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Abstract Qunf Cave oxygen isotope (δ18Oc) record from southern Oman is one of the most significant of few Holocene Indian summer monsoon cave records. However, the interpretation of the Qunf δ18Oc remains in dispute. Here we provide a multi-proxy record from Qunf Cave and climate model simulations to reconstruct the Holocene local and regional hydroclimate changes. The results indicate that besides the Indian summer monsoon, the North African summer monsoon also contributes water vapor to southern Oman during the early to middle Holocene. In principle, Qunf δ18Oc values reflect integrated oxygen-isotope fractionations over a broad moisture transport swath from moisture sources to the cave site, rather than local precipitation amount alone, and thus the Qunf δ18Oc record characterizes primary changes in the Afro-Asian monsoon regime across the Holocene. In contrast, local climate proxies appear to suggest an overall slightly increased or unchanged wetness over the Holocene at the cave site.

Abstract Background To provide a reference for clinical selection of collagen membranes by analyzing the properties of three kinds of collagen membranes widely used in clinics: Bio-Gide membrane from porcine dermis (PD), Heal-All membrane from bovine dermis (BD), and Lyoplant membrane from bovine pericardium (BP). Methods The barrier function of three kinds of collagen membranes were evaluated by testing the surface morphology, mechanical properties, hydrophilicity, and degradation rate of collagen membranes in collagenase and artificial saliva. In addition, the bioactivity of each collagen membrane as well as the proliferation and osteogenesis of MC3T3-E1 cells were evaluated. Mass spectrometry was also used to analyze the degradation products. Results The BP membrane had the highest tensile strength and Young’s modulus as well as the largest water contact angle. The PD membrane exhibited the highest elongation at break, the smallest water contact angle, and the lowest degradation weight loss. The BD membrane had the highest degradation weight loss, the highest number of proteins in its degradation product, the strongest effect on the proliferation of MC3T3-E1 cells, and the highest expression level of osteogenic genes. Conclusions The PD membrane is the best choice for shaping and maintenance time, while the BD membrane is good for osteogenesis, and the BP membrane is suitable for spatial maintenance. To meet the clinical requirements of guided bone regeneration, using two different kinds of collagen membranes concurrently to exert their respective advantages is an option worth considering.

Abstract Increasing evidence indicates that long non-coding RNA (lncRNA) is one of the most important RNA regulators in the pathogenesis of neuroblastoma (NB). Here, we found that FAM201A was low expressed in NB and a variety of gain and loss of function studies elucidated the anti-tumor effects of FAM201A on the regulation of proliferation, migration and invasion of NB cells. Intriguingly, we identified the ability of FAM201A to encode the tumor-suppressing protein, NBASP, which interacted with FABP5 and negatively regulated its expression. In vivo assays also revealed NBASP repressed NB growth via inactivating MAPK pathway mediated by FABP5. In conclusion, our findings demonstrated that NBASP encoded by FAM201A played a tumor-suppressor role in NB carcinogenesis via down-regulating FABP5 to inactivate the MAPK pathway. These results extended our understanding of the relationship of lncRNA-encoded functional peptides and plasticity of tumor progression.

Background Congenital insensitivity to pain with anhidrosis (CIPA) with Charcot arthropathy is a rare combination in orthopaedic clinical practice. The experience dealing with such patients is limited. Here with this case of approximately 10 years follow‐up, we wish to shed light on the choices of strategies of surgeries and alerting clinicians with post‐surgery complications. The possible underlying reasons for the recurrent Charcot arthropathies as well as strategies for peri‐operative management for such surgical cases are also discussed. Case Presentation The patient underwent a surgery to correct her severe kyphosis caused by CIPA‐related Charcot spine. Multiple post‐surgery complications occurred during her follow‐up, including hardware migration, adjacent segment disease (ASD), and loosening pedicle screws. Five revision surgeries were conducted consequently. From the limited experience on the management of CIPA‐related Charcot spine, surgical correction is still the first‐line treatment. Conclusions Of all the 16 cases reviewed (including our case), loosening pedicle screws, hardware migration, and ASDs are the common post‐surgery complications. Large‐scale removal of damaged vertebrae and subsequent reconstruction are not recommended, which might increase the risk of hardware migration. A 360° long‐segment fusion might be of help to reduce the risk of ASDs. In the meantime, comprehensive management including careful nursing, proper rehabilitation exercises, and treatments targeting bone mineral metabolism is also critical.

Abstract Background The elevated circulating toxins secondary to the impairment of intestinal barrier integrity commonly elicit a chronic inflammatory response and finally contribute to multiple diseases. These toxins, including bacterial by-products and heavy metals, are the potent risk factors for the development of recurrent spontaneous abortion (RSA). Preclinical evidence suggests that several dietary fibers can restore intestinal barrier function and decrease the accumulation of heavy metals. However, it is uncertain whether treatment with a newly developed blend of dietary fibers product (Holofood) benefits patients with RSA. Methods In this trial, we enrolled 70 adult women with RSA, who were randomly assigned into the experiment group and the control group in a 2:1 ratio. Upon the basis of conventional therapy, subjects in the experiment group (n = 48) received 8 weeks oral administration with Holofood three times daily at a dose of 10 g each time. Subjects without Holofood consumption were set as the control (n = 22). Blood samples were collected for the determinations of metabolic parameters, heavy mental lead, and the indices related to intestinal barrier integrity (d-lactate, bacterial endotoxin, and diamine oxidase activity). Results The reduction amplitude in blood lead from baseline to week 8 was 40.50 ± 54.28 (μg/L) in the experiment group as compared with 13.35 ± 36.81 (μg/L) in the control group (P = 0.037). The decreased level of serum d-lactate from baseline to week 8 was 5.58 ± 6.09 (mg/L) in the experiment group as compared with − 2.38 ± 8.90 (mg/L, P

Abstract In view of the long calculation cycle, high processing test and cost of the traditional aero-engine combustion chamber design process, which restricts the engine optimization design cycle, this paper innovatively proposes a surrogate model for the performance of aero-engine combustion chambers based on the POD-Hierarchical-Kriging method. Through experiments, the predicted results of the POD-Hierarchical-Kriging model are compared and analyzed with the calculated results of the one-dimensional program, and the root mean square error of the predicted values of combustion efficiency and total pressure loss is 0.0064% and 0.1995%, respectively. The accuracy of the POD-Hierarchical-Kriging model is compared with the cubic polynomial model, the basic Kriging model and the Hierarchical-Kriging model. It verifies the feasibility and accuracy of the POD-Hierarchical-Kriging model for the prediction of performance of aero-engine combustion chambers. The global sensitivity analysis method is applied to obtain the influence effect of design variables on the performance. Then, a multi-objective optimization method based on the NSGA-II algorithm is studied, and finally the optimal set of Pareto solutions is obtained and analyzed, which can be used to guide the optimal design of aero-engine combustion chambers and accelerate the progress of aero-engine development.

Abstract Background A workplace-based primary prevention intervention be an effective approach to reducing the incidence of hypertension (HTN). However, few studies to date have addressed the effect among the Chinese working population. We assessed the effect of a workplace-based multicomponent prevention interventions program for cardiovascular disease on reducing the occurrence of HTN through encouraging employees to adopt a healthy lifestyle. Methods In this post hoc analysis of cluster randomized controlled study, 60 workplaces across 20 urban regions in China were randomized to either the intervention group (n = 40) or control group (n = 20). All employees in each workplace were asked to complete a baseline survey after randomization for obtaining sociodemographic information, health status, lifestyle, etc. Employees in the intervention group were given a 2-year workplace-based primary prevention intervention program for improving their cardiovascular health, including (1) cardiovascular health education, (2) a reasonable diet, (3) tobacco cessation, (4) physical environment promotion, (5) physical activity, (6) stress management, and (7) health screening. The primary outcome was the incidence of HTN, and the secondary outcomes were improvements of blood pressure (BP) levels and lifestyle factors from baseline to 24 months. A mix effect model was used to assess the intervention effect at the end of the intervention in the two groups. Results Overall, 24,396 participants (18,170 in the intervention group and 6,226 in the control group) were included (mean [standard deviation] age, 39.3 [9.1] years; 14,727 men [60.4%]). After 24 months of the intervention, the incidence of HTN was 8.0% in the intervention groups and 9.6% in the control groups [relative risk (RR) = 0.66, 95% CI, 0.58 ~ 0.76, P

Abstract Background Primary liver cancer is a malignant tumour of the digestive system, ranking second in cancer mortality in China. In different types of cancer, such as liver cancer, microRNAs (miRNAs) have been shown to be dysregulated. However, little is known about the role of miR-5195-3p in insulin-resistant liver cancer. Methods and results In this study, in vitro and in vivo experiments were conducted to identify the altered biological behaviour of insulin-resistant hepatoma cells (HepG2/IR), and we proved that HepG2/IR cells had stronger malignant biological behaviour. Functional experiments showed that enhanced expression of miR-5195-3p could inhibit the proliferation, migration, invasion, epithelial-mesenchymal transition (EMT) and chemoresistance of HepG2/IR cells, while impaired expression of miR-5195-3p in HepG2 cells resulted in the opposite effects. Bioinformatics prediction and dual luciferase reporter gene assays proved that SOX9 and TPM4 were the target genes of miR-5195-3p in hepatoma cells. Conclusions In conclusion, our study demonstrated that miR-5195-3p plays a critical role in insulin-resistant hepatoma cells and might be a potential therapeutic target for liver cancer.

Abstract Hawking radiation is one of the quantum features of a black hole that can be understood as a quantum tunneling across the event horizon of the black hole, but it is quite difficult to directly observe the Hawking radiation of an astrophysical black hole. Here, we report a fermionic lattice-model-type realization of an analogue black hole by using a chain of 10 superconducting transmon qubits with interactions mediated by 9 transmon-type tunable couplers. The quantum walks of quasi-particle in the curved spacetime reflect the gravitational effect near the black hole, resulting in the behaviour of stimulated Hawking radiation, which is verified by the state tomography measurement of all 7 qubits outside the horizon. In addition, the dynamics of entanglement in the curved spacetime is directly measured. Our results would stimulate more interests to explore the related features of black holes using the programmable superconducting processor with tunable couplers.

Abstract To address the instability timing problem of residual coal pillars under mining disturbance, their stress migration law and instability mechanism were studied via numerical simulation, physical simulation, and engineering tests considering residual coal remining in the 3101 working face of the Shenghua Coal Industry. The results show that as the mining progresses, the stress concentrates on both sides of the remaining coal pillar and empty roadway. When the first coal pillar in front of the working face loses its bearing capacity, the stress is transmitted forward, resulting in the advanced collapse of the empty roadway roof and an excessive load on the second coal pillar in front of the working face. Additionally, the critical value prediction model of the coal pillar stability safety factor fs ${f}_{{ m{s}}}$ was constructed. If fs ${f}_{{ m{s}}}$ is less than the critical value during the repeated mining period, the remaining coal pillar must be reinforced. A hollow grouting crossed anchor is selected for coal pillar reinforcement; thus, realizing the safe mining of the remaining coal pillars. Our research results provide theoretical support for the safe secondary mining of coal in China and similar coal mines worldwide.

In order to solve the problems of methods that use a single form of sensing, the ease of causing deformation damage to the targets with a low hardness during grasping, and the slow sliding inhibition of a prosthetic hand when the grasping target slides, which are problems that exist in most current intelligent prosthetic hands, this study introduces an adaptive control strategy for prosthetic hands based on multi-sensor sensing. Using a force-sensing resistor (FSR) to collect changes in signals generated after contact with a target, a prosthetic hand can classify the target’s hardness level and adaptively provide the desired grasping force so as to reduce the deformation of and damage to the target in the process of grasping. A fiber-optic sensor collects the light reflected by the object to identify its surface roughness, so that the prosthetic hand adaptively adjusts the sliding inhibition method according to the surface roughness information to improve the grasping efficiency. By integrating information on the hardness and surface roughness of the target, an adaptive control strategy for a prosthetic hand is proposed. The experimental results showed that the adaptive control strategy was able to reduce the damage to the target by enabling the prosthetic hand to achieve stable grasping; after grasping the target with an initial force and generating sliding, the efficiency of slippage inhibition was improved, the target could be stably grasped in a shorter time, and the hardness, roughness and weight ranges of targets that could be grasped by the prosthetic hand were enlarged, thus improving the success rate of stable grasping under extreme conditions.

To investigate the effects of nano-SiO2 (NS) and polyvinyl alcohol (PVA) fibers on the durability and mechanical properties of cementitious composites subjected to saline freeze–thaw cycling, a series of PVA fiber-reinforced cementitious composite (PFRCC) specimens were prepared using various fiber contents, and a series of NS and PVA fiber-reinforced cementitious composite (NPFRCC) specimens were prepared using various combinations of NS and fiber contents. Durability and fracture toughness tests were subsequently conducted on the specimens after different numbers of saline freeze–thaw cycles. The results indicate that the degradation of material properties can be divided into slow and accelerated damage stages before/after 50 freeze–thaw cycles. The durability and fracture toughness of the specimen series tended to increase, then decrease with increasing NS and PVA contents, suggesting optimum levels. When the PVA fiber content was 0.5%, PFRCC specimens had the best durability after saline freeze–thaw cycles; when the NS and PVA fiber contents were 1.0% and 0.5%, respectively, NPFRCC specimens had the best durability and fracture properties, and the initiation toughness, destabilization toughness, and fracture energy after 100 saline freeze–thaw cycles were 120.69%, 160.02%, and 451.31%, respectively. The results of this study may guide future exploration of the durability and mechanical properties of concrete subjected to freeze–thaw action.

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Peony seed oil, known for its high nutritional value and low production yield, has become a crucial component in high-quality health products. Consequently, enhancing the extraction efficiency of peony seed oil has become an industry objective. Pulse electric field (PEF) technology, as a non-thermal extraction method, has shown promising advancements in improving plant oil yield by enhancing cell permeability. In this study, we designed a static parallel plate PEF treatment unit to process peony seed particles. By manipulating pulse voltage parameters, we investigated the effects of particle size and PEF strength on the oil yield. We also analyzed and evaluated tocopherol in the oil before and after treatment. The results demonstrated that PEF significantly increased the oil yield. Both treated and control groups exhibited gradually increased oil yields with decreasing particle size until reaching saturation at a certain particle size. Increasing voltage frequency did not have a significant impact on the oil yield; however, increasing voltage amplitude resulted in an optimal point for maximum oil yield. Analysis of oil composition indicated that PEF appropriately increased tocopherol content. These findings provide a foundation for further optimization of PEF parameters to assist in extracting peony seed oil and facilitate its industrial application.

Nano-doped hollow fiber is currently receiving extensive attention due to its multifunctionality and booming development. However, the microfluidic fabrication of nano-doped hollow fiber in a simple, smooth, stable, continuous, well-controlled manner without system blockage remains challenging. In this study, we employ a microfluidic method to fabricate nano-doped hollow fiber, which not only makes the preparation process continuous, controllable, and efficient, but also improves the dispersion uniformity of nanoparticles. Hydrogel hollow fiber doped with carbon nanotubes is fabricated and exhibits superior electrical conductivity (15.8 S m−1), strong flexibility (342.9%), and versatility as wearable sensors for monitoring human motions and collecting physiological electrical signals. Furthermore, we incorporate iron tetroxide nanoparticles into fibers to create magnetic-driven micromotors, which provide trajectory-controlled motion and the ability to move through narrow channels due to their small size. In addition, manganese dioxide nanoparticles are embedded into the fiber walls to create self-propelled micromotors. When placed in a hydrogen peroxide environment, the micromotors can reach a top speed of 615 μm s−1 and navigate hard-to-reach areas. Our nano-doped hollow fiber offers a broad range of applications in wearable electronics and self-propelled machines and creates promising opportunities for sensors and actuators.

Forest fires ignited by lightning accounted for 68.28% of all forest fires in the Greater Khingan Mountains (GKM) region of northeast China. Forecasting the incidence of lightning-triggered forest fires in the region is imperative for mitigating deforestation, preserving biodiversity, and safeguarding distinctive natural habitats and resources. Lightning monitoring data and vegetation moisture content have emerged as pivotal factors among the various influences on lightning-induced fires. This study employed innovative satellite remote sensing technology to swiftly acquire vegetation moisture content data across extensive forested regions. Firstly, the most suitable method to identify the lightning strikes that resulted in fires and two crucial lightning parameters correlated with fire occurrence are confirmed. Secondly, a logistic regression method is proposed for predicting the likelihood of fires triggered by lightning strikes. Finally, the method underwent verification using five years of fire data from the GKM area, resulting in an AUC value of 0.849 and identifying the primary factors contributing to lightning-induced fires in the region.

The drastic increase of forest fire occurrence, which in recent years has posed severe threat and damage worldwide to the natural environment and human society, necessitates smoke detection of the early forest fire. First, a semantic segmentation method based on multiple color spaces feature fusion is put forward for forest fire smoke detection. Considering that smoke images in different color spaces may contain varied and distinctive smoke features which are beneficial for improving the detection ability of a model, the proposed model integrates the function of multi-scale and multi-type self-adaptive weighted feature fusion with attention augmentation to extract the enriched and complementary fused features of smoke, utilizing smoke images from multi-color spaces as inputs. Second, the model is trained and evaluated on part of the FIgLib dataset containing high-quality smoke images from watchtowers in the forests, incorporating various smoke types and complex background conditions, with a satisfactory smoke segmentation result for forest fire detection. Finally, the optimal color space combination and the fusion strategy for the model is determined through elaborate and extensive experiments with a superior segmentation result of 86.14 IoU of smoke obtained.

Forest fires, as severe natural disasters, pose significant threats to ecosystems and human societies, and their spread is characterized by constant evolution over time and space. This complexity presents an immense challenge in predicting the course of forest fire spread. Traditional methods of forest fire spread prediction are constrained by their ability to process multidimensional fire-related data, particularly in the integration of spatiotemporal information. To address these limitations and enhance the accuracy of forest fire spread prediction, we proposed the AutoST-Net model. This innovative encoder–decoder architecture combines a three-dimensional Convolutional Neural Network (3DCNN) with a transformer to effectively capture the dynamic local and global spatiotemporal features of forest fire spread. The model also features a specially designed attention mechanism that works to increase predictive precision. Additionally, to effectively guide the firefighting work in the southwestern forest regions of China, we constructed a forest fire spread dataset, including forest fire status, weather conditions, terrain features, and vegetation status based on Google Earth Engine (GEE) and Himawari-8 satellite. On this dataset, compared to the CNN-LSTM combined model, AutoST-Net exhibits performance improvements of 5.06% in MIou and 6.29% in F1-score. These results demonstrate the superior performance of AutoST-Net in the task of forest fire spread prediction from remote sensing images.

Partially impaired sensor arrays pose a significant challenge in accurately estimating signal parameters. The occurrence of bad data is highly probable, resulting in random loss of source information and substantial performance degradation in parameter estimation. In this paper, a tensor variational sparse Bayesian learning (TVSBL) method is proposed for the estimate of direction of arrival (DOA) and polarization parameters jointly based on a conformal polarization sensitive array (CPSA), taking into account scenarios with the partially impaired sensor array. First, a sparse tensor-based received data model is developed for CPSAs that incorporates bad data. Then, a column vector detection method is proposed to diagnose the positions of the impaired sensors. In scenarios involving partially impaired sensor arrays, a low-rank matrix completion method is employed to recover the random loss of signal information. Finally, variational sparse Bayesian learning (VSBL) and minimum eigenvector methods are utilized sequentially to obtain the DOA and polarization parameters estimation, successively. Furthermore, the Cramér-Rao bound is given for the proposed method. Simulation results validated the effectiveness of the proposed method.

In clinical practice, colon cancer is a prevalent malignant tumor of the digestive system, characterized by a complex and progressive process involving multiple genes and molecular pathways. Historically, research efforts have primarily focused on investigating individual genes; however, our current study aims to explore the collective impact of multiple genes on colon cancer and to identify potential therapeutic targets associated with these genes. For this research, we acquired the gene expression profiles and RNA sequencing data of colon cancer from TCGA. Subsequently, we conducted differential gene expression analysis using R, followed by GO and KEGG pathway enrichment analyses. To construct a protein–protein interaction (PPI) network, we selected survival-related genes using the log-rank test and single-factor Cox regression analysis. Additionally, we performed LASSO regression analysis, immune infiltration analysis, mutation analysis, and cMAP analysis, as well as an investigation into ferroptosis. Our differential expression and survival analyses identified 47 hub genes, and subsequent LASSO regression analysis refined the focus to 23 key genes. These genes are closely linked to cancer metastasis, proliferation, apoptosis, cell cycle regulation, signal transduction, cancer microenvironment, immunotherapy, and neurodevelopment. Overall, the hub genes discovered in our study are pivotal in colon cancer and are anticipated to serve as important biological markers for the diagnosis and treatment of the disease.

Low-dimensional metal halides with efficient luminescence properties have received widespread attention recently. However, nontoxic and stable low-dimensional metal halides with efficient blue emission are rarely reported. We used a solvothermal synthesis method to synthesize tetravalent zirconium ion-doped all-inorganic zero-dimensional Cs2ZnCl4 for the first time. Bright blue emission in the range of 370 nm–700 nm with a emission maximum at 456 nm was observed in Zr4+:Cs2ZnCl4 accompanied by a large Stokes shift, which was due to self-trapped excitons (STEs) caused by the lattice vibrations of the twisted structure. Simultaneously, the PLQY of Zr4+:Cs2ZnCl4 achieve an impressive 89.67%, positioning it as a compelling contender for future applications in blue-light technology.

Oceanic targets, including ripples, islands, vessels, and coastlines, display distinct sparse characteristics, rendering the ocean a significant arena for sparse Synthetic Aperture Radar (SAR) imaging rooted in sparse signal processing. Deep neural networks (DNNs), a current research emphasis, have, when integrated with sparse SAR, attracted notable attention for their exceptional imaging capabilities and high computational efficiency. Yet, the efficiency of traditional unfolding techniques is impeded by their architecturally inefficient design, which curtails their information transmission capacity and consequently detracts from the quality of reconstruction. This paper unveils a novel Memory-Augmented Deep Unfolding Network (MADUN) for SAR imaging in marine environments. Our methodology harnesses the synergies between deep learning and algorithmic unfolding, enhanced with a memory component, to elevate SAR imaging’s computational precision. At the heart of our investigation is the incorporation of High-Throughput Short-Term Memory (HSM) and Cross-Stage Long-Term Memory (CLM) within the MADUN framework, ensuring robust information flow across unfolding stages and solidifying the foundation for deep, long-term informational correlations. Our experimental results demonstrate that our strategy significantly surpasses existing methods in enhancing the reconstruction of sparse marine scenes.

Martian rocks contain crucial information about the genesis of Mars and the historical evolution of Martian climate change. Consequently, extracting and examining Martian rocks are pivotal in advancing our comprehensive understanding of the red planet. However, the current core drill string is prone to wear and tear, and the samples are susceptible to thermal denaturation. To address these challenges, we introduce two novel types of drill bits, the conical straight junk slot and the conical spiral junk slot, both employing impregnated diamond as the primary material. Comparative experiments were meticulously conducted to evaluate the influence of different junk configurations on drilling parameters, including speed, abrasion resistance, drilling force loading, and sample temperature rise. The findings unequivocally demonstrate the superior performance of the spiral junk slot. Furthermore, simulations were performed to examine the drilling process on basalt using a fixed configuration drill bit, validating the occurrence of the sample temperature rise. The research presented in this paper offers valuable programmatic references and essential data support for future Martian rock coring drilling missions.

The use of automation technology in agriculture has become particularly important as global agriculture is challenged by labor shortages and efficiency gains. The automated process for harvesting apples, an important agricultural product, relies on efficient and accurate detection and localization technology to ensure the quality and quantity of production. Adverse lighting conditions can significantly reduce the accuracy of fruit detection and localization in automated apple harvesting. Based on deep-learning techniques, this study aims to develop an accurate fruit detection and localization method under adverse light conditions. This paper explores the LE-YOLO model for accurate and robust apple detection and localization. The traditional YOLOv5 network was enhanced by adding an image enhancement module and an attention mechanism. Additionally, the loss function was improved to enhance detection performance. Secondly, the enhanced network was integrated with a binocular camera to achieve precise apple localization even under adverse lighting conditions. This was accomplished by calculating the 3D coordinates of feature points using the binocular localization principle. Finally, detection and localization experiments were conducted on the established dataset of apples under adverse lighting conditions. The experimental results indicate that LE-YOLO achieves higher accuracy in detection and localization compared to other target detection models. This demonstrates that LE-YOLO is more competitive in apple detection and localization under adverse light conditions. Compared to traditional manual and general automated harvesting, our method enables automated work under various adverse light conditions, significantly improving harvesting efficiency, reducing labor costs, and providing a feasible solution for automation in the field of apple harvesting.

Logistics services are integral to urban economic activity, and delving into the spatial distribution traits and evolutionary pathways of various kinds of logistics service node facilities (LSNF) is markedly valuable for understanding a city’s functional spatial makeup and refining the spatial layout of logistics services. This study quantitatively and qualitatively analyzes the spatial congregation and spreading characteristics of diverse LSNFs in Wuhan in 2011, 2014, 2017, and 2020, employing kernel density analysis, average nearest neighbor index, mean center, and distance distribution frequency, seeking to characterize the spatial evolution characteristics of LSNF, alongside examining the trends in distances to city cores, principal adjoining roads, and production and consumption sites. The following conclusions were made: (1) Between 2011 and 2020, various types of LSNFs in Wuhan experienced a pattern characterized by the noticeable coexistence of spatial expansion and agglomeration, particularly visible after 2014. The degree of agglomeration is classified in a descending order as follows: CWC, STN, PSN, and PDN. (2) An “absolute diffusion” phenomenon characterizes the distribution of distances between various kinds of LSNFs and city cores or neighboring roads, with the lion’s share of high-frequency distribution zones spreading beyond city cores by 5–10 km, and a majority of the LSNFs being situated within 1 km from adjacent roads. (3) While the LSNF collective exhibits a stronger tendency towards the consumption facet, it reflects a surrounding of industrial production sites on the production facet and locations of manufactured goods consumption on the consumption facet, followed by locations of agricultural product consumption and comprehensive consumption sites.

Colorectal cancer (CRC), a prevalent malignant tumor of the digestive system, ranks as the third and second in global incidence and mortality, respectively, in 2020, with 1.93 million new cases (≈10% of all cancers). There are 940,000 deaths (≈9.4% of all cancers), and the incidence of CRC in younger patients (under 50 years of age) has become a new trend. The pathogenesis of CRC is primarily attributed to a series of genetic and epigenetic abnormalities within normal colonic epithelial cells, coupled with the reshaping of the tumor microenvironment in the surrounding stroma. This process leads to the transformation of colorectal adenomas into invasive adenocarcinomas. Although genetic changes are known to be the primary driving force in the occurrence and progression of CRC, recent research indicates that epigenetic regulation serves as a crucial molecular marker in cancer, playing a significant role in the pathological and physiological control of interactions between genetics and the environment. This review discusses the current global epidemiology of CRC, its risk factors, and preventive treatment strategies. The current study explores the latest advancements in the epigenetic regulation of CRC, including DNA methylation, histone modifications, and non-coding RNAs (ncRNAs). These developments hold potential as screening tools, prognostic biomarkers, and therapeutic targets for CRC.

Efforts to enhance the speed and reduce the energy consumption of underwater vehicles have led to the proposal of a novel mucus release structure inspired by the secretion of mucus cells on fish skin. This structure features interconnected microgrooves with excellent flexibility for adjusting to different states, effectively reducing drag through mucus release. Numerical analysis of the drag reduction performance of the mucous-releasing micro-pore structure was conducted using ANSYS Fluent 19.2 software. This structure is capable of reducing the velocity gradient near the wall and, owing to the presence of micro-pore structures, decreasing the overall compressed area, thereby achieving drag reduction effects. The experimental results revealed a drag reduction effect of 20.56% when the structure was bent at an angle of 120°. The drag reduction varied under different attitudes such as tension and compression. This mucus release structure achieves reusability through a direct mucous injection process. This research provides valuable insights for the drag reduction study of underwater vehicles, such as ships and submarines, laying a foundation for advancing the development and applications of this field in the future.

In order to evaluate the accuracy and applicability of a two-step chemical scheme for kerosene in supersonic combustion under low total temperature, computations of the three-dimensional combustion flow field of scramjet have been performed with this model. The results were obtained with the combustor configurations including a rectangular combustor with single-cavity and a circular combustor with dual-cavity, and with the total temperature including 950 K and 600 K. Results show that the simulated wall pressure and combustion flow field are in agreement with the experiments, and the simulated flow field can accurately reflect the chemical energy release during the combustion process. As expected, more overall information of combustion flow field including the flow structure, the physical variable distribution and the combustion mode can be obtained by analyzing the numerical results.

Abstract Background Decidual macrophages participate in immune regulation at the maternal–fetal interface. Abnormal M1/M2 polarization of decidual macrophages might predispose immune maladaptation in recurrent pregnancy loss (RPL). However, the mechanism of decidual macrophage polarization is unclear. We explored the role of Estradiol (E2)-sensitive serum-glucocorticoid regulated kinase (SGK) 1 in promoting macrophage polarization and suppressing inflammation at the maternal–fetal interface. Methods We assessed serum levels of E2 and progesterone during first trimester of pregnancy in women with or without threatened miscarriages (ended in live birth, n = 448; or early miscarriages, n = 68). For detection of SGK1 in decidual macrophages, we performed immunofluorescence labeling and western blot analysis applying decidual samples from RPL (n = 93) and early normal pregnancy (n = 66). Human monocytic THP-1 cells were differentiated into macrophages and treated with Toll-like receptor (TLR) 4 ligand lipopolysaccharide (LPS), E2, inhibitors or siRNA for in vitro analysis. Flow cytometry analysis were conducted to detect macrophages polarization. We also applied ovariectomized (OVX) mice with hormones exploring the mechanisms underlying the regulation of SGK1 activation by E2 in the decidual macrophages in vivo. Results SGK1 expression down regulation in the decidual macrophages of RPL was consistent with the lower concentration and slower increment of serum E2 from 4 to 12 weeks of gestation seen in these compromised pregnancies. LPS reduced SGK1 activities, but induced the pro-inflammatory M1 phenotype of THP-1 monocyte-derived macrophages and T helper (Th) 1 cytokines that favored pregnancy loss. E2 pretreatment promoted SGK1 activation in the decidual macrophages of OVX mice in vivo. E2 pretreatment amplified SGK1 activation in TLR4-stimulated THP-1 macrophages in vitro through the estrogen receptor beta (ERβ) and PI3K pathway. E2-sensitive activation of SGK1 increased M2 macrophages and Th2 immune responses, which were beneficial to successful pregnancy, by inducing ARG1 and IRF4 transcription, which are implicated in normal pregnancy. The experiments on OVX mice have shown that pharmacological inhibition of E2 promoted nuclear translocation of NF-κB in the decidual macrophages. Further more, pharmacological inhibition or knockdown of SGK1 in TLR4-stimulated THP-1 macrophages activated NF-κB by promoting its nuclear translocation, leading to increased secretion of pro-inflammatory cytokines involved in pregnancy loss. Conclusion Our findings highlighted the immunomodulatory roles of E2-activated SGK1 in Th2 immune responses by priming anti-inflammatory M2 macrophages at the maternal–fetal interface, resulting in a balanced immune microenvironment during pregnancy. Our results suggest new perspectives on future preventative strategies for RPL.

Abstract Quantum simulation enables study of many-body systems in non-equilibrium by mapping to a controllable quantum system, providing a powerful tool for computational intractable problems. Here, using a programmable quantum processor with a chain of 10 superconducting qubits interacted through tunable couplers, we simulate the one-dimensional generalized Aubry-André-Harper model for three different phases, i.e., extended, localized and critical phases. The properties of phase transitions and many-body dynamics are studied in the presence of quasi-periodic modulations for both off-diagonal hopping coefficients and on-site potentials of the model controlled respectively by adjusting strength of couplings and qubit frequencies. We observe the spin transport for initial single- and multi-excitation states in different phases, and characterize phase transitions by experimentally measuring dynamics of participation entropies. Our experimental results demonstrate that the recently developed tunable coupling architecture of superconducting processor extends greatly the simulation realms for a wide variety of Hamiltonians, and can be used to study various quantum and topological phenomena.

Abstract Background De novo urothelial carcinoma (UC) is a leading cause of death after kidney transplant (KT). The efficacy of various treatments, apart from surgery, and the prognosis for patients with urothelial carcinoma after kidney transplantation remain unclear. Methods We retrospectively reviewed the efficacy of chemotherapy with gemcitabine + cisplatin (GC) or gemcitabine + carboplatin (GCa), bladder infusion chemotherapy, and immunosuppression therapy for de novo UC in kidney transplantation recipients at different sites and T stages. We evaluated the prognosis and compared the difference using Kaplan-Meier analysis and the log-rank test. Results Of the 97 kidney transplantation recipients with de novo UC, 51 (52.6%) were diagnosed with upper urinary tract carcinoma (UTUC), 17 (17.5%) with bladder carcinoma (BC), and 29 (29.9%) with both UTUC and BC. The five-year survival rates for BC, UTUC, and BC + UTUC with ≤ T1 stage were 100%, 88.2%, and 57.7%, respectively, while the survival rates for UTUC, BC + UTUC with ≥ T2 stage were 90.2% and 48.2%. Cyclosporine A significantly improved progression-free survival (PFS) in UTUC with ≤ T1 stage (p = 0.017). Rapamycin significantly improved PFS in UTUC with ≥ T2 stage (p = 0.026). Bladder infusion chemotherapy and GC/GCa chemotherapy had no significant effect on each T stage and site. Patients with UTUC + BC had the poorest overall survival (OS) compared with those with BC and UTUC. Conclusion The prognosis of UC in different sites varies. GC/GCa chemotherapy and bladder infusion chemotherapy appear to have no effect on prognosis. Rapamycin can delay the progression of advanced UTUC.

Building layover detection is a crucial step in the 3D Synthetic Aperture Radar (SAR) imaging process in urban areas. It affects imaging efficiency and directly influences the final image quality. Currently, algorithms used for layover detection struggle to extract long-range global spatial characteristics and fail to fully exploit the rich features of layover in multi-channel SAR data. To address the issue of insufficient accuracy in existing layover detection algorithms to meet the requirements of urban 3D SAR imaging, this paper proposes a deep learning-powered SAR urban layover detection method that combines the advantages of the Vision Transformer (ViT) model and Convolutional Neural Network (CNN). The ViT model can efficiently extract global and long-range features through a self-attention mechanism, whereas the CNN has strong local feature extraction capabilities. Furthermore, the proposed method in this paper incorporates a module for investigating inter-channel layover features and interferometric phase layover features based on expert knowledge, which improves the accuracy and robustness of the algorithm while effectively decreasing the training pressure on the model in small-sample datasets. Finally, the proposed algorithm is tested on a self-built airborne array SAR dataset, and experimental findings revealed that the proposed algorithm achieves a detection accuracy of >94%, which is significantly higher than other layover detection algorithms, completely revealing the effectiveness of this method.

Highlights The skin-inspired multifunctional ultra-tough electronic skin with tunable mechanical properties was developed by a physically cross-linking salting-freezing-thawing method. The hydrogel integrates transparency (>60%), super toughness (up to 13.96 MJ m−3), good antibacterial properties (E. coli and S. aureus), UV protection (Filtration: 80%–90%), high electrical conductivity (4.72 S m−1), anti-swelling and recyclability. As a human–machine interface, it can be used for complex underwater activities, information encryption/decryption and finger joint rehabilitation training.

Abstract The extra‐high voltage (EHV) transformer winding disks are subjected to dynamic electromagnetic forces caused by short‐circuit currents. These periodically decaying impact forces may endanger the safety of the transformer. The winding constraint conditions around the circumference are different due to the influence of axial pressure structures and magnetic boundaries. Moreover, this difference becomes more evident as the voltage and capacity increase. To investigate the spatial differences and time effects of EHV transformer short‐circuit faults, this paper proposes a reliability evaluation method based on dynamic relative displacement (DRDEM) for the first time. Firstly, the suitable and efficient analysis method is summarized by comparing the deviation among different calculated impedances and the measured value. Then, the space‐time effect of windings is obtained by the static magnetic field and dynamic structural field based on equivalent compression supports. Furthermore, a 50 MVA/110 kV transformer is designed for the destructive short‐circuit test to simulate the short‐circuit ability feature of the EHV transformer. The disassembly phenomena after all the tests indicate that the DRDEM is more adaptable in characterizing the winding ability to withstand short circuit when investigating the spatial differences and time effects.

Abstract To screen potential pivotal targets in sepsis through peripheral blood. Septic patients (n = 23) and healthy volunteers (n = 10) were enrolled according to SEPSIS 3.0. Peripheral blood was collected within 24 h of enrollment, RNA-seq was performed on the peripheral blood. The sequencing data was screened for DEGs (p

Abstract FK506 binding proteins (FKBPs) are a highly-conserved group of proteins known to bind to FK506, an immunosuppressive drug. They play different physiological roles, including transcription regulation, protein folding, signal transduction and immunosuppression. A number of FKBP genes have been identified in eukaryotes; however, very little information about these genes has been reported in Locusta migratoria. Here, we identified and characterized 10 FKBP genes from L. migratoria. Phylogenetic analysis and comparison of domain architectures indicated that the LmFKBP family can be divided into two subfamilies and five subclasses. Developmental and tissue expression pattern analysis revealed that all LmFKBPs transcripts, including LmFKBP46, LmFKBP12, LmFKBP47, LmFKBP79, LmFKBP16, LmFKBP24, LmFKBP44b, LmFKBP53, were periodically expressed during different developmental stages and mainly expressed in the fat body, hemolymph, testis, and ovary. In brief, our work depicts a outline but panoramic picture of LmFKBP family in L. migratoria, and provides a solid foundation to further investigate the molecular functions of LmFKBPs.

Abstract Background Catheter-related bladder discomfort (CRBD) is a common postoperative bladder pain syndrome. Many drugs and interventions for managing CRBD have been studied, but their comparative effectiveness remains controversial. We made a study to assess the comparative effectiveness of interventions included Ketorolac, Lidocaine, Chlorpheniramine, Gabapentin, Magnesium, Nefopam, Oxycodone, Parecoxib, Solifenacin, Tolterodine, Bupivancaine, Dexmedetomidine, Hyoscine N-butyl bromide, Ketamine, Penile nerve block on urological postoperative CRBD. Methods We performed a network meta-analysis via Aggregate Data Drug Inormation System software included 18 studies with 1816 patients and assessed the risk of bias by Cochrane Collaboration tool. The incidence of moderate to severe CRBD at 0, 1, and 6 h after surgery and the incidence severe CRBD at 1 h after surgery were compared. Result The number of best rank is 0.48(Nefopam) and 0.22(Nefopam) in the incidence of moderate to severe CRBD at 1 h and incidence severe CRBD at 1 h. More than half of studies at unclear or high risk of bias. Conclusion Nefopam reduced the incidence of CRBD and prevented severe events, but limited by the small number of studies for each intervention and heterogeneous patients.

Abstract Background This study aimed to determine the differences among various volumes of condylar osseous patterns and the corresponding dentoskeletal characteristics based on the risk of temporomandibular disorder. Methods Craniofacial spiral computed tomography data of 60 Class II hyperdivergent female adults were divided into normal, resorptive, flattened, and osteophyte groups based on condylar osseous forms. The condylar volumes of each group were compared, and their correlations with the dentoskeletal characteristics were assessed in three dimensions. Pairwise least significant difference tests were used to examine individual pairwise differences between groups, and one-way analysis of variance was used to measure differences among multiple groups. Pearson correlation and Spearman rank correlation analyses were used to determine the correlation between condylar volume and dentofacial characteristics. Statistical significance was established at p

Abstract Epithelium‐specific ETS transcription factor 1 (ESE1) has been implicated in epithelial homeostasis, inflammation, as well as tumorigenesis, and cancer progression. However, numerous studies have reported contradictory roles—as an oncogene or a tumor suppressor of ESE1 in different cancers, and its function in the development and progression of pancreatic ductal adenocarcinoma (PDAC) has remained largely unexplored. Herein, we report that ESE1 was found upregulated in primary PDAC compared to normal pancreatic tissue, but high expression of ESE1 correlated to better relapse‐free survival in patients with PDAC. Interestingly, ESE1 was found to exhibit dual roles in regulation of malignant properties of PDAC cells in that its overexpression promoted cell proliferation, whereas its downregulation enhanced epithelial‐mesenchymal transition (EMT) phenotype. In the context of TGF‐β‐induced EMT, ESE1 is markedly downregulated at post‐transcriptional level, and reconstituted ESE1 expression partially reversed TGF‐β‐induced EMT marker expression. Furthermore, we identify AGR2 as a novel transcriptional target of ESE1 that participates in TGF‐β‐induced EMT in PDAC. Collectively, our findings reveal an ESE1/AGR2 axis that interacts with TGF‐β signaling to modulate EMT phenotype in PDAC.

Abstract The potential of microRNA regulation in oncotherapy is limited by the lack of delivery vehicles. Herein, it is shown that fluoropolymer coated DNA nanoclews (FNCs) provide outstanding ability to deliver oligonucleotide through circulation and realize near infrared (NIR) light activated angiogenesis suppression to abrogate tumors. Oligonucleotides are loaded in DNA nanoclews through sequence specific bindings and then a fluorinated zwitterionic polymer is coated onto the surface of nanoclews. Further incorporating quantum dots in the polymer coating endows the vectors with NIR‐IIb (1500–1700 nm) fluorescence and NIR light triggered release ability. The FNC vector can deliver oligonucleotides to cancer cells systemically and realize on‐demand cytosolic release of the cargo with high transfection efficiency. Taking advantage of the NIR‐IIb emission, the whole delivery process of FNCs is visualized volumetrically in vivo with a NIR light sheet microscope. Loaded by FNCs, an oligonucleotide can effectively silence the target miRNA when activated with NIR light, and inhibit angiogenesis inside tumor, leading to complete ablation of cancer. These findings suggest FNCs can be used as an efficient oligonucleotide delivery platform to modulate the expression of endogenous microRNA in gene therapy of cancer.

ObjectiveThis article aimed to evaluate the efficiency trends and influencing factors of essential public health services in Hainan Province after the healthcare reform launched in 2009 in China.MethodsThe efficiency of essential public health services (EPHS) at primary health institutions was assessed using data envelopment analysis (DEA), and the efficiency change was analyzed by employing the Malmquist productivity index (MPI). We used Tobit regression to identify the influence of environmental factors on the efficiency of public health services. The bootstrap method was adopted to reduce the impact of random errors on the result.ResultsThe bootstrapping bias-corrected efficiency revealed that the average values of technical efficiency, pure technical efficiency, and scale efficiency were 0.7582, 0.8439, and 0.8997, respectively, which meant that the EPHS in Hainan Province were not at the most effective state. The average bias-corrected MPI was 1.0407 between 2010 and 2011 and 1.7404 between 2011 and 2012. MPIs were less than 1.0000 during other periods investigated, ranging from 0.8948 to 0.9714, indicating that the efficiency of EPHS has been decreasing since 2013. The Tobit regression showed that the regression coefficients of per capita GDP, population density, the proportion of older people aged over 65, and the proportion of ethnic minority population were 0.0286, −0.0003, −0.0316, and − 0.0041 respectively, which were statistically significant (p

Trace elements play a crucial role in the growth and bioactive substance content of medicinal plants, but their utilization efficiency in soil is often low. In this study, soil and Aconitum carmichaelii samples were collected and measured from 22 different locations, followed by an analysis of the relationship between trace elements and the yield and alkaloid content of the plants. The results indicated a significant positive correlation between zinc, trace elements in the soil, and the yield and alkaloid content of A. carmichaelii. Subsequent treatment of A. carmichaelii with both bulk zinc oxide (ZnO) and zinc oxide nanoparticles (ZnO NPs) demonstrated that the use of ZnO NPs significantly enhanced plant growth and monoester-type alkaloid content. To elucidate the underlying mechanisms responsible for these effects, metabolomic analysis was performed, resulting in the identification of 38 differentially expressed metabolites in eight metabolic pathways between the two treatments. Additionally, significant differences were observed in the rhizosphere bacterial communities, with Bacteroidota and Actinobacteriota identified as valuable biomarkers for ZnO NP treatment. Covariation analysis further revealed significant correlations between specific microbial communities and metabolite expression levels. These findings provide compelling evidence that nanoscale zinc exhibits much higher utilization efficiency compared to traditional zinc fertilizer.

Objectives Ovarian serous carcinoma (OSC) is a major cause of gynaecological cancer death, yet there is a lack of reliable prognostic models. To address this, we developed and validated a nomogram based on conventional clinical characteristics and log odds of positive lymph nodes (LODDS) to predict the prognosis of OSC patients.Setting A Real-World Retrospective Cohort Study from the Surveillance, Epidemiology and End Results programme.Participants We obtained data on 4192 patients diagnosed with OSC between 2010 and 2015. Eligibility criteria included specific diagnostic codes, OSC being the primary malignant tumour and age at diagnosis over 18 years. Exclusion criteria were missing information on various factors and unknown cause of death or survival time.Primary and secondary outcome measures The primary outcome were overall survival (OS) and ovarian cancer-specific survival (OCSS).Results For OS and OCSS outcomes, we selected 7 and 5 variables, respectively, to establish the nomogram. In the training and validation cohorts, the C index for OS or OCSS was 0.716 or 0.718 and 0.731 or 0.733, respectively, with a 3-year time-dependent area under the curve (AUC) of 0.745 or 0.751 and a 5-year time-dependent AUC of 0.742 or 0.751. Calibration curves demonstrated excellent consistency between predicted and observed outcomes. The Net Reclassification Index, integrated discrimination improvement and decision curve analysis curves indicated that our nomogram performed better than the International Federation of Gynaecology and Obstetrics (FIGO) staging system in predicting OS and OCSS for OSC patients in both the training and validation cohorts.Conclusion Our nomogram, which includes LODDS, offers higher accuracy and reliability than the FIGO staging system and can predict overall and OCSS in OSC patients.

The optimal power flow problem in power systems is characterized by a number of complex objectives and constraints, which aim to optimize the total fuel cost, emissions, active power loss, voltage magnitude deviation, and other metrics simultaneously. These conflicting objectives and strict constraints challenge existing optimizers in balancing between active power and reactive power, along with good trade-offs among many metrics. To address these difficulties, this paper develops a co-evolutionary algorithm to solve the constrained many-objective optimization problem of optimal power flow, which evolves three populations with different selection strategies. These populations are evolved towards different parts of the huge objective space divided by large infeasible regions, and the cooperation between them renders assistance to the search for feasible and Pareto-optimal solutions. According to the experimental results on benchmark problems and the IEEE 30-bus, IEEE 57-bus, and IEEE 118-bus systems, the proposed algorithm is superior over peer algorithms in solving constrained many-objective optimization problems, especially the optimal power flow problems.

The increasing number of peri-implant diseases and the unsatisfactory results of conventional treatment are causing great concern to patients and medical staff. The effective removal of plaque which is one of the key causes of peri-implant disease from the surface of implants has become one of the main problems to be solved urgently in the field of peri-implant disease prevention and treatment. In recent years, with the advancement of materials science and pharmacology, a lot of research has been conducted to enhance the implant antimicrobial properties, including the addition of antimicrobial coatings on the implant surface, the adjustment of implant surface topography, and the development of new implant materials, and significant progress has been made in various aspects. Antimicrobial materials have shown promising applications in the prevention of peri-implant diseases, but meanwhile, there are some shortcomings, which leads to the lack of clinical widespread use of antimicrobial materials. This paper summarizes the research on antimicrobial materials applied to implants in recent years and presents an outlook on the future development.

Photonic neural networks (PNNs) are promising to replace conventional deep learning hardware due to their potentially higher energy efficiency and computational speed. Other than the fast progress on optical linear transformer, the nonlinear activators are much less mature. Usually, the optical activators employ the nonlinear mapping from input amplitude to output amplitude, which is limited by high threshold and loss, or rely on additional bias voltage and heterogeneous integration of external circuits. Herein, the activation induced by the Kramers–Kronig relationship is proposed, i.e., the connection between amplitude and phase of the light field, but not purely the light amplitude itself, namely, Kramers–Kronig activation (KKA). PNN with KKA exhibits learning capability apparently better than the activation‐free linear network and comparable to the network with popular activation functions like ReLU, Softplus, and so on. Moreover, PNN with KKA is highly programmable and cascadable supporting ultra‐deep networks. The essence of KKA is attributed to the learning of nonlinear features in relatively low‐dimensional RN × N space by linear features in high‐dimensional CN × N space. Considering besides the amplitude–phase coupling, several other parameters like wavelength, frequency, polarization, etc., can be also mutually linked. This approach may expand to new avenues for optical activations.