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Abstract Rhizosphere ecological factors that affect sugarcane ratoons are crucial components in the feedback mechanisms between the sugarcane plant and soil environment. However, systematic investigations on these dynamics are lacking. Therefore, this study investigated the relationship between sugarcane ratoon decline and rhizosphere ecological factors. In first-year sugarcane ratoons, ecological factors such as soil available potassium content, soil nitrogen fixation, and soil peroxidase activity were significantly positively correlated with sugarcane growth (P 0.05) between the alpha diversity of endophytic fungi and key sugarcane growth indicators. The deterioration of mainly non-microbial ecological factors in rhizosphere soil (P

Abstract Background The blunt snout bream (Megalobrama amblycephala) is an important economic freshwater fish in China with tender flesh and high nutritional value. With the cultivation of superior new varieties and the expansion of breeding scale, it becomes imperative to employ sex-control technology to cultivate monosexual populations of M. amblycephala, thereby preventing the deterioration of desirable traits. The development of specific markers capable of accurately identifying the sex of M. amblycephala would facilitate the determination of the genetic sex of the breeding population before gonad maturation, thereby expediting the processes of sex-controlled breeding of M. amblycephala. Results A whole-genome re-sequencing was performed for 116 females and 141 males M. amblycephala collected from nine populations. Seven candidate male-specific sequences were identified through comparative analysis of male and female genomes, which were further compared with the sequencing data of 257 individuals, and finally three male-specific sequences were generated. These three sequences were further validated by PCR amplification in 32 males and 32 females to confirm their potential as male-specific molecular markers for M. amblycephala. One of these markers showed potential applicability in M. pellegrini as well, enabling males to be identified using this specific molecular marker. Conclusions The study provides a high-efficiency and cost-effective approach for the genetic sex identification in two species of Megalobrama. The developed markers in this study have great potential in facilitating sex-controlled breeding of M. amblycephala and M. pellegrini, while also contributing valuable insights into the underlying mechanisms of fish sex determination.

Quality management is a constant and significant concern in enterprises. Effective determination of correct solutions for comprehensive problems helps avoid increased backtesting costs. This study proposes an intelligent quality control method for manufacturing processes based on a human–cyber–physical (HCP) knowledge graph, which is a systematic method that encompasses the following elements: data management and classification based on HCP ternary data, HCP ontology construction, knowledge extraction for constructing an HCP knowledge graph, and comprehensive application of quality control based on HCP knowledge. The proposed method implements case retrieval, automatic analysis, and assisted decision making based on an HCP knowledge graph, enabling quality monitoring, inspection, diagnosis, and maintenance strategies for quality control. In practical applications, the proposed modular and hierarchical HCP ontology exhibits significant superiority in terms of shareability and reusability of the acquired knowledge. Moreover, the HCP knowledge graph deeply integrates the provided HCP data and effectively supports comprehensive decision making. The proposed method was implemented in cases involving an automotive production line and a gear manufacturing process, and the effectiveness of the method was verified by the application system deployed. Furthermore, the proposed method can be extended to other manufacturing process quality control tasks.

Gastric cancer (GC) is a major cause of cancer-related mortality worldwide. GC is determined by multiple (epi)genetic and environmental factors; can occur at distinct anatomic positions of the stomach; and displays high heterogeneity, with different cellular origins and diverse histological and molecular features. This heterogeneity has hindered efforts to fully understand the pathology of GC and develop efficient therapeutics. In the past decade, great progress has been made in the study of GC, particularly in molecular subtyping, investigation of the immune microenvironment, and defining the evolutionary path and dynamics. Preclinical mouse models, particularly immunocompetent models that mimic the cellular and molecular features of human GC, in combination with organoid culture and clinical studies, have provided powerful tools for elucidating the molecular and cellular mechanisms underlying GC pathology and immune evasion, and the development of novel therapeutic strategies. Herein, we first briefly introduce current progress and challenges in GC study and subsequently summarize immunocompetent GC mouse models, emphasizing the potential application of genetically engineered mouse models in antitumor immunity and immunotherapy studies.

Abstract Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron scale. To study the powder samples that are widely used in materials development, scanning electron microscopes (SEMs) are increasingly used at the laboratory scale to generate large datasets with hundreds of images. Parsing these images to identify distinct particles and determine their morphology requires careful analysis, and automating this process remains challenging. In this work, we enhance the Mask R-CNN architecture to develop a method for automated segmentation of particles in SEM images. We address several challenges inherent to measurements, such as image blur and particle agglomeration. Moreover, our method accounts for prediction uncertainty when such issues prevent accurate segmentation of a particle. Recognizing that disparate length scales are often present in large datasets, we use this framework to create two models that are separately trained to handle images obtained at low or high magnification. By testing these models on a variety of inorganic samples, our approach to particle segmentation surpasses an established automated segmentation method and yields comparable results to the predictions of three domain experts, revealing comparable accuracy while requiring a fraction of the time. These findings highlight the potential of deep learning in advancing autonomous workflows for materials characterization.

Abstract Allelopathy is a process whereby a plant directly or indirectly promotes or inhibits growth of surrounding plants. Perennial sugarcane root extracts from various years significantly inhibited Bidens pilosa, Digitaria sanguinalis, sugarcane stem seedlings, and sugarcane tissue-cultured seedlings (P

As the proportion of renewable energy generation continues to increase, the participation of new energy stations with high-proportion energy storage in power system frequency regulation is of significant importance for stable and secure operation of the new power system. To address this issue, an energy storage control method based on quantum walks and model predictive control (MPC) has been proposed. First, historical frequency deviation signals and energy storage charge–discharge state signals are collected. Simulation data are generated through amplitude encoding and quantum walks, followed by quantum decoding. Subsequently, the decoded data are inputted into the MPC framework for real-time control, with parameters of the predictive model continuously adjusted through a feedback loop. Finally, a novel power system frequency regulation model with high-proportion new energy storage stations is constructed on the MATLAB/Simulink platform. Simulation verification is conducted with the proportional–integral–derivative (PID) and MPC methods as comparative approaches. Simulation results under step disturbances and random disturbances demonstrate that the proposed method exhibits stronger robustness and better control accuracy.

To study the dynamic response of multi-span mortise and tenon stone bridges under natural excitation, a bluestone multi-span stone bridge with a main span of 2.56 m in southern China was taken as the research object. Based on the collected pulsating signals of bridge piers and slabs, the natural frequencies and damping ratios of the main span bridge slab and pier were analyzed using the half-power broadband method (HPBM) and random decrement technique (RDT). Modal analysis was conducted using ANSYS, and the results were compared with those obtained from on-site experiments for further performance analysis. The research results of this article indicate that the natural frequency range of the 2.56-m bridge slab identified by measured signals is 48–49 Hz, and the damping ratio range is 33.33–36.61%. The natural frequency of the central pier is 75–76 Hz, and the damping ratio range is 26.39–27.83%. Through finite element modal analysis, the natural frequency of the bridge slab is 54.401 Hz, with an error of 10.5%. The natural frequency of the overall stone bridge is about 82.2 Hz, with an error of about 8.2%. The validated finite element model was subjected to normal water flow impact and erosion simulation. The results indicate that under erosion with fewer particles and lower flow rates, the upstream pier bottom at the center receives the highest relative erosion mass and displacement per unit area. The bridge deck near the main span also experienced relative displacement. Therefore, in the subsequent protection work, special attention should be paid to these components.

Range extender hybrid vehicles have the advantages of better dynamics and longer driving range while reducing pollution and fuel consumption. This work focuses on the control strategy of an Auxiliary Power Unit (APU) operating in power generation mode for a range-extender mixer truck. When an operating point is switched, the engine speed and generator torque of the APU will switch accordingly. In order to ensure APU fast and stable adjustment to meet the power demand of the vehicle as well as operate at the lowest fuel consumption, a fuzzy adaptive PID coordination control strategy based on particle swarm optimization (PSO) is proposed to control the APU. The optimal operating curve of APU is calculated by coupling the engine and generator first. Then, the adaptive PID algorithm is used to control the speed and torque of the APU in a dual closed loop. The PSO is used to optimize the PID control parameter. Through hardware-in-the-loop tests under different working conditions, the control strategy is verified to be effective and real-time. The results show that the proposed control strategy can coordinate the operating of engine and generator and control the APU to track target power stably and quickly under minimum fuel consumption. Compared with traditional PID control strategy, the overshoot, regulation time and steady-state error are reduced by 55.1%, 11.1% and 77.3%, respectively.

BackgroundAmounting literatures have reported the significance of systemic inflammatory markers for evaluating tumor prognosis. But few studies have systematically compared their superiority and their impact on adjuvant chemotherapy.AimsWe aimed to investigate the ability of inflammatory markers to predict the efficacy of chemotherapy in GC patients undergoing radical therapy and to identify an effective methodology based on the study’s findings that would enable clinicians to differentiate between chemotherapy-responsive populations.MethodsWe retrospectively enrolled 730 GC patients who underwent radical gastrectomy. Fibrinogen (FIB), platelet-lymphocyte ratio (PLR), systemic inflammation response index (SIRI), prognostic nutritional index (PNI), systemic immune-inflammation index (SII), neutrophil-lymphocyte ratio (NLR) and lymph node ratio (LNR) were grouped according to cutoff values. Their clinical significance for GC prognosis was determined by multivariate COX regression analysis in the 730 GC patients and high/low PLR status subgroups. Cases were divided into four groups according to PLR status and adjuvant chemotherapy status and survival was compared among groups.ResultsMultivariate analysis showed that PLR was an independent prognostic factor for overall survival (OS) and disease-free survival (DFS) of GC patients. Adjuvant chemotherapy improved survival more significantly in patients with low PLR than that with high PLR. Among patients receiving adjuvant chemotherapy, low PLR was significantly associated with prolonged survival in TNM stage II, but not in TNM stage III.ConclusionPreoperative high PLR is an independent risk factor for GC patients undergoing radical gastrectomy and adversely affects the postoperative chemotherapy effect.

Aiming at solving the problems of the high cost of manual pulling, the low reliability of existing pulling devices, and the high breaking rates and high leakage rates in the process of cotton stalk reuse after removal from the field in the Xinjiang cotton area, a soil-loosening and root-cutting cotton stalk pulling and gathering machine was researched and designed; a root-cutting force model was established; the key parameters of the V-shaped root-cutting knife were calculated and optimized; and the ranges of the slide cutting angle, the cutting-edge angle, and the soil entry angle were determined. A shoveling process simulation of the V-shaped root-cutting knife and the root–soil complex was constructed, and the working mechanism of the V-shaped root-cutting knife was clarified. In order to verify the reliability and operation performance of the V-shaped root-cutting knife, the slide cutting angle, the cutting-edge angle, and the soil entry angle were used as the test factors, and a response surface test with three factors and three levels was carried out with the root-breaking force and the mean value of the cutting resistance as the test indices. The test results were analyzed by variance analysis, and the significant factors influencing the root-breaking force in descending order were the slide cutting angle, cutting-edge angle, and soil entry angle. The degrees of influence on the mean value of the cutting resistance were ordered as follows: slide cutting angle, soil entry angle, and cutting-edge angle. In order to make the V-shaped root-cutting knife achieve the optimal working state, the parameters of the test indices were optimized, and the optimal design parameters of the V-shaped root-cutting knife were set as follows: the slide cutting angle was 48.3°, the cutting-edge angle was 43.4°, and the soil entry angle was 26.2°. The field uprooting test showed that the average pass rate of root breakage was 94.8% and the average pull-out rate of cotton stalks was 93.2%. This study provides theoretical guidance for the development of a root-breaking mechanism for cotton straw harvesters.

A horizontal towed linear coherent hydrophone array is often employed to estimate the spatial intensity distribution of incident plane waves scattered from the geological and biological features in an ocean acoustic waveguide using conventional beamforming. However, due to the physical limitations of the array aperture, the spatial resolution after conventional beamforming is often limited by the fat main lobe and the high sidelobes. Here, we propose a method originated from computer vision deblurring based on deep learning to enhance the spatial resolution of beamformed images. The effect of image blurring after conventional beamforming can be considered a convolution of beam pattern, which acts as a point spread function (PSF), and the original spatial intensity distributions of incident plane waves. A modified U-Net-like network is trained on a simulated dataset. The instantaneous acoustic complex amplitude is assumed following circular complex Gaussian random (CCGR) statistics. Both synthetic data and experimental data collected from the South China Sea Experiment in 2021 are used to illustrate the effectiveness of this approach, showing a maximum 700% reduction in a 3 dB width over conventional beamforming. A lower normalized mean square error (NMSE) is provided compared with other deconvolution-based algorithms, such as the Richardson–Lucy algorithm and the approximate likelihood model-based deconvolution algorithm. The method is applicable in various acoustic imaging applications that employ linear coherent hydrophone arrays with one-dimensional conventional beamforming, such as ocean acoustic waveguide remote sensing (OAWRS).

Ancient masonry pagodas hold significant scientific, historical, and cultural importance. However, due to the complexity of masonry materials, structures, and boundary conditions, establishing finite element static and dynamic models for ancient masonry pagodas is highly challenging. This study aimed to explore the dynamic characteristics and finite element numerical simulation methods of ancient masonry pagodas in Yongzhou, Hunan province. It focused on the Huilong Pagoda in Yongzhou, where in situ test experiments under natural excitation are conducted. The SSI and NExT-ERA methods were employed to determine the ancient pagoda’s natural frequencies, vibration patterns, and damping ratios, and to validate the NExT-ERA method. The macroscopic numerical model of the Huilong Pagoda was calibrated using measured results. Subsequently, the NExT-ERA identification results were compared and analyzed with the numerical simulation results of the dynamic characteristics. The results indicate that the first three orders of natural frequencies for the ancient pagoda in the east–west direction are 1.937 Hz, 6.802 Hz, and 21.361 Hz, respectively. Similarly, the first three orders of natural frequencies in the north–south direction are 1.935 Hz, 7.439 Hz, and 21.398 Hz. The results obtained from both methods revealed that the overall structural damping ratio ranges from 0.21% to 2.89%. The numerical model was analyzed using ANSYS, and the first three orders of natural frequencies obtained were highly consistent with the measured values, exhibiting a maximum relative error of 8.54%. The numerical simulation method developed in this study can effectively simulate masonry pagodas.

Objective: Numerous studies have highlighted an association between the gut microbiota (GM) and thyroid tumors. Employing Mendelian randomization methodology, we seek to elucidate the causal link between the gut microbiota and thyroid neoplasms.Methods: We procured data from the Mibiogen database encompassing 211 distinct gut microbiota taxa, alongside extensive genome-wide association studies (GWAS) summary data for differentiated thyroid carcinoma (DTC). Our principal analytical approach involved the application of the Inverse-Variance Weighted method (IVW) within the framework of Mendelian randomization. Simultaneously, we conducted sensitivity analyses to assess result heterogeneity, horizontal pleiotropy, and outcome stability.Results: IVW analysis revealed a dual role of the GM in thyroid carcinoma. The phylum Actinobacteria (OR, 0.249 [95% CI, 0.121–0.515]; p < 0.001) was associated with a decreased risk of DTC. Conversely, the genus Ruminiclostridium9 (OR, 11.276 [95% CI, 4.406–28.860]; p < 0.001), class Mollicutes (OR, 5.902 [95% CI, 1.768–19.699]; p = 0.004), genus RuminococcaceaeUCG004 (OR, 3.831 [95% CI, 1.516–9.683]; p = 0.005), genus Paraprevotella (OR, 3.536 [95% CI, 1.330–9.401]; p = 0.011), and phylum Tenericutes (OR, 5.902 [95% CI, 1.768–19.699]; p = 0.004) were associated with an increased risk of DTC.Conclusion: Our findings underscore that the presence of genus Ruminiclostridium9, class Mollicutes, genus RuminococcaceaeUCG004, genus Paraprevotella, and phylum Tenericutes is associated with an elevated risk of DTC, whereas the presence of the phylum Actinobacteria is linked to a decreased risk. These discoveries enhance our comprehension of the relationship between the GM and DTC.

Latent Dirichlet Allocation (LDA) is a statistical approach for topic modeling with a wide range of applications. Attracted by the exceptional computing and memory throughput capabilities, this work introduces ezLDA which achieves efficient and scalable LDA training on GPUs with the following three contributions: First, ezLDA introduces three-branch sampling method which takes advantage of the convergence heterogeneity of various tokens to reduce the redundant sampling task. Second, to enable sparsity-aware format for both D and W on GPUs with fast sampling and updating, we introduce hybrid format for W along with corresponding token partition to T and inverted index designs. Third, we design a hierarchical workload balancing solution to address the extremely skewed workload imbalance problem on GPU and scale ezLDA across multiple GPUs. Taken together, ezLDA achieves superior performance over the state-of-the-art attempts with lower memory consumption.

Abstract Background The discovery of a potent photosensitizer with desirable immunogenic cell death (ICD) ability can prominently enhance antitumor immunity in photodynamic therapy (PDT). However, majority of commercially-available photosensitizers suffer from serious aggregation and fail to elicit sufficient ICD. Pyroptosis as a newly identified pattern for potent ICD generation is rarely disclosed in reported photosensitizers. In addition, the photosensitizer with excellent mitochondria-anchored ability evokes prominent mitochondria oxidative stress, and consequently induces ICD. Results Herein, a novel supramolecular photosensitizer LDH@ZnPc is reported, without complicated preparation, but reveals desirable pyroptosis-triggered ability with mitochondria anchoring feature. LDH@ZnPc is obtained through isolation of ZnPc using positive charged layered double hydroxides (LDH), and excellent mitochondria-anchored ability is achieved. More importantly, LDH@ZnPc-mediated PDT can effectively initiate gasdermin D (GSDMD)-dependent pyroptosis of tumor cells. In vitro and in vivo results verify robust ICD ability and potent tumor inhibition efficacy, and antitumor immunity towards distant tumor inhibition. Conclusions This study reveals that LDH@ZnPc can act as an excellent pyroptosis inducer with simultaneous mitochondria anchoring ability for enhancing photodynamic therapy and boosting antitumor immunity. Graphical Abstract

Background: Pancreatic cancer (PC) is a deadly disease. The tumor microenvironment (TME) participates in PC oncogenesis. This study focuses on the assessment of the prognostic and treatment utility of TME-associated genes in PC.Methods: After obtaining the differentially expressed TME-related genes, univariate and multivariate Cox analyses and least absolute shrinkage and selection operator (LASSO) were performed to identify genes related to prognosis, and a risk model was established to evaluate risk scores, based on The Cancer Genome Atlas (TCGA) data set, and it was validated by external data sets from the Gene Expression Omnibus (GEO) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Multiomics analyses were adopted to explore the potential mechanisms, discover novel treatment targets, and assess the sensitivities of immunotherapy and chemotherapy.Results: Five TME-associated genes, namely, FERMT1, CARD9, IL20RB, MET, and MMP3, were identified and a risk score formula constructed. Next, their mRNA expressions were verified in cancer and normal pancreatic cells. Multiple algorithms confirmed that the risk model displayed a reliable ability of prognosis prediction and was an independent prognostic factor, indicating that high-risk patients had poor outcomes. Immunocyte infiltration, gene set enrichment analysis (GSEA), and single-cell analysis all showed a strong relationship between immune mechanism and low-risk samples. The risk score could predict the sensitivity of immunotherapy and some chemotherapy regimens, which included oxaliplatin and irinotecan. Various latent treatment targets (LAG3, TIGIT, and ARID1A) were addressed by mutation landscape based on the risk model.Conclusion: The risk model based on TME-related genes can reflect the prognosis of PC patients and functions as a novel set of biomarkers for PC therapy.

This study investigates the vibration response and dynamic characteristics of the Shigudeng Pavilion under environmental excitation, employing a comprehensive approach that includes vibration response measurements, theoretical analysis, and finite element numerical simulation. An in-depth examination of the appearance and stress status of the Shigudeng Pavilion in Yao Ancient Village in southern Hunan was conducted, and the horizontal acceleration of different floors of the pavilion under environmental excitation was ascertained through field measurements. The NExT-ERA method was utilized to identify the modal parameters (frequency, damping ratio, and vibration pattern) of the measured timber construction. Subsequently, a finite element analysis model of the ancient timber building was developed and refined using ANSYS Workbench finite element software. This study proposes a specific repair plan addressing apparent defects and structural damage in the measured ancient timber building, offering theoretical and technical references for the conservation and repair of similar structures.

The multi-operation scenes of extended-range concrete mixer trucks are complex and variable, and the operation mode switching process remains a challenge that involves coordinating the torque of the clutch, engine, and integrated starter generator. An unsuitable strategy will undermine the stability of the concrete mixing cylinder and shorten the service life of the clutch. This work studies the clutch control strategy based on fuzzy control theory and coordinates the torque during the mode-switching process. The improved engine control strategy is utilized to reduce friction work and energy consumption of the integrated starter generator used to compensate torque. This control strategy is verified by simulation and experiment. The results show that it can significantly decrease the torque fluctuation by 94.3%, and also reduce friction work by 20.7% compared with the conventional engine target speed ignition strategy, which substantially improves the mode switching process and prolongs the service life of the system.

Abstract 2D metal–organic frameworks are attractive filler in mixed matrix membranes (MMMs) due to the high aspect ratio and contact opportunity at the filler–polymer interface. However, their alignment in polymer matrix remains a challenge to fully play their functions. Herein, to our best knowledge, for the first time, the facile synthesis of KAUST‐7‐NH2 (KAUST, King University of Science and Technology) nanoplate is reported with 1D channels with an aspect ratio greater than 30. The nanoplates are incorporated and aligned in the 4,4′‐(hexafluoroisopropylidene) diphthalic anhydride‐2,4‐diaminomesitylene (6FDA‐DAM) polymer matrix under the shear force with a filler loading up to 50 wt%. The large difference in adsorption abilities between CO2 and CH4 from the (001)‐oriented KAUST‐7‐NH2 nanoplate‐based MMMs and the favorable interaction at the filler–polymer interface contribute to the excellent CO2/CH4 separation performance. The resultant membranes show CO2/CH4 selectivity with 66.2% enhancement (surpassed 2008 Robeson upper bound), antiplasticization up to 17 bar, and long‐term stability up to 240 h indicating its good potential for natural gas treatment.

Abstract The roles of phospholysine phosphohistidine inorganic pyrophosphate phosphatase (LHPP) in tumorigenesis have been recently proven in hepatocellular carcinoma (HCC), cervical, pancreatic, bladder, and thyroid cancers. Previous research demonstrated that LHPP repressed cell proliferation and growth by inactivating the phosphatidylinositol 3-kinase/AKT signaling pathway in vitro and in vivo. However, the functions and potential mechanisms of LHPP as a tumor suppressor in colorectal cancer (CRC) metastasis are still unknown. Consequently, the Transwell assay and xenograft nude model showed that LHPP inhibited migration and invasion of CRC cells in vitro and in vivo, respectively. The expression of total and nuclear epithelial-to-mesenchymal transition (EMT)-related proteins were significantly reduced after LHPP upregulation. Human Gene Expression Array and IPA (Ingenuity Pathway Analysis) commercial software were applied to identify differentially expressed genes (DEGs) and potential cell signaling pathways. A total of 330 different genes were observed, including 177 upregulated genes and 153 downregulated genes. Bioinformatics analysis suggested that the transforming growth factor-β (TGF-β) signaling pathway was highly inactivated in this study. Then, Smad3 phosphorylation was apparently decreased, whereas Smad7 expression was markedly enhanced after upregulating LHPP expression. These results were proven once again after TGF-β1 stimulation. Furthermore, a specific inhibitor of Smad3 phosphorylation (SIS3) was applied to verify that LHPP repressed EMT of cancer cells by attenuating TGF-β/Smad signaling. The results suggested that suppression of the TGF-β/Smad signaling pathway by LHPP overexpression could be abolished by SIS3.

Abstract The tumor immune microenvironment (TIME) has been demonstrated to be the main cause of cancer immunotherapy failure in various malignant tumors, due to poor immunogenicity and existence of immunosuppressive factors. Thus, establishing effective treatments for hostile TIME remodeling has considerable potential to enhance immune response rates for durable tumor growth retardation. This study aims to develop a novel nanocomposite, polyethyleneimine-modified dendritic mesoporous silica nanoparticles loaded with microRNA-125a (DMSN-PEI@125a) to synergistically enhance immune response and immunosuppression reversion, ultimately generating a tumoricidal environment. Our results showed that DMSN-PEI@125a exhibited excellent ability in cellular uptake by murine macrophages and the cervical cancer cell line TC-1, repolarization of tumor associated macrophages (TAMs) to M1 type in a synergistic manner, and promotion of TC-1 immunogenic death. Intratumor injection of DMSN-PEI@125a facilitated the release of more damage-related molecular patterns and enhanced the infiltration of natural killer and CD8+ T cells. Meanwhile, repolarized TAMs could function as a helper to promote antitumor immunity, thus inhibiting tumor growth in TC-1 mouse models in a collaborative manner. Collectively, this work highlights the multifunctional roles of DMSN-PEI@125a in generating an inflammatory TIME and provoking antitumor immunity, which may serve as a potential agent for cancer immunotherapy.

Sugarcane ratoon performance declines with increasing age due to the intergenerational accumulation and release of allelochemicals by old sugarcane roots. We aimed to clarify the effects of these allelochemicals on sugarcane seedling growth under continuous sugarcane ratoon cropping. We investigated the allelopathic effects of treatment with root aqueous extracts from sugarcane ratoons of different ages on the osmoregulatory substance content, antioxidant enzyme activity, membrane lipid peroxidation product content, photosynthetic physiological characteristics, and root exudate enzymatic characteristics of sugarcane seedlings. The root aqueous extracts exerted allelopathic effects on sugarcane seedlings. The relative electrolyte leakage, proline content, soluble protein content, soluble sugar content, malondialdehyde content, and catalase activity of the leaves were more sensitive than those of the roots. Conversely, the superoxide dismutase and peroxidase activities of the roots (positive response) were more sensitive than those of the leaves (negative response). The total chlorophyll content and net photosynthetic rate of the leaves exhibited relatively sensitive negative responses. Urease activity negatively responded but sucrase activity positively responded. We concluded that the root aqueous extracts of sugarcane ratoons may exert their allelopathic effects by affecting the level of osmoregulatory substances and causing peroxidative damage to the cell membranes of sugarcane seedlings and altering the activities of various enzymes in the rhizosphere.

Traffic sign detection is a crucial task in computer vision, finding wide-ranging applications in intelligent transportation systems, autonomous driving, and traffic safety. However, due to the complexity and variability of traffic environments and the small size of traffic signs, detecting small traffic signs in real-world scenes remains a challenging problem. In order to improve the recognition of road traffic signs, this paper proposes a small object detection algorithm for traffic signs based on the improved YOLOv7. First, the small target detection layer in the neck region was added to augment the detection capability for small traffic sign targets. Simultaneously, the integration of self-attention and convolutional mix modules (ACmix) was applied to the newly added small target detection layer, enabling the capture of additional feature information through the convolutional and self-attention channels within ACmix. Furthermore, the feature extraction capability of the convolution modules was enhanced by replacing the regular convolution modules in the neck layer with omni-dimensional dynamic convolution (ODConv). To further enhance the accuracy of small target detection, the normalized Gaussian Wasserstein distance (NWD) metric was introduced to mitigate the sensitivity to minor positional deviations of small objects. The experimental results on the challenging public dataset TT100K demonstrate that the SANO-YOLOv7 algorithm achieved an 88.7% mAP@0.5, outperforming the baseline model YOLOv7 by 5.3%.

This study aimed to reveal the characteristics of multi-circuit brain synergy between elite tai chi chuan athletes in resting and exercise states and to provide neuroimaging evidence of improvements in brain function by motor skill training. Functional near-infrared spectroscopy (fNIRS) was used to compare the brain activity of professional tai chi chuan athletes (expert group) and beginners (novice group) in resting and exercise states, and to assess functional connectivity (FC) between the prefrontal lobe and the sensorimotor zone. In the resting state, the FC between the left prefrontal lobe and the right sensorimotor area in the expert group was significantly lower than that in the novice group (P < 0.05). In the exercise state, the patterns of FC between the left prefrontal lobe and right sensorimotor area, the right prefrontal lobe and left sensorimotor area, and the left and right sensorimotor areas in the expert group were significantly lower than that in the novice group (P < 0.05). From the resting state to the locomotor state, the expert group experienced a greater absolute value of functional connection increment between the left prefrontal cortex and right sensorimotor area, and between the left sensorimotor area and right sensorimotor area (P < 0.05). This was positively correlated with the self-evaluation results of motor performance behavior. Under sports conditions, professional athletes’ multi-circuit brain FC strength is significantly reduced, and their elite motor skill performance supports the neural efficiency hypothesis. This may be related to the high adaptation of the brain to specific tasks and the improvement of the integration of somatic perception processing and motor function.

The Cedaya-S340 Holgutu Highway Construction Project is located in the Mongolian Autonomous Prefecture of Bayingolin in the Xinjiang Uygur Autonomous Region. It is an important traffic channel that connects Luntai County and Hejing County at the southern foot of Tianshan Mountains. As the major component of the highway project, the Huola Mountain Tunnel has a sharp topographic relief, and, therefore, commonly used land geophysical detection instruments cannot work on it. Therefore, we conducted a qualitative survey on the ground-to-air and airborne electromagnetic detection methods used at the Huola Mountain Tunnel site to provide basic data for the design of highway tunnels. The geophysical survey summarized the ground–airborne frequency-domain electromagnetic method (GAFEM) and the helicopter-borne time-domain electromagnetic method (HTEM) developed by Jilin University, and measured 15 measuring lines. Apparent resistivity imaging was performed for each section, and the results were consistent. This study comprehensively analyzed the apparent resistivity profile and geological mapping data. Then, the study inferred the major stratigraphic boundaries, fault fracture zones, rock fragmentation, weakness, karst development, and water content in accordance with background value, low-resistivity anomaly shape, low-resistivity anomaly value, and gradient value in the apparent resistivity profile. Finally, the study identified the scope of two main low-resistivity anomalies, located at the tunnel entrance and exit, respectively, which are basically consistent with the known fault location. The results of this study show that on the basis of the apparent resistivity maps of GAFEM and HTEM, the overall distribution law is basically consistent with site landform, hydrogeology, tectonic geology, and aerial image data. The results provide guidance for the construction of the Huola Mountain Tunnel and ensure the construction safety and progress of the tunnel.

Summary: Elevation of the levels of reactive oxygen species and other toxic radicals is an emerging strategy to treat certain cancers by modulating the redox status of cancer cells. The biocatalytic upregulation of singlet oxygen by neutrophilic leukocytes should utilize robust enzymes and design carriers with protective microenvironment. Here, we utilize GOx-CPO as integrated tandem enzymes to in situ generate singlet oxygen, which could be not only for oxidative cross-linking of injectable hydrogel carriers but also for continuous tumor treatment by adjustable bioconversion of blood oxygen, glucose, and chloride ion. The tandem enzymes self-restrained within peptide hydrogel exhibited superactivity for upregulating singlet oxygen relative to free enzymes, which also avoids the diffusion of enzymes from tumor. This work will not only deepen the study of enzymes in biocatalysis but also offer an enzyme therapeutic modality for treating cancers. : Biological Sciences; Medical Biochemistry; Cancer Subject Areas: Biological Sciences, Medical Biochemistry, Cancer

(1) Background: Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with high intra-tumoral heterogeneity. The epithelial-mesenchymal transition (EMT) is one of the inducers of cancer metastasis and migration. However, the description of the EMT process in TNBC using single-cell RNA sequencing (scRNA-seq) remains unclear. (2) Methods: In this study, we analyzed 8938 cellular gene expression profiles from five TNBC patients. We first scored each malignant cell based on functional pathways to determine its EMT characteristics. Then, a pseudo-time trajectory analysis was employed to characterize the cell trajectories. Furthermore, CellChat was used to identify the cellular communications. (3) Results: We identified 888 epithelium-like and 846 mesenchyme-like malignant cells, respectively. A further pseudo-time trajectory analysis indicated the transition trends from epithelium-like to mesenchyme-like in malignant cells. To characterize the potential regulators of the EMT process, we identified 10 dysregulated transcription factors (TFs) between epithelium-like and mesenchyme-like malignant cells, in which overexpressed forkhead box protein A1 (FOXA1) was recognized as a poor prognosis marker of TNBC. Furthermore, we dissected the cell-cell communications via ligand-receptor (L-R) interactions. We observed that tumor-associated macrophages (TAMs) may support the invasion of malignant epithelial cells, based on CXCL-CXCR2 signaling. The tumor necrosis factor (TNF) signaling pathway secreted by TAMs was identified as an outgoing communication pattern, mediating the communications between monocytes/TAMs and malignant epithelial cells. Alternatively, the TNF-related ligand-receptor (L-R) pairs showed promising clinical implications. Some immunotherapy and anti-neoplastic drugs could interact with the L-R pairs as a potential strategy for the treatment of TNBC. In summary, this study enhances the understanding of the EMT process in the TNBC microenvironment, and dissections of EMT-related cell communications also provided us with potential treatment targets.

Leucomeris decora is a traditional medicinal plant that is listed as an endangered species in China. Recently, L. decora has become locally rare. Here the complete chloroplast genome of L. decora was assembled and reported for the first time. Its plastome was 151,491 bp in length, including a large single-copy region (LSC; 83,155 bp), a small single-copy region (SSC; 18,216 bp), and a pair of inverted repeated regions (IRa and IRb; 25,060 bp). The overall GC content was 37.8%, and the genome contains 134 genes, including 92 protein-coding genes, 8 rRNA genes, and 34 tRNA genes. Phylogenetic analysis of thirteen representative species from the family of Asteraceae showed that L. decora is clustered into one clade with Gerbera jamesonii with high bootstrap values, indicating a close relationship between these two species.

The utilization of recycled concrete aggregate (RCA) can reduce the environmental impact and decreases the cost of concrete. In this study, a comprehensive assessment of self-consolidating concrete (SCC) using RCA as partial or total replacement of coarse aggregate was conducted. Recycled concrete aggregate self-consolidating concrete (RCA-SCC) mixtures with varied water-to-cement (W/C) ratios (0.28–0.46), sand-to-aggregate (S/A) ratios (48–52%), fly ash (FA) contents (20–40%), RCA replacement ratios (0–100%), and water reducer contents (0–1.5%) were designed and tested. 5 groups of the RCA-SCC columns with different W/C and replacement ratios of RCA were also investigated. The slump flow, the J-ring flow and the cubic compressive strength, and the compressive behaviors of the RCA-SCC columns were studied. Results indicated that W/C ratio was the dominant parameter in RCA-SCC mixture, and the failure modes of the RCA-SCC columns were similar to those of the conventional concrete columns. Based on the experimental results, the mechanical performance of RCA-SCC columns was evaluated quantitatively, and a stress–strain relation model for predicting the axial compressive behavior of RCA-SCC column was proposed. This study will provide a reference for the engineering application of the environment-friendly SCC using RCA that are derived from tested or returned concretes with better performance.

Abstract It has been reported that Cavin1 deficiency causes lipodystrophy in both humans and mice by affecting lipid metabolism. The ablation of Cavin1 in rodents also causes a significant deviation from Mendelian ratio at weaning in a background‐dependent manner, suggesting the presence of undiscovered functions of Cavin1. In the current study, the results show that Cavin1 deficiency causes neonatal death in C57BL/6J mice by dampening the storage and mobilization of glycogen in the liver, which leads to lethal neonatal hypoglycemia. Further investigation by electron microscopy reveals that Cavin1 deficiency impairs the fenestration in liver sinusoidal endothelial cells (LSECs) and impacts the permeability of endothelial barrier in the liver. Mechanistically, Cavin1 deficiency inhibits the RhoA‐Rho‐associated protein kinase 2‐LIM domain kinase‐Cofilin signaling pathway and suppresses the dynamics of the cytoskeleton, and eventually causes the reduction of fenestrae in LSECs. In addition, the defect of fenestration in LSECs caused by Cavin1 deficiency can be rescued by treatment with the F‐actin depolymerization reagent latrunculin A. In summary, the current study reveals a novel function of Cavin1 on fenestrae formation in LSECs and liver glycogen metabolism, which provide an explanation for the neonatal death of Cavin1 null mice and a potential mechanism for metabolic disorders in patients with Cavin1 mutation.

Abstract It is remarkably desirable and challenging to design a stretchable conductive material with tunable electromagnetic‐interference (EMI) shielding and heat transfer for applications in flexible electronics. However, the existing materials sustained a severe attenuation of performances when largely stretched. Here, a super‐stretchable (800% strain) liquid metal foamed elastomer composite (LMF‐EC) is reported, achieving super‐high electrical (≈104 S cm−1) and thermal (17.6 W mK−1) conductivities under a large strain of 400%, which also exhibits unexpected stretching‐enhanced EMI shielding effectiveness of 85 dB due to the conductive network elongation and reorientation. By varying the liquid and solid states of LMF, the stretching can enable a multifunctional reversible switch that simultaneously regulates the thermal, electrical, and electromagnetic wave transport. Novel flexible temperature control and a thermoelectric system based on LMF‐EC is furthermore developed. This work is a significant step toward the development of smart electromagnetic and thermal regulator for stretchable electronics.

Since the existence of the complicated coupling between mould compression and resin flow, the full 3D simulation of the filling process in force-controlled compression resin transfer moulding (CRTM) has not been realized, especially when the resin flow front is irregular on the thickness direction during thick part moulding. In this paper, the coupled resin flow and mould compression behaviors are investigated firstly, a equivalent spring method is proposed to describe the preform compaction. The lubrication effect is taken into account, so the mould compression speed can be determined when the resin flow front is irregular on the thickness direction. Then the Volume of Fluid (VOF) two-phase model is established to express the resin-air flow in narrow gap and preform simultaneously, in which the narrow gap is considered as 3D area without flow resistance. Finally, the 3D numerical method for solving the above mathematical models is developed. In this method, the changing of the mould cavity is simulated by moving mesh technology, and the master-slave element method is used to simulate the resin squeezing from the infiltrated preform. Comparisons with analysis results are provided to prove the correctness of the above method, and two 3D examples are given to demonstrate the simulating capability.

Background/Aims: This study investigated the underlying mechanisms of the antidepressant effects of curcumin and dexanabinol-loaded solid lipid nanoparticles in corticosterone-induced cell and mice depression models. Methods: Curcumin and dexanabinol-loaded solid lipid nanoparticles (Cur/SLNs-HU-211) were synthesized via an emulsifcation and low-temperature solidification method. Antidepressant activities of nanoparticles in a corticosterone-induced major depression model were investigated by MTT assay, cellular uptake by flow cytometry, behaviour by Forced Swimming Test and rotarod test, neurotransmitters by High Performance Liquid Chromatography, Western blotting, qPCR and immunofluorescence. Results: Treatment with Cur/SLNs-HU-211 induced greater dopamine (DA)/5-hydroxytryptamine (5-HT) release with reduced corticosterone-induced apoptotic cell death in PC12 cells. Additionally, in vivo Cur/SLNs-HU-211 significantly induced recovery from depressive behaviour with increased DA/5-HT levels, CB1 mRNA levels and CB1, p-MEK1 and p-ERK1/2 protein expression levels in the hippocampus and striatum. Cur/SLNs-HU-211 improved CB1 expression and inspired the proliferation of astrocytes in the hippocampus and striatum, exerted neuroprotective effects by preventing corticosterone -induced BDNF/NeuN expression reduction. Conclusion: Our study implies that Cur/SLNs-HU-211 may be a useful approach for treatment of major depression.

To improve the modeling accuracy and efficiency of the tool wear monitoring system, a generalized regression neural network is adopted to build the tool wear prediction model because its excellent performance on learning speed and fast convergence to the optimal results whether the sample data are small or large. The low predictive accuracy and efficiency are caused by traditionally manual adjustment of the spread parameters in generalized regression neural network and then the improved fruit fly optimization algorithm is proposed to optimize the spread parameters of regression neural network automatically. Combining the improved fruit fly optimization and generalized regression neural network, the tool wear prediction method is proposed in the paper. Various experiments are carried out to validate the proposed method and the comparison results show a good agreement. In addition, the proposed method is compared to the tool wear prediction method in the literature, and the comparison results also show that the proposed method can achieve better performance.

A virtual Taylor impact of cellular materials is analyzed with a wave propagation technique, i.e. the Lagrangian analysis method, of which the main advantage is that no pre-assumed constitutive relationship is required. Time histories of particle velocity, local strain, and stress profiles are calculated to present the local stress–strain history curves, from which the dynamic stress–strain states are obtained. The present results reveal that the dynamic-rigid-plastic hardening (D-R-PH) material model introduced in a previous study of our group is in good agreement with the dynamic stress–strain states under high loading rates obtained by the Lagrangian analysis method. It directly reflects the effectiveness and feasibility of the D-R-PH material model for the cellular materials under high loading rates.

In the semi-aviation frequency-domain electromagnetic measurement, the induction air-core coil and the differential pre-amplifier circuit introduce noise, which affects the sensor and results in receiving weak signals and improving the signal-to-noise ratio of the system. In response to this problem, by analyzing the physical structure of the air-core coil sensor and the mechanism of the amplification circuit, combined with the simulation and experimental tests of voltage noise, current noise, resistance noise and other noise components, analyzed that the thermal noise is the main component of the sensor noise in the system frequency band, but directly removing the matching resistor increases the instability of the circuit, causes the coil to work in an underdamped state, and generates a time domain oscillation at the resonant frequency, source impedance analysis and analysis of differential pre-amplifier circuit in the frequency-domain detection method, abandoning the matching resistance scheme and magnetic flux negative feedback scheme. The matching capacitor is added to make the receiver detect the frequency range in the 1−10 kHz range. In normal operation, the noise level reaches 10 nV level, which not only increases the stability of the circuit, but also reduces the noise of the sensor. It has far-reaching significance for the detection of weak frequency signals.

Bus Rapid Transit (BRT) has become an increasing source of concern for public transportation of modern cities. Traditional contact sensing techniques during the process of health monitoring of BRT viaducts cannot overcome the deficiency that the normal free-flow of traffic would be blocked. Advances in computer vision technology provide a new line of thought for solving this problem. In this study, a high-speed target-free vision-based sensor is proposed to measure the vibration of structures without interrupting traffic. An improved keypoints matching algorithm based on consensus-based matching and tracking (CMT) object tracking algorithm is adopted and further developed together with oriented brief (ORB) keypoints detection algorithm for practicable and effective tracking of objects. Moreover, by synthesizing the existing scaling factor calculation methods, more rational approaches to reducing errors are implemented. The performance of the vision-based sensor is evaluated through a series of laboratory tests. Experimental tests with different target types, frequencies, amplitudes and motion patterns are conducted. The performance of the method is satisfactory, which indicates that the vision sensor can extract accurate structure vibration signals by tracking either artificial or natural targets. Field tests further demonstrate that the vision sensor is both practicable and reliable.