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Highlights Introduce the role of bioelectricity and the endogenous electric field in bone tissue and summarize different techniques to electrically stimulate cells and tissue. Highlight the latest progress in exploring electroactive hybrid biomaterials as well as self-powered systems such as triboelectric and piezoelectric-based nanogenerators and photovoltaic cell-based devices in bone tissue engineering. Emphasize the significance of simulating the target tissue’s electrophysiological microenvironment and propose the opportunities and challenges faced by electroactive hybrid biomaterials and self-powered bioelectronics.

Abstract The severe mismatch between solid bioelectronics and dynamic biological tissues has posed enduring challenges in the biomonitoring community. Here, we developed a reconfigurable liquid cardiac sensor capable of adapting to dynamic biological tissues, facilitating ambulatory cardiac monitoring unhindered by motion artifacts or interference from other biological activities. We employed an ultrahigh-resolution 3D scanning technique to capture tomographic images of the skin on the wrist. Then, we established a theoretical model to gain a deep understanding of the intricate interaction between our reconfigurable sensor and dynamic biological tissues. To properly elucidate the advantages of this sensor, we conducted cardiac monitoring alongside benchmarks such as the electrocardiogram. The liquid cardiac sensor was demonstrated to produce stable signals of high quality (23.1 dB) in ambulatory settings.

In order to investigate the non-Darcy seepage characteristics of crushed gangue filling in the goaf under the action of the overlying rock layer, the self-developed crushed rock seepage test system is utilized to carry out uniaxial lateral limit compression and seepage tests using the steady state permeability method on four kinds of pressurized crushed gangue with different initial grades, and to obtain the porosity, fractal dimensions, permeability, Euler’s number, and the energy dissipation law in the non-Darcy seepage process of the crushed gangue under different effective stress conditions. The study shows that: under high osmotic pressure and high porosity, the fluid flow rate is faster, resulting in the E value is much larger than 0.1, at this time, it shows the characteristics of high-speed non-Darcy seepage; the change process of porosity with the effective stress can be divided into two phases, when the n value tends to be 0.4, the particles of each size interval have a good mass ratio, and it is easy to be compacted; with the increase of fractal dimension, the degree of particle fragmentation is increased, and the permeability of the sample is linearly decreasing; it is deduced that there is an inverse relationship between the Euler number and the flow rate, and the momentum transfer of the fluid gradually decreases with the increase of flow rate.

With characteristics and advantages of functional composite materials, they are commendably adopted in numerous fields especially in oxygen electrocatalysis, which is due to the significant synergies between various components. Herein, a novel bifunctional oxygen electrocatalyst (Co-CNT@COF-Pyr) has been synthesized through in-situ growth of covalent organic frameworks (COFs) layers on the outer surface of highly conductive carbon nanotubes (CNTs) followed by coordination with Co(Ⅱ). For electrocatalytic OER, Co-CNT@COF-Pyr reveals a low overpotential (438 ​mV) in alkaline electrolyte (1.0 ​M aqueous solution of KOH) with a current density of 10 ​mA ​cm−2, which is comparable to most discovered COF-based catalysts. For electrocatalytic ORR, Co-CNT@COF-Pyr exhibits a low H2O2 yield range (9.0 ​%–10.1 ​%) and a reaction pathway close to 4e− (n ​= ​3.82–3.80) in alkaline electrolyte (0.1 ​M aqueous solution of KOH) within the test potential range of 0.1–0.6 ​V vs. RHE, which is superior to most reported COF-based catalysts. Hence, this research could not only offer an innovative insight into the construction of composites, but also facilitate the practical application of renewable fuel cells, closed water cycle, and rechargeable metal-air batteries.

Abstract Light‐sheet fluorescence microscopy (LSFM) introduces fast scanning of biological phenomena with deep photon penetration and minimal phototoxicity. This advancement represents a significant shift in 3‐D imaging of large‐scale biological tissues and 4‐D (space + time) imaging of small live animals. The large data associated with LSFM require efficient imaging acquisition and analysis with the use of artificial intelligence (AI)/machine learning (ML) algorithms. To this end, AI/ML‐directed LSFM is an emerging area for multiorgan imaging and tumor diagnostics. This review will present the development of LSFM and highlight various LSFM configurations and designs for multiscale imaging. Optical clearance techniques will be compared for effective reduction in light scattering and optimal deep‐tissue imaging. This review will further depict a diverse range of research and translational applications, from small live organisms to multiorgan imaging to tumor diagnosis. In addition, this review will address AI/ML‐directed imaging reconstruction, including the application of convolutional neural networks (CNNs) and generative adversarial networks (GANs). In summary, the advancements of LSFM have enabled effective and efficient post‐imaging reconstruction and data analyses, underscoring LSFM's contribution to advancing fundamental and translational research.

Abstract Early‐stage nonalcoholic fatty liver disease (NAFLD) is a silent condition, with most cases going undiagnosed, potentially progressing to liver cirrhosis and cancer. A non‐invasive and cost‐effective detection method for early‐stage NAFLD detection is a public health priority but challenging. In this study, an adhesive, soft on‐skin sensor with low electrode‐skin contact impedance for early‐stage NAFLD detection is fabricated. A method is developed to synthesize platinum nanoparticles and reduced graphene quantum dots onto the on‐skin sensor to reduce electrode‐skin contact impedance by increasing double‐layer capacitance, thereby enhancing detection accuracy. Furthermore, an attention‐based deep learning algorithm is introduced to differentiate impedance signals associated with early‐stage NAFLD in high‐fat‐diet‐fed low‐density lipoprotein receptor knockout (Ldlr−/−) mice compared to healthy controls. The integration of an adhesive, soft on‐skin sensor with low electrode‐skin contact impedance and the attention‐based deep learning algorithm significantly enhances the detection accuracy for early‐stage NAFLD, achieving a rate above 97.5% with an area under the receiver operating characteristic curve (AUC) of 1.0. The findings present a non‐invasive approach for early‐stage NAFLD detection and display a strategy for improved early detection through on‐skin electronics and deep learning.

Abstract Stretchable displays that combine light-emitting capabilities with mechanical compliance are essential building blocks of next-generation wearable electronics. However, their widespread applications are currently limited by complex device architecture, limited pixel density, and immature fabrication processes. In this study, we present the device design and material developments of intrinsically stretchable light-emitting drawing displays that can show arbitrary hand-drawing features. The alternating-current electroluminescent display uses a simplified architecture comprising coplanar interdigitated liquid metal electrodes, an electroluminescent layer, and a dielectric encapsulation layer. Ink patterns on the device are coupled with the interdigitated electrodes under alternating voltage stimulations, generating localized electric fields for bright emissions. Various inks are prepared for painting, stamping, and stencil printing. Arbitrary luminous features on the devices can be either long-lasting or transient in characteristics. These skin-like devices are made entirely of compliant materials that can withstand bending, twisting, and stretching manipulations. Due to the excellent mechanical deformability, the drawing displays can be conformally laminated on the skin as body-integrated optoelectronic communication devices for graphic information.

Abstract Plasma etching treatment is an effective strategy to improve the electrocatalytic activity, but the improvement mechanism is still unclear. In this work, a nitrogen‐doped carbon nanotube‐encased iron nanoparticles (Fe@NCNT) catalyst is synthesized as the model catalyst, followed by plasma etching treatment with different parameters. The electrocatalytic activity improvement mechanism of the plasma etching treatment is revealed by combining the physicochemical characterizations and electrochemical results. As a result, highly active metal–nitrogen species introduced by nitrogen plasma etching treatment are recognized as the main contribution to the improved electrocatalytic activity, and the defects induced by plasma etching treatment also contribute to the improvement of the electrocatalytic activity. In addition, the prepared catalyst also demonstrates superior ORR activity and stability than the commercial Pt/C catalyst.

Abstract The characterization of atherosclerotic plaques to predict their vulnerability to rupture remains a diagnostic challenge. Despite existing imaging modalities, none have proven their abilities to identify metabolically active oxidized low‐density lipoprotein (oxLDL), a marker of plaque vulnerability. To this end, we developed a machine learning‐directed electrochemical impedance spectroscopy (EIS) platform to analyze oxLDL‐rich plaques, with immunohistology serving as the ground truth. We fabricated the EIS sensor by affixing a six‐point microelectrode configuration onto a silicone balloon catheter and electroplating the surface with platinum black (PtB) to improve the charge transfer efficiency at the electrochemical interface. To demonstrate clinical translation, we deployed the EIS sensor to the coronary arteries of an explanted human heart from a patient undergoing heart transplant and interrogated the atherosclerotic lesions to reconstruct the 3D EIS profiles of oxLDL‐rich atherosclerotic plaques in both right coronary and left descending coronary arteries. To establish effective generalization of our methods, we repeated the reconstruction and training process on the common carotid arteries of an unembalmed human cadaver specimen. Our findings indicated that our DenseNet model achieves the most reliable predictions for metabolically vulnerable plaque, yielding an accuracy of 92.59% after 100 epochs of training.

Abstract Since the initial discovery of Ti3C2 a decade ago, there has been a significant surge of interest in 2D MXenes and MXene‐based composites. This can be attributed to the remarkable intrinsic properties exhibited by MXenes, including metallic conductivity, abundant functional groups, unique layered microstructure, and the ability to control interlayer spacing. These properties contribute to the exceptional electrical and mechanical performance of MXenes, rendering them highly suitable for implementation as candidate materials in flexible and wearable energy storage devices. Recently, a substantial number of novel research has been dedicated to exploring MXene‐based flexible materials with diverse functionalities and specifically designed structures, aiming to enhance the efficiency of energy storage systems. In this review, a comprehensive overview of the synthesis and fabrication strategies employed in the development of these diverse MXene‐based materials is provided. Furthermore, an in‐depth analysis of the energy storage applications exhibited by these innovative flexible materials, encompassing supercapacitors, Li‐ion batteries, Li–S batteries, and other potential avenues, is conducted. In addition to presenting the current state of the field, the challenges encountered in the implementation of MXene‐based flexible materials are also highlighted and insights are provided into future research directions and prospects.

Abstract Highly stretchable and robust strain sensors are rapidly emerging as promising candidates for a diverse of wearable electronics. The main challenge for the practical application of wearable electronics is the energy consumption and device aging. Energy consumption mainly depends on the conductivity of the sensor, and it is a key factor in determining device aging. Here, we design a liquid metal (LM)‐embedded hydrogel as a sensing material to overcome the barrier of energy consumption and device aging of wearable electronics. The sensing material simultaneously exhibits high conductivity (up to 22 S m−1), low elastic modulus (23 kPa), and ultrahigh stretchability (1500%) with excellent robustness (consistent performance against 12 000 mechanical cycling). A motion monitoring system is composed of intrinsically soft LM‐embedded hydrogel as sensing material, a microcontroller, signal‐processing circuits, Bluetooth transceiver, and self‐organizing map developed software for the visualization of multi‐dimensional data. This system integrating multiple functions including signal conditioning, processing, and wireless transmission achieves monitor hand gesture as well as sign‐to‐verbal translation. This approach provides an ideal strategy for deaf‐mute communicating with normal people and broadens the application of wearable electronics.

Over the last few decades, electrical impedance-based sensors have been investigated for clinical translation to detect changes in tissue conductivities, including cardiac output and pulmonary function. Recently, electrochemical impedance spectroscopy (EIS) provides metabolic measurements that occur at the electrode-tissue interface, and the 3-D EIS can be reconstructed to generate electrical impedance tomography (EIT) for detecting the impedimetric properties of the vascular wall or fatty liver disease. In both EIS and EIT applications, the electrochemical properties of the interface electrodes are essential to address the signal-to-noise ratio or sensitivity of measurements in the biological environment. To enhance the conductive properties, we will survey a series of carbon-based nanomaterials as the emerging candidates for coating the electrodes of bioimpedance sensors. In this review, we will provide a theoretical background on impedance-based measurements and highlight the current state of EIS and EIT, including their applications for cancer screening and detection of vulnerable atherosclerotic plaques. Next, we will focus on the strengths of different nanomaterials when used as an electrode coating to optimize charge transfer across the electric double layers and to enhance measurement sensitivity. We will also identify some unmet clinical needs, such as the ability to adapt to different hemodynamic conditions and blood vessel geometries, that can be realized by the novel biomaterials for the future EIS-based sensors.

With the rapid development of multimedia technology, personnel verification systems have become increasingly important in the security field and identity verification. However, unimodal verification systems have performance bottlenecks in complex scenarios, thus triggering the need for multimodal feature fusion methods. The main problem with audio–visual multimodal feature fusion is how to effectively integrate information from different modalities to improve the accuracy and robustness of the system for individual identity. In this paper, we focus on how to improve multimodal person verification systems and how to combine audio and visual features. In this study, we use pretrained models to extract the embeddings from each modality and then perform fusion model experiments based on these embeddings. The baseline approach in this paper involves taking the fusion feature and passing it through a fully connected (FC) layer. Building upon this baseline, we propose three fusion models based on attentional mechanisms: attention, gated, and inter–attention. These fusion models are trained on the VoxCeleb1 development set and tested on the evaluation sets of the VoxCeleb1, NIST SRE19, and CNC-AV datasets. On the VoxCeleb1 dataset, the best system performance achieved in this study was an equal error rate (EER) of 0.23% and a detection cost function (minDCF) of 0.011. On the evaluation set of NIST SRE19, the EER was 2.60% and the minDCF was 0.283. On the evaluation set of the CNC-AV set, the EER was 11.30% and the minDCF was 0.443. These experimental results strongly demonstrate that the proposed fusion method can significantly improve the performance of multimodal character verification systems.

While selective CO2 reduction is crucial for its removal from the environment, the presence of O2 hinders this process. Here authors show CO2 photoreduction in the presence of O2 by incorporating Pd(II) sites into a coordination polymer on TiO2 to selectively adsorb CO2.

Abstract Liquid metal represents a highly conductive and inherently deformable conductor for the development of stretchable electronics. The widespread implementations of liquid metal towards functional sensors and circuits are currently hindered by the lack of a facile and scalable patterning approach. In this study, we report a fully solution-based process to generate patterned features of the liquid metal conductor. The entire process is carried out under ambient conditions and is generally compatible with various elastomeric substrates. The as-prepared liquid metal feature exhibits high resolution (100 μm), excellent electrical conductivity (4.15 × 104S cm−1), ultrahigh stretchability (1000% tensile strain), and mechanical durability. The practical suitability is demonstrated by the heterogeneous integration of light-emitting diode (LED) chips with liquid metal interconnects for a stretchable and wearable LED array. The solution-based technique reported here is the enabler for the facile patterning of liquid metal features at low cost, which may find a broad range of applications in emerging fields of epidermal sensors, wearable heaters, advanced prosthetics, and soft robotics.

Renewable CO2 conversion to useful products presents a sustainable, carbon-neutral method to limit climate change, yet few materials can perform this complex chemistry. Here, authors prepare a polymer-TiO2-graphene composite that can take up CO2 and convert it to CH4 using light and water.

Probiotics are gaining attention due to their functions of regulating the intestinal barrier and promoting human health. The production of bacteriocins is one of the important factors for probiotics to exert beneficial properties. This study aimed to screen bacteriocin-producing Lactiplantibacillus plantarum and evaluate the probiotic potential in vitro. It was found that L. plantarum Q7, L. plantarum F3-2 and L. plantarum YRL45 could produce bacteriocins and inhibit common intestinal pathogens. These three strains had probiotic potential with tolerance to the gastrointestinal environmental and colonization in the gut, and exhibited various degrees of anti-inflammatory activity and tight junction function in the intestinal barrier. Particularly, L. plantarum YRL45 could significantly (p < 0.05) reduce the increase in nitric oxide (NO), prostaglandin E2 (PGE2), necrosis factor-α (TNF-α) and interleukin-1β (IL-1β) induced by lipopolysaccharide (LPS), thereby easing inflammatory response. L. plantarum F3-2 could remarkably (p < 0.05) up-regulate the expression levels of ZO-1, Occludin and Claudin-1 in intestinal epithelial injured cells, which was conducive to protecting the intestinal barrier. These findings provided fundamental information about the probiotic properties of bacteriocin-producing L. plantarum, which suggested that L. plantarum Q7, L. plantarum F3-2 and L. plantarum YRL45 had the potential to be used as novel probiotic strains.

This study was conducted to compare the microbiome and metabolome differences in the colon lumen from two pig breeds with different genetic backgrounds. Fourteen weaned piglets at 30 days of age, including seven Landrace piglets (a lean-type pig breed with a fast growth rate) and seven Meihua piglets (a fatty-type Chinese local pig breed with a slow growth rate), were fed the same diets for 35 days. Untargeted metabolomics analyses showed that a total of 401 metabolites differed between Landrace and Meihua. Seventy of these 401 metabolites were conclusively identified. Landrace accumulated more short-chain fatty acids (SCFAs) and secondary bile acids in the colon lumen. Moreover, expression of the SCFAs transporter (solute carrier family 5 member 8, SLC5A8) and receptor (G protein-coupled receptor 41, GPR41) in the colon mucosa was higher, while the bile acids receptor (farnesoid X receptor, FXR) had lower expression in Landrace compared to Meihua. The relative abundances of 8 genera and 16 species of bacteria differed significantly between Landrace and Meihua, and were closely related to the colonic concentrations of bile acids or SCFAs based on Pearson's correlation analysis. Collectively, our results demonstrate for the first time that there were differences in the colonic microbiome and metabolome between Meihua and Landrace piglets, with the most profound disparity in production of SCFAs and secondary bile acids.