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Abstract Traditional hydraulic structures rely on manual visual inspection for apparent integrity, which is not only time-consuming and labour-intensive but also inefficient. The efficacy of deep learning models is frequently constrained by the size of available data, resulting in limited scalability and flexibility. Furthermore, the paucity of data diversity leads to a singular function of the model that cannot provide comprehensive decision support for improving maintenance measures. This paper proposes an efficacious methodology for identifying diverse apparent damages in hydraulic structures to address the limitations of existing technologies. The advanced features of apparent damage in hydraulic structures were elucidated by fine-tuning the top-level parameters of the lightweight pre-trained model, thereby mitigating the data dependency issue inherent in the model. Ensemble learning algorithms are employed to classify high-dimensional samples to enhance the accuracy and stability of the classification. However, ensemble learning algorithms are subject to time consuming issues when applied to high-dimensional datasets. To this end, we propose a robust discriminative feature selection model to identify the most salient features, thereby enhancing the performance of apparent damage recognition in hydraulic structures while concurrently reducing the inference time. The results demonstrated that the accuracies of this method in identifying crack, fracture, hole and normal structures were 87.65%, 87.82%, 96.99%, and 95.25%, respectively. This methodology exhibits significant applicability and practical value for the intelligent inspection of hydraulic structures.

In this study, toughening of WC-Co composite prepared by amorphous-crystallization method was investigated. Co-rich nanoparticles, a Co(W,C) solid solution, were incorporated into the WC matrix through the process integrating crystallization of amorphous Co2W4C powder and its in-situ reaction with carbon. The microstructural evolution of the ceramic-metal composite during fabrication was studied in detail. Owing to the interactions between Co-rich nanoparticles coherent with the WC matrix and the dislocations and stacking faults inside WC grains, the composite exhibited high hardness and strength combined with exceptional fracture toughness. The mechanisms for the synergistic improvement of mechanical properties of the composite were disclosed.

目的 采用光学相干断层扫描血管成像（optical coherence tomography angiography，OCTA）技术，探讨颈内动脉狭窄（internal carotid artery stenosis，ICAS）患者黄斑区微血管特征及其与血管狭窄的相关性。 方法 连续纳入2023年1月—2024年9月西安市第一医院（西北大学附属第一医院）神经内科和神经眼科收治的经血管评估确诊的ICAS患者，按狭窄侧别、程度分别进行分组，并纳入年龄、性别、既往史等相匹配的参与者为健康对照组。对研究对象进行黄斑区OCTA检查，并收集其小血管密度、血管密度、灌注面积、脉络膜层大中血管血管容积及血管指数等数据进行组间比较。 结果 本研究共纳入66例研究对象，其中单侧ICAS组20例、双侧ICAS组26例、健康对照组20例，男性54例（81.8%），平均年龄为（67.5±8.7）岁。3组间除既往卒中或TIA病史外，其他临床特征差异均无统计学意义。单侧ICAS组与健康对照组相比，双眼脉络膜毛细血管层灌注面积低于健康对照组，但单侧ICAS患者双眼间各指标差异均无统计学意义。双侧ICAS组与健康对照组相比，浅层血管复合体小血管密度、视网膜内层灌注面积、脉络膜毛细血管层灌注面积、视网膜内层血管密度、浅层血管复合体血管密度差异均有统计学意义（P0.05）。所有ICAS狭窄侧眼按狭窄程度分为中度及以下狭窄组（31只）、重度及以上狭窄组（41只），与健康对照组3组进行比较，发现浅层血管复合体小血管密度、脉络膜毛细血管层灌注面积、视网膜内层血管密度及浅层血管复合体血管密度差异均具有统计学意义（P0.05）。 结论 ICAS患者黄斑区微血管指标较健康对照组参与者降低，一侧ICAS病变可导致双眼黄斑区微循环受损，且受狭窄程度影响。 Abstract: Objective To explore the microvascular characteristics of the macular lutea in patients with internal carotid artery stenosis (ICAS) and their correlation with vascular stenosis using optical coherence tomography angiography (OCTA). Methods Patients diagnosed with ICAS through vascular assessment, who were admitted to the Department of Neurology and Neuro-Ophthalmology at The First Hospital of Xi’an (The First Affiliated Hospital of Northwest University) from January 2023 to September 2024, were consecutively included. Patients were grouped according to the lesion side and stenosis degree. Age, gender, and medical history-matched participants were included as a healthy control group. OCTA examinations were conducted in the macular lutea for the enrolled subjects, and the data of small vessel density, vessel density, perfusion area, volume of medium to large choroidal vessels, and vascular index were all collected for inter-group comparison. Results A total of 66 subjects were included in this study, including 20 cases in the unilateral ICAS group, 26 cases in the bilateral ICAS group, and 20 cases in the healthy control group. Among them, 54 (81.8%) were male, with an average age of (67.5 ± 8.7) years. There were no statistically significant differences in clinical characteristics among the three groups, except for the history of previous stroke or TIA. Compared with the healthy control group, the perfusion area of the choroidal capillary layer in both eyes of the unilateral ICAS group was lower than that of the healthy control group. However, there were no statistically significant differences in these indicators between both eyes of the unilateral ICAS patients. Compared with the healthy control group, there were statistically significant differences in the small vessel density of the superficial vascular complex, the perfusion area of the inner retinal layer, the perfusion area of the choroidal capillary layer, the vessel density of the inner retinal layer, and the vessel density of the superficial vascular complex in the bilateral ICAS group (P0.05). All eyes with ICAS were divided into moderate and below (31 cases) and severe and above (41 cases) stenosis groups. When comparing these two groups with the healthy control group, it was found that the differences in small vessel density of the superficial vascular complex, the perfusion area of the choroidal capillary layer, the vessel density of the inner retinal layer, and the vessel density of the superficial vascular complex were statistically significant (P0.05). Conclusions In ICAS patients, microvascular indicators in the macular lutea were reduced compared to those in the healthy control group. Unilateral ICAS lesions can lead to impaired macular microcirculation in both eyes, with the degree of impairment influenced by the severity of stenosis.

Abstract Background Medication overuse headache (MOH) is the most common secondary headache disorder, resulting from chronic and excessive use of medication to treat headaches, for example, sumatriptan. In a recent study, we have shown that the peripheral C-C motif ligand 2 (CCL2), C-C motif chemokine receptor 2 (CCR2) and calcitonin-gene-related peptide (CGRP) signaling pathways interact with each other and play critical roles in the development of chronic migraine-related behavioral and cellular sensitization. In the present study, we investigated whether CCL2-CCR2 and CGRP signaling pathways play a role in the development of sumatriptan overuse-induced sensitization, and whether they are involved in its resolution by the low-dose interleukin-2 (LD-IL-2) treatment. Methods Mice received daily sumatriptan administration for 12 days. MOH-related behavioral sensitization was assessed by measuring changes of periorbital mechanical thresholds for 3 weeks. CCL2-CCR2 and CGRP signaling pathways were inhibited by targeted gene deletion or with an anti-CCL2 antibody. Ca2+-imaging was used to examine whether repetitive sumatriptan treatment enhances CGRP and pituitary adenylate cyclase–activating polypeptide (PACAP) signaling in trigeminal ganglion (TG) neurons. LD-IL-2 treatment was initiated after the establishment of sumatriptan-induced sensitization. Immunohistochemistry and flow cytometry analyses were used to examine whether CCL2-CCR2 signaling controls regulatory T (Treg) cell proliferation and/or trafficking. Results CCL2, CCR2 and CGRPα global KO mice exhibited robust sumatriptan-induced behavioral sensitization comparable to wild-type controls. Antibody neutralization of peripheral CCL2 did not affect sumatriptan-induced behaviors either. Repeated sumatriptan administration did not enhance the strength of CGRP or PACAP signaling in TG neurons. Nevertheless, LD-IL-2 treatment, which facilitated the resolution of sumatriptan-induced sensitization in wild-type and CGRPα KO mice, was completely ineffective in mice with compromised CCL2-CCR2 signaling. In CCL2 KO mice, we observed normal LD-IL-2-induced Treg expansion in peripheral blood, but the increase of Treg cells in dura and TG tissues was significantly reduced in LD-IL-2-treated CCL2 KO mice relative to wild-type controls. Conclusions These results indicate that the endogenous CCL2-CCR2 and CGRP signaling pathways are not involved in sumatriptan-induced behavioral sensitization, suggesting that distinct molecular mechanisms underlie chronic migraine and MOH. On the other hand, peripheral CCL2-CCR2 signaling is required for LD-IL-2 to reverse chronic headache-related sensitization. Graphical abstract

ObjectiveExploring the effects of combination of nostalgic activity-based therapies, including music therapy on cognitive function, negative emotions, and sleep quality in patients with mild to moderate Alzheimer's disease.MethodsA total of 63 patients with mild to moderate Alzheimer's disease who were treated at the Sichuan Provincial Psychiatric Center of the People's Hospital of Sichuan Province from January to June 2023 were selected as the research subjects. They were randomly divided into a study group (n = 31) and a control group (n = 32) using a random number table method. The control group received routine treatment and nursing care, while the study group received nostalgic music therapy intervention on the basis of the control group. The Mini Mental State Examination (MMSE), Montreal Cognitive Assessment Scale (MOCA), Self Rating Anxiety and Depression Scale (SAS, SDS), and Pittsburgh Sleep Quality Index (PSQI) of the two groups were compared.ResultsA total of 30 cases from each group completed the study. After 12 weeks of intervention, the MMSE and MOCA scores of both groups of patients increased, and the treatment group was higher than the control group (P < 0.05); SAS, SDS and PSQI scores decreased compared with those before intervention, and the treatment group was lower than the control group (P < 0.05).ConclusionNostalgic music therapy can improve cognitive function, alleviate negative emotions, and improve sleep quality in patients with mild to moderate Alzheimer's disease.

BackgroundEnterokinase deficiency (EKD,OMIM #226200) is a rare autosomal recessive genetic disorder caused by mutations in transmembrane protease serine 15 (TMPRSS15). Herein, we report a case of EKD in a patient with novel compound heterozygous TMPRSS15 mutations.Case presentationA 2-month-old female infant presented with chronic diarrhea, vomiting, pallor, general edema, skin lesions, and a failure to gain weight. Further examination revealed anemia, hypoalbuminemia, and multiorgan damage. Whole-exome sequencing further revealed two novel heterozygous variants of TMPRSS15: c.2611C>T (p.Arg871Ter) and c.1584_1585insCTTT (p.Glu529LeufsTer2). The clinical symptoms dramatically improved following pancreatic enzyme replacement. During a one-year follow-up, the patient showed a normal rate of physical development, with no recurrence of anemia, hypoproteinemia, coagulopathy or skin lesions.ConclusionHerein, we presented a clinical case of EKD with two novel compound heterozygous mutations in TMPRSS15 who achieved dramatic symptom improvements following pancreatic enzyme supplementation. This case enriches the genotypic spectrum of EKD and provides a reference for the diagnosis and treatment of similar cases. This case suggests that if zymogen activation testing is not possible, genetic analysis may be an effective tool to facilitate early diagnosis. Further, early pancreatic enzyme supplementation is a clinical strategy which can achieve satisfactory outcomes.

This systematic review aimed to statistically profile the medication burden and associated influencing factors, and outcomes in patients with dialysis-dependent chronic kidney disease (DD-CKD). Studies of medication burden in patients with DD-CKD in the last 10 years from 1 January 2013 to 31 March 2024 were searched from PubMed, Embase, and Cochrane databases. Newcastle-Ottawa Scale (NOS) or Agency for Healthcare Research and Quality (AHRQ) methodology checklist was used to evaluate quality and bias. Data extraction and combining from multiple groups of number (n), mean, and standard deviation (SD) were performed using R programming language (version4.3.1; R Core Team, Vienna, Austria). A total of 10 studies were included, and the results showed a higher drug burden in patients with DD-CKD. The combined pill burden was 14.57 ± 7.56 per day in hemodialysis (HD) patients and 14.63 ± 6.32 in peritoneal dialysis (PD) patients. The combined number of medications was 9.74 ± 3.37 in HD and 8 ± 3 in PD. Four studies described the various drug classes and their proportions, in general, antihypertensives and phosphate binders were the most commonly used drugs. Five studies mentioned factors associated with medication burden. A total of five studies mentioned medication burden-related outcomes, with one study finding that medication-related burden was associated with increased treatment burden, three studies finding that poor medication adherence was associated with medication burden, and another study finding that medication complexity was not associated with self-reported medication adherence. Limitations: meta-analysis was not possible due to the heterogeneity of studies.

Engineering inspection is of great significance to ensure the safe operation of the project. However, the unclear query statements of the detectors pose a challenge to the intelligent question answering task. Existing knowledge graph-based question-answering systems face issues of vocabulary limitations and reliance on fixed templates. Solely relying on Large Language Models (LLMs) for questioning introduces noise and randomness due to their extensive knowledge base. Therefore, this paper proposes a novel approach that synergistically employs both knowledge graphs and LLMs for intelligent question-answering in hydroengineering inspection. The method divides the overall task into five units, progressively clarifying query statements for accurate answers. Leveraging LLM’s vast prior knowledge, robust semantic understanding, and contextual learning mitigates issues related to vocabulary limitations and template dependence. Simultaneously, the knowledge contained in the graph is integrated into an optimal clarification path and transferred to LLM to address noise and randomness, thereby enhancing the efficiency of the clarification process. Benchmark experiments demonstrate that the proposed method achieves Mean Reciprocal Rank (MRR), Mean Average Precision (MAP), Precision, and Recall metrics all above 0.73. The results affirm the method’s effectiveness in improving the accuracy of intelligent question-answering in hydroengineering inspection, with potential implications for similar applications in other domains of hydraulic engineering.

Combining multiple crop protection Unmanned Aerial Vehicles (UAVs) as a team for a scheduled spraying mission over farmland now is a common way to significantly increase efficiency. However, given some issues such as different configurations, irregular borders, and especially varying pesticide requirements, it is more important and more complex than other multi-Agent Systems (MASs) in common use. In this work, we focus on the mission arrangement of UAVs, which is the foundation of other high-level cooperations, systematically propose Efficiency-first Spraying Mission Arrangement Problem (ESMAP), and try to construct a united problem framework for the mission arrangement of crop protection UAVs. Besides, to characterise the differences in sub-areas, the varying pesticide requirement per unit is well considered based on Normalized Difference Vegetation Index (NDVI). Firstly, the mathematical model of multiple crop-protection UAVs is established and ESMAP is defined. Furthermore, an acquisition method of a farmland’s NDVI map is proposed, and the calculation method of pesticide volume based on NDVI is discussed. Secondly, an improved Genetic Algorithm (GA) is proposed to solve ESMAP, and a comparable combination algorithm is introduced. Numerical simulations for algorithm analysis are carried out within MATLAB, and it is determined that the proposed GA is more efficient and accurate than the latter. Finally, a mission arrangement tested with three UAVs was carried out to validate the effectiveness of the proposed GA in spraying operation. Test results illustrated that it performed well, which took only 90.6 % of the operation time taken by the combination algorithm.

Abstract Reservoir dispatching regulations are a crucial basis for reservoir operation, and using information extraction technology to extract entities and relationships from heterogeneous texts to form triples can provide structured knowledge support for professionals in making dispatch decisions and intelligent recommendations. Current information extraction technologies require manual data labeling, consuming a significant amount of time. As the number of dispatch rules increases, this method cannot meet the need for timely generation of dispatch plans during emergency flood control periods. Furthermore, utilizing natural language prompts to guide large language models in completing reservoir dispatch extraction tasks also presents challenges of cognitive load and instability in model output. Therefore, this paper proposes an entity and relationship extraction method for reservoir dispatch based on structured prompt language. Initially, a variety of labels are refined according to the extraction tasks, then organized and defined using the Backus–Naur Form (BNF) to create a structured format, thus better guiding large language models in the extraction work. Moreover, an AI agent based on this method has been developed to facilitate operation by dispatch professionals, allowing for the quick acquisition of structured data. Experimental verification has shown that, in the task of extracting entities and relationships for reservoir dispatch, this AI agent not only effectively reduces cognitive burden and the impact of instability in model output but also demonstrates high extraction performance (with F1 scores for extracting entities and relationships both above 80%), offering a new solution approach for knowledge extraction tasks in other water resource fields.

Understanding how underwater topography affects phytoplankton succession by influencing hydrodynamics is crucial for maintaining the ecological health of lakes. However, there is a lack of in-depth research that accurately depicts underwater topography and coupleing hydrodynamics to establish the reproduction and migration mechanisms of phytoplankton, especially in seasonal ice-covered lakes. A typical seasonally ice-covered lake, Lake Chagan, was selected, and 164 water column and plankton samples were collected in 2023. An integrated underwater topographic-hydrodynamic model was constructed based on topographic data from 597 exploration points and long-term hydrological and meteorological observational data. The dominant algal species and their three-dimensional distribution and succession processes during different periods were studied in detail. The effects of topographic factors (relief, surface curvature, water depth, slope gradient, roughness, and slope aspect) on the hydrodynamic field and phytoplankton distribution were discussed. The results showed that the phytoplankton species diversity was higher in the bottom water column during the non-ice-covered period (March to October). The dominant species of phytoplankton varied with seasons, with diatoms dominating in the ice-covered period and harmful phytoplankton such as cyanobacteria in the non-ice-covered period. The biomass and biomass density of cyanobacteria were also higher than those of other phytoplankton. Phytoplankton species diversity and richness indices in the surface water column had a significant combined effect on the entire lake ecosystem. Surface curvature and slope gradient were the main factors affecting flow velocity during the non-ice-covered period (p ≤ 0.05, r = −0.58 and − 0.62), directly affecting the spatial distribution of cyanobacterial biomass (p ≤ 0.05, r = 0.65; p ≤ 0.01, r = −0.71). Therefore, attention should be paid to the surface curvature and slope of the sediment when controlling cyanobacterial blooms via by sediment dredging. These studies explored the behavior of phytoplankton in response to their fluid environment from a combined biological and physical-dynamic perspective and provided an effective reference for the water environment management of seasonal ice-covered lakes with harmful algal blooms.

Efficiency of harvesting robots remains a major bottleneck for increasing productivity, and the usual approach is to improve the parallelism between fruit separation and fruit crating. However, during robotic harvesting, achieving continuous and efficient fruit crating with low damage after fruit separation still needs to be urgently addressed, which is often overlooked but it is critical for maintaining fruit quality and harvesting efficiency. This study focuses on the dynamic mechanical damage analysis and optimization of a double-buffered post-picking crating process based on multiscale finite element model of tomatoes. First, by comparing the Burgers model and Multiscale Finite Element (MSFE) model, a framework for evaluating and optimizing tomato mechanical damage is presented. Then, the dynamic impacts and deformations of tomatoes during crating were simulated using the MSFE model, and critical damage thresholds were determined. A double-buffered cushioning system is introduced into the design of the tomato crating unit to constrain the impact velocities that may cause mechanical damage to the tomatoes. Based on the MSFE model and Response Surface Methodology (RSM), the double-buffered cushioning structure was optimized for efficient picking, low-damage crating process, and the crating process was validated with a customized test bench. Simulation tests the crating process determined safe impact velocities for tomato-to-tomato and tomato-to-container impacts, with maximum thresholds of 1530 mm/s and 911 mm/s, respectively. The optimal crating scheme with a primary buffer height of 40 mm, a secondary buffer angle of 30°, and the use of silicone pads as a cushioning material resulted in impact velocities of 1446.2 mm/s between the tomatoes at average mass and 676.45 mm/s with the container, which is well below the damage threshold. The results of the prototype tests showed that when fed at one per second, the damage rate of tomatoes was significantly reduced, the damage rate of only 2 %, and the mean crating time for tomatoes was 1.82 s which meets the robotic picking efficiency and low-damage requirements.

Northeast China, recognized as a global flash drought hotspot and a region of nationally important commercial grains and ecological fragility, is highly susceptible to the profound impacts of droughts on both food security and ecological safety. However, the regional-scale characteristics, possible causes and impacts of flash droughts across Northeast China are rarely investigated. Soil moisture data from 2000 to 2022 were utilized to identify the onset, frequency and duration of flash droughts using the quantile method. The spatial trajectories of flash droughts were determined based on the patch-scale centroid transfers. Further, the possible drivings and ecological impacts of flash droughts were analyzed using datasets of climatic variables and gross primary productivity. We found that flash drought coverage with short onset (1- pentad onset) was generally larger than that with long onset (2-, 3- and 4-pentad onset). The affected area of flash droughts generally decreased, while the onset speed increased over the past two decades. Flash droughts frequently occurred the intersection of western Jilin Province, southern Inner Mongolia Autonomous Region, and northern Liaoning Province but with short duration. Compared with 2001–2011, the start, middle and end centroids of flash droughts in 2012–2021 showed more spatial dynamic changes, mainly shifting towards the northeast-southwest and southeast-northwest directions. The onset of flash drought due to potential evapotranspiration, temperature, precipitation deficit, and vapor pressure anomalies account for an average of 33%, 28%, 22%, and 16%, respectively. However, the contributions of dominant meteorological factors and their combinations varied remarkably in different sub-regions. Long onset flash droughts exhibited larger impact on GPP than short onset flash droughts. This study highlights that due to climate change, the affected area of flash droughts in hotspot regions decreased, but the onset speed and spatial dynamics increased, and followed by a more severe ecological impact of short-onset flash drought. Therefore, it is imperative to incorporate the increasing impacts of flash droughts, which is critical to ensuring regional food security and ecological safety in the Northeast China.

Abstract Helicobacter pylori (HP), a common microanaerobic bacteria that lives in the human mouth and stomach, is reported to infect ≈50% of the global population. The current diagnostic methods for HP are either invasive, time‐consuming, or harmful. Therefore, a noninvasive and label‐free HP diagnostic method needs to be developed urgently. Herein, reduced graphene oxide (rGO) is composited with different metal‐based materials to construct a graphene‐based electronic nose (e‐nose), which exhibits excellent sensitivity and cross‐reactive response to several gases in exhaled breath (EB). Principal component analysis (PCA) shows that four typical types of gases in EB can be well discriminated. Additionally, the potential of the e‐nose in label‐free detection of HP infection is demonstrated through the measurement and analysis of EB samples. Furthermore, a prototype of an e‐nose device is designed and constructed for automatic EB detection and HP diagnosis. The accuracy of the prototype machine integrated with the graphene‐based e‐nose can reach 92% and 91% in the training and validation sets, respectively. These results demonstrate that the highly sensitive graphene‐based e‐nose has great potential for the label‐free diagnosis of HP and may become a novel tool for non‐invasive disease screening and diagnosis.

Abstract Colorectal cancer (CRC) is a malignancy that is widely prevalent worldwide. Due to its unsatisfactory treatment outcome and extremely poor prognosis, many studies on the molecular mechanisms and pathological mechanisms of CRC have been published in recent years. The tumor microenvironment (TME) is an extremely important feature of tumorigenesis and one of the hallmarks of tumor development. Metabolic reprogramming is currently a hot topic in tumor research, and studies on this topic have provided important insights into CRC development. In particular, metabolic reprogramming in cancer causes changes in the composition of energy and nutrients in the TME. Furthermore, it can alter the complex crosstalk between immune cells and associated immune factors, such as associated macrophages and T cells, which play important immune roles in the TME, in turn affecting the immune escape of tumors by altering immune surveillance. In this review, we summarize several metabolism-related processes affecting the immune microenvironment of CRC tumors. Our results showed that the immune microenvironment is regulated by metabolic reprogramming and influences the development of CRC.

Abstract Solute carrier family 26 member 9 (SLC26A9) is a member of the Slc26a family of multifunctional anion transporters that functions as a Cl- channel in parietal cells during acid secretion. We explored the role of SLC26A9 in colorectal cancer (CRC) and its related mechanisms through clinical samples from CRC patients, CRC cell lines and mouse models. We observed that SLC26A9 was expressed at low levels in the cytoplasm of adjacent tissues, polyps and adenomas but was significantly increased in colorectal adenocarcinoma. Moreover, increased levels of SLC26A9 were associated with a high risk of disease and poor prognosis. In addition, downregulation of SLC26A9 in CRC cells induced cell cycle arrest and apoptosis but inhibited cell proliferation and xenograft tumor growth both in vitro and in vivo. Mechanistic analysis revealed that SLC26A9 was colocalized with β-catenin in the nucleus of CRC cells. The translocation of these two proteins from the cytoplasm to the nucleus reflected the activation of Wnt/β-catenin signaling, and promoted the transcription of downstream target proteins, including CyclinD1, c-Myc and Snail, but inhibited the expression of cytochrome C (Cyt-c), cleaved Caspase9, cleaved Caspase3 and apoptosis-inducing factor (AIF). CRC is accompanied by alteration of epithelial mesenchymal transition (EMT) markers. Meanwhile, further studies showed that in SW48 cells, overexpressing SLC26A9 was cocultured with the β-catenin inhibitor XAV-939, β-catenin was downregulated, and EMT was reversed. Our study demonstrated SLC26A9 may be responsible for alterations in the proliferative ability and aggressive potential of CRC by regulating the Wnt/β-catenin signaling pathway.

Objectives: The rapid spread of the New Delhi Metal-β-lactamase-1 (NDM-1) gene in Klebsiella pneumoniae poses a substantial challenge to pediatric therapeutic care. Here, we aimed to characterise the IncX3-type plasmid carrying the blaNDM-1 gene in ST76 carbapenem resistance K. pneumoniae (CRKP) strains and assess the in vitro and in vivo bactericidal efficacy of Aztreonam (ATM) combined with Avibactam (AVI) (ATM+AVI) against CRKP. Methods: The broth microdilution method and PCR were used to detect antimicrobial susceptibility and antibiotic resistance genes. Genetic relatedness was determined using Pulsed-Field Gel Electrophoresis (PFGE) and Multilocus Sequence Typing (MLST). The plasmid conjugation assay was used to verify the transmissibility of drug-resistant plasmids. Whole-Genome Sequencing (WGS) was employed to elucidate the genomic attributes of the genes. The Fractional Inhibitory Concentration (FIC) was calculated based on the checkerboard titration assay to determine the antimicrobial effect of ATM+AVI. The time-kill curve assay and a mouse anti-infection model were used to investigate the in vitro and in vivo bactericidal efficiency of ATM+AVI. Results: Seven blaNDM-1-producing strains were found to be highly resistant to carbapenems, and they all belonged to the same sequence type (ST76) and were classified into the same PFGE clusters with an 89.1% similarity. The conjugation assay showed that the blaNDM-1-carrying plasmid was successfully transferred to Escherichia coli 600, resulting in transconjugants with carbapenem antibiotic resistance. A 54-kb IncX3 plasmid (pNDM-XZA88) carried the blaNDM-1 gene located on a Tn125 transposon-like element structure, demonstrating the transferability of resistance genes. Genome comparative analysis revealed that pNDM-XZA88 was highly similar to pCQ17 × 3 and pRor-30818cz and had relatively conserved backbones and variable accessory regions compared to the other four plasmids (pC39-334 kb, pNDM-1-DY1928, pNDM-K725, and pNDM-Z244). The checkerboard titration and time-kill curve assays revealed that the ATM+AVI combination therapy exerted significant bactericidal efficacy against the blaNDM-1-producing strains in vitro. The ATM+AVI combination also significantly reduced the bacterial burden in a mouse infection model constructed using the blaNDM-1-producing K. pneumoniae. Conclusion: This study demonstrated the clone dissemination of blaNDM-1-harboring IncX3 plasmids among the ST76 K. pneumoniae isolated from pediatric patients. Therefore, more attention should be paid to preventing this high-risk clone from harming pediatric patients. Moreover, we deduced that the ATM+AVI combination therapy is an effective strategy for treating blaNDM-1-producing K. pneumoniae.

In China, there are approximately 36.7 million hectares of available saline–alkali land. The quality of land preparation significantly influences the yield of crops grown in saline–alkali soil. However, saline–alkali soil is highly compacted, and, currently, the market lacks land-preparation products specifically tailored to the unique characteristics of saline–alkali land. The soil crushing performance of existing power harrows fails to meet the requirements for high-quality land preparation, thus affecting crop planting yields. Consequently, it is imperative to conduct research on the design and performance improvement of the soil crushing components of power harrows for saline–alkali land. This paper centers on the key soil crushing component, the harrow blade, and conducts research from the perspectives of kinematics and dynamics. Initially, the ranges of key structural and motion parameters are determined, such as the angle of the harrow blade cutting edge, the thickness of the of the harrow blade cutting edge, and the ratio of the circumferential speed to the forward speed. Subsequently, through simulation tests integrating the Discrete Element Method (DEM) and the Box–Behnken Design (BBD), the optimal parameter combination is identified. The impact of the forward speed and the rotational speed of the vertical-shaft rotor on soil disturbance is analyzed. The relationship between soil disturbance and soil heaping is explored, and an optimal forward speed of around 6 km/h is determined. Field tests are conducted to verify the cause of soil heaping. The test results show that the soil crushing rates are all above 85%, with an average soil crushing rate of 88.66%. These test results have achieved the predetermined objectives and meet the design requirements.

In China, there are around 36.7 million hectares of saline–alkali lands that hold utilization potential. Precision fertilization stands as a vital measure for enhancing the quality of saline–alkali soil and promoting a significant increase in crop yields. The performance of the fertilization device is a decisive factor in determining the effectiveness of fertilization. To optimize the fertilizer utilization rate in coastal saline–alkali soils and substantially reduce fertilizer waste, it is imperative to transport fertilizers to the deep soil layers and execute layered variable-rate fertilization. In light of this, a chisel-type variable-rate layered electronically controlled deep-fertilization device specifically designed for saline–alkali soils has been developed. Extensive experimental research on its fertilization performance has also been carried out. Drawing on the principles of soil dynamics, this paper meticulously investigates the structures of key components and the operating parameters of the fertilization device. Key parameters such as the penetration angle of the fertilizer shovel, the penetration clearance angle, the curvature of the shovel handle, the angle between the fertilizer baffle and the fertilizer pipe wall, the angle between the fertilizer pipe and the horizontal plane, and the forward speed are precisely determined. Moreover, this study explores the quantitative relationship between the fertilizer discharge amount of the fertilizer applicator and the effective working width. Simultaneously, this research mainly focuses on analyzing the impact of the forward speed on the operational effect of layered and variable-rate fertilization. Through a series of field experiments, it was conclusively determined that the optimal fertilization effect was attained when the forward speed was set at 6 km/h. Under this condition, the average deviation in the fertilization amount was merely 2.76%, and the average coefficients of variation in the fertilizer amount uniformity in each soil layer were 7.62, 6.32, 6.06, and 5.65%, respectively. Evidently, the experimental results not only successfully met the pre-set objectives, but also fully satisfied the design requirements. Undoubtedly, this article can offer valuable methodological references for the research and development of fertilization devices tailored for diverse crops cultivated on saline–alkali lands.

There are approximately 36.7 million hectares of saline alkali land available in China. To enhance the comprehensive utilization value of coastal saline alkali land and boost crop yields in such areas, it is essential to conduct research on optimizing the operational performance of high-performance soil contact components in light of the soil characteristics of coastal saline alkali land. Discrete element simulation can be employed to investigate the operational mechanisms of various key components. Nevertheless, at present, there is a dearth of discrete element models for the key physical parameters and soil structure of coastal saline alkali land soil. In this article, typical coastal saline alkali field soil was sampled, and the physical properties of the saline alkali soil, including salt content, moisture content, particle size distribution, and particle size, as well as intrinsic parameters such as soil compaction, density, Poisson’s ratio, and shear modulus, were measured. The Hertz Mindlin with Bonding contact model was employed. Physical experiments on soil accumulation angles at different depths were carried out using the cylindrical lifting method. Subsequently, by means of the discrete element method and the BBD experimental design method, a response surface model was established, and an optimization analysis was performed on the optimal parameters for the soil–soil collision recovery coefficient, static friction coefficient, and dynamic friction coefficient at each depth. Test benches for measuring the collision recovery coefficient, static friction coefficient, and rolling friction coefficient of saline alkali soil at -65Mn were set up, calculation formulas for each parameter were derived, and the contact parameters between soil at different depths and 65Mn were obtained. The results of the sliding friction angle test on different depths of saline alkali soil at -65Mn were further verified using the discrete element method, with a maximum error of 3.11%, which falls within the allowable range. This suggests that the calibration results of the discrete element simulation parameters for the interaction between soil and contact components are reliable, providing data and model support for future research on enhancing the operational performance of high-performance contact components.

Grey jujube (Zizyphus jujuba Mill. cv. Huizao), a prominent cultivar from Xinjiang, China, is well known for its high nutritional value and medicinal benefits. This study investigates the effects of long-term storage on the quality attributes of grey jujube, focusing on color, texture, physicochemical properties, bioactive ingredients, amino acid profiles, sensory characteristics, and volatile compounds. Over a three-year storage period, significant changes were observed, including a decline in lightness and redness of the peel, accompanied by textural modifications such as increased hardness and chewiness, primarily attributed to moisture loss. Physicochemical analyses revealed significant reductions in moisture content, sugars (particularly reducing sugars), and bioactive compounds such as vitamin C, total flavonoids, and cyclic adenosine monophosphate (cAMP). In contrast, total acidity showed a significant increase over time. Sensory evaluation indicated a substantial loss of fresh aroma and flavor, with the development of off-flavors over time. Additionally, a comprehensive analysis of volatile compounds highlighted significant transformations in aroma profiles, with notable reductions in desirable esters and increases in acetic acid concentrations. This study investigates the quality changes of grey jujubes during storage from sensory and physicochemical perspectives, aiming to provide a novel approach for differentiating between newly harvested and aged grey jujubes. Furthermore, these findings provide theoretical support for improving and optimizing storage conditions. Future research should focus on elucidating the underlying mechanisms of these changes, identifying key markers for quality control during grey jujube storage, and providing a scientific basis for distinguishing between newly harvested and aged grey jujubes, while improving storage quality.

BackgroundIgA nephropathy (IgAN) is a significant contributor to chronic kidney disease (CKD). Renal arteriolar damage is associated with IgAN prognosis. However, simple tools for predicting arteriolar damage of IgAN remain limited. We aim to develop and validate a nomogram model for predicting renal arteriolar damage in IgAN patients.MethodsWe retrospectively analyzed 547 cases of biopsy-proven IgAN patients. Least absolute shrinkage and selection operator (LASSO) regression and logistic regression were applied to screen for factors associated with renal arteriolar damage in patients with IgAN. A nomogram was developed to evaluate the renal arteriolar damage in patients with IgAN. The performance of the proposed nomogram was evaluated based on a calibration plot, ROC curve (AUC) and Harrell’s concordance index (C-index).ResultsIn this study, patients in the arteriolar damage group had higher levels of age, mean arterial pressure (MAP), serum creatinine, serum urea nitrogen, serum uric acid, triglycerides, proteinuria, tubular atrophy/interstitial fibrosis (T1–2) and decreased eGFR than those without arteriolar damage. Predictors contained in the prediction nomogram included age, MAP, eGFR and serum uric acid. Then, a nomogram model for predicting renal arteriolar damage was established combining the above indicators. Our model achieved well-fitted calibration curves and the C-indices of this model were 0.722 (95%CI 0.670–0.774) and 0.784 (95%CI 0.716–0.852) in the development and validation groups, respectively.ConclusionWith excellent predictive abilities, the nomogram may be a simple and reliable tool to predict the risk of renal arteriolar damage in patients with IgAN.

ObjectiveInfertility remains a significant global burden over the years. Reproductive surgery is an effective strategy for infertile women. Early prediction of spontaneous pregnancy after reproductive surgery is of high interest for the patients seeking the infertility treatment. However, there are no high-quality models and clinical applicable tools to predict the probability of natural conception after reproductive surgery.MethodsThe eligible data involving 1013 patients who operated for infertility between June 2016 and June 2021 in Yantai Yuhuangding Hospital in China, were randomly divided into training and internal testing cohorts. 195 subjects from the Linyi People’s Hospital in China were considered for external validation. Both univariate combining with multivariate logistic regression and the least absolute shrinkage and selection operator (LASSO) algorithm were performed to identify independent predictors. Multiple common machine learning algorithms, namely logistic regression, decision tree, random forest, support vector machine, k-nearest neighbor, and extreme gradient boosting, were employed to construct the predictive models. The optimal model was verified by evaluating the model performance in both the internal and external validation datasets.ResultsSix clinical indicators, including female age, infertility type, duration of infertility, intraoperative diagnosis, ovulation monitoring, and anti-Müllerian hormone (AMH) level, were screened out. Based on the logistic regression model’s superior clinical predictive value, as indicated by the area under the receiver operating characteristic curve (AUC) in both the internal (0.870) and external (0.880) validation sets, we ultimately selected it as the optimal model. Consequently, we utilized it to generate a web-based nomogram for predicting the probability of spontaneous pregnancy after reproductive surgery. Furthermore, the calibration curve, Hosmer–Lemeshow (H-L) test, the decision curve analysis (DCA) and clinical impact curve analysis (CIC) demonstrated that the model has superior calibration degree, clinical net benefit and generalization ability, which were confirmed by both internal and external validations.ConclusionOverall, our developed first nomogram with online operation provides an early and accurate prediction for the probability of natural conception after reproductive surgery, which helps clinicians and infertile couples make sensible decision of choosing the mode of subsequent conception, natural or IVF, to further improve the clinical practices of infertility treatment.

Seismic landslide susceptibility evaluation models are usually built on the basis of historical sample data; however, the evaluation results are often unsatisfactory when the environmental settings differ between the historical sample data region and application region. Therefore, similarity between the environmental settings is important for the application of such models. In this paper, a seismic landslide susceptibility evaluation model was first built using data from the 2008 Ms 8.0 Wenchuan earthquake-induced landslide, and the model was then used to evaluate the 2022 Ms 6.8 Luding earthquake area. In addition, the grade of susceptibility is typically represented by the landslide density, which is insufficient for capturing the details of landslides, such as their sizes, frequencies, and spatial distribution patterns. The authors therefore use a large and concentrated landslide as the susceptibility grade for the Luding earthquake area. The test results demonstrate that these two areas have similar background environments. The area under the curve (AUC) value of the receiver operating characteristics (ROC) curve of the evaluation accuracy for the model applied to the Luding earthquake area is 0.889, which indicates relatively high accuracy. Besides, the results also demonstrate that the evaluations are consistent with the disaster situation of the Moxi Platform, Wandong Village, as well as the Dagangshan Hydropower Station area. Therefore, it is reliable to apply the susceptibility evaluation model based on the Wenchuan earthquake data to the Luding earthquake area. These results show that better evaluations can be obtained based on environmental similarity tests between the areas used for historical data modeling and areas to which the models are applied.

BackgroundThis study aims to screen inflammation-related genes closely associated with the prognosis of hepatocellular carcinoma (HCC) to accurately forecast the prognosis of HCC patients.MethodsGene expression matrices and clinical information for liver cancer samples were obtained from the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). An intersection of differentially expressed genes of HCC and normal and GeneCards yielded inflammation-related genes associated with HCC. Cox regression and the minor absolute shrinkage and selection operator (LASSO) regression analysis to filter genes associated with HCC prognosis. The prognostic value of the model was confirmed by drawing Kaplan–Meier and ROC curves. Select differentially expressed genes between the high-risk and low-risk groups and perform GO and KEGG pathways analyses. CIBERSORT analysis was conducted to assess associations of risk models with immune cells and verified using real-time qPCR.ResultsA total of six hub genes (C3, CTNNB1, CYBC1, DNASE1L3, IRAK1, and SERPINE1) were selected using multivariate Cox regression to construct a prognostic model. The validation evaluation of the prognostic model showed that it has an excellent ability to predict prognosis. A line plot was drawn to indicate the HCC patients’ survival, and the calibration curve revealed satisfactory predictability. Among the six hub genes, C3 and DNASE1L3 are relatively low expressed in HCCLM3 and 97H liver cancer cell lines, while CTNNB1, CYBC1, IRAK1, and SERPINE1 are relatively overexpressed in liver cancer cell lines.ConclusionOne new inflammatory factor-associated prognostic model was constructed in this study. The risk score can be an independent predictor for judging the prognosis of HCC patients’ survival.

The Sichuan basin (SCB) is situated at the southeastern edge of the Tibetan Plateau where widespread seismicity has occurred. In the past decades, seismic events occurred in and around SCB have been responsible for more than 100 thousand casualties. To quantify the present-day seismic hazard of this region, especially the densely populated Chengdu-Chongqing economic zone (CCEZ), we develop a probabilistic earthquake forecast model using strain rates derived from 187 Global Navigation Satellite System (GNSS) horizontal velocities, of which 102 velocity vectors are first released. The second invariant of the strain rate tensor suggests that the Shimian County and its surroundings are exposed to the highest seismic hazard in and around SCB. The second most dangerous area is located between 103–105°E. The Chongqing area is the least dangerous. The principal strain rate axes interior of the Sichuan basin suggest that this region is experiencing broad-scale extension, which according to our knowledge, is first revealed by our dense GNSS network. The comparison between the cumulative histograms of the second invariant of geodetic strain rate and earthquake count indicates that the geodetic strain rates in this region can serve as a reliable predictor of M≥6 earthquake locations. Thus, we proceed to calculate the total seismic moment anticipated for the entire area within the next 30 years.

Abstract Simultaneous improvement of strength and conductivity is urgently demanded but challenging for bimetallic materials. Here we show by creating a self-assembled lamellar (SAL) architecture in W-Cu system, enhancement in strength and electrical conductivity is able to be achieved at the same time. The SAL architecture features alternately stacked Cu layers and W lamellae containing high-density dislocations. This unique layout not only enables predominant stress partitioning in the W phase, but also promotes hetero-deformation induced strengthening. In addition, the SAL architecture possesses strong crack-buffering effect and damage tolerance. Meanwhile, it provides continuous conducting channels for electrons and reduces interface scattering. As a result, a yield strength that doubles the value of the counterpart, an increased electrical conductivity, and a large plasticity were achieved simultaneously in the SAL W-Cu composite. This study proposes a flexible strategy of architecture design and an effective method for manufacturing bimetallic composites with excellent integrated properties.

In response to the limited capability of extracting semantic information in knowledge graph completion methods, we propose a model that combines spatial transformation and attention mechanisms (STAM) for knowledge graph embedding. Firstly, spatial transformation is applied to reorganize entity embeddings and relation embeddings, enabling increased interaction between entities and relations while preserving shallow information. Next, a two-dimensional convolutional neural network is utilized to extract complex latent information among entity relations. Simultaneously, a multi-scale channel attention mechanism is constructed to enhance the capture of local detailed features and global semantic features. Finally, the surface-level shallow information and latent information are fused to obtain feature embeddings with richer semantic expression. The link prediction results on the public datasets WN18RR, FB15K237 and Kinship demonstrate that STAM achieved improvements of 8.8%, 10.5% and 6.9% in the mean reciprocal rank (MRR) evaluation metric compared to ConvE, for the respective datasets. Furthermore, in the link prediction experiments on the hydraulic engineering dataset, STAM achieves better experimental results in terms of MRR, Hits@1, Hits@3 and Hits@10 evaluation metrics, demonstrating the effectiveness of the model in the task of hydraulic engineering knowledge graph completion.

Although the academic community has come to accept the Carbon Emissions Trading Scheme (CETS) as a viable market incentive for environmental control, more research is needed to determine if the creation of such a scheme can spur the development of green technologies. Based on the panel data of 274 Chinese cities from 2010 to 2017, this paper uses the propensity score matching-difference in difference (PSM-DID) method to empirically test the green innovation effect of the pilot areas relative to the non-pilot areas before and after the implementation of the policy, uses the mediating effect model and the moderating effect model to test its internal influence mechanism, and further examines the heterogeneity of the policy effects. The findings indicate that pilot CETS deployment can significantly improve green technology innovation (GTI), and the conclusion is still valid after a series of robustness tests. Moreover, the human capital input and the science and technology support have a significant partial mediating effect in the policy effect of CETS on GTI, with the latter contributing greatly. The overall marketization and the financial development positively moderate the impact of CETS on GTI, but government involvement have a reverse moderating effect. In addition, the policy effects is better in cities with higher administrative levels in China and in cities in eastern and western China, while the policy effects in cities with lower administrative levels and in central China is weak or not significant. This study has far-reaching theoretical value and momentous practical significance for China and other developing countries in terms of further deepening and improving the CETS, enhancing GTI, and promoting urban sustainable development.

Abstract Particulate matter (PM) toxicity has mostly been investigated through in vitro exposure or tracheal infusion in animal models. However, given the complexity of ambient conditions, most animal studies do not mimic real-life PM exposure. In this work, we established a novel integrated exposure model to study the dynamic inflammatory response and defense strategies in ambient PM-exposed mice. Three groups of male C57BL/6 mice were kept in three chambers with pre-exposure to filtered air (FA), unfiltered air (UFA), or the air with a low PM concentration (PM2.5 ≤ 75 μg/m3) (LPM), respectively, for 37 days. Then all three groups of mice were exposed to haze challenge for 3 days, followed by exposure in filtered air for 7 days to allow recovery. Our results suggest that following a haze challenge, the defense strategies of mice of filtered air (FA) and low PM (LPM) groups comprised a form of “counterattack”, whereas the response of the unfiltered air (UFA) group could be viewed as a “silence”. While the latter strategy protected the lung tissues of mice from acute inflammatory damage, it also foreshadowed the development of chronic inflammatory diseases. These findings contribute to explaining previously documented PM-associated pathogenic mechanisms.

Baseflow is a vital water source for environmental and economic growth. To reveal the changes in baseflow in an arid area, Loss Plateau, China, we analyzed the annual, seasonal, and monthly baseflow fluctuations in 1981–1990 and 2006–2010. We discussed the effects of PET (potential evapotranspiration), precipitation, HI (humidity index), and temperature might have on baseflow in the basin. Results showed that the annual baseflow decreased significantly, and seasonal baseflow and baseflow index (BFI) were distributed differently in the four seasons. Baseflow and BFI were stable during the winter, but during May and June, baseflow was unstable while BFI remained stable. During 1981–1990, January and December exhibited a slight variation in baseflow, while January, May, and June exhibited a slight variation in BFI. From 2006 to 2015, baseflow was stable, with limited fluctuations in January, February, March, April, May, November, and December. The correlations between baseflow and PET, precipitation, HI, and temperature were neither statistically significant nor robust. Increases in PET, precipitation, HI, and temperature did not result in a corresponding increase or decrease in baseflow from the annual, seasonal, and monthly time scales. HIGHLIGHTS Annual, seasonal, and monthly time scale baseflow and BFI in a semi-arid river basin were analyzed.; Baseflow and BFI showed the opposite trend. A small BFI accompanied a large baseflow, and when the baseflow fluctuated, the BFI remained stable.; The correlations between baseflow (BFI) and PET, precipitation, HI, and temperature were neither statistically significant nor robust.;

Objective To report the genetic information of a patient with non-classic 21 hydroxylase deficiency (21-OHD) for enriching the genetic database of this disease. Methods The clinical data and gene sequencing results of a patient with non-classic 21-OHD admitted to our hospital were collected. The patient’s relatives underwent high-throughput CYP21A2 gene sequencing using peripheral blood. At the same time, a literature review was performed. Results This 16-year-old female patient presented with clitoral hypertrophy, primary amenorrhea, hirsutism, acne, and growth acceleration during pre-puberty with advanced bone age. Gene testing results showed that the CYP21A2 gene had two compound heterozygous mutations: A missense mutation, c.1451G>A (p:R484Q); and a deletion mutation, deletion exon 1-3. Her relatives’ sequencing results indicated that the missense mutation c.1451G>A (p:R484Q) originated from her maternal grandfather and mother, and the deletion mutation deletion exon 1-3 inherited from her paternal grandmother and father. Conclusion We discovered a case of non-classic 21-OHD caused by new compound heterozygous gene mutations, which enriched the pathogenic mutation database of 21-OHD and could help improve clinicians’ understanding of the disease.

The development of epoxy resins is mainly dependent on non-renewable petroleum resources, commonly diglycidyl ether bisphenol A (DGEBA)-type epoxy monomers. Most raw materials of these thermoset resins are toxic to the health of human beings. To alleviate concerns about the environment and health, the design and synthesis of bio-based epoxy resins using biomass as raw materials have been widely studied in recent decades to replace petroleum-based epoxy resins. With the improvement in the requirements for the performance of bio-based epoxy resins, the design of bio-based epoxy resins with unique functions has attracted a lot of attention, and bio-based epoxy resins with flame-retardant, recyclable/degradable/reprocessable, antibacterial, and other functional bio-based epoxy resins have been developed to expand the applications of epoxy resins and improve their competitiveness. This review summarizes the research progress of functional bio-based epoxy resins in recent years. First, bio-based epoxy resins were classified according to their unique function, and synthesis strategies of functional bio-based epoxy resins were discussed, then the relationship between structure and performance was revealed to guide the synthesis of functional bio-based epoxy resins and stimulate the development of more types of functional bio-based epoxy resins. Finally, the challenges and opportunities in the development of functional bio-based epoxy resins are presented.

The emergency plans for water diversion projects suffer from weak knowledge correlation, inadequate timeliness, and insufficient support for intelligent decision-making. This study incorporates knowledge graph technology to enable intelligent recommendations for emergency plans in water diversion projects. By employing pre-trained language models (PTMs) with entity masking, the model's ability to recognize domain-specific entities is enhanced. By leveraging matrix-based two-dimensional transformations and feature recombination, an interactive convolutional neural network (ICNN) is constructed to enhance the processing capability of complex relationships. By integrating PTM with ICNN, a PTM–ICNN method for joint extraction of emergency entity relationships is constructed. By utilizing the Neo4j graph database to store emergency entity relationships, an emergency knowledge graph is constructed. By employing the mutual information criterion, intelligent retrieval and recommendation of emergency plans are achieved. The results demonstrate that the proposed approach achieves high extraction accuracy (F1 score of 91.33%) and provides reliable recommendations for emergency plans. This study can significantly enhance the level of intelligent emergency management in water diversion projects, thereby mitigating the impact of unforeseen events on engineering safety. HIGHLIGHTS Pre-trained language models with entity masking to improve the ability of the models to recognize domain entities.; Matrix-based two-dimensional transformation and feature reorganization to enhance the processing of complex relationships.; Intelligent retrieval and recommendation of emergency plans based on mutual information criterion.;

Abstract Background Epithelial–mesenchymal transition (EMT) plays a key role in tubulointerstitial fibrosis, which is a hallmark of diabetic kidney disease (DKD). Our previous studies showed that CRTC2 can simultaneously regulate glucose metabolism and lipid metabolism. However, it is still unclear whether CRTC2 participates in the EMT process in DKD. Methods We used protein‒protein network (PPI) analysis to identify genes that were differentially expressed during DKD and EMT. Then, we constructed a diabetic mouse model by administering STZ plus a high-fat diet, and we used HK-2 cells that were verified to confirm the bioinformatics research results. The effects that were exerted by CRTC2 on epithelial-mesenchymal transition in diabetic kidney disease through the CREB-Smad2/3 signaling pathway were investigated in vivo and in vitro by real-time PCR, WB, IHC and double luciferase reporter gene experiments. Results First, bioinformatics research showed that CRTC2 may promote EMT in diabetic renal tubules through the CREB-Smad2/3 signaling pathway. Furthermore, the Western blotting and real-time PCR results showed that CRTC2 overexpression reduced the expression of E-cadherin in HK-2 cells. The CRTC2 and α-SMA levels were increased in STZ-treated mouse kidneys, and the E-cadherin level was reduced. The luciferase activity of α-SMA, which is the key protein in EMT, was sharply increased in response to the overexpression of CRTC2 and decreased after the silencing of CREB and Smad2/3. However, the expression of E-cadherin showed the opposite trends. In the real-time PCR experiment, the mRNA expression of α-SMA increased significantly when CRTC2 was overexpressed but partially decreased when CREB and Smad2/3 were silenced. However, E-cadherin expression showed the opposite result. Conclusion This study demonstrated that CRTC2 activates the EMT process via the CREB-Smad2/3 signaling pathway in diabetic renal tubules.

Abstract Phosphofructokinase, platelet (PFKP) is a rate-limiting enzyme of glycolysis that plays a decisive role in various human physio-pathological processes. PFKP has been reported to have multiple functions in different cancer types, including lung cancer and breast cancer. However, no systematic pancancer analysis of PFKP has been performed; this type of analysis could elucidate the clinical value of PFKP in terms of diagnosis, prognosis, drug sensitivity, and immunological correlation. Systematic bioinformation analysis of PFKP was performed based on several public datasets, including The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), Genotype-Tissue Expression Project (GTEx), and Human Protein Atlas (HPA). Prospective carcinogenesis of PFKP across cancers was estimated by expression analysis, effect on patient prognosis, diagnosis significance evaluation, and immunity regulation estimation. Then, pancancer functional enrichment of PFKP was also assessed through its effect on the signaling score and gene expression profile. Finally, upstream expression regulation of PFKP was explored by promoter DNA methylation and transcription factor (TF) prediction. Our analysis revealed that high expression of PFKP was found in most cancer types. Additionally, a high level of PFKP displayed a significant correlation with poor prognosis in patients across cancers. The diagnostic value of PFKP was performed based on its positive correlation with programmed cell death-ligand 1 (PD-L1). We also found an obvious immune-regulating effect of PFKP in most cancer types. PFKP also had a strong negative correlation with several cancer drugs. Finally, ectopic expression of PFKP may depend on DNA methylation and several predicated transcription factors, including the KLF (KLF transcription factor) and Sp (Sp transcription factor) families. This pancancer analysis revealed that a high expression level of PFKP might be a useful biomarker and predictor in most cancer types. Additionally, the performance of PFKP across cancers also suggested its meaningful role in cancer immunity regulation, even in immunotherapy and drug resistance. Overall, PFKP might be explored as an auxiliary monitor for pancancer early prognosis and diagnosis.

Abstract Background With the decline of cognitive function in vascular cognitive impairment, the burden on the family and society will increase. Therefore, early identification of vascular mild cognitive impairment (VaMCI) is crucial. The focus of early identification of VaMCI is on the attention of risk factors. Therefore, this study aimed to investigate the relationship between diabetes and VaMCI among the Chinese, hoping to predict the risk of VaMCI by diabetes and to move the identification of vascular cognitive impairment forward. Methods We collected data from seven clinical centers and nine communities in China. All participants were over 50 years of age and had cognitive complaints. We collected basic information of the participants, and cognitive function was professionally assessed by the Montreal Cognitive Assessment scale. Finally, logistic regression analysis was used to analyze the correlation between each factor and VaMCI. Results A total of 2020 participants were included, including 1140 participants with VaMCI and 880 participants with normal cognition. In univariate logistic regression analysis, age, heavy smoking, and diabetes had a positive correlation with VaMCI. At the same time, being married, high education, and light smoking had a negative correlation with VaMCI. After correction, only diabetes (OR = 1.04, 95% CI: 1.01–1.09, p = 0.05) had a positive correlation with VaMCI, and high education (OR = 0.60, 95% CI:.45–.81, p = 0.001) had a negative correlation with VaMCI. Conclusion In our study, we found that diabetes had a positive correlation with VaMCI, and high education had a negative correlation with VaMCI. Therefore, early identification and timely intervention of diabetes may reduce the risk of VaMCI and achieve early prevention of VaMCI.