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Abstract Plasma membrane lysis is an effective anticancer strategy, which mostly relying on soluble molecular membranolytic agents. However, nanomaterial-based membranolytic agents has been largely unexplored. Herein, we introduce a mesoporous membranolytic nanoperforators (MLNPs) via a nano- and molecular-scale multi-patterning strategy, featuring a spiky surface topography (nanoscale patterning) and molecular-level periodicity in the spikes with a benzene-bridged organosilica composition (molecular-scale patterning), which cooperatively endow an intrinsic membranolytic activity. Computational modelling reveals a nanospike-mediated multivalent perforation behaviour, i.e., multiple spikes induce nonlinearly enlarged membrane pores compared to a single spike, and that benzene groups aligned parallelly to a phospholipid molecule show considerably higher binding energy than other alignments, underpinning the importance of molecular ordering in phospholipid extraction for membranolysis. Finally, the antitumour activity of MLNPs is demonstrated in female Balb/c mouse models. This work demonstrates assembly of organosilica based bioactive nanostructures, enabling new understandings on nano-/molecular patterns co-governed nano-bio interaction.

Abstract Background This study was performed to analyze the clinical effect of different concentrations of ropivacaine in the labor analgesia of the dural puncture epidural (DPE) technique for obese puerperae. Methods One hundred and fifty first-term obese women who received vaginal delivery and required labor analgesia in our hospital were selected prospectively for this study, and divided into groups A, B, and C. The three groups of puerpera were given epidurals with different concentrations of ropivacaine (0.075%, 0.10%, and 0.125%) with sufentanil (0.5 μg/ml) for the labor analgesia regimen. The visual analog scale (VAS), Ramsay scale, and Bromage scale of puerperae before analgesia and at different time points after anesthesia, and analgesic onset time, analgesia time, first PCEA time, PCEA pressing time, ropivacaine consumption, labor time, maternal blood pressure and heart rate, maternal adverse reactions, blood gas analysis in the neonatal umbilical artery, and Apgar score were observed. Results The analgesia onset time, PCEA pressing time, and ropivacaine consumption in group C were lower and the analgesia time and the first PCEA time were longer than those in groups A and B. At T1-T3 and T5, VAS scores of group A were higher than those in groups B and C, Ramsay score of group A was lower than that of groups B and C at T2–T3, and Bromage score of group C at any time point was higher than other two groups. The time of the second stage of labor in groups B and C was longer than that in group A, which in group C was longer than that in group B. Compared with groups A and C, the blood pressure and heart rate of puerperae in group B were closer to normal values. Three different concentrations of ropivacaine had no significant effect on the umbilical artery blood gas analysis indices and Apgar scores at 1st minute and 5th minute in neonates. The incidence of maternal adverse reactions in group C was lower than those in groups A and B. Conclusion 0.1% ropivacaine combined with 0.5 μg/ml sufentanil through DPE technique has good analgesic efficacy and few adverse effects in obese puerperae.

Abstract The capacity to identify small amounts of pathogens in real samples is extremely useful. Herein, we proposed a sensitive platform for detecting pathogens using cyclic DNA nanostructure@AuNP tags (CDNA) and a cascade primer exchange reaction (cPER). This platform employs wheat germ agglutinin-modified Fe3O4@Au magnetic nanoparticles (WMRs) to bind the E. coli O157:H7, and then triggers the cPER to generate branched DNA products for CDNA tag hybridization with high stability and amplified SERS signals. It can identify target pathogens as low as 1.91 CFU/mL and discriminate E. coli O157:H7 in complex samples such as water, milk, and serum, demonstrating comparable or greater sensitivity and accuracy than traditional qPCR. Moreover, the developed platform can detect low levels of E. coli O157:H7 in mouse serum, allowing the discrimination of mice with early-stage infection. Thus, this platform holds promise for food analysis and early infection diagnosis.

Drought stress limits agricultural productivity worldwide. Identifying and characterizing genetic components of drought stress-tolerance networks may improve crop resistance to drought stress. We show that the regulatory module formed by miR166 and its target gene, ATHB14-LIKE, functions in the regulation of drought tolerance in soybean (Glycine max). Drought stress represses the accumulation of miR166, leading to upregulation of its target genes. Optimal knockdown of miR166 in the stable transgenic line GmSTTM166 conferred drought tolerance without affecting yield. Expression of ABA signaling pathway genes was regulated by the miR166-mediated regulatory pathway, and ATHB14-LIKE directly activates some of these genes. There is a feedback regulation between ATHB14-LIKE and MIR166 genes, and ATHB14-LIKE inhibits MIR166 expression. These findings reveal that drought-triggered regulation of the miR166-mediated regulatory pathway increases plants drought resistance, providing new insights into drought stress regulatory network in soybean.

One of the key challenge faced by space-based network is how to maximize the demand for on-board resources for ground communication tasks, given the limited availability of satellite resources. For this challenge, firstly, we propose a joint state space of satellite task requirements and resource pools to obtain the global information of the environment, avoiding convergence to local optimal strategies. Secondly, we propose a new joint partitioning method for frequency and time resources, which avoids the fragmentation of the resource to the maximum extent. Thirdly, a new algorithm called dynamic weight based soft actor critic (DWSAC) is proposed, which enhances the update range when the actions taken by the agent significantly contribute to the improvement of system performance, otherwise weakens the update range, significantly improving the convergence efficiency and performance of the soft actor critic (SAC). The results show that the proposed model and algorithm have good practicability, which can make the average resource occupancy rate higher and the running cost lower.

Brominated flame retardants (BFRs), categorized as persistent organic pollutants (POPs) are difficult to degrade, exhibiting reproductive toxicity and carcinogenicity. Exposure to dust and soil particles containing BFRs may cause various health problems. The research aimed to assess the concentrations, potential origins, and health risks associated with polybrominated diphenyl ethers (PBDEs) and novel BFRs (NBFRs) in road dust and green belt soil in Harbin. The study revealed that ΣPBDE concentrations ranging from 0.15 to 193.75 ng/g (median: 48.01 ng/g) in road dust and 8.07 to 195.33 ng/g (median: 38.19 ng/g) in green belt soil. Notably, TBBPA contributed the most to the ΣPBDEs concentrations. And the concentrations of ΣNBFRs ranged from 2.34 to 130.53 ng/g (median: 18.48 ng/g) in road dust and 2.50 to 46.70 ng/g (median: 7.85 ng/g) in green belt soil. And tetrabromobisphenol A (TBBPA) was the most dominant compound in both samples. Highways exhibited lower ΣPBDE concentrations in dust samples but higher ΣNBFR concentrations in soil samples compared to other roads. Moreover, most of the BFRs had a positive correlation with each other, suggesting that they may have similar sources. Principal component analysis (PCA) suggested BFRs sources in road dust may come from wire, paint, building materials or commercial products, likewise, BFRs in green belt soil may come from household or industrial products. Health risk assessment indicated that BFRs in both types of samples in Harbin had no non-carcinogenic risk to residents. These findings provide valuable insights into understanding BFR pollution characteristics, identifying specific sources, and recognizing health hazards in dust and soil samples on roads from Harbin.

In order to solve the problem of grasping failure or missing grasping due to the change of target gangue position and posture caused by belt slip, deviation and belt speed fluctuation of belt conveyor when the gangue sorting robot sorts gangue, an improved ORB-FLANN efficient matching method of gangue recognition image and sorting image is proposed. An improved ORB feature point detection method is proposed to detect the feature points in the recognition image and sorting image of coal gangue, so as to realize fast detection of image feature points; An improved FLANN matching algorithm is proposed to match the image feature points to achieve efficient matching between the recognition image of coal gangue and the sorting image. Aiming at the problem of long time and low repetition rate of traditional ORB method for coal gangue image feature detection, an improved ORB feature detection method is proposed to improve the speed and repetition rate of image feature point detection; Aiming at the low accuracy of traditional FLANN matching method for coal gangue image matching, an improved FLANN matching method integrating PROSAC algorithm is proposed to eliminate the wrong feature matching point pairs and improve the accuracy of image matching. The method, SURF feature matching method, HU moment invariant matching method, SIFT feature matching method and ORB feature matching method are applied on the experimental platform of the double mechanical arm truss type gangue sorting robot independently developed by the team to carry out gangue matching experiments under different belt speeds, scales and rotation angles. The results show that the matching rate of the method in this paper is 98.2%, and the matching time is 141 ms. It has the characteristics of high matching rate, good real-time performance and strong robustness, It can meet the requirements of efficient and accurate matching of gangue recognition image and sorting image.

Abstract Objective To explore the risk factors for disease progression after initial treatment of type B thymomas using a predictive nomogram model. Methods A single-center retrospective study of patients with type B thymoma was performed. The Cox proportional hazard model was used for univariate and multivariate analyses. Variables with statistical and clinical significance in the multivariate Cox regression were integrated into a nomogram to establish a predictive model for disease progression. Results A total of 353 cases with type B thymoma were retrieved between January 2012 and December 2021. The median follow-up was 58 months (range: 1–128 months). The 10-year progression-free survival (PFS) was 91.8%. The final nomogram model included R0 resection status and Masaoka stage, with a concordance index of 0.880. Non-R0 resection and advanced Masaoka stage were negative prognostic factors for disease progression (p

Abstract The Gabija system is a newly discovered bacterial immune system that consists of GajA and GajB. Here we report the cryo-EM structure of the Gabija complex from Bacillus cereus VD045 at 3.6 Å, which provides the direct evidence of interactions between GajA and GajB. The Gabija complex is an octameric ring structure with four GajA and four GajB. GajA is an OLD nucleases family protein, while GajB belongs to the SF1 helicases. The Gabija complex has sequence-specific DNA nuclease activity and prefers circular rather than linear DNA as substrate, its activity is more sensitive to concentrations change of nucleotides compared to GajA alone. Our data suggest a mechanism of Gabija immunity: the nuclease activity of Gabija complex is inhibited under physiological conditions, while it is activated by depletion of NTP and dNTP upon the replication and transcription of invading phages and cleave the circular DNA to prevent phage DNA replication.

Abstract Background Engrailed homeobox 1 (EN1) is a candidate oncogene that is epigenetically modified in salivary adenoid cystic carcinoma (SACC). We investigated the expression of EN1 in SACC tissues and cells, EN1 promoter methylation, and the role of EN1 in tumour progression in SACC. Methods Thirty-five SACC samples were screened for key transcription factors that affect tumour progression. In vitro and in vivo assays were performed to determine the viability, tumorigenicity, and metastatic ability of SACC cells with modulated EN1 expression. Quantitative methylation-specific polymerase chain reaction analysis was performed on SACC samples. Results EN1 was identified as a transcription factor that was highly overexpressed in SACC tissues, regardless of clinical stage and histology subtype, and its level of expression correlated with distant metastasis. EN1 promoted cell invasion and migration through epithelial-mesenchymal transition in vitro and enhanced SACC metastasis to the lung in vivo. RNA-seq combined with in vitro assays indicated that EN1 might play an oncogenic role in SACC through the PI3K-AKT pathway. EN1 mRNA levels were negatively correlated with promoter hypermethylation, and inhibition of DNA methylation by 5-aza-dC increased EN1 expression. Conclusions The transcription factor EN1 is overexpressed in SACC under methylation regulation and plays a pivotal role in SACC progression through the PI3K-AKT pathway. These results suggest that EN1 may be a diagnostic biomarker and a potential therapeutic target for SACC.

The response capacities of urban flood forecasting and risk control can be improved by strengthening the computational abilities of urban flood numerical models. In this work, a GPU-based hydrodynamic model is developed to simulate urban rainstorm inundations. By simulating rainstorm floods in a certain area of Xixian New City, the established model can implement high-resolution urban rainstorm inundation simulations with significantly accelerated computing performances. The accelerated computation efficiencies of the different rainstorm event simulations under resolutions of 5 and 2 m are quantitatively analysed, showing that the absolute and relative speedup ratios for all scenarios of applying two GPUs range from 10.8 to 12.6 and 1.32 to 1.68 times as much as those of a CPU and a single GPU, respectively. The application of a large-scale rainstorm inundation simulation shows the excellent acceleration performance of the model compared to previous research. In addition, the greater the number of computational grids included in the simulation, the more significant the effect on the acceleration computing performance. The proposed model efficiently predicts the spatial variation in the inundation water depth. The simulation results provide guidance for urban rainstorm inundation management, and they improve the time and efficiency of urban flood emergency decision-making. HIGHLIGHTS The GPU-based hydrodynamic model is used to evaluate sponge city rainstorm inundation.; Significant speedup of the model executed on multi-GPU compared to a single GPU.; The model is efficient for performing high-resolution sponge city inundation simulation.; Validation and speedup computing performance tests on real urban city-scale areas.;

Abstract Backgroud Laparoscopic adenomyomectomy combined with intraoperative placement of levonorgestrel-releasing intrauterine device (LNG-IUS) is a novel conservative surgical procedure for adenomyosis. Our study aimed to compare the efficacy of surgery with or without intraoperative placement of LNG-IUS treatment in adenomyosis. Methods We retrospectively reviewed the medical records of adenomyosis patients who received laparoscopic adenomyomectomy from January 2014 to April 2020, finally including 70 patients undergoing surgery-LNG-IUS as group A and 69 patients undegoing surgery only as group B. Risk factors for three-year relapse were analyzed using Cox’s multivariate proportional hazard analysis. Results Visual analog scale and Mansfield-Voda-Jorgensen Menstrual Bleeding Scale scores of group A at 3, 6, 12, 24, and 36 months were significantly lower than those of group B at the corresponding points (P

Adolescent binge drinking leads to long-lasting disorders of the adult central nervous system, particularly aberrant hippocampal neurogenesis. In this study, we applied in vivo fluorescent tracing using NestinCreERT2::Rosa26-tdTomato mice and analyzed the endogenous neurogenesis lineage progression of neural stem cells (NSCs) and dendritic spine formation of newborn neurons in the subgranular zone of the dentate gyrus. We found abnormal orientation of tamoxifen-induced tdTomato+ (tdTom+) NSCs in adult mice 2 months after treatment with EtOH (5.0 g/kg, i.p.) for 7 consecutive days. EtOH markedly inhibited tdTom+ NSCs activation and hippocampal neurogenesis in mouse dentate gyrus from adolescence to adulthood. EtOH (100 mM) also significantly inhibited the proliferation to 39.2% and differentiation of primary NSCs in vitro. Adult mice exposed to EtOH also exhibited marked inhibitions in dendritic spine growth and newborn neuron maturation in the dentate gyrus, which was partially reversed by voluntary running or inhibition of the mammalian target of rapamycin-enhancer of zeste homolog 2 pathway. In vivo tracing revealed that EtOH induced abnormal orientation of tdTom+ NSCs and spatial misposition defects of newborn neurons, thus causing the disturbance of hippocampal neurogenesis and dendritic spine remodeling in mice.

Objective: Accurate prognostic predictions and personalized decision-making on induction chemotherapy (IC) for individuals with locally advanced nasopharyngeal carcinoma (LA-NPC) remain challenging. This research examined the predictive function of tumor burden-incorporated machine-learning algorithms for overall survival (OS) and their value in guiding treatment in patients with LA-NPC. Methods: Individuals with LA-NPC were reviewed retrospectively. Tumor burden signature-based OS prediction models were established using a nomogram and two machine-learning methods, the interpretable eXtreme Gradient Boosting (XGBoost) risk prediction model, and DeepHit time-to-event neural network. The models' prediction performances were compared using the concordance index (C-index) and the area under the curve (AUC). The patients were divided into two cohorts based on the risk predictions of the most successful model. The efficacy of IC combined with concurrent chemoradiotherapy was compared to that of chemoradiotherapy alone. Results: The 1 221 eligible individuals, assigned to the training (n = 813) or validation (n = 408) set, showed significant respective differences in the C-indices of the XGBoost, DeepHit, and nomogram models (0.849 and 0.768, 0.811 and 0.767, 0.730 and 0.705). The training and validation sets had larger AUCs in the XGBoost and DeepHit models than the nomogram model in predicting OS (0.881 and 0.760, 0.845 and 0.776, and 0.764 and 0.729, P < 0.001). IC presented survival benefits in the XGBoost-derived high-risk but not low-risk group. Conclusion: This research used machine-learning algorithms to create and verify a comprehensive model integrating tumor burden with clinical variables to predict OS and determine which patients will most likely gain from IC. This model could be valuable for delivering patient counseling and conducting clinical evaluations.

Abstract Background This study aimed to develop alternative prediction equations to predict isokinetic muscle strength at 60°/s based on anthropometric characteristics, including body mass, height, age, and sex for young and middle-aged non-athlete populations. Methods Three hundred and thirty-two healthy non-athletic participants (174 females, 158 males) between 20 and 59 years underwent a 60°/s isokinetic knee joint concentric contraction test. Forty people were randomly selected for retesting to assess the reliability of the isokinetic instrument. Multivariate linear regression was used to establish extension peak torque (EPT) and flexion peak torque (FPT) prediction equations. Sixty extra participants were used individually to validate the prediction equations, and Bland Altman plots were constructed to assess the agreement of predicted values with actual measurements. Results The result demonstrated that the instrument we used has excellent reliability. The multivariable linear regression model showed that body mass, age, and sex were significant predictors of PT (EPT: Adjusted R2 = 0.804, p

The unique structure and complex deformation characteristics of concrete face rockfill dams (CFRDs) create safety monitoring challenges. This study developed an improved random forest (IRF) model for dam health monitoring modeling by replacing the decision tree in the random forest (RF) model with a novel M5' model tree algorithm. The factors affecting dam deformation were preliminarily selected using the statistical model, and the grey relational degree theory was utilized to reduce the dimensions of model input variables. Finally, a deformation prediction model of CFRDs was established using the IRF model. The ten-fold cross-validation method was used to quantitatively analyze the parameters affecting the IRF algorithm. The performance of the established model was verified using data from three specific measurement points on the Jishixia dam and compared with other dam deformation prediction models. At point ES-10, the performance evaluation indices of the IRF model were superior to those of the M5' model tree and RF models and the classical support vector regression (SVR) and back propagation (BP) neural network models, indicating the satisfactory performance of the IRF model. The IRF model also outperformed the SVR and BP models in settlement prediction at points ES2-8 and ES4-10, demonstrating its strong anti-interference and generalization capabilities. This study has developed a novel method for forecasting and analyzing dam settlements with practical significance. Moreover, the established IRF model can also provide guidance for modeling health monitoring of other structures.

Objectives: To investigate prognostic factors in patients with head and neck Mucoepidermoid Carcinoma (MEC), especially the impact of treatment modalities on survival. Methods: Patients with primary head and neck MEC between 2000 and 2015 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Prognostic factors related to Overall Survival (OS) and Cancer-Specific Survival (CSS), as well as the impact of treatments, were evaluated by multivariable Cox regression analysis. Results: We identified 2692 patients diagnosed with head and neck MEC, of whom 1397 (51.89%) had a parotid gland primary, 569 (22.14%) died, and 341 (12.67%) died of MEC. Older age (≥53 years), males, unmarried, lower income, tumor site in other head and neck areas, higher tumor grade, larger tumor size, and higher stage were related to poorer OS and CSS. Patients who did not undergo surgery (HR = 3.20, 95% CI 2.45‒4.18) had worse OS, while no significant difference was detected between partial and total organ excision on patients’ OS (p = 0.729). For combination therapy, patients who received radiotherapy only (HR = 3.21, 95% CI 2.27–4.53) or no surgery and no radiotherapy (HR = 2.59, 95% CI 1.83–3.67) were correlated with worse OS (vs. surgery only), but no significant difference was detected between surgery only and surgery combined with radiotherapy on patients’ OS (p = 0.218). For CSS, the corresponding results were consistent with OS. Conclusion: Surgical resection only may be a better survival option for head and neck MEC.

Leaves of Melaleuca alternifolia are abundant in essential oils comprising terpenoids and volatile organic compounds, which play an important role in plant abiotic stress response. However, the molecular mechanisms underlying terpenoid biosynthesis in M. alternifolia remain poorly understood. To fill this knowledge gap, we profiled terpenoid content and composition across four distinct growth phases using gas chromatography-mass spectrometry (GC/MS). We also performed an integrated analysis of gene expression in leaf tissues through full-length transcriptome sequencing combined with high throughput RNA sequencing. We identified 46,313 transcripts, 99 % (45,848 transcripts) of which were annotated using existing databases. Our study also revealed 2,792 transcription factors (TFs) and 1,812 alternative splicing (AS) events. Through weighted gene co-expression network analysis (WGCNA), we clustered these identified genes into 11 co-expressed modules. Notably, two modules—designated as blue and brown—were significantly correlated with essential oil content. Homologous annotation with the Arabidopsis database revealed that genes within the blue module are largely involved in the 2-C-methyl-d-erythritol 4-phosphate (MEP) pathway, suggesting its pivotal role in essential oil synthesis in M. alternifolia. Furthermore, elevated expression levels of VAMP72 and DGK1 in the brown module indicate their potential function as negative regulators of essential oil synthesis. Our findings unveil key differentially expressed genes (DEGs) and pathways that can be targeted to enhance essential oil production in M. alternifolia. The identified TFs may serve as potential candidates for genetic modification through genome editing technologies. This research provides valuable insights into the processes involved in essential oil biosynthesis and highlights key genes for functional characterization in M. alternifolia.

BACKGROUND The palm oil (PO), leaf lard oil (LO), rapeseed oil (RO), sunflower oil (SO) and linseed oil (LN) are five of the most typical dietary lipids in most Asian countries. However, their influences on gut health, and the connections between the fatty acid composition, the gut microbiota, and the bile acid metabolism are not fully understood. RESULTS: In the present study, results showed that compared with polyunsaturated fatty acid (PUFA)‐rich SO and LN, the saturated fatty acid (SFA)‐rich and monounsaturated fatty acid (MUFA)‐rich PO, LO and RO were more likely to decrease the re‐absorption of bile acid in the colon, which was probably caused by their different role in modulating the gut microbiota structure. LO consumption significantly up‐regulated the Cyp27a1, FXR and TGR5 gene expression level (P < 0.05). The correlation results suggested that the C18:0 was significantly positive correlated with these three genes, indicating that intake of SFA‐rich dietary lipids, especially for the C18:0, could specifically increase the bile acid production by stimulating the bile acid alternative synthesis pathway. Although the bile acid receptor expression in the colon was increased, the re‐absorption of bile acid did not show a significant increase (P > 0.05) as compared with other dietary lipids. Moreover, the C18:2‐rich SO maintained the bile acid metabolic balance probably by decreasing the Romboutsia, while increasing the Bifidobacterium abundance in the colon. CONCLUSIONS: The different dietary lipids showed different effects on the bile acid metabolism, which was probably connected with the alterations in the gut microbiota structure. The present study could provide basic understandings about the influences of the different dietary lipids consumption on gut homeostasis and bile acid metabolism. © 2021 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The numerical shock instability problem significantly limits the application of the finite volume method in hypersonic flow simulations, especially for high-order schemes, which will encounter more severe shock instability problems. In the previous work, the MSAT (matrix stability analysis tool) was introduced to quantitatively analyze the numerical shock instability problem. However, the utilization of the three-point reconstruction stencil in the original version of MSAT presents challenges in conducting investigations into high-order schemes. The current work provides an extension of MSAT by extending the reconstruction stencil to five points, a challenging but necessary endeavor for high-order schemes. This extension enables MSAT to provide analyses for schemes with high-order reconstruction methods. Furthermore, the updated MSAT can be utilized to investigate the impact of characteristic variable reconstruction on the shock instability problem. Results demonstrate the reliability of the updated MSAT and reveal novel characteristics in the shock instability of high-order schemes. Consequently, the updated MSAT will contribute to the investigation of shock instabilities for high-order schemes, ultimately aiding in mitigating this challenging problem.