiological and pathological processes within the biological system. Several pathogens exploit HA degradation within the extracellular matrix to facilitate infection. While many intestinal microorganisms play significant roles in HA utilization in the human body, there remains a scarcity of related studies. This paper addressed this gap by screening intestinal microorganisms capable of degrading HA, resulting in the isolation of Clostridium perfringens G1121, which had been demonstrated the ability to degrade HA. Subsequent genome sequencing and analysis of C. perfringens G1121 revealed its utilization of the polysaccharide utilization loci of HA (PULHA), which was obtained by horizontal gene transfer. The PULHA contains a sequence encoding a hyaluronic acid-specific degradation enzyme designated CpHly8, belonging to polysaccharide lyase family 8. The specific activity of CpHly8 towards HA was 142.98 U/mg, with the optimum reaction temperature and pH observed at 50℃ and 6.0, respectively. The final product of HA degradation by CpHly8 was unsaturated hyaluronic acid disaccharide. Moreover, subcutaneous diffusion experiments with trypan blue in mice revealed that CpHly8 effectively promoted subcutaneous diffusion and sustained its effects long-term, suggesting its potential application as an adjunct in drug delivery. Overall, our study enriches our understanding of intestinal microbial degradation of HA, provides new evidence for horizontal gene transfer among intestinal microorganisms, and confirms that CpHly8 is a promising candidate for intestinal microbial hyaluronidase.

Fusion of convolutional neural network with XGBoost feature extraction for predicting multi-constituents in corn using near infrared spectroscopy.

Near-infrared (NIR) spectroscopy has been widely utilized to predict multi-constituents of corn in agriculture. However, directly extracting constituent information from the NIR spectra is challenging due to many issues such as broad absorption band, overlapping and non-specific nature. To solve these problems and extract implicit features from the raw data of NIR spectra to improve performance of quantitative models, a one-dimensional shallow convolutional neural network (CNN) model based on an eXtreme Gradient Boosting (XGBoost) feature extraction method was proposed in this paper. The leaf node feature information in the XGBoost was encoded and reconstructed to obtain the implicit features of raw data in the NIR spectra. A two-parametric Swish (TSwish or TS) activation function was proposed to improve the performance of CNN, and the elastic net (EN) was also applied to avoid the overfitting problem of the CNN model. Performance of the developed XGBoost-CNN-TS-EN model was evaluated using two public NIR spectroscopy datasets of corn and soil, and the obtained determination coefficients (R2) for moisture, oil, protein, and starch of the corn on test set were 0.993, 0.991, 0.998, and 0.992, respectively, with that of the soil organic matter being 0.992. The XGBoost-CNN-TS-EN model exhibits superior stability, good prediction accuracy, and generalization ability, demonstrating its great potentials for quantitative analysis of multi-constituents in spectroscopic applications.

Flexible surface acoustic wave technology for enhancing transdermal drug delivery.

Transdermal drug delivery provides therapeutic benefits over enteric or injection delivery because its transdermal routes provide more consistent concentrations of drug and avoid issues of drugs affecting kidneys and liver functions. Many technologies have been evaluated to enhance drug delivery through the relatively impervious epidermal layer of the skin. However, precise delivery of large hydrophilic molecules is still a great challenge even though microneedles or other energized (such as electrical, thermal, or ultrasonic) patches have been used, which are often difficult to be integrated into small wearable devices. This study developed a flexible surface acoustic wave (SAW) patch platform to facilitate transdermal delivery of macromolecules with fluorescein isothiocyanates up to 2000 kDa. Two surrogates of human skin were used to evaluate SAW based energized devices, i.e., delivering dextran through agarose gels and across stratum corneum of pig skin into the epidermis. Results showed that the 2000 kDa fluorescent molecules have been delivered up to 1.1 mm in agarose gel, and the fluorescent molecules from 4 to 2000 kDa have been delivered up to 100 µm and 25 µm in porcine skin tissue, respectively. Mechanical agitation, localised streaming, and acousto-thermal effect generated on the skin surface were identified as the main mechanisms for promoting drug transdermal transportation, although micro/nanoscale acoustic cavitation induced by SAWs could also have its contribution. SAW enhanced transdermal drug delivery is dependent on the combined effects of wave frequency and intensity, duration of applied acoustic waves, temperature, and drug molecules molecular weights.

XGBoost algorithm assisted multi-component quantitative analysis with Raman spectroscopy.

To improve prediction performance and reduce artifacts in Raman spectra, we developed an eXtreme Gradient Boosting (XGBoost) preprocessing method to preprocess the Raman spectra of glucose, glycerol and ethanol mixtures. To ensure the robustness and reliability of the XGBoost preprocessing method, an X-LR model (which combined XGBoost preprocessing and a linear regression (LR) model) and a X-MLP model (which combined XGBoost preprocessing and a multilayer perceptron (MLP) model) were developed. These two models were used to quantitatively analyze the concentrations of glucose, glycerol and ethanol in the Raman spectra of mixed solutions. The proportion map of hyperparameters was firstly used to narrow down the search range of hyperparameters in the X-LR and the X-MLP models. Then the correlation coefficients (R2), root mean square of calibration (RMSEC), and root mean square error of prediction (RMSEP) were used to evaluate the models' performance. Experimental results indicated that the XGBoost preprocessing method achieved higher accuracy and generalization capability, with better performance than those of other preprocessing methods for both LR and MLP models.

Controlling bacterial growth and inactivation using thin film-based surface acoustic waves.

Formation of bacterial films on structural surfaces often leads to severe contamination of medical devices, hospital equipment, implant materials, etc., and antimicrobial resistance of microorganisms has indeed become a global health issue. Therefore, effective therapies for controlling infectious and pathogenic bacteria are urgently needed. Being a promising active method for this purpose, surface acoustic waves (SAWs) have merits such as nanoscale earthquake-like vibration/agitation/radiation, acoustic streaming induced circulations, and localised acoustic heating effect in liquids. However, only a few studies have explored controlling bacterial growth and inactivation behaviour using SAWs. In this study, we proposed utilising piezoelectric thin film-based SAW devices on a silicon substrate for controlling bacterial growth and inactivation with and without using ZnO micro/nanostructures. Effects of SAW powers on bacterial growth for two types of bacteria, i.e., E. coli and S. aureus, were evaluated. Varied concentrations of ZnO tetrapods were also added into the bacterial culture to study their effects and the combined antimicrobial effects along with SAW agitation. Our results showed that when the SAW power was below a threshold (e.g., about 2.55 W in this study), the bacterial growth was apparently enhanced, whereas the further increase of SAW power to a high power caused inactivation of bacteria. Combination of thin film SAWs with ZnO tetrapods led to significantly decreased growth or inactivation for both E. coli and S. aureus, revealing their effectiveness for antimicrobial treatment. Mechanisms and effects of SAW interactions with bacterial solutions and ZnO tetrapods have been systematically discussed.

Acoustofluidic Diversity Achieved by Multiple Modes of Acoustic Waves Generated on Piezoelectric-Film-Coated Aluminum Sheets.

Excitation of multiple acoustic wave modes on a single chip is beneficial to implement diversified acoustofluidic functions. Conventional acoustic wave devices made of bulk LiNbO3 substrates generally generate few acoustic wave modes once the crystal-cut and electrode pattern are defined, limiting the realization of acoustofluidic diversity. In this paper, we demonstrated diversity of acoustofluidic behaviors using multiple modes of acoustic waves generated on piezoelectric-thin-film-coated aluminum sheets. Multiple acoustic wave modes were excited by varying the ratios between IDT pitch/wavelength and substrate thickness. Through systematic investigation of fluidic actuation behaviors and performances using these acoustic wave modes, we demonstrated fluidic actuation diversities using various acoustic wave modes and showed that the Rayleigh mode, pseudo-Rayleigh mode, and A0 mode of Lamb wave generally have better fluidic actuation performance than those of Sezawa mode and higher-order modes of Lamb wave, providing guidance for high-performance acoustofluidic actuation platform design. Additionally, we demonstrated diversified particle patterning functions, either on two sides of acoustic wave device or on a glass sheet by coupling acoustic waves into the glass using the gel. The pattern formation mechanisms were investigated through finite element simulations of acoustic pressure fields under different experimental configurations.

Surface Acoustic Wave-Enhanced Multi-View Acoustofluidic Rotation Cytometry (MARC) for Pre-Cytopathological Screening.

Cytopathology, crucial in disease diagnosis, commonly uses microscopic slides to scrutinize cellular abnormalities. However, processing high volumes of samples often results in numerous negative diagnoses, consuming significant time and resources in healthcare. To address this challenge, a surface acoustic wave-enhanced multi-view acoustofluidic rotation cytometry (MARC) technique is developed for pre-cytopathological screening. MARC enhances cellular morphology analysis through comprehensive and multi-angle observations and amplifies subtle cell differences, particularly in the nuclear-to-cytoplasmic ratio, across various cell types and between cancerous and normal tissue cells. By prioritizing MARC-screened positive cases, this approach can potentially streamline traditional cytopathology, reducing the workload and resources spent on negative diagnoses. This significant advancement enhances overall diagnostic efficiency, offering a transformative vision for cytopathological screening.

High-sensitivity narrow­band T-shaped cantilever Fabry-perot acoustic sensor for photoacoustic spectroscopy.

Photoacoustic spectroscopy (PAS) has been rapidly developed and applied to different detection scenarios. The acoustic pressure detection is an important part in the PAS system. In this paper, an ultrahigh sensitivity Fabry-Perot acoustic sensor with a T-shaped cantilever was proposed. To achieve the best acoustic pressure effect, the dimension of the cantilever structure was designed and optimized by finite element analysis using COMSOL Multiphysics. Simulation results showed that the sensitivity of such T-shaped cantilever was 1.5 times higher than that based on a rectangular cantilever, and the resonance frequency of T-shaped cantilever were able to modulate from 800 Hz to 1500 Hz by adjusting the multi-parameter characteristics. Experimental sensing results showed that the resonance frequency of T-shaped Fabry-Perot acoustic sensor was 1080 Hz, yielding a high sensitivity of 1.428 µm/Pa, with a signal-to-noise ratio (SNR) of 84.8 dB and a detectable pressure limit of 1.9 µPa/Hz1/2@1 kHz. We successfully used such acoustic sensor to measure acetylene (C2H2) concentration in the PAS. The sensitivity of PAS for C2H2 gas was 3.22 pm/ppm with a concentration range of 50 ppm ∼100 ppm, and the minimum detection limit was 24.91ppb.

Achieving consistency of flexible surface acoustic wave sensors with artificial intelligence.

Flexible surface acoustic wave technology has garnered significant attention for wearable electronics and sensing applications. However, the mechanical strains induced by random deformation of these flexible SAWs during sensing often significantly alter the specific sensing signals, causing critical issues such as inconsistency of the sensing results on a curved/flexible surface. To address this challenge, we first developed high-performance AlScN piezoelectric film-based flexible SAW sensors, investigated their response characteristics both theoretically and experimentally under various bending strains and UV illumination conditions, and achieved a high UV sensitivity of 1.71 KHz/(mW/cm²). To ensure reliable and consistent UV detection and eliminate the interference of bending strain on SAW sensors, we proposed using key features within the response signals of a single flexible SAW device to establish a regression model based on machine learning algorithms for precise UV detection under dynamic strain disturbances, successfully decoupling the interference of bending strain from target UV detection. The results indicate that under strain interferences from 0 to 1160 µÎµ the model based on the extreme gradient boosting algorithm exhibits optimal UV prediction performance. As a demonstration for practical applications, flexible SAW sensors were adhered to four different locations on spacecraft model surfaces, including flat and three curved surfaces with radii of curvature of 14.5, 11.5, and 5.8 cm. These flexible SAW sensors demonstrated high reliability and consistency in terms of UV sensing performance under random bending conditions, with results consistent with those on a flat surface.

Morin reverses P-glycoprotein-mediated multidrug-resistance in KBChR-8-5 cancer cell lines.

Multidrug resistance (MDR) during clinical chemotherapy for cancer has been considered a major obstacle to treatment efficacy. The involvement of adenosine triphosphate-binding cassette (ABC) transporters in the MDR mechanism significantly reduces the efficacy of chemotherapeutics. This study investigates the potential of morin, a dietary bioflavonoid, to overcome colchicine resistance in KBChR-8-5 MDR cells. The P-gp inhibitory activity by morin was measured by calcein-AM drug efflux assay. Western blot analysis was employed to evaluate P-gp messenger RNA and protein expressions following morin treatment. Flow cytometry analysis and acridine orange/ethidium bromide fluorescence staining were utilised to investigate the induction of apoptosis and cell cycle arrest upon treatment with morin and paclitaxel in combination. Additionally, polymerase chain reaction (PCR) array analysis was conducted to study the gene expression profiles related to MDR, apoptosis and cell cycle arrest during treatment with morin, paclitaxel or their combination. Morin exhibited a strong binding interaction with human P-gp. This was corroborated by drug efflux assays, which showed a reduction in P-gp efflux function with increasing morin concentration. Furthermore, morin and paclitaxel combination potentiated the induction of apoptosis and G2/M phase cell cycle arrest. Morin treatment significantly downregulated the gene expression of ABCB1 and P-gp membrane expressions in MDR cells. Additionally, PCR array gene expression analysis revealed that the combination treatment with morin and paclitaxel upregulated proapoptotic and cell cycle arrest genes while downregulating ABCB1 gene and antiapoptotic genes. Thus, morin effectively reversed paclitaxel resistance in KBChR-8-5 drug-resistant cancer cells and concluded that morin resensitized the paclitaxel resistance in KBChR8-5 drug-resistant cancer cells.

A nanonewton force sensor using a U-shape tapered microfiber interferometer.

Nanomechanical measurements, especially the detection of weak contact forces, play a vital role in many fields, such as material science, micromanipulation, and mechanobiology. However, it remains a challenging task to realize the measurement of ultraweak force levels as low as nanonewtons with a simple sensing configuration. In this work, an ultrasensitive all-fiber nanonewton force sensor structure based on a single-mode-tapered U-shape multimode-single-mode fiber probe is proposed and experimentally demonstrated with a limit of detection of ~5.4 nanonewtons. The use of the sensor is demonstrated by force measurement on a human hair sample to determine the spring constant of the hair. The results agree well with measurements using an atomic force microscope for the spring constant of the hair. Compared with other force sensors based on optical fiber in the literature, the proposed all-fiber force sensor provides a substantial advancement in the minimum detectable force possible, with the advantages of a simple configuration, ease of fabrication, and low cost.

Capillary wave tweezer.

Precise control of microparticle movement is crucial in high throughput processing for various applications in scalable manufacturing, such as particle monolayer assembly and 3D bio-printing. Current techniques using acoustic, electrical and optical methods offer precise manipulation advantages, but their scalability is restricted due to issues such as, high input powers and complex fabrication and operation processes. In this work, we introduce the concept of capillary wave tweezers, where mm-scale capillary wave fields are dynamically manipulated to control the position of microparticles in a liquid volume. Capillary waves are generated in an open liquid volume using low frequency vibrations (in the range of 10-100 Hz) to trap particles underneath the nodes of the capillary waves. By shifting the displacement nodes of the waves, the trapped particles are precisely displaced. Using analytical and numerical models, we identify conditions under which a stable control over particle motion is achieved. By showcasing the ability to dynamically control the movement of microparticles, our concept offers a simple and high throughput method to manipulate particles in open systems.

Open source board based acoustofluidic transwells for reversible disruption of the blood-brain barrier for therapeutic delivery.

BACKGROUND: Blood-brain barrier (BBB) is a crucial but dynamic structure that functions as a gatekeeper for the central nervous system (CNS). Managing sufficient substances across the BBB is a major challenge, especially in the development of therapeutics for CNS disorders. METHODS: To achieve an efficient, fast and safe strategy for BBB opening, an acoustofluidic transwell (AFT) was developed for reversible disruption of the BBB. The proposed AFT was consisted of a transwell insert where the BBB model was established, and a surface acoustic wave (SAW) transducer realized using open-source electronics based on printed circuit board techniques. RESULTS: In the AFT device, the SAW produced acousto-mechanical stimulations to the BBB model resulting in decreased transendothelial electrical resistance in a dose dependent manner, indicating the disruption of the BBB. Moreover, SAW stimulation enhanced transendothelial permeability to sodium fluorescein and FITC-dextran with various molecular weight in the AFT device. Further study indicated BBB opening was mainly attributed to the apparent stretching of intercellular spaces. An in vivo study using a zebrafish model demonstrated SAW exposure promoted penetration of sodium fluorescein to the CNS. CONCLUSIONS: In summary, AFT effectively disrupts the BBB under the SAW stimulation, which is promising as a new drug delivery methodology for neurodegenerative diseases.

High-precision prediction of blood glucose concentration utilizing Fourier transform Raman spectroscopy and an ensemble machine learning algorithm.

Raman spectroscopy has gained popularity in analyzing blood glucose levels due to its non-invasive identification and minimal interference from water. However, the challenge lies in how to accurately predict blood glucose concentrations in human blood using Raman spectroscopy. This paper researches a novel integrated machine learning algorithm called Bagging-ABC-ELM. The optimal input weights and biases of extreme learning machine (ELM) model are obtained by artificial bee colony (ABC) algorithm. The bagging algorithm is used to obtain a better the stability of the model and higher performance than ELM algorithm. The results show that the mean value of coefficient of determination is 0.9928, and root mean square error is 0.1928. Compared to other regression models, the Bagging-ABC-ELM model exhibited superior prediction accuracy, robustness, and generalization capability. The Bagging-ABC-ELM model presents a promising alternative for analyzing blood glucose levels in clinical and research settings.

5.7 GHz Ultrasensitive Shear Horizontal-Surface Acoustic Wave Humidity Sensor Based on LiNbO3/SiO2/SiC Heterostructures with a Sensitive Layer of Polyethyleneimine-SiO2 Nanocomposites.

Humidity sensing and water molecule monitoring have become hot research topics attributed to their potential applications in monitoring breathing/physiological conditions of humans, air conditioning in greenhouses, and soil moisture in agriculture. However, there is a huge challenge for highly sensitive and precision humidity detection with wireless and fast responsive capabilities. In this work, a hybrid/synergistic strategy was proposed using a LiNbO3/SiO2/SiC heterostructure to generate shear-horizontal (SH) surface acoustic waves (SAWs) and using a nanocomposite of polyethylenimine-silicon dioxide nanoparticles (PEI-SiO2 NPs) to form a sensitive layer, thus achieving an ultrahigh sensitivity of SAW humidity sensors. Ultrahigh frequencies (1∼15 GHz) of SAW devices were obtained on a high-velocity heterostructure of LiNbO3/SiO2/SiC. Among the multimodal wave modes, we selected SH waves for humidity sensing and achieved a high mass-sensitivity of 5383 MHz · mm2 · µg-1. With the PEI-SiO2 NP composite as the sensitive layer, an ultrahigh sensitivity of 2.02 MHz/% RH was obtained, which is two orders of magnitude higher than those of the conventional SAW humidity sensors (∼202.5 MHz frequency) within a humidity range of 20-80% RH.

Power-controlled acoustofluidic manipulation of microparticles.

Recently, surface acoustic wave (SAW) based acoustofluidic separation of microparticles and cells has attracted increasing interest due to accuracy and biocompatibility. Precise control of the input power of acoustofluidic devices is essential for generating optimum acoustic radiation force to manipulate microparticles given their various parameters including size, density, compressibility, and moving velocity. In this work, an acoustophoretic system is developed by employing SAW based interdigital electrode devices. Power meters are applied to closely monitor the incident and reflected powers of the SAW device, which are associated with the separation efficiency. There exists a range of input powers to migrate the microparticles to the pressure node due to their random locations when entering the SAW field. Theoretical analysis is performed to predict a proper input power to separate mixtures of polystyrene microspheres, and the end lateral position of microspheres being acoustically separated. The separation efficiency of four sizes of microspheres, including 20 µm, 15 µm, 10 µm, and 5 µm, is calculated and compared with experimental results, which suggest the input power for separating the mixture of these microspheres. The study provides a practical guidance on operating SAW devices for bioparticle separation using the incident power as a control parameter.

The novel π-d conjugated TM2B3N3S6 (TM = Mo, Ti and W) monolayers as highly active single-atom catalysts for electrocatalytic synthesis of ammonia.

Recently, single-atom catalysts (SACs) are receiving significant attention in electrocatalysis fields due to their excellent specific activities and extremely high atomic utilization ratio. Effective loading of metal atoms and high stability of SACs increase the number of exposed active sites, thus significantly improving their catalytic efficiency. Herein, we proposed a series (29 in total) of two-dimensional (2D) conjugated structures of TM2B3N3S6 (TM means those 3d to 5d transition metals) and studied the performance as single-atom catalysts for nitrogen reduction reaction (NRR) using density functional theory (DFT). Results show that TM2B3N3S6 (TM = Mo, Ti and W) monolayers have superior performance for ammonia synthesis with low limiting potentials of -0.38, -0.53 and -0.68 V, respectively. Among them, the Mo2B3N3S6 monolayer shows the best catalytic performance of NRR. Meanwhile, the π conjugated B3N3S6 rings undergo coordinated electron transfer with the d orbitals of TM to exhibit good chargeability, and these TM2B3N3S6 monolayers activate isolated N2 according to the "acceptance-donation" mechanism. We have also verified the good stability (i.e., Ef < 0, and Udiss > 0) and high selectivity (Ud = -0.03, 0.01 and 0.10 V, respectively) of the above four types of monolayers for NRR over hydrogen evolution reaction (HER). The NRR activities have been clarified by multiple-level descriptors (ΔG*N2H, ICOHP, and Ɛd) in the terms of basic characteristics, electronic property, and energy. Moreover, the aqueous solution can promote the NRR process, leading to the reduction of ΔGPDS from 0.38 eV to 0.27 eV for the Mo2B3N3S6 monolayer. However, the TM2B3N3S6 (TM = Mo, Ti and W) also showed excellent stability in aqueous phase. This study proves that the π-d conjugated monolayers of TM2B3N3S6 (TM = Mo, Ti and W) as electrocatalysts show great potentials for the nitrogen reduction.

Fundamentals of Monitoring Condensation and Frost/Ice Formation in Cold Environments Using Thin-Film Surface-Acoustic-Wave Technology.

Moisture condensation, fogging, and frost or ice formation on structural surfaces cause severe hazards in many industrial components such as aircraft wings, electric power lines, and wind-turbine blades. Surface-acoustic-wave (SAW) technology, which is based on generating and monitoring acoustic waves propagating along structural surfaces, is one of the most promising techniques for monitoring, predicting, and also eliminating these hazards occurring on these surfaces in a cold environment. Monitoring condensation and frost/ice formation using SAW devices is challenging in practical scenarios including sleet, snow, cold rain, strong wind, and low pressure, and such a detection in various ambient conditions can be complex and requires consideration of various key influencing factors. Herein, the influences of various individual factors such as temperature, humidity, and water vapor pressure, as well as combined or multienvironmental dynamic factors, are investigated, all of which lead to either adsorption of water molecules, condensation, and/or frost/ice in a cold environment on the SAW devices. The influences of these parameters on the frequency shifts of the resonant SAW devices are systematically analyzed. Complemented with experimental studies and data from the literature, relationships among the frequency shifts and changes of temperature and other key factors influencing the dynamic phase transitions of water vapor on SAW devices are investigated to provide important guidance for icing detection and monitoring.

Progress in wearable acoustical sensors for diagnostic applications.

With extensive and widespread uses of miniaturized and intelligent wearable devices, continuously monitoring subtle spatial and temporal changes in human physiological states becomes crucial for daily healthcare and professional medical diagnosis. Wearable acoustical sensors and related monitoring systems can be comfortably applied onto human body with a distinctive function of non-invasive detection. This paper reviews recent advances in wearable acoustical sensors for medical applications. Structural designs and characteristics of the structural components of wearable electronics, including piezoelectric and capacitive micromachined ultrasonic transducer (i.e., pMUT and cMUT), surface acoustic wave sensors (SAW) and triboelectric nanogenerators (TENGs) are discussed, along with their fabrication techniques and manufacturing processes. Diagnostic applications of these wearable sensors for detection of biomarkers or bioreceptors and diagnostic imaging have further been discussed. Finally, main challenges and future research directions in these fields are highlighted.

Highly-Exposed Co-CoO Derived from Nanosized ZIF-67 on N-Doped Porous Carbon Foam as Efficient Electrocatalyst for Zinc-Air Battery.

Non-precious-metal based electrocatalysts with highly-exposed and well-dispersed active sites are crucially needed to achieve superior electrocatalytic performance for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) toward zinc-air battery (ZAB). Herein, Co-CoO heterostructures derived from nanosized ZIF-67 are densely-exposed and strongly-immobilized onto N-doped porous carbon foam (NPCF) through a self-sacrificial pyrolysis strategy. Benefited from the high exposure of Co-CoO heterostructures and the favorable mass and electron transfer ability of NPCF, the Co-CoO/NPCF electrocatalyst exhibits remarkable performance for both ORR (E1/2  = 0.843 V vs RHE) and OER (Ej = 10 mA cm-2  = 1.586 V vs RHE). Further application of Co-CoO/NPCF as the air-cathode in rechargeable ZAB achieves superior performance for liquid-state ZAB (214.1 mW cm-2 and 600 cycles) and flexible all-solid-state ZAB (93.1 mW cm-2 and 140 cycles). Results from DFT calculations demonstrate that the electronic metal-support interactions between Co-CoO and NPCF via abundant C-Nx sites is favorable for electronic structure modulation, accounting for the remarkable performance.