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To study the impact energy release behavior, damage effect behavior and space forming behavior of the debris cloud behind the target of La32.5Ce32.5Al10Co25 amorphous alloy spherical fragment, the impact energy release test of an amorphous fragment at different velocities is carried out by using a φ 14.5 mm ballistic gun launching device and a quasi-closed reaction vessel. The impact energy release damage behavior of fragments and the space-forming behavior of debris clouds are analyzed based on the fragment penetrating target fragmentation theory. The results show that the perforation mode of the amorphous fragment penetrating the 2A12 front target is mainly plug damage mode. The average oxygen content of amorphous fragments respectively is 27.73 % and 55.24 % at 793 m‧s−1 and 1397 m‧s−1. When the impact velocity is 1397 m‧s−1, the energy release efficiency of the amorphous fragment is the largest, which is about 65 % and the energy density is 4.7473 kJ‧g−1. When the critical activation reaction occurs, the critical impact velocity is 439 m‧s−1, and the critical impact pressure P0 is 9.02 GPa. The theoretical model of debris cloud space forming behind the target is established. The evolution law of debris cloud space and impact energy releases damage model of amorphous fragments is obtained.

Pod size is a key agronomic trait that influences peanut yield greatly. However, our understanding of the mechanisms underlying pod size is limited. In this study, we employed a segregating population derived from a cross between the small-pod line ND_S and the large-pod line ND_L to map quantitative trait loci (QTL) associated with pod size. Initial mapping performed using bulk segregant analysis revealed a candidate interval on chromosome A05 referred to as qPSW05. We refined this interval to a 256.9 kb genomic region using newly developed molecular markers. Through sequence and expression analyses, we identified the candidate gene AhXE45GC, which encodes an AN1 zinc finger protein. We discovered a 33-bp insertion in the intron of AhXE45GC in ND_S. Accessions that lack this insertion, such as ND_L, had significantly larger pods than those with the insertion, including ND_S. To facilitate marker-assisted selection for peanut pod size, we developed a molecular marker associated with this polymorphism. This marker could provide a valuable genetic resource for breeding high-yielding peanut varieties.

Peanut (Arachis hypogaea L.) is an important oil crop. Oleic acid is a major factor that determines the quality of peanuts. Therefore, the high oleic and high oleic to linoleic acid ratio are the target traits in an advanced peanut breeding program. This study provided an extensive evaluation of the genetic and physical characteristics as well as disease resistance of 220 high oleic peanut varieties in China. Notably, these varieties clustered into five major categories based on their traits. A majority of these varieties have been bred using interspecific hybridization or selected from mutants of self-crossed parents, with the main parent varieties being Kaixuan 016 and CTWE. Analysis of disease resistance showed that most high oleic peanut varieties could resist two or three diseases. However, those varieties with resistance to multiple diseases were relatively scarce. Moreover, some high oleic peanut varieties showed no disease resistance or inadequate testing. The results further indicate that the genetic basis for high oleic peanut breeding is insufficient, highlighting the need for its further development. Importantly, our findings lay a critical foundation for future high oleic peanut breeding and promote better understanding of the genetic and trait diversity offered by these varieties.

Abstract Based on the experimentally reported stable and conductive two-dimensional covalent organic frameworks with copper phthalocyanine (CuPc) as building block and cyan substituted phenyl as connector (CuCOF-CN) as an electrocatalyst for CO2 reduction reaction (RR), first principle calculations were performed on CuCOF-CN and its analog with the CN being replaced by H (CuCOF). Comparatively studied on the crystal structures, electronic properties, and CO2RR performance of the two catalysts found that CuCOF has reduced crystal unit size, more positive charge on Cu and CuPc segments, smaller band gap, and lower reaction barrier for CO2 RR than CuCOF-CN. CuCOF is proposed to be good potential electrocatalyst with good environment friendliness. The substituent effect and structure-property-performance relationship would help for designing and fabricating new electrocatalysts.

Abstract Enhancing drought tolerance in crops and understanding the underlying mechanisms have been subject of intense research. The precise function and molecular mechanisms of B-box zinc finger proteins (BBX) remain elusive. Here, we report a natural allele of BBX18 (BBX18 TT ) that encodes a C-terminal truncated protein. While most wild tomato germplasms contain the BBX18 CC allele and show more drought tolerant, modern cultivated tomatoes mostly carry BBX18 TT allele and are more drought sensitive. Knockout of BBX18 leads to improved drought tolerance in transgenic plants of cultivated tomato. Ascorbate peroxidase 1 (APX1) is identified as a BBX18-interacting protein that acts as a positive regulator of drought resistance in tomato. Chromatin immunoprecipitation sequencing analyses reveal that BBX18 binds to a unique cis-acting element of the APX1 promoter and represses its gene expression. This study provides insights into the molecular mechanism underlying drought resistance mediated by the BBX18-APX1 module in plants.

Abstract Background Protein–protein interactions are the primary means through which proteins carry out their functions. These interactions thus have crucial roles in life activities. The wide availability of fully sequenced animal and plant genomes has facilitated establishment of relatively complete global protein interaction networks for some model species. The genomes of cultivated and wild peanut (Arachis hypogaea L.) have also been sequenced, but the functions of most of the encoded proteins remain unclear. Results We here used homologous mapping of validated protein interaction data from model species to generate complete peanut protein interaction networks for A. hypogaea cv. ‘Tifrunner’ (282,619 pairs), A. hypogaea cv. ‘Shitouqi’ (256,441 pairs), A. monticola (440,470 pairs), A. duranensis (136,363 pairs), and A. ipaensis (172,813 pairs). A detailed analysis was conducted for a putative disease-resistance subnetwork in the Tifrunner network to identify candidate genes and validate functional interactions. The network suggested that DX2UEH and its interacting partners may participate in peanut resistance to bacterial wilt; this was preliminarily validated with overexpression experiments in peanut. Conclusion Our results provide valuable new information for future analyses of gene and protein functions and regulatory networks in peanut.

Abstract The susceptibility of mechanomyography (MMG) signals acquisition to sensor donning and doffing, and the apparent time-varying characteristics of biomedical signals collected over different periods, inevitably lead to a reduction in model recognition accuracy. To investigate the adverse effects on the recognition results of hand actions, a 12-day cross-time MMG data collection experiment with eight subjects was conducted by an armband, then a novel MMG-based hand action recognition framework with densely connected convolutional networks (DenseNet) was proposed. In this study, data from 10 days were selected as a training subset, and the remaining data from another 2 days were used as a test set to evaluate the model’s performance. As the number of days in the training set increases, the recognition accuracy increases and becomes more stable, peaking when the training set includes 10 days and achieving an average recognition rate of 99.57% (± 0.37%). In addition, part of the training subset is extracted and recombined into a new dataset and the better classification performances of models can be achieved from the test set. The method proposed effectively mitigates the adverse effects of sensor donning and doffing on recognition results.

The bonding joints of 2219 aluminum alloy with different deformations of 30%, 45% and 55% were fabricated using hot-compression bonding, and subsequent subjected to homogenization treatment. The interfacial microstructure and interfacial oxide evolution of the bonding joints were systematically investigated. The results showed that increasing deformation can effectively reduce the formation of interfacial voids and promote the interfacial grain boundary migration (IGBM). As the deformation increased from 30% to 55%, the flat bonding interface transformed into curved grain boundaries, and ultimately being occupied by dynamically recrystallized (DRXed) grains. The development of IGBM and interfacial DRXed grains is crucial for ensuring high-quality bonding joints. At 55% deformation, the interface bonding strength reached 156.2 MPa, corresponding to 98.1% of the matrix bonding strength. In addition, the residual interfacial oxide film Al2O3 reacted with MgO and transformed into MgAl2O4 spinel. The final evolution products at the bonding interface were the mixture of MgO, Al2Cu, Al2O3, and MgAl2O4. The bonding interface at 55% deformation successfully achieved relatively clean atomic bonding after homogenization. Based on interfacial void closure, interfacial oxide film fragmentation and evolution, and interfacial recrystallization, the bonding mechanism of 2219 aluminum alloy joints was proposed. These findings contribute to our understanding of the interfacial bonding process in metal solid bonding.

Ground hydraulic fracturing plays a crucial role in controlling the far-field hard roof, making it imperative to identify the most suitable target stratum for effective control. Physical experiments are conducted based on engineering properties to simulate the gradual collapse of the roof during longwall top coal caving (LTCC). A numerical model is established using the material point method (MPM) and the strain-softening damage constitutive model according to the structure of the physical model. Numerical simulations are conducted to analyze the LTCC process under different hard roofs for ground hydraulic fracturing. The results show that ground hydraulic fracturing releases the energy and stress of the target stratum, resulting in a substantial lag in the fracturing of the overburden before collapse occurs in the hydraulic fracturing stratum. Ground hydraulic fracturing of a low hard roof reduces the lag effect of hydraulic fractures, dissipates the energy consumed by the fracture of the hard roof, and reduces the abutment stress. Therefore, it is advisable to prioritize the selection of the lower hard roof as the target stratum.

The accurate measurement of orchard canopy volume serves as a crucial foundation for wind regulation and dosage adjustments in precision orchard management. However, existing methods for measuring canopy volume fail to satisfy the high precision and real-time requirements necessary for accurate variable-rate applications in fruit orchards. To address these challenges, this study develops a canopy volume measurement model for orchard spraying using LiDAR point cloud data. In the domain of point cloud feature extraction, an improved Alpha Shape algorithm is proposed for extracting point cloud contours. This method improves the validity judgment for contour line segments, effectively reducing contour length errors on each 3D point cloud projection plane. Additionally, improvements to the mesh integral volume method incorporate the effects of canopy gaps in height difference calculations, significantly enhancing the accuracy of canopy volume estimation. For feature selection, a random forest-based recursive feature elimination method with cross-validation was employed to filter 10 features. Ultimately, five key features were retained for model training: the number of point clouds, the 2D point cloud contour along the X- and Z-projection directions, the 2D width in the Y-projection direction, and the 2D length in the Z-projection direction. During model construction, the study optimized the hyperparameters of partial least squares regression (PLSR), backpropagation (BP) neural networks, and gradient boosting decision trees (GBDT) to build canopy volume measurement models tailored to the dataset. Experimental results indicate that the PLSR model outperformed other approaches, achieving optimal performance with three principal components. The resulting canopy volume measurement model achieved an R2 of 0.9742, an RMSE of 0.1879, and an MAE of 0.1161. These results demonstrate that the PLSR model exhibits strong generalization ability, minimal prediction bias, and low average prediction error, offering a valuable reference for precision control of canopy spraying in orchards.

Peanut (Arachis hypogaea L.) is an oilseed crop grown worldwide. Flavonoids have profound benefits for plant growth and development because of their powerful antioxidant properties. Seed vigor is an important indicator of seed quality. However, how flavonoids impact seed vigor formation in large-seed peanuts is still poorly understood. Here, we profiled flavonoids, phytohormones, and transcriptomes of developing seeds of large-seed peanut varieties with low (ZP06) and high (H8107) seed vigor. A total of 165 flavonoids were identified, 51 of which were differentially accumulated in ZP06 and H8107. Lower levels of dihydromyricetin (0.28 times) and hesperetin-7-O-glucoside (0.26 times) were observed in ZP06 seeds than in H8107. All flavonoid biosynthesis structural genes were down-regulated in ZP06. The different hormone levels found in ZP06 and H8107 seeds could be associated with the expression of flavonoid biosynthesis genes via MYB and bHLH transcription factors. Dihydromyricetin could relate to ZP06′s poor seed vigor by impacting its seed antioxidant properties. Thus, the presence of flavonoids in large-seed peanuts could contribute to their physiological quality and germination potential through controlling the accumulation of reactive oxygen species to improve seed antioxidant properties.

Gesture recognition techniques based on surface electromyography (sEMG) signals face instability problems caused by electrode displacement and the time-varying characteristics of the signals in cross-time applications. This study proposes an incremental learning framework based on densely connected convolutional networks (DenseNet) to capture non-synchronous data features and overcome catastrophic forgetting by constructing replay datasets that store data with different time spans and jointly participate in model training. The results show that, after multiple increments, the framework achieves an average recognition rate of 96.5% from eight subjects, which is significantly better than that of cross-day analysis. The density-based spatial clustering of applications with noise (DBSCAN) algorithm is utilized to select representative samples to update the replayed dataset, achieving a 93.7% recognition rate with fewer samples, which is better than the other three conventional sample selection methods. In addition, a comparison of full dataset training with incremental learning training demonstrates that the framework improves the recognition rate by nearly 1%, exhibits better recognition performance, significantly shortens the training time, reduces the cost of model updating and iteration, and is more suitable for practical applications. This study also investigates the use of the incremental learning of action classes, achieving an average recognition rate of 88.6%, which facilitates the supplementation of action types according to the demand, and further improves the application value of the action pattern recognition technology based on sEMG signals.

Multi-stage fracturing in Horizontal well increases the permeability of coalbed methane by generating multiple fractures. However, the heterogeneity of coal reservoirs is a crucial factor that cannot be ignored in the study of multiple hydraulic fracture propagation. Therefore, we established a two-dimensional model for multiple hydraulic fracture propagation based on the combined finite-discrete element method (FDEM) and assigned a Weibull distribution function to the heterogeneity of the physical parameters of the cohesive elements in the model. The objective was to simulate and study the fracture propagation law of multi-cluster fracturing in horizontal wells in heterogeneous coal reservoirs. The research results indicated that: 1) as the heterogeneity of the coal reservoir weakened, the deflection angle of the main fracture increased. More secondary fractures were generated in the coal reservoir, leading to significant discontinuity. 2) The fracturing disturbance area was always concentrated at the tip of the main fracture, with a double wing shape. However, the fracturing disturbance areas at the tips of multiple main fractures could easily converge, with a square shape; 3) It is recommended to use a moderate injection rate and increase the perforation spacing appropriately when hydraulic fracturing is carried out in coal reservoirs with a heterogeneity coefficient m=5.

In typical traffic scenarios such as non-signalized roads or shared spaces where vehicles and pedestrians interact without clear separations. The interaction distance between objects is usually shorter due to the simultaneous motion of road users. Pedestrian-crossing scenarios in these areas make the scenario complex due to the unpredictability of the pedestrians intention and the need to balance between safety, comfort, and time consumption. To address this collision avoidance(CA) problem, a novel strategy using Social Force Model (SFM)-based adaptive parameters was proposed. The interaction system between the ego vehicle and the pedestrian was simplified as a Markov process to adopt the SFM-based dynamic model, and the validity of this simplification was demonstrated using real-world driving data. Based on the current state of the interaction system that consists of vehicle and pedestrian, this research adopted the optimal parameters that were generated by particle swarm optimization (PSO) to generate optimal parameters for the SFM-based vehicle dynamic model, which helps the vehicle avoid pedestrians with random motion. The proposed method was validated through bench testing, and the results showed that the proposed method balanced the safety, comfort, and time consumption requirements during the CA process in the studied scenario.

In this paper, we give a kind of strongly regular Cayley graphs and a class of codebooks. Both constructions are based on choosing subsets of finite fields, and the main tools that we employed are Gauss sums. In particular, these obtained codebooks are asymptotically optimal with respect to the Welch bound and they have new parameters.

To investigate the compression properties and failure mechanisms of syntactic foams, two different resin matrices and three types of hollow glass microspheres (HGMs) were used to prepare syntactic foams with different properties. Results showed that the compression strength of syntactic foams increases with the increase in the compression strength of HGMs or resin matrix. Low-strength HGMs will be the first to break down as a source of cracks under stress. When the stress value exceeds the compression strength of the matrix, the matrix will deform and break, leading to the overall destruction of syntactic foam. High-strength HGMs not only act as a lightweight filler but also act as a reinforcing phase to improve the strength of the syntactic foam. The matrix located at the interface will experience initial cracking when subjected to stress, becoming the origin of subsequent cracks. Consequently, the weaker part between the HGMs and the matrix will be the initial point of failure, resulting in the formation of a crack source. The failure of the matrix will ultimately result in the complete destruction of the syntactic foam.

Shi-related sequence (SRS) proteins, which consist of the RING-like zinc finger domain and IGGH domain, are plant-specific transcription factors that have been well-studied in several plant species. However, information about SRS genes and their roles in cucumber (Cucumis sativus L.) is limited. Therefore, we performed detailed bioinformatic analysis of the SRS gene family, including gene numbers and positions, genes structures, conserved motif distribution patterns, phylogenetic analysis, and promoter cis-element analysis. Eight SRS genes were identified in cucumber and distributed on all seven cucumber chromosomes. SRS genes are conserved in plants and divided into two groups in cucumber based on their protein sequence. In silico analysis predicted that most genes may function in response to abiotic stresses and phytohormones. Gene ontology analysis predicted the possible involvement of genes in development and reproduction, and DNA and protein binding on a molecular level. Furthermore, the differential expression pattern of SRS genes in leaf, stem and root under the condition of Zn2+ stress suggested their roles in response to Zn2+ stress. Furthermore, our metal tolerance assay suggested that CsSRS2 and CsSRS5 mediated enhanced tolerance to Zn2+ stress in Escherichia coli cells. Our study provides a foundation for the functional study of SRS genes in cucumber.

Lactic acid bacteria (LAB) are the most common probiotics, and they present excellent inhibitory effects on pathogenic bacteria. This study aimed to explore the anti-biofilm potential of the purified active substance of Lactiplantibacillus plantarum, named Z102-E. The effects of Z102-E on Listeria monocytogenes were investigated in detail, and a transcriptomic analysis was conducted to reveal the anti-biofilm mechanism. The results indicated that the sub-MIC of Z102-E (3.2, 1.6, and 0.8 mg/mL) decreased the bacterial growth and effectively reduced the self-aggregation, surface hydrophobicity, sugar utilization, motility, biofilm formation, AI-2 signal molecule, contents of extracellular polysaccharides, and extracellular protein of L. monocytogenes. Moreover, the inverted fluorescence microscopy observation confirmed the anti-biofilm effect of Z102-E. The transcriptomic analysis indicated that 117 genes were up-regulated and 214 were down-regulated. Z102-E regulated the expressions of genes related to L. monocytogenes quorum sensing, biofilm formation, etc. These findings suggested that Z102-E has great application potential as a natural bacteriostatic agent.

The brick-and-mortar biomimetic structure Ti/Al3Ti metal-intermetallic laminate (BMS-MIL) composites were prepared by vacuum hot pressing. BMS-MIL composites with various Ti volume fractions from 45–71% were obtained by controlling the high-temperature diffusion time of Al–Ti. The phase composition of the BMS-MIL composites was analyzed, and the influence of Ti volume fraction on the microstructure was quantitatively characterized. Quasi-static compression and three-point bending tests were carried out to study the mechanical properties and fracture mechanism of the BMS-MIL composites. The results indicated that, in BMS-MIL composites, Al3Ti appears as polygonal platelets, and Ti fills the gaps between the platelets. With decreasing Ti volume fraction, the size of Al3Ti platelets increased, the number of platelets decreased, and the aspect ratio of platelets first increased and then decreased. The decrease of Ti volume fraction leads to the decrease of mechanical properties of composites. However, as a reasonable and efficient material design strategy, the brick-and-mortar structure ensured that the specific strength of the BMS-MIL composites with load perpendicular to the layer remained stable, with specific strength maintained between 345 and 353 kN m/kg. The compression properties with load parallel to the layer are significantly affected by the platelet's aspect ratio. The sample with 65% volume fraction Ti exhibited the optimal strength, specific strength, and failure strain when compressed parallel to the layer, with a strength of 1347.3 MPa, specific strength of 330.2 kN m/kg, and a failure strain of 6.32%.

Patients with systemic autoimmune rheumatic diseases are at a high risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and effective antiviral treatments including nirmatrelvir/ritonavir can improve their outcomes. However, there might be potential drug-drug interactions when these patients take nirmatrelvir/ritonavir together with immunosuppressants with a narrow therapeutic window, such as tacrolimus and cyclosporine. We present a case of paralytic ileus resulting from tacrolimus toxicity mediated by the use of nirmatrelvir/ritonavir in a patient with systemic lupus erythematosus (SLE). A 37-year-old female SLE patient was prescribed nirmatrelvir/ritonavir without discontinuing tacrolimus. She presented to the emergency room with symptoms of paralytic ileus including persistent abdominal pain, nausea, and vomiting, which were verified to be associated with tacrolimus toxicity. The blood concentration of tacrolimus was measured >30 ng/mL. Urgent medical intervention was initiated, while tacrolimus was withheld. The residual concentration was brought within the appropriate range and tacrolimus was resumed 8 days later. Physicians must be aware of the potential DDIs when prescribing nirmatrelvir/ritonavir, especially to those taking immunosuppresants like tacrolimus.

IntroductionIn the middle of December 2022, the Chinese government adjusted the lockdown policy on coronavirus disease 2019 (COVID-19), a large number of infected patients flooded into the emergency department. The emergency medical staff encountered significant working and mental stress while fighting the COVID-19 pandemic. We aimed to investigate the workload change, and the prevalence and associated factors for depression symptoms among emergency medical staff after the policy adjustment.MethodsWe conducted a cross-sectional online survey of emergency medical staff who fought against COVID-19 in Shandong Province during January 16 to 31, 2023. The respondents’ sociodemographic and work information were collected, and they were asked to complete the 9-item Patient Health Questionnaire (PHQ-9) then. Univariate and multivariate logistic regression analyses were applied to identify the potential associated factors for major depression.ResultsNine hundred and sixteen emergency medical personnel from 108 hospitals responded to this survey. The respondents’ weekly working hours (53.65 ± 17.36 vs 49.68 ± 14.84) and monthly night shifts (7.25 ± 3.85 vs 6.80 ± 3.77) increased after the open policy. About 54.3% of the respondents scored more than 10 points on the PHQ-9 standardized test, which is associated with depressive symptoms. In univariate analysis, being doctors, living with family members aged ≤16 or ≥ 65 years old, COVID-19 infection and increased weekly working hours after the open policy were significantly associated with a PHQ-9 score ≥ 10 points. In the multivariate analysis, only increased weekly working hours showed significant association with scoring ≥10 points.ConclusionEmergency medical staff’ workload had increased after the open policy announcement, which was strongly associated with a higher PHQ-9 scores, indicating a very high risk for major depression. Emergency medical staff working as doctors or with an intermediate title from grade-A tertiary hospitals had higher PHQ-9 scores, while COVID-19 infection and weekly working hours of 60 or more after the open policy were associated with higher PHQ-9 scores for those from grade-B tertiary hospitals. Hospital administrators should reinforce the importance of targeted emergency medical staff support during future outbreaks.

In recent years, there have been several outbreaks of extensive flooding in northern provinces. Asparagus stem blight disease and brown spot diseases have become increasingly serious, significantly reducing the yield of asparagus grown in large fields, and asparagus production has developed toward facility agriculture. To solve the problems of high labor costs, labor shortages, and low production efficiency faced by facility agriculture, the adoption of mechanized harvesting for asparagus is an inevitable trend. A prerequisite for mechanized harvesting is target detection. Compared with algorithms such as Faster R-CNN, which require the use features of candidate regions for classification and recognition and cannot meet the real-time requirements of mechanized harvesting, this paper proposes a YOLO-based asparagus recognition scheme that can quickly perform target detection with a detection accuracy of 85.45% and significantly enhanced interference resistance, which can greatly improve the production efficiency of facility agriculture and accelerate the mechanization process of facility agriculture.

Bicycles are frequently involved in traffic collisions with vehicles, particularly when sudden changes in direction occur. This paper presents a robust risk-predictive braking policy to ensure collision avoidance in all possible crossing behaviors of a bicycle. The policy controls the vehicle to follow an upper limit of the safe speed before the bicycle changes direction, ensuring that the vehicle can stop in time by the advanced emergency braking system before a collision occurs in any situation. The upper limit of the safe speed is the solution of an intractable robust optimization problem. Therefore, a scenario approach is adapted to develop a tractable approximate problem for the original robust optimization problem. The feasibility and optimality of the problem reduction are theoretically proved. A bisection method-based fast algorithm is designed to solve the approximate problem of the original robust optimization problem, making it applicable in practical scenarios. The convergence of the algorithm is also proven. The effectiveness of the proposed method is validated through hardware-in-the-loop simulations using CarMaker.

The brick-and-mortar structure of shell nacre allows for the simultaneous enhancement of strength and plasticity through the synergistic effect of multiple toughening mechanisms at different scales. In this work, a novel nacre-like brick-and-mortar structure Ti6Al4V/Al3Ti metal-intermetallic laminate (BMS-MIL) composite was successfully fabricated via vacuum hot pressing sintering method. The BMS-MIL composite is mainly composed of Al3Ti and Ti phases, with a small amount of Al2Ti and AlTi phases. Al3Ti is in the shape of polygonal platelet, and a 5–8 μm diffusion layer composed of Al2Ti and AlTi is distributed on the surface of the platelets. Ti6Al4V connects the platelets and is present in a continuous network frame structure. Compared with the layered structure Ti6Al4V/Al3Ti metal-intermetallic laminate (LS-MIL) composite, the fracture strain of BMS-MIL composite increases by 125.1% while maintaining high strength under load perpendicular to layer, and the compressive strength of BMS-MIL composite increases by 26.3% under load parallel to layer, respectively. Material isotropy in compressive properties has been significantly improved. In bending tests, the strength of the BMS-MIL composite is 1.9 times that of the LS-MIL composite. The brick-and-mortar structure’s excellent strengthening and toughening effect benefits from the enhancement of its crack constraint.

Electromagnetic continuous casting technology serves as a significant means for enhancing the casting performance of 2219 aluminum alloy. Investigating the influence of electromagnetic field variations on the solidification process is crucial for studying the microstructure and mechanical properties of electromagnetic cast billets. Through experimental research, variations in the microstructure and mechanical properties were examined for ordinary direct chill casting, as well as three different electromagnetic power casting ingots. The COMSOL software (COMSOL Multiphysics 6.0) was utilized to simulate the temperature and flow field, enabling an explanation of the resulting performance changes. The results showed the effect on electromagnetic continuous casting technology by the electromagnetic field generated by the Lorentz force and melt stirring, improving the melt flow and temperature distribution so that the melt center and the edge of the melt forcible convection were enhanced, thus realizing the tissue refinement, mechanical properties, and Cu element segregation of the improvement. With an increase in electromagnetic power, the distribution of the temperature field was more homogeneous, the segregation phenomenon was more alleviated, and the improvement in mechanical properties was more significant. The optimal microstructure and mechanical properties were achieved at a power of 20.0 kW, with a 74.7% improvement in grain refinement in the center and a tensile strength increase of 30.8%. Additionally, significant improvements were observed in segregation phenomena.

To study the inhibitory effects of Enterococcus faecalis Z096 on the biofilm and quorum sensing (QS) system of Vibrio parahaemolyticus, the competition, elimination and exclusion were performed to simulate the interaction between Z096 and V. parahaemolyticus in microbial communities. In addition, the effects of Z096 extract (Z096-E) on V. parahaemolyticus biofilm formation, mature biofilm elimination, cell surface hydrophobicity, auto-aggregation, QS signal molecule AI-2 activity, motility ability (swarming and swimming), extracellular polysaccharide and protein synthesis were further explored. The results showed that Z096 could significantly reduce the number of V. parahaemolyticus cells in plankton and biofilm by competition, elimination and exclusion, and interfere with the adhesion of V. parahaemolyticus on the carrier surface. Moreover, Z096-E could significantly inhibit biofilm formation and effectively eliminate the mature biofilm of V. parahaemolyticus. When treated with 1.6 mg/mL of Z096-E for 12 h, the biofilm inhibition rate was 70.43%, and the metabolic activity decreased by 84.15%; When the mature biofilm of V. parahaemolyticus was treated with 12.8 mg/mL of Z096-E for 4 h, the biofilm removing rate was 58.21%, and the metabolic activity decreased by 69.84%. The swarming and swimming ability, cell surface hydrophobicity and auto-aggregation, extracellular polysaccharide and protein synthesis of V. parahaemolyticus were inhibited by 1.6 mg/mL of Z096-E by 47.26%, 53.56%, 63.37%, 89.38%, 77.65% and 51.91%, respectively, and the inhibitory effect was dose-dependent. In addition, Z096-E weakened the activity of QS signal molecule AI-2 of V. parahaemolyticus, indicating that Z096-E was an AI-2 quorum sensing inhibitor, which could affect the physiological characteristics of V. parahaemolyticus by interfering with the QS system. Therefore, we found one strain of lactic acid bacteria (LAB) that could inhibit V. parahaemolyticus biofilm, and the Z096-E could be used as a novel LAB-based biological agent to prevent and control V. parahaemolyticus biofilm. This study would be of positive significance to eliminate V. parahaemolyticus biofilm pollution and develop novel antibacterial agents.

Summary: Cytosine methylation is an important epigenetic modification involved in regulation of plant development. However, the epigenetic mechanisms governing peanut seed development remain unclear. Herein, we generated DNA methylation profiles of developmental seeds of peanut H2014 and its smaller seed mutant H1314 at 15 and 60 days after pegging (DAP, S1, S4). Accompanying seed development, globally elevated methylation was observed in both lines. The mutant had a higher methylation level of 31.1% than wild type at S4, and 27.1–35.9% of the differentially methylated regions (DMRs) between the two lines were distributed in promoter or genic regions at both stages. Integrated methylome and transcriptome analysis revealed important methylation variations closely associated with seed development. Furthermore, some genes showed significantly negative correlation of expression with the methylation level within promoter or gene body. The results provide insights into the roles of DNA methylation in peanut seed development.

Peanut (Arachis hypogea L.) bacterial wilt (BW) is a devastating disease caused by Ralstonia solanacearum that results in severe yield and quality losses. Plant defensins are short cysteine-rich peptides with antimicrobial activity. The role of defensin genes (AhDef) in peanut is unclear. A genome-wide investigation of AhDef genes was undertaken, and 12 identified AhDef genes were classified into two groups containing the gamma-thionin domain formed by four disulfide pairs: Cys1-Cys8, Cys2-Cys5, Cys3-Cys6, and Cys4-Cys7. In silico analysis revealed that AhDef genes showed highly conserved architectural features and contained cis-elements associated with phytohormone signaling and defense responses. A highly resistant cultivar, H108 (R) and a susceptible accession, H107 (S) were tested by R. solanacearum inoculation. H108 (R) showed fewer symptoms than H107 (S) owing to inhibition of bacterial reproduction and spread in the vascular bundles of roots and stems. In a transcriptomic expression profile, AhDef genes, particularly AhDef1.6 and AhDef2.2, were up-regulated in H108 (R) compared with H107 (S) under R. solanacearum infection and phytohormone treatment. Subcellular localization showed that the AhDef1.6 and AhDef2.2 proteins were both expressed specifically on the plasma membrane. Overexpression of protein fusion AhDef2.2-YFP in Nicotiana benthamiana and peanut leaves increased resistance to R. solanacearum, suggesting its role in response to BW infection. AhDef2.2 may be valuable for peanut resistance breeding.

The quenching effects of ethyl acetate extract of Lactobacillus pentosus DF9 as quorum sensing inhibitor on the quorum sensing (QS) of Vibrio parahaemolyticus were studied. Based on determining the effects of DF9-QSI on the growth of V. parahaemolyticus and V. harveyi BB170, the effects of DF9-QSI at sub-inhibitory concentration on QS signal molecule AI-2 activity, motility (swarming, swimming and twitching), biofilm formation and extracellular polysaccharide (EPS) synthesis of V. parahaemolyticus were investigated. The results showed that DF9-QSI had no effect on the growth of V. parahaemolyticus at the concentration lower than 0.8 mg/mL, but effectively reduced the AI-2 activity, and inhibited the movement, biofilm formation and EPS synthesis of V. parahaemolyticus in a concentration-dependent manner. The destructive effects of DF9-QSI on biofilms were further confirmed by the observations using optical microscope, scanning electron microscope and laser confocal microscope. These results indicated that DF9-QSI possessed AI-2 QS quenching activity, which might provide the theoretical basis for developing a novel QSI from lactic acid bacteria, and supply the potential microbial resources for controlling QS system of V. parahaemolyticus.

Phosphorothioate (PT) modification by the dnd gene cluster is the first identified DNA backbone modification and has been shown to constitute a multifunctional epigenetic system. Despite a variety of advantages for hosting dnd systems, these systems are surprisingly distributed sporadically among contemporary microbial genomes. To address this ecological paradox, Jian et al. systematically investigated the occurrence and phylogeny of dnd systems in prokaryotes, and provided evidence to suggest that dnd systems have originated in ancient Cyanobacteria (probably Nostocales) after the Great Oxygenation Event.

Abstract Background Three-dimensional (3D) chromatin organization provides a critical foundation to investigate gene expression regulation and cellular homeostasis. Results Here, we present the first 3D genome architecture maps in wild type and mutant allotetraploid peanut lines, which illustrate A/B compartments, topologically associated domains (TADs), and widespread chromatin interactions. Most peanut chromosomal arms (52.3%) have active regions (A compartments) with relatively high gene density and high transcriptional levels. About 2.0% of chromosomal regions switch from inactive to active (B-to-A) in the mutant line, harboring 58 differentially expressed genes enriched in flavonoid biosynthesis and circadian rhythm functions. The mutant peanut line shows a higher number of genome-wide cis-interactions than its wild-type. The present study reveals a new TAD in the mutant line that generates different chromatin loops and harbors a specific upstream AP2EREBP-binding motif which might upregulate the expression of the GA2ox gene and decrease active gibberellin (GA) content, presumably making the mutant plant dwarf. Conclusions Our findings will shed new light on the relationship between 3D chromatin architecture and transcriptional regulation in plants.

The supply chain of Agaricus bisporus constitutes a complex, multi-layered production and distribution network, encompassing various stages. Challenges in information transmission and process integration between these stages often lead to reduced query efficiency, subsequently compromising the credibility of traceability results and the flexibility of the system. In traditional traceability systems, data for multiple service recipients may be stored on a single blockchain, resulting in complex data structures and making it challenging for users to conduct effective queries and analyses. To address this issue, this paper proposes a solution: a multi-chain tracing model tailored for stakeholders in the traceability process of Agaricus bisporus. This model establishes public chains, enterprise chains, and supervision chains for consumers, enterprises, and regulatory authorities, respectively, to enhance system storage and query efficiency. Additionally, leveraging the modular design of Hyperledger Fabric, the paper optimizes and upgrades the supply chain of Agaricus bisporus. The proposed multi-chain tracing model, designed for traceability for stakeholders, undergoes rigorous validation. Analysis and application results demonstrate that this approach significantly improves the query efficiency and credibility of traceability information while markedly enhancing system flexibility.

Abstract Background Tuberculous meningitis (TBM) is the most lethal form of tuberculosis worldwide. Data on critically ill TBM patients in the intensive care unit (ICU) of China are lacking. We tried to identify prognostic factors of adult TBM patients admitted to ICU in China. Methods We conducted a retrospective study on adult TBM in ICU between January 2008 and April 2018. Factors associated with unfavorable outcomes at 28 days were identified by logistic regression. Factors associated with 1-year mortality were studied by Cox proportional hazards modeling. Results Eighty adult patients diagnosed with TBM (age 38.5 (18–79) years, 45 (56 %) males) were included in the study. An unfavorable outcome was observed in 39 (49 %) patients and were independently associated with Acute Physiology and Chronic Health Evaluation (APACHE) II > 23 (adjusted odds ratio (aOR) 5.57, 95 % confidence interval (CI) 1.55–19.97), Sequential Organ Failure Assessment (SOFA) > 8 (aOR 9.74, 95 % CI 1.46–64.88), and mechanical ventilation (aOR 18.33, 95 % CI 3.15–106.80). Multivariate Cox regression analysis identified two factors associated with 1-year mortality: APACHE II > 23 (adjusted hazard ratio (aHR) 4.83; 95 % CI 2.21–10.55), and mechanical ventilation (aHR 9.71; 95 % CI 2.31–40.87). Conclusions For the most severe adult TBM patients of Medical Research Council (MRC) stage III, common clinical factors aren’t effective enough to predict outcomes. Our study demonstrates that the widely used APACHE II and SOFA scores on admission can be used to predict short-term outcomes, while APACHE II could also be used to predict long-term outcomes of adult patients with TBM in ICU.

The rapid development of Internet of Things (IoT) communication devices has brought about significant convenience. However, simultaneously, the destruction of communication infrastructure in emergency situations often leads to communication disruptions and challenges in information dissemination, severely impacting rescue operations and the safety of the affected individuals. To address this challenge, IoT big data analytics and unmanned aerial vehicle (UAV) technologies have emerged as key elements in the solution. By analyzing large-scale sensor data, user behavior, and communication traffic, IoT big data analytics can provide real-time communication demand prediction and network optimization strategies, offering decision support for post-disaster communication reconstruction. Given the unique characteristics of post-disaster scenarios, this paper proposes a UAV-assisted communication coverage strategy based on IoT big data analytics. This strategy employs UAVs in a cruising manner to assist in communication by partitioning the target area into multiple cells, each satisfying the minimum data requirements for user communication. Depending on the distribution characteristics of users, flight–communication or hover-communication protocols are selectively employed to support communication. By optimizing the UAV’s flight speed and considering the coverage index, fairness index, and average energy efficiency of the mission’s target area, the Inner Spiral Cruise Communication Coverage (IS-CCC) algorithm is proposed to plan the UAV’s cruising trajectory and achieve UAV-based communication coverage. Simulation results demonstrate that this strategy can achieve energy-efficient cruising communication coverage in regions with complex user distributions, thereby reducing energy consumption in UAV-based communication.

The effect of the distribution of the primary phase Si and TiB2 particles in the hypereutectic Al-Si alloy was studied and found to be influenced by the cooling rate. Therefore, this article studies the effect of the cooling rate on the multi-phase structure of TiB2 particles in Al-20Si using a wedge-shaped mold. The sizes, shapes, and distribution of primary phase Si and TiB2 particles inside primary phase Si were observed through SEM. The effect of TiB2 particles on cracks in primary phase Si was studied using nanoindentation technology, and the interface relationship between primary Si and TiB2 was studied using TEM. Finally, based on the experimental results, the trapping mechanism of primary Si for TiB2 particles is discussed. The results indicate that the faster the cooling rate, the finer and more uniform the size distribution of the primary Si phase in the structure. TiB2 mostly exists as individual particles. Moreover, the pushing rate of the solid–liquid interface during solidification is faster, resulting in more TiB2 particles being engulfed by the primary Si phase.

In cross-border transactions, the transmission and processing of logistics information directly affect the trading experience and efficiency. The use of Internet of Things (IoT) technology can make this process more intelligent, efficient, and secure. However, most traditional IoT logistics systems are provided by a single logistics company. These independent systems need to withstand high computing loads and network bandwidth when processing large-scale data. Additionally, due to the complex network environment of cross-border transactions, the platform’s information security and system security are difficult to guarantee. To address these challenges, this paper designs and implements an intelligent cross-border logistics system platform that combines serverless architecture and microservice technology. This system can uniformly distribute the services of all logistics companies and divide microservices based on actual business needs. It also studies and designs corresponding Application Programming Interface (API) gateways to solve the interface exposure problem of microservices, thereby ensuring the system’s security. Furthermore, asymmetric encryption technology is used in the serverless architecture to ensure the security of cross-border logistics data. The experiments show that this research solution validates the advantages of combining serverless architecture and microservices, which can significantly reduce the operating costs and system complexity of the platform in cross-border logistics scenarios. It allows for resource expansion and billing based on application program requirements at runtime. The platform can effectively improve the security of cross-border logistics service processes and meet cross-border transaction needs in terms of data security, throughput, and latency.

Herein we performed bioinformatics analysis of patatin-like protein (PLP) family genes, including gene numbers, gene structure, chromosomal distribution, and expression levels, in order to establish a theoretical foundation for genes encoding PLPs in peanut (Arachis hypogaea L.). In total, 49 PLP family members were identified: 26 in A. hypogaea, 11 in A. duranansis (AA), and 12 in A. ipaënsis (BB). They were classified into four categories (class II, III, V and VI), and unevenly distributed on 20 chromosomes. Gene structure analysis revealed that the exon numbers varied from 2 to 14, and the length of amino acid ranged from 157 to 812 aa with isoelectric point (pI) ranged from 4.55 to 8.74. All the PLP family members contained the conserved patatin-like phospholipase domain, but none of them contained signal peptides, and only four contained transmembrane domains. Promoter analysis showed that PLP-encoding genes contained cis-acting regulatory elements related to hormone responses, environmental adaptability and stress response induction. RNA-seq data showed that these genes were expressed under different spatiotemporal conditions. The relative expression levels of PLP-encoding genes in different tissues were detected using quantitative real-time polymerase chain reaction (qRT-PCR). AhPLP1 and AhPLP10 expression levels in flowers were relatively high, while AhPLP4 expression level in roots, stems, and flowers was extremely low, which indicated the potential functions of PLPs in peanut.

Abstract Background Corticoid therapy has been recommended in the treatment of critically ill patients with COVID-19, yet its efficacy is currently still under evaluation. We investigated the effect of corticosteroid treatment on 90-day mortality and SARS-CoV-2 RNA clearance in severe patients with COVID-19. Methods 294 critically ill patients with COVID-19 were recruited between December 30, 2019 and February 19, 2020. Logistic regression, Cox proportional-hazards model and marginal structural modeling (MSM) were applied to evaluate the associations between corticosteroid use and corresponding outcome variables. Results Out of the 294 critically ill patients affected by COVID-19, 183 (62.2%) received corticosteroids, with methylprednisolone as the most frequently administered corticosteroid (175 accounting for 96%). Of those treated with corticosteroids, 69.4% received corticosteroid prior to ICU admission. When adjustments and subgroup analysis were not performed, no significant associations between corticosteroids use and 90-day mortality or SARS-CoV-2 RNA clearance were found. However, when stratified analysis based on corticosteroid initiation time was performed, there was a significant correlation between corticosteroid use (≤ 3 day after ICU admission) and 90-day mortality (logistic regression adjusted for baseline: OR 4.49, 95% CI 1.17–17.25, p = 0.025; Cox adjusted for baseline and time varying variables: HR 3.89, 95% CI 1.94–7.82, p

Abstract Background Long noncoding RNAs (lncRNAs) have several known functions involving various biological regulatory processes in plant. However, the possible roles of lncRNAs during peanut seed development have not been fully explored. Results In this study, two peanut recombinant inbred lines (RIL8) that differ in seed size were used to investigate comprehensive lncRNA profiles derived from the seed development at 15 and 35 days after flowering (DAF). We identified a total of 9388 known and 4037 novel lncRNAs, from which 1437 were differentially expressed lncRNAs. Interestingly, the expression patterns of a number of lncRNAs can be very different between two closely related inbred lines and these lncRNAs were expressed predominantly in only one RIL at 35 DAF. Some differentially expressed lncRNAs were found related to putative cis-acting target genes and predicted to be involved in transcription, transport, cell division, and plant hormone biosynthesis. The expression patterns of several representative lncRNAs and 12 protein-coding genes were validated by qPCR. Same expression pattern was observed between most lncRNAs and their target genes. 11 lncRNAs, XR_001593099.1, MSTRG.18462.1, MSTRG.34915.1, MSTRG.41848.1, MSTRG.22884.1, MSTRG.12404.1, MSTRG.26719.1, MSTRG.35761.1, MSTRG.20033.1, MSTRG.13500.1, and MSTRG.9304.1 and their cis-acting target genes may play key roles in peanut seed development. Conclusions These results provided new information on lncRNA-mediated regulatory roles in peanut seed development, contributing to the comprehensive understanding of the molecular mechanisms involved in peanut seed development.

Abstract Background In December 2019, coronavirus disease 2019 (COVID-19) outbreak was reported from Wuhan, China. Information on the clinical course and prognosis of COVID-19 was not thoroughly described. We described the clinical courses and prognosis in COVID-19 patients. Methods Retrospective case series of COVID-19 patients from Zhongnan Hospital of Wuhan University in Wuhan and Xishui Hospital, Hubei Province, China, up to February 10, 2020. Epidemiological, demographic, and clinical data were collected. The clinical course of survivors and non-survivors were compared. Risk factors for death were analyzed. Results A total of 107 discharged patients with COVID-19 were enrolled. The clinical course of COVID-19 presented as a tri-phasic pattern. Week 1 after illness onset was characterized by fever, cough, dyspnea, lymphopenia, and radiological multi-lobar pulmonary infiltrates. In severe cases, thrombocytopenia, acute kidney injury, acute myocardial injury, and adult respiratory distress syndrome were observed. During week 2, in mild cases, fever, cough, and systemic symptoms began to resolve and platelet count rose to normal range, but lymphopenia persisted. In severe cases, leukocytosis, neutrophilia, and deteriorating multi-organ dysfunction were dominant. By week 3, mild cases had clinically resolved except for lymphopenia. However, severe cases showed persistent lymphopenia, severe acute respiratory dyspnea syndrome, refractory shock, anuric acute kidney injury, coagulopathy, thrombocytopenia, and death. Older age and male sex were independent risk factors for poor outcome of the illness. Conclusions A period of 7–13 days after illness onset is the critical stage in the COVID-19 course. Age and male gender were independent risk factors for death of COVID-19.

This paper, for the first time, reports an electrically inspired flexible electrochemical film power supply for long-term epidermal sensors. This device can periodically provide electrical power for several hours after a short-time electrical activation. The electrical activation makes acetylcholine, which is infused into the subcutaneous tissue by iontophoresis. The interstitial fluid (ISF) with glucose molecules is then permeated autonomously for several hours. At this period, the device can provide electrical power. The electrical power is generated from the catalyzing reaction between the glucose oxidase immobilized on the anode and the permeated glucose molecules. After the ISF permeation stops, we give a short-time electrical activation to provide electrical power for several hours again. The power supply is flexible, which makes it adaptively conform to skin. The episodic short-time electrical activation can be enabled by an integrated small film lithium-ion battery. This method extends the service life of a lithium-ion battery 10-fold and suggests the application of small lithium-ion batteries for long-term epidermal sensors.

Aiming at the problem that the existing crowd counting methods cannot achieve accurate crowd counting and map visualization in a large scene, a crowd density estimation and mapping method based on surveillance video and GIS (CDEM-M) is proposed. Firstly, a crowd semantic segmentation model (CSSM) and a crowd denoising model (CDM) suitable for high-altitude scenarios are constructed by transfer learning. Then, based on the homography matrix between the video and remote sensing image, the crowd areas in the video are projected to the map space. Finally, according to the distance from the crowd target to the camera, the camera inclination, and the area of the crowd polygon in the geographic space, a BP neural network for the crowd density estimation is constructed. The results show the following: (1) The test accuracy of the CSSM was 96.70%, and the classification accuracy of the CDM was 86.29%, which can achieve a high-precision crowd extraction in large scenes. (2) The BP neural network for the crowd density estimation was constructed, with an average error of 1.2 and a mean square error of 4.5. Compared to the density map method, the MAE and RMSE of the CDEM-M are reduced by 89.9 and 85.1, respectively, which is more suitable for a high-altitude camera. (3) The crowd polygons were filled with the corresponding number of points, and the symbol was a human icon. The crowd mapping and visual expression were realized. The CDEM-M can be used for crowd supervision in stations, shopping malls, and sports venues.

Internet of Things (IoT) finance extends financial services to the whole physical commodity society with the help of IoT technology to realize financial automation and intelligence. However, the security of IoT finance still needs to be improved. Blockchain has the characteristics of decentralization, immutability, faster settlement, etc., and has been gradually applied to the field of IoT finance. Blockchain is also considered to be an effective way to resolve the problems of the traditional supply chain finance industry, such as the inability to transmit core enterprise credit, the failure of full-chain business information connections and the difficulty of clearing and settlement. Supply chain finance allows the strongest enterprise in the supply chain to apply for credit guarantee from the bank to obtain bank loans, and use the funds for circulation in the supply chain to ensure that each enterprise in the whole supply chain can obtain working capital to realize profits, so as to maximize common interests. In this paper, a financial management platform based on the integration of blockchain and supply chain has been designed and implemented. Blockchain is used to integrate supply chain finance to synchronize the bank account payment system, realize the automatic flow of funds, process supervision and automatically settle account periods based on smart contracts. The four functional modules of the system are designed using unified modeling language (UML), and the model view controller (MVC) architecture is selected as the main architecture of the system. The results of the system test show that the proposed platform can effectively improve the system security, and can use the information in the blockchain to provide multi-level financing services for enterprises in supply chain finance.

Auxin response factors (ARFs) are transcription factors that regulate the expression of auxin response genes, and have important functions in plant growth and development. In this study, available genome data for peanut (Arachis hypogaea L.) were used to identify AhARF genes. In total, 61 AhARFs and 23 AtARFs were divided into six groups (I–VI). Molecular structural analysis revealed that the protein members of AhARF contain at least two domains, the B3 domain and the Auxin-resp domain, and that some have a C-terminal dimerisation domain. Screening of the transcriptome data of 22 tissues of A. hypogaea cv. Tifrunner in a public database showed high expression levels of AhARF2 and AhARF6. AhARF6 was expressed more highly in the stem and branch than in the root and leaf of the wild species Arachis monticola (A. mon) and cultivated species H103. After treatment with exogenous auxin (NAA), the expression of AhARF6 was inhibited, and this inhibition was greater in A. mon than in H103. The transcriptome map revealed that the expression of AhARF6 was higher in the larger pods of H8107 and ZP06 than in the medium pods of H103 and small pods of A. mon. Moreover, AhARF6-5 was proven to be localised in the nucleus, consistent with the location of AtARF6. These results suggest that AhARF6 may play an important role in pod development in peanut.

In rhizospheres, chemical barrier-forming natural compounds play a key role in preventing pathogenic bacteria from infecting plant roots. Here, we sought to identify specific phenolic exudates in tobacco (Nicotiana tobaccum) plants infected by the soil-borne pathogen Ralstonia solanacearum that may exhibit antibacterial activity and promote plant resistance against pathogens. Among detected phenolic acids, only caffeic acid was significantly induced in infected plants by R. solanacearum relative to healthy plants, and the concentration of caffeic acid reached 1.95 μg/mL. In vivo, caffeic acid at 200 μg/mL was highly active against R. solanacearum and obviously damaged the membrane structure of the R. solanacearum cells, resulting in the thinning of the cell membrane and irregular cavities in cells. Moreover, caffeic acid significantly inhibited biofilm formation by repressing the expression of the lecM and epsE genes. In vitro, caffeic acid could effectively activate phenylalanine ammonia-lyase (PAL) and peroxidase (POD) and promote the accumulation of lignin and hydroxyproline. In pot and field experiments, exogenous applications of caffeic acid significantly reduced and delayed the incidence of tobacco bacterial wilt. Taken together, all these results suggest that caffeic acid played a crucial role in defending against R. solanacearum infection and was a potential and effective antibacterial agent for controlling bacterial wilt.

Abstract Background Circular RNAs (circRNAs), a class of widely expressed endogenous regulatory RNAs, are involved in diverse physiological and developmental processes in eukaryotic cells. However, there have been no related studies on the number of circRNAs and their overall characteristics including circRNA abundance and expression profiles in peanut, which is one of the most important edible oil seed crops in the world. Results We performed a genome-wide identification of circular RNAs using ribosomal-depleted RNA-sequencing from the seeds of two peanut eighth-generation recombinant inbred lines (RIL8): ‘RIL 8106’ (a medium-pod variety) and ‘RIL 8107’ (a super-pod variety), at 15 and 35 days after flowering (DAF), respectively. A total of 347 circRNA candidates were detected by two computational pipelines: CIRCexplorer and CIRI, with at least two supporting junction reads. All these circRNAs were generated from exons of annotated genes, and widespread on the 20 peanut chromosomes. The expression profiles revealed that circRNAs were differentially expressed between two stages and between two lines. GO enrichment analysis of the host genes produced differentially-expressed circRNAs suggested that circRNAs are involved in seed development and regulation of seed size. Fifteen circRNAs were experimentally analyzed by qRT-PCR with divergent primers, and six circRNAs were resistant to digestion with RNase R exonuclease, and the back-splicing sites were further validated by Sanger DNA sequencing. Conclusions We present the first systematical investigation of the genomic characteristics and expression profiles of circRNAs in peanut. The results revealed that circRNAs are abundant and widespread in peanut, and the differentially-expressed circRNAs between two lines suggested that they might play regulatory roles in peanut seeds development.

Although microRNAs have been validated to play prominent roles in the occurrence and development of human bladder cancer (BC), alterations and function of many microRNAs (miRNAs) in bladder cancer invasion are not fully explored yet. miR-146b was reported to be a tumor suppressor or oncomiRNA in various types of cancer. However, its accurate expression, function, and mechanism in bladder cancer remain unclear. Here we discovered that miR-146b was frequently upregulated in bladder cancer tissues compared with adjacent non-cancerous tissues. Inhibition of miR-146b resulted in a significant inhibitory effect on the invasion of bladder cancer cells by reducing mmp2 mRNA transcription and protein expression. We further demonstrated that knockdown of miR-146b attenuated ETS2 expression, which was the transcription factor of matrix metalloproteinase (MMP)2. Moreover, mechanistic studies revealed that miR-146b inhibition stabilized ARE/poly(U)-binding/degradation factor 1 (auf1) mRNA by directly binding to its mRNA 3′ UTR, further reduced ets2 mRNA stability, and finally inhibited mmp2 transcription and attenuated bladder cancer invasion abilities. The identification of the miR-146b/AUF1/ETS2/MMP2 mechanism for promoting bladder cancer invasion provides significant insights into understanding the nature of bladder cancer metastasis. Targeting the pathway described here may be a novel approach for inhibiting invasion and metastasis of bladder cancer. Keywords: miR-146b, human bladder cancer invasion, MMP2, AUF1, ETS2

Seed size/weight, a key domestication trait, is also an important selection target during peanut breeding. However, the mechanisms that regulate peanut seed development are unknown. We re-sequenced 12 RNA samples from developing seeds of two cultivated peanut accessions (Lines 8106 and 8107) and wild Arachis monticola at 15, 30, 45, and 60 days past flowering (DPF). Transcriptome analyses showed that ∼36,000 gene loci were expressed in each of the 12 RNA samples, with nearly half exhibiting moderate (2 ≤ FPKM < 10) expression levels. Of these genes, 12.2% (4,523) were specifically expressed during seed development, mainly at 15 DPF. Also, ∼12,000 genes showed significant differential expression at 30, 45, and/or 60 DPF within each of the three peanut accessions, accounting for 31.8–34.1% of the total expressed genes. Using a method that combined comprehensive transcriptome analysis and previously mapped QTLs, we identified several candidate genes that encode transcription factor TGA7, topless-related protein 2, IAA-amino acid hydrolase ILR1-like 5, and putative pentatricopeptide repeat-containing (PPR) protein. Based on sequence variations identified in these genes, SNP markers were developed and used to genotype both 30 peanut landraces and a genetic segregated population, implying that EVM0025654 encoding a PPR protein may be associated with the increased seed size/weight of the cultivated accessions in comparison with the allotetraploid wild peanut. Our results provide additional knowledge for the identification and functional research into candidate genes responsible for the seed size/weight phenotype in peanut.

Vibrio parahaemolyticus is a widespread foodborne pathogen that causes serious seafood-borne gastrointestinal infections. Biofilm and quorum sensing (QS) are critical in regulating these infections. In this study, first, the ability of Lactiplantibacillus plantarum Z057 to compete, exclude, and displace V. parahaemolyticus biofilm was evaluated. Then, the inhibitory effects of L. plantarum Z057 extract (Z057-E) on V. parahaemolyticus biofilm and QS were explored from the aspects of biofilm biomass, metabolic activity, physicochemical properties, extracellular polymer matrix content, QS signal AI-2 activity, biofilm microstructure, and the expression levels of biofilm and QS-related genes. Results showed that L. plantarum Z057 effectively inhibited biofilm formation of V. parahaemolyticus and interfered with the adhesion of V. parahaemolyticus on the carrier surface. In addition, the Z057-E could significantly reduce the biofilm biomass, metabolic activity, hydrophobicity, auto-aggregation ability, swimming and swarming migration diameter, AI-2 activity, extracellular polysaccharide (EPS), and extracellular protein content of V. parahaemolyticus. Fluorescence microscope and scanning electron microscope (SEM) images demonstrated that the Z057-E could efficiently inactivate the living cells, destroy the dense and complete biofilm architectures, and reduce the essential component of the extracellular polymer matrix. Real-time fluorescence quantitative PCR revealed that the Z057-E treatment down-regulated the expression of flagellum synthesis-related genes (flaA, flgM), EPS, and extracellular protein synthesis-related genes (cpsA, cpsQ, cpsR, ompW), QS-related genes (luxS, aphA, opaR), and hemolysin secretion-related genes (toxS, toxR) of V. parahaemolyticus. Thus, our results suggested that L. plantarum Z057 could represent an alternative biocontrol strategy against foodborne pathogens with anti-adhesive, antibiofilm, and antiquorum sensing activities.

This study investigated the feasibility to improve the emulsifying capacity of chicken liver (CL) protein using different isoelectric solubilization/precipitation (ISP) processes. The CL proteins were first solubilized at alkaline pH 10.5, 11.0, 11.5, and 12.0, followed by precipitation at pH 5.0, 5.5, and 6.0, respectively. Fresh CL paste was set as the control (raw). With the increase in solubilization pH, the protein recovery yield increased under the same precipitation pH, and the pH 12.0, 5.5 treatment obtained the highest recovery yield of 82% (p < 0.05), followed by the pH 5.0 precipitation treatments and the pH 12.0, 6.0 treatment. The particle size distribution of D3,2 and D4,3 was smaller for the pH 10.5 (except for the D4,3 of pH 10.5, 5.0) and pH 11.0 solubilization treatments than those of the other treatments (p < 0.05), regardless of precipitation pH. Compared with that of the raw control, the emulsions of the pH 10.5 and pH 11.0 solubilization treatments, and pH 12.0, 6.0 treatment showed good stability. The pH 10.5, 6.0 treatment showed the best emulsification activity, followed by the pH 10.5, 5.5, pH 11.0, 6.0, pH 12.0, 6.0, pH 10.5, 5.0, pH 11.0, 5.5, and pH 11.0, 5.0 treatments, which were uniformly distributed and were stable without the stratification of emulsions. It was concluded that CL protein recovered through suitable ISP showed potential as an emulsifier, and thus expanded the application of CL protein for human consumption.