Search

Text matching is a basic and important task in natural language understanding, this paper proposes a new model BBMC for the problem of insufficient feature extraction ability of existing text matching models, which integrates BiLSTM and multi-scale CNN on the basis of BERT. First, the word embedding representation of the text is obtained by the BERT, and then the semantic features of the text are further extracted by the double-layer BiLSTM, followed by the multi-scale CNN model, the key local features are extracted, and finally the linear and SoftMax function are used to classify. Experimental results on the LCQMC dataset show that the BBMC has been improved to a certain extent compared with other methods, and the accuracy on the test set can be best achieved 88.01%.

The aquila optimization algorithm (AO) is an efficient swarm intelligence algorithm proposed recently. However, considering that AO has better performance and slower late convergence speed in the optimization process. For solving this effect of AO and improving its performance, this paper proposes an enhanced aquila optimization algorithm with a velocity-aided global search mechanism and adaptive opposition-based learning (VAIAO) which is based on AO and simplified Aquila optimization algorithm (IAO). In VAIAO, the velocity and acceleration terms are set and included in the update formula. Furthermore, an adaptive opposition-based learning strategy is introduced to improve local optima. To verify the performance of the proposed VAIAO, 27 classical benchmark functions, the Wilcoxon statistical sign-rank experiment, the Friedman test and five engineering optimization problems are tested. The results of the experiment show that the proposed VAIAO has better performance than AO, IAO and other comparison algorithms. This also means the introduction of these two strategies enhances the global exploration ability and convergence speed of the algorithm.

Emulsified isoflurane was designed to circumvent the deficiencies of inhalation anesthetics, which have a longer time to onset, result in a higher drug consumption, and for which a specific anesthesia machine is required for clinical use. The aim of this study was to compare the efficacy and safety of emulsified isoflurane with propofol for anesthesia induction in adults patients.This multicenter, randomized, double-blind, positive-controlled, non-inferiority, phase III clinical trial compared the efficacy and safety of emulsified isoflurane with propofol for anesthesia induction. Each patient in the emulsified isoflurane group received a single bolus injection of 12% emulsified isoflurane at a dose of 30 mg/kg, and each patient in the propofol group received a single bolus injection of 0.8% propofol at a dose of 2 mg/kg. The primary outcome of the efficacy evaluation was the proportion of participants with successful anesthesia induction, which was regarded as a Modified Observer's Assessment of Alertness/Sedation (MOAA/S) score of 1 and lack of use of other sedative drugs. A number of secondary efficacy outcomes were also assessed. Safety was monitored based on (1) adverse events, (2) repeated measurement of vital signs; (3) physical examination, (4) routine laboratory examinations of hematology, biochemistry, urine, coagulation function, and (5) 12-lead electrocardiogram.A total of 416 patients were enrolled (n = 208 in each group) and 398 patients were administered study drug. The proportion of participants with successful anesthesia induction was 100% with a 95% confidence interval of - 1.9% to + 1.9% for the emulsified isoflurane and propofol groups, which met the predesigned non-inferiority criteria of 5%. The study demonstrated the non-inferiority of sedation produced by emulsified isoflurane compared to propofol. Among the secondary efficacy outcomes, emulsified isoflurane showed a better cardiovascular stability than propofol. The number of patients from the emulsified isoflurane group who experienced drug-related adverse events was significantly higher than that of patients from the propofol group. However, there was no significant difference between the two groups in terms of adverse events or drug-related adverse events of grades 3-5.Emulsified isoflurane exhibited non-inferiority of anesthesia/sedation compared to propofol in patients undergoing anesthesia induction.ChiCTR2000038185, registered on 12 December, 2020 ( www.chictr.org.cn ).

The intercropping treatment has been widely used to improve the crop productivity and achieve the development of efficient agricultural practice. In this study, to further explore the effect of Gramineae and Leguminosae intercropping, Sophora davidii (Franch.) Skeels and Pennisetum sinese Roxb under monoculture and intercropping were performed, the rhizosphere soil was collected, the physical and chemical properties (pH, AP, AK), enzyme activities (βG, LAP, NAG and AcP) and fungal community diversity were tested. In the results, intercropping changed the physical and chemical properties and enzyme activities of rhizosphere soil. Compared with the monoculture, intercropping decreased the α-diversity of soil fungal communities. At the phylum level, intercropping significantly increased the relative abundance of Ascomycota and Ciliophora, while decreased the relative abundance of Mucoromycota and Chytridiomycota, compared with monoculture. At the genus level, the relative abundances of Fusarium, Talaromyces, Preussia, Mycoleptodiscus, Plectosphaerella and Bracteacoccus in intercropping were higher than those under monoculture, while the relative abundances of Lablab, Aspergillus and Rumex were lower. RDA analysis showed that, soil fungal community structure was mainly affected by soil enzyme activity under intercropping system. In conclusion, the soil fungal community depends largely on management measures of monoculture and intercropping, compared with the dynamic changes in soil environmental parameters. This study can provide a reference for the assessment of soil ecological effect of intercropping.

People's daily sports and patient rehabilitation movement requires standard movement guidance, this paper puts forward a real-time movement guidance in mobile terminal system, the main function of using the camera to obtain the user movement posture, identify the current posture in the application of the category, and the current posture with the standard movement, in the user movement key body with different color grading tips, in order to prompt the user and correct the user posture.

Breast cancer (BC), the most common cancer in women, is caused by the uncontrolled proliferation of mammary epithelial cells under the action of a variety of carcinogenic factors. Cuproptosis-related targets have been found to be closely associated with breast cancer development. TCGA obtained 1226 tumor samples, 1073 clinical data, and 37 lncRNAs during univariate Cox multivariate analysis. We used nonnegative matrix factoring (NMF) agglomeration to spot thirty-three potential molecular subsets with totally different cuproptosis-related lncRNA expression patterns. The least absolute shrinkage and selection operator (LASSO) formula and variable Cox multivariate analysis were not used to construct the best prognostic model. The variations in neoplasm mutation burden and factor gene ontology (GO) and gene set enrichment analysis (GSEA) within the high- and low-risk teams were analyzed, and therefore, the potential mechanism of the development of carcinoma was analyzed. We created a prognostic profile consisting of nineteen cuproptosis-related genes (NFE2L2, LIPT1, LIPT2, DLD, etc.) and their connected targets. The correlation between tumor mutational burden (TMB) and clinical manifestations of tumors demonstrates the importance of high- and low-expression bunch data on the incidence of clinical manifestations of tumors. The area under the curve (AUC) shows moderate prophetic power for copper mortality. GO enrichment analysis showed that immunorelated responses were enriched. Correlation analysis of immune cells showed that pathology could play an important role in the prevalence and prognosis of tumors, and there were variations in immune cells between the probable and low-risk groups. Our study suggests that the prognostic characteristic genes associated with cuproptosis can be used as new biomarkers to predict the prognosis of breast cancer patients. In addition, we found that immunotherapy may play a key role in breast cancer treatment regimens. Levels of immune-associated cells and pathways vary significantly among risk groups of breast cancer patients.

To construct a predictive nomogram of the risk of nosocomial infections among patients after cardiac valve replacement surgery.Nosocomial infections are a standout challenge that worsens the prognosis of patients after valve replacement surgery. However, studies on the nomogram of nosocomial infections in these patients have remained scarce.A retrospective cohort study.Patients (n = 720) following valve replacement surgery from 2018 to 2019 were selected. LASSO regression and multivariate logistic regression were utilised to ascertain predictors of nosocomial infections. The predictive performance of the nomogram was appraised by calibration and discrimination. Decision and impact curves were used to assess the clinical utility. Internal validation was implemented via 1000 bootstrap samples to mitigate overfitting. TRIPOD guidelines were used in this study.One hundred and fifty one patients (20.97%) experienced nosocomial infections following valve replacement surgery. Heart failure, preoperative anaemia, valve material, American Society of Anesthesiologists score ≥ IV, prolonged duration of surgery, duration of mechanical ventilation ≥ 24 h and indwelling nasogastric tube were predictors of nosocomial infections. Using these variables, we developed a predictive nomogram of the occurrence of nosocomial infections and the internal validation results demonstrated good discrimination and calibration of the nomogram. The clinical decision and impact curve revealed significant clinical utility.The present study constructed a nomogram for predicting the risk of nosocomial infections in patients following cardiac valve replacement surgery. This nomogram may strengthen the effective screening of patients at high risk of nosocomial infections.This risk warning tool can assist clinical staff in making decisions and providing individualised infection control measures for patients, which has a significant reference value for clinical practice.The data for this study were obtained from the hospital database, and the entire process of the study did not involve patient participation.

This paper constructs a lightweight text matching model. This model fully extracts the features of two text through the fusion of double tower and interactive methods, and then conducts deep interaction. Then, it classifies the last extracted text features through the classification network, and conducts training, validation and testing on the Chinese text matching dataset LCQMC. Although the experimental results show that the model in this paper is relatively good, it still needs to be improved.

To introduce the surgical approach and clinical effect of transferring the partial slips of the flexor digitorum superficialis (FDS) tendon to reconstruct the insertion of the central slip of the extensor tendon (CSET) through an established bone tunnel (BT).From April 2019 to March 2021, nine patients (six males and three females) with the CSET insertion rupture or defect were admitted to the institution and the CSET insertion was reconstructed with partial tendon slips on both sides of the FDS. The active range of motion of the interphalangeal joint of the affected finger was measured by a goniometer, the degree of pain was evaluated by visual analogue scale (VAS), and the grip strength of the affected limb was measured by an electronic hand dynamometer.The average postoperative follow-up was 12 months. No complications occurred. At the last follow-up, six of the patients were very satisfied and three were satisfied with their recovery.The reconstruction of the CSET insertion by transferring the partial tendon slips of the FDS seem to be safe and feasible with minimal invasion to the donor tendon.Therapeutic IV.

Antimicrobial peptides (AMPs) and their mimics are rapidly gaining attention as a new class of antimicrobials due to their clinical potential. AMPs are widely distributed throughout nature and participate in the innate host defense. In this study, 18 AMPs, including 3 β-defensins, 3 hepcidins, 4 liver-expressed antimicrobial peptide 2 (LEAP-2) compounds, 4 g-type lysozymes, 2 c-type lysozymes, and 2 NK-lysins, were identified from the genome of Carassius auratus by a homologous search and were further classified based on their fundamental structural features and molecular phylogeny. C. auratus AMPs were found to be ubiquitously distributed in all tested tissues and showed similar expression profiles, with the exception of β-defensins, when RT-qPCR was used to investigate the tissue distribution of AMPs in healthy Carassius gibel. In addition, the expression levels of NK-lysin genes in the tested tissues tended to be upregulated upon bacterial and viral infection when representative NK-lysins were chosen to examine their relative expression levels in various tissues. Importantly, the synthetic peptide caNKL2

Heterogenization of homogeneous catalysis through supported single-atom catalysts (SACs) provided a feasible solution to recycling catalysts while keeping its efficiency in chemical synthesis. In this work, Cu SACs anchored on N-doped graphene (Cu SACs/NG) were prepared and first used for C-N coupling reactions. During the preparation, Cu-N-C structures, including Cu-N

IntroductionRepair and regeneration of the peripheral nerve are important for the treatment of peripheral nerve injury (PNI) caused by mechanical tears, external compression injuries and traction injuries. Pharmacological treatment can promote the proliferation of fibroblasts and Schwann cells (SCs), which longitudinally fill the endoneurial canal and form Bungner’s band, helping the repair of peripheral nerves. Therefore, the development of new drugs for the treatment of PNI has become a top priority in recent years.MethodsHere, we report that small extracellular vesicles (sEVs) produced from umbilical cord mesenchymal stem cells (MSC-sEVs) cultured under hypoxia promote repair and regeneration of the peripheral nerve in PNI and may be a new therapeutic drug candidate.ResultsThe results showed that the amount of secreted sEVs was significantly increased in UC-MSCs compared with control cells after 48 h of culture at 3% oxygen partial pressure in a serum-free culture system. The identified MSC-sEVs could be taken up by SCs in vitro, promoting the growth and migration of SCs. In a spared nerve injury (SNI) mouse model, MSC-sEVs accelerated the recruitment of SCs at the site of PNI and promoted peripheral nerve repair and regeneration. Notably, repair and regeneration in the SNI mouse model were enhanced by treatment with hypoxic cultured UC-MSC-derived sEVs.DiscussionTherefore, we conclude that hypoxic cultured UC-MSC-derived sEVs may be a promising candidate drug for repair and regeneration in PNI.

Energy sustainability is critical for social activities in the human world. The quaternary compound Cu2ZnSnSe4 (CZTSe), as a promising candidate for thin-film solar cell absorption with medium-level thermoelectric performance, is of interest for the purpose of utilizing solar energy. The defect chemistry and atomic ordering in this particular compound also triggers interests in understanding its crystallographic structure as well as defects. Hereby, high energy resolution X-ray absorption spectroscopy is employed to investigate the electronic and geometric structural complexity in pristine and cobalt-doped Cu2ZnSnSe4. The occupational atomic sites of Cu are found to be mixed with the Zn atoms, forming CuZn anti-defects, which serve as a knob to tune local electronic structures. With proper doping, the band structure can be manipulated to improve the optical and thermoelectric properties of the CZTSe compounds.

IntroductionLong-term grazing profoundly affects grassland ecosystems, whereas how the soil microbiome and multiple soil ecosystem functions alter in response to two-decades of grazing, especially how soil microbiome (diversity, composition, network complexity, and stability) forms soil multifunctionality is rarely addressed.MethodsWe used a long-term buffalo grazing grassland to measure the responses of soil physicochemical attributes, stoichiometry, enzyme activities, soil microbial niche width, structure, functions, and networks to grazing in a subtropical grassland of Guizhou Plateau, China.ResultsThe evidence from this work suggested that grazing elevated the soil hardness, available calcium content, and available magnesium content by 6.5, 1.9, and 1.9 times (p = 0.00015–0.0160) and acid phosphatase activity, bulk density, pH by 59, 8, and 0.5 unit (p = 0.0014–0.0370), but decreased the soil water content, available phosphorus content, and multifunctionality by 47, 73, and 9–21% (p = 0.0250–0.0460), respectively. Grazing intensified the soil microbial carbon limitation (+78%, p = 0.0260) as indicated by the increased investment in the soil β-glucosidase activity (+90%, p = 0.0120). Grazing enhanced the complexity and stability of the bacterial and fungal networks but reduced the bacterial Simpson diversity (p < 0.05). The bacterial diversity, network complexity, and stability had positive effects, while bacterial and fungal compositions had negative effects on multifunctionality.DiscussionsThis work is an original attempt to show that grazing lowered multifunctionality via the reduced bacterial diversity and shifted soil bacterial and fungal compositions rather than the enhanced bacterial and fungal network complexities and stability by grazing. Protecting the bacterial diversity from decreasing, optimizing the composition of bacteria and fungi, and enhancing the complexity and stability of bacterial network may be conducive to improving the soil multifunction of grazing grassland, on a subtropical grassland.

The anomalous Hall effect (AHE) is a quantum coherent transport phenomenon that conventionally vanishes at elevated temperatures because of thermal dephasing. Therefore, it is puzzling that the AHE can survive in heavy metal (HM)/antiferromagnetic (AFM) insulator (AFMI) heterostructures at high temperatures yet disappears at low temperatures. In this paper, we report that an unconventional high-temperature AHE in HM/AFMI is observed only around the N\'eel temperature of AFM, with large anomalous Hall resistivity up to 40 n$\Omega$ cm. This mechanism is attributed to the emergence of a noncollinear AFM spin texture with a non-zero net topological charge. Atomistic spin dynamics simulation shows that such a unique spin texture can be stabilized by the subtle interplay among the collinear AFM exchange coupling, interfacial Dyzaloshinski-Moriya interaction, thermal fluctuation, and bias magnetic field.

By installing on-board diagnostics (OBD) on tested vehicles, the after-treatment exhaust emissions can be monitored in real time to construct driving cycle-based emission models, which can provide data support for the construction of dynamic emission inventories of mobile source emission. However, in actual vehicle emission detection systems, due to the equipment installation costs and differences in vehicle driving conditions, engine operating conditions, and driving behavior patterns, it is impossible to ensure that the emission monitoring data of different vehicles always follow the same distribution. The traditional machine learning emission model usually assumes that the training set and test set of emission test data are derived from the same data distribution, and a unified emission model is used for estimation of different types of vehicles, ignoring the difference in monitoring data distribution. In this study, we attempt to build a diesel vehicle NOx emission prediction model based on the deep transfer learning framework with a few emission monitoring data. The proposed model firstly uses Spearman correlation analysis and Lasso feature selection to accomplish the selection of factors with high correlation with NOx emission from multiple sources of external factors. Then, the stacked sparse AutoEncoder is used to map different vehicle working condition emission data into the same feature space, and then, the distribution alignment of different vehicle working condition emission data features is achieved by minimizing maximum mean discrepancy (MMD) in the feature space. Finally, we validated the proposed method with the diesel vehicle OBD data that were collected by the Hefei Environmental Protection Bureau. The comprehensive experiment results show that our method can achieve the feature distribution alignment of emission data under different vehicle working conditions and improve the prediction performance of the NOx inversion model given a little amount of NOx emission monitoring data.

Network flows are the basic components of the Internet. Considering the serious consequences of abnormal flows, it is crucial to provide timely anomaly detection in dynamic communication networks. To obtain accurate anomaly detection results in dynamic networks, supervision from experts is highly demanded. However, to obtain high-quality ground truth of abnormal flows, we suffer from two major problems: (1) limited labor resources: experts with the latest domain knowledge are much fewer than the large number of flows; and (2) dynamic environment: considering the new abnormal patterns (i.e., new attacks) and continuously changing network structures, it requires timely supervision to adaptively update the parameters. To tackle these problems, we propose HADDN, a novel bandit framework for periodic-updated anomaly detection in dynamic communication networks. We formulate the task as a bandit problem, where by interactions, supervision is offered by human experts to provide the ground truth to a fraction of flows. We construct semi-parametric expected rewards to optimize the estimation of flows' abnormality in limited interactions. Also, we utilize feature-based clusters and structural correlations to make connections between historical flows and new flows to improve both efficiency and accuracy of abnormality estimation. What's more, we provide two implementations for the semi-parametric expected reward of the proposed HADDN with theoretical proof. Experimental evaluations on public datasets demonstrate the substantial improvement of our proposed approaches compared to state-of-art anomaly detection methods.

An electrocatalytic membrane reactor (ECMR) with an anode consisting of Pt nanoparticles (NPs) loaded on a Ti membrane electrode (Pt NPs/Ti) was designed to oxidize cyclohexanone (K) to produce sodium adipate (SA) under mild conditions. The effects of residence time, reaction temperature, current density and initial K concentration on K conversion were investigated. Optimization experiments were conducted to determine the effects of and interactions between different operating parameters on K conversion using a central composite design within the response surface methodology. A 88.3% conversion of K and 99% selectivity to SA were obtained by the ECMR under the optimum conditions of reaction temperature = 30.8 °C, K concentration = 22.54 mmol L−1, residence time = 25 min and current density = 2.07 mA cm−2. The high performance of the ECMR is attributed to electrocatalytic oxidation (at the Pt NPs/Ti electrode), convection-enhanced mass transfer, and the timely removal of the desired products.

Variable industrial strains have been applied in the fermentation of bulk amino acids. Strain discovery and evolution, process optimization are traditional approaches to improve the yield and efficiency of the bio-production process, hence to compete with chemical or enzymatic process in amino acids production. With the fast development of bioengineering and synthetic biology, the strains can be rationally engineered to achieve better performance and gain the capacity in the fermentation of broader range of amino acids, especially for value-added amino acids. This proposed review aims to summarize traditional and recent strains in the microbial production of amino acids, characterize their metabolic pathways and present potential objectives for rational evolution. In addition, this proposed review prospect the recent opportunities and challenges in the microbial production of value-added amino acids (rare amino acids, non-canonical amino acids, and unnatural amino acids).

Non-small cell lung cancers (NSCLC) frequently contain KRAS mutation but retain wild-type TP53. Abundant senescent cells are observed in premalignant but not in malignant tumors derived from the Kras-driven mouse model, suggesting that KRAS oncogenic signaling would have to overcome the intrinsic senescence burden for cancer progression. Here, we show that the nuclear Beclin 1-mediated inhibition of p53-dependent senescence drives Kras-mediated tumorigenesis. KRAS activates USP5 to stabilize nuclear Beclin 1, leading to MDM2-mediated p53 protein instability. KrasG12D mice lacking Beclin 1 display retarded lung tumor growth. Knockdown of USP5 or knockout of Becn1 leads to increased senescence and reduced autophagy. Mechanistically, KRAS elevates ROS to induce USP5 homodimer formation by forming the C195 disulfide bond, resulting in stabilization and activation of USP5. Together, these results demonstrate that activation of the USP5-Beclin 1 axis is pivotal in overriding intrinsic p53-dependent senescence in Kras-driven lung cancer development.

To understand the metabolite dynamics and genetic regulatory mechanism of apricot shell, a typical endocarp, before and after lignification are unknown, we investigated the metabolite differences of the endocarp of ‘Youyi,’ a popular kernel-using apricot cultivar, using ultra-performance liquid chromatography tandem mass spectrometry strategy. The endocarp thickness increased rapidly from 8 to 37 days after flowering (DAF) and lignin deposition began at 37 DAF. In total, 626 non-volatile metabolites were obtained from the endocarp tissues before (33 DAF) and after (41 and 45 DAF) lignification. The relative sugar and organic acid contents decreased continuously and those of L-phenylalanine and L-tyrosine increased after lignification. In the non-lignified endocarp, the phenylpropanoid metabolites were mainly in the form of p-coumaric acid, ferulic acid, neochlorogenic acid, dicumarol, coniferin, and some lignans. After lignification, the metabolites were mainly in the form of glycoside lignin or lactone coumarins, and the relative contents of L-asarinin and forsythin increased. The results of transcriptome confirmed the upregulation of genes related to lignin biosynthesis, including β-glucosidase and coniferyl-alcohol glucosyltransferase and laccases, accelerated lignification. This study provides insights into the formation of lignified endocarp in a kernel-using apricot and clarifies the role of monolignin transport and oxidative polymerization.

Herpes zoster (HZ) is a localized, painful cutaneous eruption that occurs upon reactivation of the herpes virus. Postherpetic neuralgia (PHN) is the most common chronic complication of HZ. In this study, we examined the metabolomic and proteomic signatures of disease progression in patients with HZ and PHN. We identified differentially expressed metabolites (DEMs), differentially expressed proteins (DEPs), and key signaling pathways that transition from healthy volunteers to the acute or/and chronic phases of herpetic neuralgia. Moreover, some specific metabolites correlated with pain scores, disease duration, age, and pain in sex dimorphism. In addition, we developed and validated three optimal predictive models (AUC > 0.9) for classifying HZ and PHN from healthy individuals based on metabolic patterns and machine learning. These findings may reveal the overall metabolomics and proteomics landscapes and proposed the optimal machine learning predictive models, which provide insights into the mechanisms of HZ and PHN.

To ensure the security and stabilization of the communication networks , anomaly detection is the first line of defense. However, their learning process suffers two major issues: (1) inadequate labels: there are many different kinds of attacks but rare abnormal nodes in mt of these atstacks; and (2) inaccurate labels : considering the heavy network flows and new emerging attacks, providing accurate labels for all nodes is very expensive. The inadequate and inaccurate label problem challenges many existing methods because the majority normal nodes result in a biased classifier while the noisy labels will further degrade the performance of the classifier. To tackle these issues, we propose SemiADC, a Semi -supervised A nomaly D etection framework for dynamic C ommunication networks. SemiADC first approximately learns the feature distribution of normal nodes with regularization from abnormal ones. It then cleans the datasets and extracts the nodes sasainaccurate labels by the learned feature distribution and structure-based temporal correlations. These self-learning processes run iteratively with mutual promotion, and finally help increase the accuracy of anomaly detection. Experimental evaluations on real-world datasets demonstrate the effectiveness of our SemiADC, which performs substantially better than the state-of-art anomaly detection approaches without the demand of adequate and accurate supervision.

The addition of carbon nanotubes (CNT) in ceramic composites has stimulated a substantial interest due to their high mechanical, thermal and electrical properties. This approach used fluoride additives (AlF3 and MgF2) to prepare multi-walled carbon nanotubes/silicon nitride (MWCNT/Si3N4) composite densified at 1700 °C for 1 h by hot press (HP) sintering. The microstructural analyses of MWCNT/Si3N4 composites indicate that the fluoride additives have substantially improved densification and the transformation of α-Si3N4 to β-Si3N4. As observed, the mechanical properties, i.e. flexural strength, fracture toughness, Young's modulus and hardness of MWCNT/Si3N4 composites are improved with an increasing concentration of MWCNT. These results attributed to the highly dense composites, strong interfacial interaction and the pull-out mechanism of MWCNT and β-Si3N4. The maximum values of fracture toughness flexural strength, Young's modulus, and hardness were 12.76 ± 1.15 MPa.m0.5, 883 ±46 MPa, 260 ±9 GPa, and 26.4 ± 1.3 GPa, respectively. The improved mechanical properties also ascribed to the synergistic strengthening and toughening influence of MWCNT and β-Si3N4.

CCK-8, Cell Counting Kit 8; Chip, Chromatin Immunoprecipitation; EC, Esophageal cancer; EMT, epithelial-to-mesenchymal transition; ESCC, Esophageal squamous cell carcinomas; LLGL2, lethal (2) giant larvae protein homolog 2; LLGL2ov, LLGL2 overexpression; MET, mesenchymal-epithelial transition; miRNAs, MicroRNAs; PRM-MS, Parallel reaction monitoring-Mass spectrometry; SD, Standard deviation; SOX, sex determining region Y (SRY)-like box; SOX2-Kd, SOX2-knockdwon; TUNEL, TdT-mediated dUTP Nick-End Labeling.

Microbes, especially abundant microbes in bulk soils, form multiple ecosystem functions, which is relatively well studied. However, the role of rhizosphere microbes, especially rhizosphere rare taxa vs. rhizosphere abundant taxa in regulating the element circling, multifunctionality, aboveground net primary productivity (ANPP) and the trade-offs of multiple functions remains largely unknown. Here, we compared the multiple ecosystem functions, the structure and function of rhizosphere soil bacterial and fungal subcommunities (locally rare, locally abundant, regionally rare, regionally abundant, and entire), and the role of subcommunities in the Zea mays and Sophora davidii sole and Z. mays/S. davidii intercropping ecosystems in subtropical China. Results showed that intercropping altered multiple ecosystem functions individually and simultaneously. Intercropped Z. mays significantly decreased the trade-off intensity compared to sole Z. mays, the trade-off intensity under intercropped S. davidii was significantly higher than under intercropped Z. mays. The beta diversities of bacterial and fungal communities, and fungal functions in each subcommunity significantly differed among groups. Network analysis showed intercropping increased the complexity and positive links of rare bacteria in Z. mays rhizosphere, but decreased the complexity and positive links of rare bacteria in S. davidii rhizosphere and the complexity and positive links of fungi in both intercropped plants rhizosphere. Mantel test showed significant changes in species of locally rare bacteria were most strongly related to nitrogen-cycling multifunctionality, ANPP and trade-offs intensity, significant changes in species of locally rare fungus were most strongly related to carbon-cycling multifunctionality, phosphorus-cycling multifunctionality, and average ecosystem multifunctionality. This research highlights the potential and role of rare rhizosphere microorganisms in predicting and regulating system functions, productivity, and trade-offs.