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Abstract CO2 electroreduction is a potential pathway to achieve net-zero emissions in the chemical industry. Yet, CO2 loss, resulting from (bi)carbonate formation, renders the process energy-intensive. Acidic environments can address the issue but at the expense of compromised product Faradaic efficiencies (FEs), particularly for multi-carbon (C2+) products, as rapid diffusion and migration of protons (H+) favors competing H2 and CO production. Here, we present a strategy of tuning the 2-position substituent length on benzimidazole (BIM)-based copper (Cu) coordination polymer (CuCP) precatalyst – to enhance CO2 reduction to C2+ products in acidic environments. Lengthening the substituent from H to nonyl enhances H+ diffusion retardation and decreases Cu-Cu coordination numbers (CNs), favoring further reduction of CO. This leads to a nearly 24× enhancement of selectivity towards CO hydrogenation and C-C coupling at 60 mA cm−2. We report the highest C2+ product FE of more than 70% at 260 mA cm−2 on pentyl-CuCP and demonstrate a CO2-to-C2+ single-pass conversion (SPC) of ~54% at 180 mA cm−2 using pentyl-CuCP in zero-gap electrolyzers.

Abstract Background The stromal cell derived factor 2 (SDF2) relates closely to the occurrence and development of several kind of cancers. There are few studies to investigate the clinicopathological and prognostic significance of SDF2 in gastric cancer (GC) patients. Methods We detected SDF2 expression in GC and normal gastric tissues using bioinformatics, western blot and immunohistochemistry. Furthermore, we tested the relationship between SDF2 expression and clinicopathological characteristics and prognosis of GC patients. Results Bioinformatics, western blot and immunohistochemistry results showed that SDF2 expression in GC tissue was higher than that in normal gastric tissue (P

Abstract Distant metastasis is a primary cause of mortality and contributes to poor surgical outcomes in cancer patients. Before the development of organ-specific metastasis, the formation of a pre-metastatic niche is pivotal in promoting the spread of cancer cells. This review delves into the intricate landscape of the pre-metastatic niche, focusing on the roles of tumor-derived secreted factors, extracellular vesicles, and circulating tumor cells in shaping the metastatic niche. The discussion encompasses cellular elements such as macrophages, neutrophils, bone marrow-derived suppressive cells, and T/B cells, in addition to molecular factors like secreted substances from tumors and extracellular vesicles, within the framework of pre-metastatic niche formation. Insights into the temporal mechanisms of pre-metastatic niche formation such as epithelial-mesenchymal transition, immunosuppression, extracellular matrix remodeling, metabolic reprogramming, vascular permeability and angiogenesis are provided. Furthermore, the landscape of pre-metastatic niche in different metastatic organs like lymph nodes, lungs, liver, brain, and bones is elucidated. Therapeutic approaches targeting the cellular and molecular components of pre-metastatic niche, as well as interventions targeting signaling pathways such as the TGF-β, VEGF, and MET pathways, are highlighted. This review aims to enhance our understanding of pre-metastatic niche dynamics and provide insights for developing effective therapeutic strategies to combat tumor metastasis.

Abstract Metastasis has been one of the primary reasons for the high mortality rates associated with tumours in recent years, rendering the treatment of current malignancies challenging and representing a significant cause of recurrence in patients who have undergone surgical tumour resection. Halting tumour metastasis has become an essential goal for achieving favourable prognoses following cancer treatment. In recent years, increasing clarity in understanding the mechanisms underlying metastasis has been achieved. The concept of premetastatic niches has gained widespread acceptance, which posits that tumour cells establish a unique microenvironment at distant sites prior to their migration, facilitating their settlement and growth at those locations. Neutrophils serve as crucial constituents of the premetastatic niche, actively shaping its microenvironmental characteristics, which include immunosuppression, inflammation, angiogenesis and extracellular matrix remodelling. These characteristics are intimately associated with the successful engraftment and subsequent progression of tumour cells. As our understanding of the role and significance of neutrophils in the premetastatic niche deepens, leveraging the presence of neutrophils within the premetastatic niche has gradually attracted the interest of researchers as a potential therapeutic target. The focal point of this review revolves around elucidating the involvement of neutrophils in the formation and shaping of the premetastatic niche (PMN), alongside the introduction of emerging therapeutic approaches aimed at impeding cancer metastasis.

Abstract Cancer immunotherapy has sparked a wave of cancer research, driven by recent successful proof-of-concept clinical trials. However, barriers are emerging during its rapid development, including broad adverse effects, a lack of reliable biomarkers, tumor relapses, and drug resistance. Integration of nanomedicine may ameliorate current cancer immunotherapy. Ultra-large surface-to-volume ratio, extremely small size, and easy modification surface of nanoparticles enable them to selectively detect cells and kill cancer cells in vivo. Exciting synergistic applications of the two approaches have emerged in treating various cancers at the intersection of cancer immunotherapy and cancer nanomedicine, indicating the potential that the combination of these two therapeutic modalities can lead to new paradigms in the treatment of cancer. This review discusses the status of current immunotherapy and explores the possible opportunities that the nanomedicine platform can make cancer immunotherapy more powerful and precise by synergizing the two approaches.

Objective Percutaneous vertebroplasty (PVP) is currently the most common surgical procedure for unstable Kummell disease (KD), but cement loosening or displacement often occurs after PVP. We had been using percutaneous pediculoplasty (PPP) or a self-developed bone cement bridging screw system to avoid this severe complication. This study intends to compare these novel surgical procedures through a 2-year follow-up evaluation. Methods From May 2017 to May 2021, 77 patients with single-level unstable KD were included in the PPP group, and 42 patients received the PVP-bone cement bridging screw system were included in the screw group. The changes in the vertebral body index (VBI), bisegmental Cobb angle, visual analogue scale (VAS) and Oswestry Disability Index (ODI) and the cement loosening rate and displacement rate at different follow-up time points were used to evaluate the clinical efficacy. Results There was no significant difference in VBI or bisegmental Cobb angle between the 2 groups (p > 0.05) before operation, immediately after operation and at 6-month follow-up, while at 1-year and 2-year postoperative evaluations, the screw group had higher VBI and bisegmental Cobb angle than the PPP group (p < 0.05). Before operation, immediately after operation, at 6-month and 1-year follow-up, there was no significant difference in VAS or ODI score between the 2 groups (p > 0.05), while at 2-year follow-up, the screw group still had higher VAS and ODI scores than the PPP group (p < 0.05). No bone cement displacement occurred in both groups, but the rate of bone cement loosening was 14.29% in group PPP, and 0 in screw group (p < 0.05). Conclusion This 2-year follow-up study shows that the PVP-bone cement bridging screw system combined therapy had better midterm treatment efficacy than the PVP-PPP combined therapy in patients with unstable KD, and the bone cement bridging screw system is a preferred therapy with better anti cement loosening ability.

Abstract Background Artemisia selengensis, classified within the genus Artemisia of the Asteraceae family, is a perennial herb recognized for its dual utility in culinary and medicinal domains. There are few studies on the chloroplast genome of A. selengensis, and the phylogeographic classification is vague, which makes phylogenetic analysis and evolutionary studies very difficult. Results The chloroplast genomes of 10 A. selengensis in this study were highly conserved in terms of gene content, gene order, and gene intron number. The genome lengths ranged from 151,148 to 151,257 bp and were typical of a quadripartite structure with a total GC content of approximately 37.5%. The chloroplast genomes of all species encode 133 genes, including 88 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Due to the contraction and expansion of the inverted repeats (IR), the overlap of ycf1 and ndhF genes occurred at the inverted repeats B (IRB) and short single copy sequence (SSC) boundaries. According to a codon use study, the frequent base in the chloroplast genome of A. selengensis’ third codon position was A/T. The number of SSR repeats was 42–44, most of which were single nucleotide A/T repeats. Sequence alignment analysis of the chloroplast genome showed that variable regions were mainly distributed in single copy regions, nucleotide diversity values of 0 to 0.009 were calculated by sliding window analysis, 8 mutation hotspot regions were detected, and coding regions were more conserved than non-coding regions. Analysis of non-synonymous substitution (Ka) and synonymous substitution (Ks) revealed that accD, rps12, petB, and atpF genes were affected by positive selection and no genes were affected by neutral selection. Based on the findings of the phylogenetic analysis, Artemisia selengensis was sister to the genus Artemisia Chrysanthemum and formed a monophyletic group with other Artemisia genera. Conclusions In this research, the present study systematically compared the chloroplast genomic features of A. selengensis and provided important information for the study of the chloroplast genome of A. selengensis and the evolutionary relationships among Asteraceae species.

Background: Cystitis glandularis is a chronic inflammatory disease of the urinary system characterized by high recurrence rates, the reasons for which are still unknown. Objectives: This study aims to identify potential factors contributing to recurrence and propose a simple and feasible prognostic model through nomogram construction. Design: Patients with confirmed recurrence based on outpatient visits or readmissions were included in this study, which was subsequently divided into training and validation cohorts. Methods: Machine learning techniques were utilized to screen for the most important predictors, and these were then employed to construct the nomogram. The reliability of the nomogram was assessed through receiver operating characteristic curve analysis, decision curve analysis, and calibration curves. Results: A total of 252 patients met the screening criteria and were enrolled in this study. Over the 12-month follow-up period, the relapse rate was found to be 57.14% ( n = 144). The five final predictors identified through machine learning were urinary infections, urinary calculi, eosinophil count, lymphocyte count, and serum magnesium. The area under curve values for all three time points assessing recurrence exceeded 0.75. Furthermore, both calibration curves and decision curve analyses indicated good performance of the nomogram. Conclusion: We have developed a reliable machine learning-based nomogram for predicting recurrence in cystitis glandularis

Abstract Macrophages, as pivotal cells within the tumour microenvironment, significantly influence the impact of and reactions to treatments for solid tumours. The rapid evolution of bioengineering technology has revealed the vast potential of engineered macrophages in immunotherapy, disease diagnosis, and tissue engineering. Given this landscape, the goal of harnessing and innovating macrophages as a novel strategy for solid tumour immunotherapy cannot be overstated. The diverse strategies for engineered macrophages in the realm of cancer immunotherapy, encompassing macrophage drug delivery systems, chimeric antigen receptor macrophage therapy, and synergistic treatment approaches involving bacterial outer membrane vesicles and macrophages, are meticulously examined in this review. These methodologies are designed to enhance the therapeutic efficacy of macrophages against solid tumours, particularly those that are drug-resistant and metastatic. Collectively, these immunotherapies are poised to supplement and refine current solid tumour treatment paradigms, thus heralding a new frontier in the fight against malignant tumours.

Abstract The voltage-gated calcium channel CaV1.2 is essential for cardiac and vessel smooth muscle contractility and brain function. Accumulating evidence demonstrates that malfunctions of CaV1.2 are involved in brain and heart diseases. Pharmacological inhibition of CaV1.2 is therefore of therapeutic value. Here, we report cryo-EM structures of CaV1.2 in the absence or presence of the antirheumatic drug tetrandrine or antihypertensive drug benidipine. Tetrandrine acts as a pore blocker in a pocket composed of S6II, S6III, and S6IV helices and forms extensive hydrophobic interactions with CaV1.2. Our structure elucidates that benidipine is located in the DIII-DIV fenestration site. Its hydrophobic sidechain, phenylpiperidine, is positioned at the exterior of the pore domain and cradled within a hydrophobic pocket formed by S5DIII, S6DIII, and S6DIV helices, providing additional interactions to exert inhibitory effects on both L-type and T-type voltage gated calcium channels. These findings provide the structural foundation for the rational design and optimization of therapeutic inhibitors of voltage-gated calcium channels.

Abstract Acinetobacters pose a significant threat to human health, especially those with weakened immune systems. Type IV pili of acinetobacters play crucial roles in virulence and antibiotic resistance. Single-stranded RNA bacteriophages target the bacterial retractile pili, including type IV. Our study delves into the interaction between Acinetobacter phage AP205 and type IV pili. Using cryo-electron microscopy, we solve structures of the AP205 virion with an asymmetric dimer of maturation proteins, the native Acinetobacter type IV pili bearing a distinct post-translational pilin cleavage, and the pili-bound AP205 showing its maturation proteins adapted to pilin modifications, allowing each phage to bind to one or two pili. Leveraging these results, we develop a 20-kilodalton AP205-derived protein scaffold targeting type IV pili in situ, with potential for research and diagnostics.

Abstract Background The TGF-β signalling pathway is intricately associated with the progression of glioblastoma (GBM). The objective of this study was to examine the role of circRNAs in the TGF-β signalling pathway. Methods In our research, we used transcriptome analysis to search for circRNAs that were activated by TGF-β. After confirming the expression pattern of the selected circRYK, we carried out in vitro and in vivo cell function assays. The underlying mechanisms were analysed via RNA pull-down, luciferase reporter, and RNA immunoprecipitation assays. Results CircRYK expression was markedly elevated in GBM, and this phenotype was strongly associated with a poor prognosis. Functionally, circRYK promotes epithelial-mesenchymal transition and GSC maintenance in GBM. Mechanistically, circRYK sponges miR-330-5p and promotes the expression of the oncogene VLDLR. In addition, circRYK could enhance the stability of VLDLR mRNA via the RNA-binding protein HuR. Conclusion Our findings show that TGF-β promotes epithelial-mesenchymal transition and GSC maintenance in GBM through the circRYK-VLDLR axis, which may provide a new therapeutic target for the treatment of GBM.

Background: In recent years, infectious diseases like COVID-19 have had profound global socio-economic impacts. mRNA vaccines have gained prominence due to their rapid development, industrial adaptability, simplicity, and responsiveness to new variants. Notably, the 2023 Nobel Prize in Physiology or Medicine recognized significant contributions to mRNA vaccine research. Methods: Our study employed a comprehensive bibliometric analysis using the Web of Science Core Collection (WoSCC) database, encompassing 5,512 papers on mRNA vaccines from 2003 to 2023. We generated cooperation maps, co-citation analyses, and keyword clustering to evaluate the field’s developmental history and achievements. Results: The analysis yielded knowledge maps highlighting countries/institutions, influential authors, frequently published and highly cited journals, and seminal references. Ongoing research hotspots encompass immune responses, stability enhancement, applications in cancer prevention and treatment, and combating infectious diseases using mRNA technology. Conclusions: mRNA vaccines represent a transformative development in infectious disease prevention. This study provides insights into the field’s growth and identifies key research priorities, facilitating advancements in vaccine technology and addressing future challenges.

ABSTRACTControlling pressure impact of water hammer is an important guarantee for safe and stable running of pipeline systems. Previously, we proposed a spring self-adaptive auxiliary control (SAC) system to improve the pressure control ability of a surge tank. However, the working efficiency of the SAC system is affected by various parameters. A reasonable designing strategy becomes an urgent need to properly determine the parameters of the SAC controller. In this study, based on our calibrated numerical model, various transient responses of a SAC system with different parameters were further investigated. The latency response threshold and the spring orifice coefficient were identified to be the two most sensitive parameters that determine the controller working efficiency. Based on the objectives of reducing the in-pipe extreme pressure and in-tank water level fluctuation, an analytical dual-objective optimizing Method was proposed for application. The results demonstrated that the pressure control capability of SAC controller can be optimized by the proposed method.

As a green building material, recycled aggregate concrete (RAC) can reduce construction solid waste and carbon emissions. In this paper, a combination of macroscale physical experiments of thermal performance and mesoscale numerical simulations of heat transfer were used to investigate the thermal conductivity (TC) of RAC. Firstly, the TC of RAC was measured using the steady-state method. Secondly, the mesoscale numerical analysis method of steady-state heat transfer of RAC was established by self-programming. Finally, by comparing with experimental results, the validity of the mesoscale numerical analysis method in this paper is verified. The results indicates that the TC of RAC is positively correlated with the recycled coarse aggregate dosage and the TC of each component, while it is negatively correlated with the water-binder ratio, the recycled fine aggregate replacement ratio, the old mortar adhesion ratio, the interface transition zone thickness, and the porosity. The six-phase mesoscale model of random convex polygonal aggregate for RAC constructed in this paper can effectively predict the TC of RAC, which provides a new idea for analyzing the TC of RAC.

Key parameters describing the spatial variability of soil properties based on the random field theory are the scale of fluctuation (SOF) and coefficient of variation (COV). To characterize the spatial variability of soil properties, reducing the impact of these errors and uncertainties is necessary. To accomplish this, for the five main layers of soil, we collected 18 cone penetration test (CPT) data from a highly heterogeneous region in Lianyungang New Airport, Jiangsu Province, China, and used the control variable method to analyze the influence of the estimation method of tendency, its function type and outliers. The results show that, compared with the ordinary least square method (OLSM), the least absolute deviation method (LADM) can more truly reflect the trend component of CPT parameters in the vertical direction, and the influence of other factors on SOF and COV is also studied, such as outliers and estimation functions of trend components. On this basis, a reasonable calculation process of SOF and COV is summarized, which provides a reference for the calculation of SOF and COV in vertical direction in the future. By comparing the SOF calculated by different models, the results show that the squared exponential (SQX) model has the highest SOF in 68.3% of the evaluation, and the single exponential (SNX) model has the lowest SOF in 64.4% of the evaluation. Moreover, we compared the SOF and COV of cone tip resistance (qc) and sleeve friction (fs), which showed that SOF of qc and COV of qc is lower than that of fs in 54.4 and 73.3% of all evaluations, respectively.

Abstract Prohexadione-Calcium (Pro-Ca) plays key roles in improving fruit quality and yield by regulating various aspects of plant growth. However, the effects of how Pro-Ca regulates the regulation of sugar and acid balance and its impact on the production of volatile aroma substances during fruit growth and development are poorly understood. In this study, the Pro-Ca solutions developed at concentrations of 200, 400, 600 and 800 mg·L-1 were sprayed on the entire “Chardonnay” grape tree 22, 42, 62 and 82 days after initial flowering. The values of endogenous hormones, sugar and acid content, enzyme activities and flavor content were then measured in grapes 45, 65, 85 and 105 days (ripeness stage) after the initial flowering. The results showed that Pro-Ca had significant effects on fruits during development, including reducing ABA content, increasing ZT, GA3 and IAA levels, promoting fruit ripening and enhancing enzymes, which are involved in sugar and acid synthesis. Consequently, these effects led to an increase in sugar and acid content in the berries. Particularly during the ripening phase, the application of 600 mg L-1 Pro-Ca resulted in an increase in soluble sugar content of 11.28% and a significant increase in citric acid and malic acid content of 97.80% and 68.86%, respectively. Additionally, Pro-Ca treatment enhanced both the variety and quantity of aroma compounds present in the berries, with the 600 mg·L-1 Pro-Ca treatment showcasing the most favorable impact on volatile aroma compounds in ‘Chardonnay’ grapes. The levels of aldehydes, esters, alcohols, phenols, acids, ketones, and terpenes were significantly higher under the 600 mg·L-1 Pro-Ca treatment compared to those of control with 51.46 − 423.85% increase. In conclusion, Pro-Ca can regulate the content of endogenous hormones and the activities of enzymes related to sugar and acid metabolism in fruit, thereby increasing the content of soluble sugar and organic acid in fruit and the diversity and concentration of fruit aroma substances. Among them, foliar spraying 600 mg · L-1 Pro-Ca has the best effect. In the future, we need to further understand the molecular mechanism of Pro-Ca in grape fruit to lay a solid foundation for quality improvement breeding.

Purpose - Convenience stores are the main driving force of the small retail format in China. In order to meet customer demands, maintain product quality, reduce waste, and stay competitive in the fast-paced retail environment, convenience stores conduct daily food deliveries, with transportation costs accounting for the largest share of logistics expenses. Consequently, the daily operation costs of chain convenience stores increase. Therefore, the aim of this paper is to optimize the distribution paths of chain convenience stores with multiple distribution centers in order to reduce operational costs, reduce carbon dioxide emissions, etc. Design/methodology/approach - A mathematical model of the multi-temperature joint distribution problem with multiple distribution centers was constructed to minimize the total cost. In the model, six kinds of costs were considered. In addition, a two-stage algorithm was designed. The K-means algorithm was used to cluster match the demand points with the distribution centers, and the genetic algorithm was used to solve the routing problem of each distribution center. Subsequently, the costs of the multi-temperature joint distribution and multi-vehicle distribution were compared. Findings - The results showed that the optimization rate of total cost was 26.35%, the optimization rate of other costs was greater than 45%. Note that through case solving, the K-means algorithm was used to convert the single problem of multiple distribution centers into multiple problems of one distribution center. The multi-temperature joint distribution pattern was applied to the food distribution of chain convenience stores so that they could improve the delivery time and reduce the number of vehicles, carbon dioxide emissions, and total cost. Originality/value - Previous research on multi-temperature joint deliveries has predominantly focused on distribution from a single distribution center, overlooking the study of multi-distribution center scenarios. This article addresses this gap and explores the feasibility of applying a multi-temperature joint delivery service model to food distribution for chain convenience stores with multiple distribution centers.

The high cost associated with high-fidelity computational fluid dynamics (CFD) is one of the main challenges that inhibit the design and optimisation of new fluid-flow systems. In this study, we explore the feasibility of a physics-informed deep learning approach to predict turbulence evolution and mixing without requiring a classical CFD solver. The deep learning architecture was inspired by integrating U-Net with inception modules for capturing the multi-scale nature of turbulent flows. In addition, a physics-constrained loss function was designed to enforce the mass and pressure conservation of the predicted solution. After trained, the optimised model was validated in the large eddy simulation (LES) of a forced turbulent mixing layer at two distinct Reynolds numbers ( $\mathrm {Re} =3000$ and 30000). The results demonstrate that the proposed approach achieves a promising solution accuracy and extrapolation ability with a significant reduction in computing time when compared to those obtained using a classical LES flow solver. The success in developing such a physics-informed deep learning approach not only justifies the potential of ML-based surrogate solvers for fast prototyping and design of generic fluid-flow systems but also highlights the key challenges arising from data-driven surrogate solver development for turbulence modelling.

In this paper, the discharge coefficient prediction model for this structure in a subcritical flow regime is first established by extreme learning machine (ELM) and Bayesian network, and the model's performance is analyzed and verified in detail. In addition, the global sensitivity analysis method is introduced to the optimal prediction model to analyze the sensitivity for the dimensionless parameters affecting the discharge coefficient. The results show that the Bayesian extreme learning machine (BELM) can effectively predict the discharge coefficients of the symmetric stepped labyrinth side weir. The range of 95% confidence interval [−0.055,0.040] is also significantly smaller than that of the ELM ([−0.089,0.076]) and the Kernel extreme learning machine (KELM) ([−0.091,0.081]) at the testing stage. The dimensionless parameter ratio of upstream water depth of stepped labyrinth side weir p/y1 has the greatest effect on the discharge coefficient Cd, accounting for 55.57 and 54.17% under single action and other parameter interactions, respectively. Dimensionless step number bs/L has little effect on Cd, which can be ignored. Meanwhile, when the number of steps is less (N = 4) and the internal head angle is smaller (θ = 45°), a larger discharge coefficient value can be obtained. HIGHLIGHTS The discharge coefficient model of a symmetrical stepped labyrinth side weir is developed.; The quantitative model of the discharge coefficient is established.; The discharge characteristics of a symmetrical stepped labyrinth side weir are analyzed comprehensively.; The effects of different dimensionless parameters on the discharge coefficient are compared.;

AbstractContext (-)-Epigallocatechin-3-gallate (EGCG) is involved in cell proliferation and ischemia/reperfusion (I/R) injury of several organs.Objective To identify the role of EGCG in intestinal epithelial proliferation and barrier exposed to I/R injury.Material and methods Fifty Sprague-Dawley rats were divided into sham, I/R, I/R + EGCG (12.5 mg/kg), I/R + EGCG (25 mg/kg) and I/R + EGCG (50 mg/kg). I/R group rats were subjected to intestinal ischemia for 1 h and 6 h reperfusion. The rats were supplemented with EGCG 12.5, 25 and 50 mg/kg daily for 3 days via intraperitoneal injection before surgery. We used IEC-6 to expose to hypoxia/reoxygenation (H/R) injury to mimic I/R in vivo. IEC-6 cells were divided into control, H/R and H/R + EGCG (40 μmol/L). The effects of EGCG and its mechanism was explored.Results Pharmacological treatment with EGCG notably improves intestinal epithelial proliferation (12.5 mg/kg, 1.74-fold; 25 mg/kg, 2.93-fold, and 50 mg/kg, 4.33-fold) and barrier function after I/R injury. EGCG promoted cell proliferation (2.99-fold) and increased the expression of occludin (2.36-fold) and ZO-1 (1.64-fold) in IEC-6 cells after H/R injury. EGCG promoted proliferation of IEC-6 cells with ED50 values of 18.16 μmol/L. Further investigations indicated that EGCG activated Nurr1 expression in intestine after I/R injury. EGCG promote cell proliferation and increased the expression of occludin and ZO-1 in IEC-6 cells after H/R injury were abrogated in the knockdown of Nurr1 by siRNA.Discussion and conclusion Our findings indicate that EGCG promotes intestinal epithelial cell proliferation and barrier function after I/R injury in vitro and in vivo via activation of Nurr1.

Rapid advancements in electric vehicle (EV) technology have highlighted the importance of lithium-ion (Li) batteries. These batteries are essential for safety and reliability. Battery data show non-stationarity and complex dynamics, presenting challenges for current monitoring and prediction methods. These methods often fail to manage the variability seen in real-world environments. To address these challenges, we propose a Transformer model with a wavelet transform dynamic attention mechanism (WADT). The dynamic attention mechanism uses wavelet transform. It focuses adaptively on the most informative parts of the battery data to enhance the anomaly detection accuracy. We also developed a deep learning model with an improved Transformer architecture. This architecture is tailored for the complex dynamics of battery data time series. The model accounts for temporal dependencies and adapts to non-stationary behavior. Experiments on public battery datasets show our approach’s effectiveness. Our model significantly outperforms existing technologies with an accuracy of 0.89 and an AUC score of 0.88. These results validate our method’s innovation and effectiveness.

Understanding the strength development of alkali-activated materials (AAMs) with fly ash (FA) and granulated blast furnace slag (GBFS) is crucial for designing high-performance AAMs. This study investigates the strength development mechanism of AAMs using machine learning. A total of 616 uniaxial compressive strength (UCS) data points from FA-GBFS-based AAM mixtures were collected from published literature to train four tree-based machine learning models. Among these models, Gradient Boosting Regression (GBR) demonstrated the highest prediction accuracy, with a correlation coefficient (R-value) of 0.970 and a root mean square error (RMSE) of 4.110 MPa on the test dataset. The SHapley Additive exPlanations (SHAP) analysis revealed that water content is the most influential variable in strength development, followed by curing periods. The study recommends a calcium-to-silicon ratio of around 1.3, a sodium-to-aluminum ratio slightly below 1, and a silicon-to-aluminum ratio slightly above 3 for optimal AAM performance. The proposed design model was validated through laboratory experiments with FA-GBFS-based AAM mixtures, confirming the model’s reliability. This research provides novel insights into the strength development mechanism of AAMs and offers a practical guide for elemental design, potentially leading to more sustainable construction materials.

Aiming at the demand for long-range and high-resolution imaging detection of small targets such as submerged submarine markers in shallow coastal waters, research on single-photon lidar imaging technology is carried out. This paper reports the sequential two-mode fusion imaging algorithm, which has a strong information extraction capability and can reconstruct scene target depth and reflection intensity images from complex signal photon counts. The algorithm consists of four steps: data preprocessing, extremely large group value estimation, noise sieving, and total variation smoothing constraints to image the target with high quality. Simulation and test results show that the imaging performance and imaging characteristics of the method are better than the current high-performance first-photon group imaging algorithm, indicating that the method has a great advantage in sparse photon counting imaging, and the method proposed in this paper constructs a clear depth and reflectance intensity image of the target scene, even in the 50,828 Lux ambient strong light and strong interference, the 0.1 Lux low-light environment, or the underwater high-attenuation environment.

Abstract Background Cancer is a thorny problem which cannot be conquered by mankind at present and recent researchers have put their focus on tumor microenviroment. Neutrophils, the prominent leukocytes in peripheral blood that accumulate in tumours, serves as frontline cells in response to tumour progression owing to the rapid development of micro biotechnology. Hence, targeted therapy with these neutrophils has made targeting treatment a promising field in cancer therapy. Main body We broadly summarise some studies on the phenotypes and functions of tumour‐associated neutrophils as well as the unique web‐like products of neutrophils that play a role in cancer progression—neutrophil extracellular traps—and the interactions between neutrophils and the tumour microenvironment. Moreover, several targeted neutrophils therapeutic studies have made some progress and provided potential strategies for the treatment of cancer. Conclusion This review aims to offer a holistic perspective on therapeutic interventions targeting neutrophils to further inspire more researches on cancer therapies.

BackgroundThe tumor microenvironment (TME) plays a pivotal role in the progression and metastasis of lung adenocarcinoma (LUAD). However, the detailed characteristics of LUAD and its associated microenvironment are yet to be extensively explored. This study aims to delineate a comprehensive profile of the immune cells within the LUAD microenvironment, including CD8+ T cells, CD4+ T cells, and myeloid cells. Subsequently, based on marker genes of exhausted CD8+ T cells, we aim to establish a prognostic model for LUAD.MethodUtilizing the Seurat and Scanpy packages, we successfully constructed an immune microenvironment atlas for LUAD. The Monocle3 and PAGA algorithms were employed for pseudotime analysis, pySCENIC for transcription factor analysis, and CellChat for analyzing intercellular communication. Following this, a prognostic model for LUAD was developed, based on the marker genes of exhausted CD8+ T cells, enabling effective risk stratification in LUAD patients. Our study included a thorough analysis to identify differences in TME, mutation landscape, and enrichment across varying risk groups. Moreover, by integrating risk scores with clinical features, we developed a new nomogram. The expression of model genes was validated via RT-PCR, and a series of cellular experiments were conducted, elucidating the potential oncogenic mechanisms of GALNT2.ResultsOur study developed a single-cell atlas for LUAD from scRNA-seq data of 19 patients, examining crucial immune cells in LUAD’s microenvironment. We underscored pDCs’ role in antigen processing and established a Cox regression model based on CD8_Tex-LAYN genes for risk assessment. Additionally, we contrasted prognosis and tumor environments across risk groups, constructed a new nomogram integrating clinical features, validated the expression of model genes via RT-PCR, and confirmed GALNT2’s function in LUAD through cellular experiments, thereby enhancing our understanding and approach to LUAD treatment.ConclusionThe creation of a LUAD single-cell atlas in our study offered new insights into its tumor microenvironment and immune cell interactions, highlighting the importance of key genes associated with exhausted CD8+ T cells. These discoveries have enabled the development of an effective prognostic model for LUAD and identified GALNT2 as a potential therapeutic target, significantly contributing to the improvement of LUAD diagnosis and treatment strategies.

Abstract In recent years, convolutional neural networks (CNN)‐based automatic segmentation of medical images has become one of the hot topics in clinical disease diagnosis. It is still a challenging task to improve the segmentation accuracy of the network model with the large variation of pathological regions in different patients and the fuzzy boundary of pathological regions. A Dual‐path Multi‐scale Attention Guided network (DMAGNet) for medical image segmentation is proposed in this paper. First, the Dual‐path Multi‐scale Attention Fusion Module (DMAF) is proposed as a novel skip connection strategy, which is applied to encode semantic dependencies between high‐level and low‐level channels. Second, the Multi‐scale Normalized Channel Attention Module (MNCA) based on the atrous convolution, normalization channel attention mechanism, and the Depthwise Separable Convolutions (DSConv) is developed to strengthen dependencies between channels. Finally, the encoder–decoder backbone employs the DSConv, as well as the pretrained Resnet34 block is combined in the encoder part to further improve the backbone network performance. Comprehensive experiments on brain, lung, and liver segmentation tasks show that the proposed DMAGNet outperforms the original U‐Net method and other advanced methods.

Objective The Early Cambrian superlarge rare earth-rich phosphate deposit in Xinhua, Zhijin County, Guizhou Province, is a typical marine sedimentary deposit. There have long been controversial on the mineralisation environment and mineralisation mechanism. Methods In this paper, the sedimentary environment and formation mechanism of the phosphorus-bearing rock series in the Gezhongwu Formation are verified, through the study of the microscopic characteristics of phosphorus-bearing rock series rocks or ores and the evidence of elemental geochemistry. Results This study reveal the regular changes in the structure of phosphorite from the bottom up of the phosphorous-bearing rock series: the grain sizes decreasing; the interstitial materials between grains vary from bright dolomite cement to micritic matrix, such as siliceous and collophanite, followed by bright dolomite cement and finally micrite collophanite and siliceous. The cementation mode has mainly converted from pore cementation to pore-based cementation, and the supports change from grain to grain-matrix supports. Moreover, the single layers of the rocks become thinner and darker, and the development of staggered bedding was decreased. Conclusion These characteristics reflect that the sedimentary environment of the phosphorus-bearing rock series is a subtidal zone with strong hydrodynamic forces, and of the upper section has sedimentary depths higher and hydrodynamic conditions slightly weaker than those of the lower section. The significant negative Ce anomalies (δCe between 0.32-0.39) and low Ni/Co (0.98-6.07) and V/Cr ratios (0.57-12.50) of the phosphorus-bearing rock series show that the sedimentary water had oxidation characteristics similar to those of a modern marine environment. The lower 103·Sr/Ca(2.00-3.38) and 1/Σ(Al2O3+TiO2) ratios (0.57-3.45) indicate that the ancient water depth was generally shallow, but the relative depth changed frequently. The distribution characteristics of Fe, Cu and Ba contents indicate that the palaeoproductivity of carbonate in the lower section is higher than that in the upper section. In the palaeoenvironment where various conditions are coupled, the phosphorite was finally enriched and formed by precipitation-stirring-subdivision-cementation-solidification.

Abstract The severe fever with thrombocytopenia syndrome virus (SFTSV) is a tick-borne human-infecting bunyavirus, which utilizes two envelope glycoproteins, Gn and Gc, to enter host cells. However, the structure and organization of these glycoproteins on virion surface are not yet known. Here we describe the structure of SFTSV determined by single particle reconstruction, which allows mechanistic insights into bunyavirus assembly at near-atomic resolution. The SFTSV Gn and Gc proteins exist as heterodimers and further assemble into pentameric and hexameric peplomers, shielding the Gc fusion loops by both intra- and inter-heterodimer interactions. Individual peplomers are associated mainly through the ectodomains, in which the highly conserved glycans on N914 of Gc play a crucial role. This elaborate assembly stabilizes Gc in the metastable prefusion conformation and creates some cryptic epitopes that are only accessible in the intermediate states during virus entry. These findings provide an important basis for developing vaccines and therapeutic drugs.

Abstract Objective Carbon ion radiotherapy (C-ion RT) for chordomas has been gradually performed in several research centres. This study aimed to systematically review the results of clinical reports from these institutions and to evaluate the safety and efficacy of C-ion RT. Methods In accordance with the PRISMA guidelines and set search strategies, we searched four databases for articles from their inception to February 11, 2023. These articles were screened, and data were extracted independently by two researchers. STATA 14.0 was used for statistical analysis of survival results. Results A total of 942 related articles were retrieved, 11 of which were included. Regarding lesion location, 57% (n = 552) originated in the sacral region, 41% (n = 398) in the skull base, and 2% (n = 19) in the spine (upper cervical). The local control (LC) rates at 1, 2, 3, 5, 9, and 10 years in these studies were 96%, 93%, 83%, 76%, 71%, and 54%, respectively. The overall survival (OS) rates at 1, 2, 3, 5, 9, and 10 years in these studies were 99%, 100%, 93%, 85%, 76%, and 69%, respectively. Acute and late toxicities were acceptable, acute toxicities were mainly grade 1 to grade 2 and late toxicities were mainly grade 1 to grade 3. Conclusion C-ion RT has attractive clinical application prospects and is an important local treatment strategy for chordomas. Encouraging results were observed in terms of LC and OS. Meanwhile, the acute and late toxicities were acceptable. PROSPERO registration number: CRD42023398792.

Abstract Objective To develop and validate a prediction model for early recurrence of stage I lung adenocarcinoma (LUAD) that combines radiomics features based on preoperative CT with tumour spread through air spaces (STAS). Materials and methods The most recent preoperative thin-section chest CT scans and postoperative pathological haematoxylin and eosin-stained sections were retrospectively collected from patients with a postoperative pathological diagnosis of stage I LUAD. Regions of interest were manually segmented, and radiomics features were extracted from the tumour and peritumoral regions extended by 3 voxel units, 6 voxel units, and 12 voxel units, and 2D and 3D deep learning image features were extracted by convolutional neural networks. Then, the RAdiomics Integrated with STAS model (RAISm) was constructed. The performance of RAISm was then evaluated in a development cohort and validation cohort. Results A total of 226 patients from two medical centres from January 2015 to December 2018 were retrospectively included as the development cohort for the model and were randomly split into a training set (72.6%, n = 164) and a test set (27.4%, n = 62). From June 2019 to December 2019, 51 patients were included in the validation cohort. RAISm had excellent discrimination in predicting the early recurrence of stage I LUAD in the training cohort (AUC = 0.847, 95% CI 0.762–0.932) and validation cohort (AUC = 0.817, 95% CI 0.625–1.000). RAISm outperformed single modality signatures and other combinations of signatures in terms of discrimination and clinical net benefits. Conclusion We pioneered combining preoperative CT-based radiomics with STAS to predict stage I LUAD recurrence postoperatively and confirmed the superior effect of the model in validation cohorts, showing its potential to assist in postoperative treatment strategies.

Teaching point: A ruptured aorto-iliac aneurysm, complicated by an iliac arteriovenous fistula, is rare but has a possibly fatal outcome and requires prompt diagnosis and appropriate treatment.

For distributed fiber-optic sensors, slowly varying vibration signals down to 5 mHz are difficult to measure due to low signal-to-noise ratios. We propose and demonstrate a forward transmission-based distributed sensing system, combined with a polarization-generated carrier for detection bandwidth reduction, and cross-correlation for vibration positioning. By applying a higher-frequency carrier signal using a fast polarization controller, the initial phase of the known carrier frequency is monitored and analyzed to demodulate the vibration signal. Only the polarization carrier needs to be analyzed, not the arbitrary-frequency signal, which can lead to hardware issues (reduced detection bandwidth and less noise). The difference in arrival time between the two detection ends obtained through cross-correlation can determine the vibration position. Our experimental results demonstrate a sensitivity of 0.63 mrad/με and a limit of detection (LoD) of 355.6 pε/Hz1/2 at 60 Hz. A lock-in amplifier can be used on the fixed carrier to achieve a minimal LoD. The sensing distance can reach 131.5 km and the positioning accuracy is 725 m (root-mean-square error) while the spatial resolution is 105 m. The tested vibration frequency range is between 0.005 Hz and 160 Hz. A low frequency of 5 mHz for forward transmission-based distributed sensing is highly attractive for seismic monitoring applications.

The coal floor develops various water-conducting channels, which seriously threaten the safe production of mines. In order to establish a more scientific multi-information identification technology system for the water-conducting channels in the coal floor, and prevent floor water inrush. Firstly, the principles of reasonable trajectory, reasonable target layer and exploration area maximization are proposed based on the characteristics of the water-conducting channels and the advantages of the ground directional drilling area exploration technology. Diversified types, unclear locations, and significant water inrush hazards are the characteristics of water-conducting channels. Secondly, the summary analysis is conducted on the exploration process of water diversion channels in areas such as HuaiBei Mining Area, Huainan Mining Area, Xingtai Mining Area, and Huanghebei Coal Field. When revealing the water-conducting channels, there are significant differences in visual indicators such as rock debris, drilling time, drilling fluid leakage, and confirmatory indicators such as permeability and grouting parameters compared to revealing normal formations. Therefore, the identification indicators of multi-information during the drilling process are divided into two types: qualitative and quantitative. Based on the variation amplitude of two qualitative indicators, rock debris and drilling time, when encountering water-conducting channels, it gives corresponding standard curves, and determines the classification system for water-conducting channel types. Subsequently, a comprehensive analysis is conducted on the changes in the two quantitative indicators of drilling fluid leakage and permeability when encountering water-conducting channels. 30 m3/h of drilling fluid leakage and 10 Lu of permeability are proposed as the classification criteria for conductivity. Based on this, a dual factor comprehensive classification system for water-conducting channels conductivity is established, and the conductivity is divided into four levels. Finally, taking a typical mine in the North China coalfield as a case study, the principle of exploration is adopted to explore the water-conducting channels. The multi-information identification technology is applied to successfully identify four faults, two karst fracture zones and a collapse in the detection area, and determines conductivity levels of water-conducting channels. The research results have guiding effect and important significance for improving the identification and control of water-conducting channels.

Abstract Salt-overly-sensitive 1 (SOS1) is a unique electroneutral Na+/H+ antiporter at the plasma membrane of higher plants and plays a central role in resisting salt stress. SOS1 is kept in a resting state with basal activity and activated upon phosphorylation. Here, we report the structures of SOS1. SOS1 forms a homodimer, with each monomer composed of transmembrane and intracellular domains. We find that SOS1 is locked in an occluded state by shifting of the lateral-gate TM5b toward the dimerization domain, thus shielding the Na+/H+ binding site. We speculate that the dimerization of the intracellular domain is crucial to stabilize the transporter in this specific conformation. Moreover, two discrete fragments and a residue W1013 are important to prevent the transition of SOS1 to an alternative conformational state, as validated by functional complementation assays. Our study enriches understanding of the alternate access model of eukaryotic Na+/H+ exchangers.

Abstract Effective electrocatalysts are crucial for facilitating the oxygen evolution reaction (OER), the anodic reaction of water electrolysis for renewable green hydrogen production. Perovskite oxides are a group of potential catalysts featuring the lattice oxygen mechanism (LOM) for OER, where O2 formation commences via a lattice oxygen redox process. The LOM pathway breaks the thermodynamic limitation of the adsorbate evolution mechanism (AEM) and achieves a high intrinsic activity. However, perovskite oxides often suffer high OER overpotentials due to the insufficient activation of the LOM pathway. Typically, the overpotential exceeds 300 mV at 10 mA cm−2. This greatly impedes the practical applications of perovskite oxide based OER catalysts. Here, it is demonstrated that the B‐site‐metal exsolution of a La0.6Sr0.4Fe0.8Ni0.2O3‐δ perovskite increases the activity of LOM by a factor of 3.8 at 400 mV overpotential. The activated LOM pathway leads to a 36‐mV reduction in the overpotential at 10 mA cm−2 (from 310 mV to 274 mV) and a 2× increase in the turnover frequency (TOF) at 450 mV overpotential. A membrane electrode assembly (MEA) water electrolyzer equipped with this LSFN‐based catalyst offers 1 A cm−2 current density at 2.46 V and 24‐h operation stability.

Largemouth bass virus (LMBV) poses a significant threat to largemouth bass farming, leading to substantial economic losses. In December 2022, massive largemouth bass juveniles died at a fish farm in the city of Xinxiang, China. Through a series of experiments, we conclusively identified LMBV as the causative pathogen. The affected fish displayed anorexia, lethargy, and hemorrhage at the pectoral and caudal fin base. No parasites or pathogenic bacteria were detected on the body surface or gills, or isolated from the diseased fish. Severe hemorrhage, lymphocyte infiltration, and extensive necrosis were observed in the liver, spleen, intestine, and stomach of the moribund fish. The tissue homogenate from the diseased fish induced epithelioma papulosum cyprini cells (EPC) cell death, while no such effects were observed in grouper spleen (GS) cells. Sequence similarity analysis of the major capsid protein (MCP) indicated the virus shared 100% similarity with the LMBV-FS2021 strain, placing it within the Ranavirus genus. Transmission electron microscopy (TEM) observations revealed plenty of hexagonal virions accumulated in the cytoplasm of infected EPC cells. Artificial infection demonstrated that LMBV-XX01 was highly fatal to Micropterus salmoides juveniles, with an LD50 of 103.081 TCID50/fish. RT-qPCR detection confirmed that LMBV appeared in all sampled tissues of the challenged largemouth bass, with significantly higher viral loads detected in the liver and heart compared to other tissues. Additionally, we successfully obtained a highly purified recombinant MCP of LMBV and developed two strains of monoclonal antibodies targeting MCP of LMBV-XX01. Overall, our findings provide valuable materials and insights for the design of prevention strategies and the development of detection methods for LMBV.

In order to mitigate the irreversible damage caused by cold start and preserve cell performance, this paper proposes a real-time prediction method based on the remaining cold start time of the proton exchange membrane fuel cell (PEMFC). This method can protect the cell by referencing the current cold start effect. In this work, a real-time prediction model for the remaining cold start time based on the backpropagation (BP) neural network, long short-term memory (LSTM) neural network, and nonlinear regression of logarithmic function is established. Furthermore, a combined prediction model with variable weight is established by integrating these three prediction methods. Results demonstrated that, when considering two distinct cold start experimental conditions as samples, the average prediction accuracy of the three single models across all prediction times is 78.80%, 71.76%, 67.07% and 84.72%, 84.66%, 87.03%, respectively. In comparison to the optimal single prediction model, the combined prediction model exhibits an improvement in prediction accuracy by 9.84% and 2.83% under the two different experimental conditions, respectively. In addition, the maximum average prediction error between predicted values and actual values at each time instant within a range of only 3 s, thereby providing substantial support for accurate cold start performance prediction.

Summary: Regional climate strongly regulates the occurrence of wildfires partly because drying of fuel load increases fires. The large amounts of aerosols released by wildfires can also strongly affect regional climate. Here we show positive feedback (a seasonal burned area enhancement of 7–17%) due to wildfire aerosol forcing in Africa found in the simulations using the interactive REgion-Specific ecosystem feedback Fire (RESFire) model in the Community Earth System Model (CESM). The positive feedback results partly from the transport of fire aerosols from burning (dry) to wet regions, reducing precipitation and drying fuel load to enhance fires toward the non-burning (wet) region. This internally self-enhanced burning is an important mechanism for the regulation of African ecosystems and for understanding African fire behaviors in a changing climate. A similar mechanism may also help sustain wildfires in other tropical regions.

Global climate models (GCMs) are the state-of-the-art tool for understanding climate change and predicting future. However, little research has been reported on the latest NEX-GDDP-CMIP6 product in China. The purpose of this study was to evaluate the simulated performance and drought capture utility of the NEX-GDDP-CMIP6 over China. First, the simulation skills of the 16 GCMs in NEX-GDDP-CMIP6 was evaluated by the 'DISO', a big data evaluation method. Second, the DISO framework for drought identification was constructed by coupling the Correlation Coefficient (CC), False Alarm Rate (FAR) and Probability of Detection (POD). Then, it was combined with SPI and SPEI to evaluate the drought detection capability of NEX-GDPD-CMIP6. The result shows that: (1) NEX-GDPD-CMIP6 can reproduce the spatial distribution pattern of historical precipitation and temperature, which performs well in simulating warming trend but fails to capture precipitation's fluctuation characteristics. (2) The best performing model in precipitation is ACCESS-CM2 (DISO 1.630) and in temperature is CESM2 (DISO 3.246). (3) The 16MME performs better than the best single model, indicating that multi-model ensemble can effectively reduce the uncertainty inherent in models. (4) The SPEI calculated by 16MME identifying drought well in arid, while SPI is recommended for other climate classifications of China. HIGHLIGHTS Sixteen multi-mode ensembles outperform the best-performing single climate model.; Enlighteningly, CC, FAR and POD are coupled to construct a DISO framework for assessing drought identification capabilities.; The drought identification ability between the SPEI and the SPI calculated from NEX-GDDP-CMIP6 over China varies greatly, with the SPEI performing well in an arid region and inferior to the SPI over other climate classifications.;

Abstract Differential interference contrast (DIC) microscopy allows high-contrast, low-phototoxicity, and label-free imaging of transparent biological objects, and has been applied in the field of cellular morphology, cell segmentation, particle tracking, optical measurement and others. Commercial DIC microscopy based on Nomarski or Wollaston prism resorts to the interference of two polarized waves with a lateral differential offset (shear) and axial phase shift (bias). However, the shear generated by these prisms is limited to the rectilinear direction, unfortunately resulting in anisotropic contrast imaging. Here we propose an ultracompact metasurface-assisted isotropic DIC (i-DIC) microscopy based on a grand original pattern of radial shear interferometry, that converts the rectilinear shear into rotationally symmetric along radial direction, enabling single-shot isotropic imaging capabilities. The i-DIC presents a complementary fusion of typical meta-optics, traditional microscopes and integrated optical system, and showcases the promising and synergetic advancements in edge detection, particle motion tracking, and label-free cellular imaging.

In order to make further study on the mechanical property of CRTSIII type slab non-ballast track structures, which was self-designed in China, based on the method of the multiscale finite element model (FEM), the traditional FEM of slab non-ballast track structures was improved. The multiscale FEM of CRTSIII type slab non-ballast track structures was established based on the general finite element program ABAQUS. Then the comparative calculation was made between various FEMs, showing that the high solution precision, fast modelling speed and high solution efficiency could be obtained. Therefore, the multiscale FEM was suitable for the parametric study on mechanical behaviour of CRTSIII type slab non-ballast track structures, and then the key influence factor and constructions could be optimized.

Abstract With the development of information technology, various social fields have gradually realised informatisation and digitisation, and today's society has entered the era of big data. A large amount of data exists in different departments and systems. At present, cross‐organisational data sharing is often realised by point‐to‐point authorisation. However, there are still some threats in the management and control schedule for the whole region. To realise secure and credible data sharing, this paper proposes a cross‐organisational data‐sharing framework based on Blockchain‐Probes using distributed digital identity technology. By using a star data link of the complex network, our system realises the synchronisation of heterogeneous data sources by using a data probe as the inter‐central transmission carrier to link different data sources. The proposed framework is applied to the real scenario; compared with the traditional method, the efficiency and accuracy are improved, and the total cost is reduced by 60%. The framework could be employed in multiple complex system application scenarios such as transportation, finance and urban management.

TA15 titanium alloy is sensitive to temperature, and it is one of the main materials used in aircraft bearing parts that operate for long periods of time at 500 °C. The thermomechanical processing of this alloy is difficult to control because of its high activity and oxidation. In the present research, nanosecond pulse lasers of various powers were used to polish the TA15 surface. The surface morphology, microstructure evolution, oxidation depth and mechanical properties were investigated. The results revealed that the initial sample has a rough surface, and both high-power and low-power lasers can significantly decrease the surface roughness. Three methods, SEM morphology analysis, EDS line scanning and EDS mapping, are used to detect the oxidation depth of the polished zone. The TEM images and XRD patterns show typical Al2O3, Ti2O3 and TiO2 constituents, which affect the tensile strength of the alloy. A low-power laser has a better polishing effect than a high-power laser; the oxidation depth with a high power is approximately 100 μm, while the oxidation depth with a low power is less than 10 μm. The polished surface roughness parameters Ra (arithmetical mean deviation of the profile) and Sa (arithmetical mean height of the scale limited surface) obtained with a low-power laser are reduced from approximately 6 μm–3.197 μm and 4.298 μm, respectively.

Abstract Due to the rise of 5G, IoT, AI, and high-performance computing applications, datacenter traffic has grown at a compound annual growth rate of nearly 30%. Furthermore, nearly three-fourths of the datacenter traffic resides within datacenters. The conventional pluggable optics increases at a much slower rate than that of datacenter traffic. The gap between application requirements and the capability of conventional pluggable optics keeps increasing, a trend that is unsustainable. Co-packaged optics (CPO) is a disruptive approach to increasing the interconnecting bandwidth density and energy efficiency by dramatically shortening the electrical link length through advanced packaging and co-optimization of electronics and photonics. CPO is widely regarded as a promising solution for future datacenter interconnections, and silicon platform is the most promising platform for large-scale integration. Leading international companies (e.g., Intel, Broadcom and IBM) have heavily investigated in CPO technology, an inter-disciplinary research field that involves photonic devices, integrated circuits design, packaging, photonic device modeling, electronic-photonic co-simulation, applications, and standardization. This review aims to provide the readers a comprehensive overview of the state-of-the-art progress of CPO in silicon platform, identify the key challenges, and point out the potential solutions, hoping to encourage collaboration between different research fields to accelerate the development of CPO technology. Graphical Abstract

Objectives: Bloodstream infections (BSIs) caused by extended-spectrum beta-lactamase-producing Enterobacteriaceae (ESBL-PE) have become a worldwide public health threat, and beta-lactam/beta-lactamase inhibitor combinations (BLBLIs) are considered as one reliable carbapenem-sparing antibiotic. However, it is still controversial whether BLBLIs are truly noninferior to carbapenems. Therefore, we conducted this meta-analysis to compare the efficacy of BLBLIs with carbapenems for ESBL-PE BSIs. Methods: A systematic search of PubMed, Cochrane Library, and Embase was conducted until December 2021 to enroll studies comparing BLBLIs with carbapenems for ESBL-PE BSIs. A subgroup analysis was performed based on the choice of therapy (empirical, definitive, and mixed therapy). The protocol was registered in the International Prospective Register of Systematic Reviews (#CRD42022316011). Results: A total of 2786 patients from one randomized clinical trial and 25 cohorts were included. There was no statistically significant difference between BLBLIs and carbapenems groups in therapeutical response (odds ratio [OR] = 1.19, P = 0.45) and mortality (OR = 1.06, P = 0.68). Furthermore, although the statistical difference was also not found in the subgroup analysis, BLBLIs performed better in definitive therapy than empirical therapy than carbapenems, with a numerically higher therapeutical response (OR = 1.42 vs 0.89) and a mildly lower mortality (OR = 0.85 vs 1.14). Conclusion: BLBLIs were noninferior to carbapenems for ESBL-PE BSIs, especially in definitive therapy. BLBLIs may be a valid alternative to spare the use of carbapenems.

The sand cat swarm optimization algorithm (SCSO) is a novel metaheuristic algorithm that has been proposed in recent years. The algorithm optimizes the search ability of individuals by mimicking the hunting behavior of sand cat groups in nature, thereby achieving robust optimization performance. It is characterized by few control parameters and simple operation. However, due to the lack of population diversity, SCSO is less efficient in solving complex problems and is prone to fall into local optimization. To address these shortcomings and refine the algorithm’s efficacy, an improved multi-strategy sand cat optimization algorithm (IMSCSO) is proposed in this paper. In IMSCSO, a roulette fitness–distance balancing strategy is used to select codes to replace random agents in the exploration phase and enhance the convergence performance of the algorithm. To bolster population diversity, a novel population perturbation strategy is introduced, aiming to facilitate the algorithm’s escape from local optima. Finally, a best–worst perturbation strategy is developed. The approach not only maintains diversity throughout the optimization process but also enhances the algorithm’s exploitation capabilities. To evaluate the performance of the proposed IMSCSO, we conducted experiments in the CEC 2017 test suite and compared IMSCSO with seven other algorithms. The results show that the IMSCSO proposed in this paper has better optimization performance.

Background: Gliomas are characterized by aggressive behavior, leading to severe disability and high mortality. Ubiquitin-like modifier activating enzyme 2 (UBA2) is a subunit of the E1-activating enzyme involved in the SUMOylation (SUMO, small ubiquitin-related modifier) of numerous proteins. Although the abnormality of UBA2 is linked to the progression of various tumor types, the role of UBA2 in glioma is still unknown. Methods: A bioinformatic analysis using several public databases was conducted to examine the expression level, clinicopathological correlations, and prognostic significance of UBA2 in glioma. The correlation between UBA2 expression and drug sensitivity in cancers was also explored. Multiple cellular experiments were conducted to validate the role of UBA2 in glioma. Results: Analysis of multiple databases and cellular experiments revealed that UBA2 was overexpressed in glioma tissues and cell lines, respectively. UBA2 expression in gliomas correlated with World Health Organization (WHO) grade, IDH gene status, 1p19q deletion, histological type, and immune cell infiltration in glioma. UBA2 expression in carcinomas also correlated with drug sensitivity. Kaplan-Meier analysis revealed that high expression of UBA2 predicted poorer survival in glioma patients. A nomogram model containing UBA2 expression was constructed for clinical practice. Knockdown of UBA2 was observed to suppress glioma cell progression and sensitize glioma cells to irradiation in vitro. Conclusion: Overall, this research showed that UBA2 might be involved not only in the development of glioma but also in the regulation of immunity, drug sensitivity, and radiosensitivity. Therefore, UBA2 may be a potential target for therapy and a candidate biomarker for glioma diagnosis and prognosis.