Early systemic anticoagulation reduces hospital readmission in acute necrotizing pancreatitis patients: A retrospective cohort study.

BACKGROUND: Early systemic anticoagulation (SAC) is a common practice in acute necrotizing pancreatitis (ANP), and its impact on in-hospital clinical outcomes had been assessed. However, whether it affects long-term outcomes is unknown. This study aimed to evaluate the effect of SAC on 90-day readmission and other long-term outcomes in ANP patients. METHODS: During January 2013 and December 2018, ANP patients admitted within 7 days from the onset of abdominal pain were screened. The primary outcome was 90-day readmission after discharge. Cox proportional-hazards regression model and mediation analysis were used to define the relationship between early SAC and 90-day readmission. RESULTS: A total of 241 ANP patients were enrolled, of whom 143 received early SAC during their hospitalization and 98 did not. Patients who received early SAC experienced a lower incidence of splanchnic venous thrombosis (SVT) [risk ratio (RR) = 0.40, 95% CI: 0.26-0.60, P < 0.01] and lower 90-day readmission with an RR of 0.61 (95% CI: 0.41-0.91, P = 0.02) than those who did not. For the quality of life, patients who received early SAC had a significantly higher score in the subscale of vitality (P = 0.03) while the other subscales were all comparable between the two groups. Multivariable Cox regression model showed that early SAC was an independent protective factor for 90-day readmission after adjusting for potential confounders with a hazard ratio of 0.57 (95% CI: 0.34-0.96, P = 0.04). Mediation analysis showed that SVT mediated 37.0% of the early SAC-90-day readmission causality. CONCLUSIONS: The application of early SAC may reduce the risk of 90-day readmission in the survivors of ANP patients, and reduced SVT incidence might be the primary contributor.

Multienzyme-Like Nanozyme Encapsulated Ocular Microneedles for Keratitis Treatment.

Keratitis, an inflammation of the cornea caused by bacterial or fungal infections, is one of the leading causes of severe visual disability and blindness. Keratitis treatment requires both the prevention of infection and the reduction of inflammation. However, owing to their limited therapeutic functions, in addition to the ocular barrier, existing conventional medications are characterized by poor efficacy and low bioavailability, requiring high dosages or frequent topical treatment, which represents a burden on patients and increases the risk of side effects. In this study, manganese oxide nanocluster-decorated graphdiyne nanosheets (MnOx/GDY) are developed as multienzyme-like nanozymes for the treatment of infectious keratitis and loaded into hyaluronic acid and polymethyl methacrylate-based ocular microneedles (MGMN). MGMN not only exhibits antimicrobial and anti-inflammatory effects owing to its multienzyme-like activities, including oxidase, peroxidase, catalase, and superoxide dismutase mimics but also crosses the ocular barrier and shows increased bioavailability via the microneedle system. Moreover, MGMN is demonstrated to eliminate pathogens, prevent biofilm formation, reduce inflammation, alleviate ocular hypoxia, and promote the repair of corneal epithelial damage in in vitro, ex vivo, and in vivo experiments, thus providing a better therapeutic effect than commercial ophthalmic voriconazole, with no obvious microbial resistance or cytotoxicity.

Enhanced recovery after surgery in congenital duodenal obstruction.

BACKGROUND: The present study aims to explore the clinical application of enhanced recovery after surgery (ERAS) in pediatric patients with congenital upper gastrointestinal obstruction (CUGIO). METHODS: A total of 82 pediatric patients with CUGIO admitted to the neonatal intensive care unit in Kunming Children's Hospital between June 2017 and June 2021 were enrolled in the present study and divided into two groups: the ERAS group (n = 46) and the control group (n = 36). The ERAS management mode was adopted in the ERAS group, and the conventional perioperative management mode was adopted in the control group. RESULTS: In the ERAS group and the control group, the time to the first postoperative bowel movement was 49.2 ± 16.6 h and 58.4 ± 18.8 h, respectively, and the time to the first postoperative feeding was 79 ± 7.1 h and 125.2 ± 8.3 h, respectively. The differences in the above two indicators between the two groups were statistically significant (P < 0.05). In the ERAS group, the days of parenteral nutrition and the length of hospital stay were 14.5 ± 2.3 d and 18.8 ± 6.4 d, respectively. In the control group, 17.6 ± 2.2 d and 23.1 ± 8.1 d, respectively. The differences in these two indicators between the two groups were statistically significant (P < 0.05). CONCLUSION: The ERAS management model had a positive effect on early postoperative recovery in pediatric patients with CUGIO.

Research on the Performance of Self-Made Open-Cathode Fuel Cell Stacks under Different Operating Conditions.

The traditional fuel cell power system requires external ventilation and humidification systems for both the anode and cathode, which not only increases the application cost but also restrict its widespread use. In order to further enhance the applicability and reduce the operating costs of fuel cell power systems, this paper investigates the open-cathode proton exchange membrane fuel cell power system. This approach not only lowers the cost but also reduces the weight of the power system, enabling its potential application in a wider range of vehicles. In this study, two versions of the open-cathode fuel cell stacks were developed and performance and stability tests were conducted under various operating conditions. Additionally, tests were carried out with different materials of carbon paper to find a balance between performance and stability. Through the research presented in this paper, the application scope of fuel cells has been expanded, providing valuable insights for their further development.

X3DFast model for classifying dairy cow behaviors based on a two-pathway architecture.

Behavior is one of the important factors reflecting the health status of dairy cows, and when dairy cows encounter health problems, they exhibit different behavioral characteristics. Therefore, identifying dairy cow behavior not only helps in assessing their physiological health and disease treatment but also improves cow welfare, which is very important for the development of animal husbandry. The method of relying on human eyes to observe the behavior of dairy cows has problems such as high labor costs, high labor intensity, and high fatigue rates. Therefore, it is necessary to explore more effective technical means to identify cow behaviors more quickly and accurately and improve the intelligence level of dairy cow farming. Automatic recognition of dairy cow behavior has become a key technology for diagnosing dairy cow diseases, improving farm economic benefits and reducing animal elimination rates. Recently, deep learning for automated dairy cow behavior identification has become a research focus. However, in complex farming environments, dairy cow behaviors are characterized by multiscale features due to large scenes and long data collection distances. Traditional behavior recognition models cannot accurately recognize similar behavior features of dairy cows, such as those with similar visual characteristics, i.e., standing and walking. The behavior recognition method based on 3D convolution solves the problem of small visual feature differences in behavior recognition. However, due to the large number of model parameters, long inference time, and simple data background, it cannot meet the demand for real-time recognition of dairy cow behaviors in complex breeding environments. To address this, we developed an effective yet lightweight model for fast and accurate dairy cow behavior feature learning from video data. We focused on four common behaviors: standing, walking, lying, and mounting. We recorded videos of dairy cow behaviors at a dairy farm containing over one hundred cows using surveillance cameras. A robust model was built using a complex background dataset. We proposed a two-pathway X3DFast model based on spatiotemporal behavior features. The X3D and fast pathways were laterally connected to integrate spatial and temporal features. The X3D pathway extracted spatial features. The fast pathway with R(2 + 1)D convolution decomposed spatiotemporal features and transferred effective spatial features to the X3D pathway. An action model further enhanced X3D spatial modeling. Experiments showed that X3DFast achieved 98.49% top-1 accuracy, outperforming similar methods in identifying the four behaviors. The method we proposed can effectively identify similar dairy cow behaviors while improving inference speed, providing technical support for subsequent dairy cow behavior recognition and daily behavior statistics.

Research on Robot Grasping Based on Deep Learning for Real-Life Scenarios.

The application of robots, especially robotic arms, has been primarily focused on the industrial sector due to their relatively low level of intelligence. However, the rapid development of deep learning has provided a powerful tool for conducting research on highly intelligent robots, thereby offering tremendous potential for the application of robotic arms in daily life scenarios. This paper investigates multi-object grasping in real-life scenarios. We first analyzed and improved the structural advantages and disadvantages of convolutional neural networks and residual networks from a theoretical perspective. We then constructed a hybrid grasping strategy prediction model, combining both networks for predicting multi-object grasping strategies. Finally, we deployed the trained model in the robot control system to validate its performance. The results demonstrate that both the model prediction accuracy and the success rate of robot grasping achieved by this study are leading in terms of performance.

Boosting charge separation in graphdiyne quantum dots/hollow tubular carbon nitride heterojunction for water pollutant degradation.

Non-desirable solar energy absorption and poor charge transfer efficiency are two problems that limit the peroxymonosulfate (PMS) photocatalytic techniques. Herein, a metal-free boron-doped graphdiyne quantum dot (BGDs) modified hollow tubular g-C3N4 photocatalyst (BGD/TCN) was synthesized to activate PMS and achieved effective space separation of carriers for degradation of bisphenol A. With 0.5 mM PMS, the degradation rate of bisphenol A (20 ppm) was 0.0634 min-1, 3.7-fold higher than that of TCN itself. The roles of BGDs in the distribution of electrons and photocatalytic property were well identified by experiments and density functional theory (DFT) calculations. The possible degradation intermediate products of bisphenol A were monitored by mass spectrometer and demonstrated to be nontoxic using ecological structure activity relationship modeling (ECOSAR). Finally, this newly-designed material was successfully applied in actual water bodies, which further renders its promising prospect for actual water remediation.

The significance of spread through air spaces in the prognostic assessment model of stage I lung adenocarcinoma and the exploration of its invasion mechanism.

PURPOSE: Spread through air spaces (STAS) is a crucial invasive mode of lung cancer and has been shown to be associated with early recurrence and metastasis. We aimed to develop a prognostic risk assessment model for stage I lung adenocarcinoma based on STAS and other pathological features and to explore the potential relationship between CXCL-8, Smad2, Snail, and STAS. METHODS: 312 patients who underwent surgery at Harbin Medical University Cancer Hospital with pathologically diagnosed stage I lung adenocarcinoma were reviewed in the study. STAS and other pathological features were identified by H&E staining, and a prognostic risk assessment model was established. The expression levels of CXCL8, Smad2, and Snail were determined by immunohistochemistry. RESULTS: The nomogram was established based on age, smoking history, STAS, tumor lymphocyte infiltration, tissue subtype, nuclear grade, and tumor size. The C-index for DFS was (training set 0.84 vs validation set 0.77) and for OS was (training set 0.83 vs validation set 0.78). Decision curve analysis showed that the model constructed has a better net benefit than traditional reporting. The prognostic risk score validated the risk stratification value for stage I lung adenocarcinoma. STAS was an important prognostic factor associated with stronger invasiveness and higher expression of CXCL8, Smad2, and Snail. CXCL8 was associated with poorer DFS and OS. CONCLUSIONS: We developed and validated a survival risk assessment model and the prognostic risk score formula for stage I lung adenocarcinoma. Additionally, we found that CXCL8 could be used as a potential biomarker for STAS and poor prognosis, and its mechanism may be related to EMT.

MafB-restricted local monocyte proliferation precedes lung interstitial macrophage differentiation.

Resident tissue macrophages (RTMs) are differentiated immune cells that populate distinct niches and exert important tissue-supportive functions. RTM maintenance is thought to rely either on differentiation from monocytes or on RTM self-renewal. Here, we used a mouse model of inducible lung interstitial macrophage (IM) niche depletion and refilling to investigate the development of IMs in vivo. Using time-course single-cell RNA-sequencing analyses, bone marrow chimeras and gene targeting, we found that engrafted Ly6C+ classical monocytes proliferated locally in a Csf1 receptor-dependent manner before differentiating into IMs. The transition from monocyte proliferation toward IM subset specification was controlled by the transcription factor MafB, while c-Maf specifically regulated the identity of the CD206+ IM subset. Our data provide evidence that, in the mononuclear phagocyte system, the ability to proliferate is not merely restricted to myeloid progenitor cells and mature RTMs but is also a tightly regulated capability of monocytes developing into RTMs in vivo.

Ultrasound activatable microneedles for bilaterally augmented sono-chemodynamic and sonothermal antibacterial therapy.

Chemodynamic therapy (CDT) employs Fenton catalysts to kill bacteria by converting hydrogen peroxide (H2O2) into toxic hydroxyl radical (•OH). Among them, Fenton-type metal peroxide nanoparticles fascinate nanomaterials with intriguing physiochemical properties, but research on this antibacterial agent is still in its infancy. Herein, a distinct CuO2/TiO2 heterostructure constituted of ultrasmall copper peroxide (CuO2) nanoclusters and sonosensitized ultrathin oxygen vacancy-rich porous titanium oxide (OV-TiO2) nanosheets was developed and was incorporated into microneedles for bilaterally augmented sono-chemodynamic and sonothermal antibacterial therapy. Engineering CuO2 nanoclusters on the surface of TiO2 nanosheets not only endows the Fenton catalytic activity for sono-chemodynamic therapy (SCDT), but also improves the sonodynamic and sonothermal performance of TiO2 by narrowing the bandgap of TiO2 and suppressing the recombination of electron-hole pairs. The high efficacy of this CuO2/TiO2 integrated microneedle (CTMN) patch was systematically demonstrated both in vitro and in vivo with the eliminating rate >99.9999% against multidrug resistant (MDR) pathogens in 5 min as well as accelerated wound tissue healing. This work highlights a promisingly new and efficient strategy for the development of sonosensitive and chemoreactive nanomedicine for non-antibiotic therapies. STATEMENT OF SIGNIFICANCE: Feton-type metal peroxides, a novel nanomaterial with self-supplied oxygen and hydrogen peroxide, can achieve effective antimicrobial activity in vitro. However, there is a lack of effective nanomaterial delivery systems and suitable means for in vivo activation/enhancement of antimicrobial activity during bacterial infected skin wound treatment. In this study, we designed and prepared efficient ultrasound activable microneedles that effectively addressed the deficiencies mentioned above and established a new paradigm for efficient utilization of metal peroxide nanomaterials and ultrasound based strategies. Noticeably, copper peroxide nanoclusters/oxygen vacancy-rich porous titanium oxide nanosheets (CuO2/TiO2) integrated microneedle (CTMN) patch combines advantages of both sono-chemodynamic and sonothermal antibacterial therapy, achieving one of the most instant and effective antibacterial efficacy (>99.9999% in 5 min) in vivo reported till now.

Association of demographic and clinical factors with risk of acute pancreatitis: An exposure-wide Mendelian randomization study.

BACKGROUND: The incidence of acute pancreatitis (AP) is increasing over years, which brings enormous economy and health burden. However, the aetiologies of AP and underlying mechanisms are still unclear. Here, we performed a two-sample Mendelian randomization (MR) analysis to investigate the associations between all reported possible risk factors and AP using publicly available genome-wide association study summary statistics. METHODS: A series of quality control steps were taken in our analysis to select eligible instrumental single nucleotide polymorphisms which were strongly associated with exposures. To make the conclusions more robust and reliable, we utilized several analytical methods (inverse-variance weighting, MR-PRESSO method, weighted median, MR-Egger regression) that are based on different assumptions of two-sample MR analysis. The MR-Egger intercept test, radial regression and leave-one-out sensitivity analysis were performed to evaluate the horizontal pleiotropy, heterogeneities, and stability of these genetic variants on each exposure. A two-step MR method was applied to explore mediators in significant associations. RESULTS: Genetic predisposition to cholelithiasis (effect estimate: 17.30, 95% CI: 12.25-22.36, p = 1.95 E-11), body mass index (0.32, 95% CI: 0.13-0.51, p < 0.001), body fat percentage (0.57, 95% CI: 0.31-0.83, p = 1.31 E-05), trunk fat percentage (0.36, 95% CI: 0.14-0.59, p < 0.005), ever smoked (1.61, 95% CI: 0.45-2.77, p = 0.007), and limbs fat percentage (0.55, 95% CI: 0.41-0.69, p < 0.001) were associated with an increased risk of AP. In addition, whole-body fat-free mass (-0.32, 95% CI: -0.55 to -0.10, p = 0.004) was associated with a decrease risk of AP. CONCLUSION: Genetic predisposition to cholelithiasis, obesity and smoking could be causally associated with an increased risk of AP, and whole body fat-free mass could be associated with a decreased risk of AP.

Dimethyl Itaconate Reduces Cognitive Impairment and Neuroinflammation in APPswe/PS1ΔE9 Transgenic Mouse Model of Alzheimer's Disease.

Alzheimer's disease (AD) is the most common type of dementia characterized by abnormal accumulation of amyloid-ß (Aß) plaques, neuroinflammation, and neuronal loss. Dimethyl itaconate (DI), a membrane-permeable derivative of itaconate, has been recently reported to limit inflammation. However, the effect of DI in the APPswe/PS1ΔE9 (APP/PS1) transgenic mouse model of AD remains unclear. We treated APP/PS1 mice with DI or saline. Our results showed that DI ameliorated the cognitive deficits of APP/PS1 mice. Further, DI significantly decreased brain Aß deposition and Aß levels, inhibited cell apoptosis, decreased hippocampal and cortical neuronal damage. We also found that DI promoted the expression of the Nrf2/HO-1 signaling pathway, while inhibited cognitive impairment, cell apoptosis, and the proinflammatory cytokine levels in the brains of APP/PS1 mice. Our results indicated that DI attenuated memory impairment and neuroinflammation via the Nrf2 signaling pathway in APP/PS1 mice, suggesting that DI might be recognized as a promising candidate for the treatment of AD.

Research on Intelligent Robot Point Cloud Grasping in Internet of Things.

The development of Internet of Things (IoT) technology has enabled intelligent robots to have more sensing and decision-making capabilities, broadening the application areas of robots. Grasping operation is one of the basic tasks of intelligent robots, and vision-based robot grasping technology can enable robots to perform dexterous grasping. Compared with 2D images, 3D point clouds based on objects can generate more reasonable and stable grasping poses. In this paper, we propose a new algorithm structure based on the PointNet network to process object point cloud information. First, we use the T-Net network to align the point cloud to ensure its rotation invariance; then we use a multilayer perceptron to extract point cloud characteristics and use the symmetric function to get global features, while adding the point cloud characteristics attention mechanism to make the network more focused on the object local point cloud. Finally, a grasp quality evaluation network is proposed to evaluate the quality of the generated candidate grasp positions, and the grasp with the highest score is obtained. A grasping dataset is generated based on the YCB dataset to train the proposed network, which achieves excellent classification accuracy. The actual grasping experiments are carried out using the Baxter robot and compared with the existing methods; the proposed method achieves good grasping effect.

Definitive local therapy for extracranial single-organ oligorecurrent non-small-cell lung cancer: A single institutional retrospective study.

Oligometastatic non-small-cell lung cancer (NSCLC) is potentially curable. Oligo-recurrence occurs with oligometastatic disease characterized by well-controlled primary lesion. The purpose of the present study was to explore the value of definitive local therapy (DLT) for extracranial single-organ oligorecurrent NSCLC. A total of 81 patients with NSCLC who had extracranial single-organ oligorecurrence after receiving radical treatment at the Cancer Hospital of the University of Chinese Academy of Sciences from January 2010 to December 2017 were analyzed. The primary endpoint was progression-free survival (PFS), and the secondary endpoint was overall survival (OS). The median follow-up time of the 81 patients was 65.8 months. A total of 39 patients received DLT. A large proportion of patients who did not accept DLTs received specific tyrosine kinase inhibitors (TKIs). The results of multivariate analysis showed that DLT and specific TKI therapy were favorable prognostic factors significantly related to PFS. Further analysis showed that for patients without specific TKI therapy, DLT significantly improved PFS and the 5-year PFS rate. The 5-year OS rate also improved, but the improvement was not significant. For extracranial single-organ oligorecurrent NSCLC, PFS was significantly superior in patients receiving DLT. Among them, for the subgroup of patients who did not receive specific TKI therapy, DLT is expected to improve long-term prognostic outcomes.

Single-cell RNA sequencing reveals a novel inhibitory effect of ApoA4 on NAFL mediated by liver-specific subsets of myeloid cells.

The liver immune microenvironment is a key element in the development of hepatic inflammation in NAFLD. ApoA4 deficiency increases the hepatic lipid burden, insulin resistance, and metabolic inflammation. However, the effect of ApoA4 on liver immune cells and the precise immune cell subsets that exacerbate fatty liver remain elusive. The aim of this study was to profile the hepatic immune cells affected by ApoA4 in NAFL. We performed scRNA-seq on liver immune cells from WT and ApoA4-deficient mice administered a high-fat diet. Immunostaining and qRT-PCR analysis were used to validate the results of scRNA-seq. We identified 10 discrete immune cell populations comprising macrophages, DCs, granulocytes, B, T and NK&NKT cells and characterized their subsets, gene expression profiles, and functional modules. ApoA4 deficiency led to significant increases in the abundance of specific subsets, including inflammatory macrophages (2-Mφ-Cxcl9 and 4-Mφ-Cxcl2) and activated granulocytes (0-Gran-Wfdc17). Moreover, ApoA4 deficiency resulted in higher Lgals3, Ctss, Fcgr2b, Spp1, Cxcl2, and Elane levels and lower Nr4a1 levels in hepatic immune cells. These genes were consistent with human NAFLD-associated marker genes linked to disease severity. The expression of NE and IL-1ß in granulocytes and macrophages as key ApoA4 targets were validate in the presence or absence of ApoA4 by immunostaining. The scRNA-seq data analyses revealed reprogramming of liver immune cells resulted from ApoA4 deficiency. We uncovered that the emergence of ApoA4-associated immune subsets (namely Cxcl9+ macrophage, Cxcl2+ macrophage and Wfdc17+ granulocyte), pathways, and NAFLD-related marker genes may promote the development of NAFL. These findings may provide novel therapeutic targets for NAFL and the foundations for further studying the effects of ApoA4 on immune cells in various diseases.

A Siamese Vision Transformer for Bearings Fault Diagnosis.

Fault diagnosis methods based on deep learning have progressed greatly in recent years. However, the limited training data and complex work conditions still restrict the application of these intelligent methods. This paper proposes an intelligent bearing fault diagnosis method, i.e., Siamese Vision Transformer, suiting limited training data and complex work conditions. The Siamese Vision Transformer, combining Siamese network and Vision Transformer, is designed to efficiently extract the feature vectors of input samples in high-level space and complete the classification of the fault. In addition, a new loss function combining the Kullback-Liebler divergence both directions is proposed to improve the performance of the proposed model. Furthermore, a new training strategy termed random mask is designed to enhance input data diversity. A comparative test is conducted on the Case Western Reserve University bearing dataset and Paderborn dataset and our method achieves reasonably high accuracy with limited data and satisfactory generation capability for cross-domain tasks.

Ultrathin Graphdiyne/Graphene Heterostructure as a Robust Electrochemical Sensing Platform.

Graphdiyne (GDY) has been considered as an appealing electrode material for electrochemical sensing because of its alkyne-rich structure and high degrees of π-conjugation, which shows great affinity to heavy metal ions and pollutant molecules via d-π and π-π interactions. However, the low surface area and poor conductivity of bulk GDY limit its electrochemical performance. Herein, a two-dimensional ultrathin GDY/graphene (GDY/G) nanostructure was synthesized and used as an electrode material for electrochemical sensing. Graphene plays the role of an epitaxy template for few-layered GDY growth and conductive layers. The formed few-layered GDY with a high surface area possesses abundant affinity sites toward heavy metal ions (Cd2+, Pb2+) and toxic molecules, for example, nitrobenzene and 4-nitrophenol, via d-π and π-π interactions, respectively. Moreover, hemin as a key part of the enzyme catalytic motif was immobilized on GDY/G via π-π interactions. The artificial enzyme mimic hemin/GDY/G-modified electrode exhibited promising ascorbic acid and uric acid detection performance with excellent sensitivity and selectivity, a good linear range, and reproducibility. More importantly, real sample detection and the feasibility of this electrochemical sensor as a wearable biosensor were demonstrated.

Computation-accelerated discovery of the K2NiF4-type oxyhydrides combing density functional theory and machine learning approach.

The emerging K2NiF4-type oxyhydrides with unique hydride ions (H-) and O2- coexisting in the anion sublattice offer superior functionalities for numerous applications. However, the exploration and innovations of the oxyhydrides are challenged by their rarity as a limited number of compounds reported in experiments, owing to the stringent laboratory conditions. Herein, we employed a suite of computations involving ab initio methods, informatics and machine learning to investigate the stability relationship of the K2NiF4-type oxyhydrides. The comprehensive stability map of the oxyhydrides chemical space was constructed to identify 76 new compounds with good thermodynamic stabilities using the high-throughput computations. Based on the established database, we reveal geometric constraints and electronegativities of cationic elements as significant factors governing the oxyhydrides stabilities via informatics tools. Besides fixed stoichiometry compounds, mixed-cation oxyhydrides can provide promising properties due to the enhancement of compositional tunability. However, the exploration of the mixed compounds is hindered by their huge quantity and the rarity of stable oxyhydrides. Therefore, we propose a two-step machine learning workflow consisting of a simple transfer learning to discover 114 formable oxyhydrides from thousands of unknown mixed compositions. The predicted high H- conductivities of the representative oxyhydrides indicate their suitability as energy conversion materials. Our study provides an insight into the oxyhydrides chemistry which is applicable to other mixed-anion systems, and demonstrates an efficient computational paradigm for other materials design applications, which are challenged by the unavailable and highly unbalanced materials database.

Piezoelectric Activatable Nanozyme-Based Skin Patch for Rapid Wound Disinfection.

Nanozymes are promising new-generation antibacterial agents owing to their low cost, high stability, broad-spectrum activity, and minimal antimicrobial resistance. However, the inherent low catalytic activity of nanozymes tends to limit their antibacterial efficacy. Herein, a heterostructure of zinc oxide nanorod@graphdiyne nanosheets (ZnO@GDY NR) with unparallel piezocatalytic enzyme mimic activity is reported, which concurrently possesses intrinsic peroxidase-like activity and strong piezoelectric responses and effectively promotes the decomposition of hydrogen peroxide (H2O2) and generation of reactive oxygen species under ultrasound irradiation. Moreover, this piezocatalytic nanozyme exhibits almost 100% antibacterial efficacy against multidrug-resistant pathogens involving methicillin-resistant Staphylococcus aureus and Pseudomonas aeruginosa in vitro and in vivo. In addition, a piezoelectric activatable nanozyme-based skin patch is developed for rapid skin wound disinfections with satisfactory hemocompatibility and cytocompatibility. This work not only sheds light on the development of an innovative piezoelectric activatable nanozyme-based skin patch for rapid wound disinfection but also provides new insights on the engineering of piezocatalytic nanozymes for nanozyme antibacterial therapy.

Nonmetal Graphdiyne Nanozyme-Based Ferroptosis-Apoptosis Strategy for Colon Cancer Therapy.

Ferroptosis-apoptosis, a new modality of induced cell death dependent on reactive oxygen species, has drawn tremendous attention in the field of nanomedicine. A metal-free ferroptosis-apoptosis inducer was reported based on boron and nitrogen codoped graphdiyne (BN-GDY) that possesses efficient glutathione (GSH) depletion capability and concurrently induces ferroptosis by deactivation of GSH-dependent peroxidases 4 (GPX4) and apoptosis by downregulation of Bcl2. The high catalytic activity of BN-GDY is explicated by both kinetic experiments and density functional theory (DFT) calculations of Gibbs free energy change during hydrogen peroxide (H2O2) decomposition. In addition, a unique sequence Bi-Bi mechanism is discovered, which is distinct from the commonly reported ping-pong Bi-Bi mechanism of most peroxidase mimics and natural enzymes. We anticipate that this nonmetal ferroptosis-apoptosis therapeutic concept by carbon-based nanomaterials would provide proof-of-concept evidence for nanocatalytic medicines in cancer therapy.