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Purpose The rapid expansion of high-speed railway (HSR) networks in Western China has increased the exposure of linear infrastructure to active faults. This study establishes and applies a probabilistic fault displacement hazard analysis (PFDHA) framework to quantify both on-fault surface rupture and distributed off-fault permanent ground deformation (PGD) hazards for HSR crossings of the Xiaojiang Fault Zone (XJFZ). Design/methodology/approach A PFDHA framework is developed, integrating a Poissonian seismicity model with spatial rupture randomness. The methodology is applied to the XJFZ, which crosses the Nanning-Kunming (NK) and Shanghai-Kunming (SK) HSR. Permanent displacement hazards are evaluated for 2 probability levels: 10% and 2% probability of exceedance in 50 years. Findings Through the evaluation of displacement hazards for 50-year exceedance probabilities of 10% and 2%, this study finds that for the NK and SK HSR, permanent displacements at a 10% probability of exceedance range from 1.0 m to 2.9 m, peaking at fault intersections. Comparative analysis shows that traditional deterministic estimates (1.3–2.0 m) generally align with the probabilistic results but fail to capture the full range of risk. Originality/value This work adapts PFDHA to linear infrastructure in a tectonically active region of China, explicitly considering both on- and off-fault displacement within engineering-relevant corridors. The integration of regional rupture scaling and segment-based constraints provides a reproducible basis for displacement hazard assessment in HSR planning and retrofit.

Background Cognitive impairment and stroke constitute major health challenges for the aging global population, adversely impacting quality of life and increasing healthcare burdens. The American Heart Association’s “Life’s Essential 8” (LE8) framework has served as a key tool for evaluating cardiovascular health (CVH); however, it omits mental health, a critical factor influencing both cognitive function and stroke risk. The introduction of “Life’s Crucial 9” (LC9), which includes depressive symptoms, provides a more comprehensive approach. This study investigates the relationship between LC9, cognitive function, and stroke risk. Methods Utilizing the National Health and Nutrition Examination Survey (NHANES) dataset from 2011 to 2014, cross-sectional data from 2,327 participants were analyzed. Stratified analyses were performed according to demographic and health-related factors. A Restricted Cubic Spline (RCS) model was employed to examine potential threshold effects. Additionally, weighted linear regression models were used to evaluate cognitive performance, and logistic regression models were applied to assess stroke risk. Results Higher LC9 scores were positively associated with better cognitive function and lower odds of stroke. Within the cognitive function analysis, higher LC9 scores were significantly associated with superior performance on the Digit Symbol Substitution Test (DSST) (β = 0.18, 95% CI: 0.11– 0.26, P  < 0.001). In the stroke analysis, individuals with higher LC9 scores exhibited decreased odds of experiencing a stroke (OR = 0.97, 95% CI: 0.95–0.99, P  = 0.005). RCS analysis identified a non-linear relationship between LC9 scores and the odds of stroke, with the greatest decreases in stroke odds observed at lower LC9 scores, plateauing around a score of 70. Conclusions Higher LC9 scores are associated with better cognitive function and lower odds of stroke. These findings suggest that incorporating mental health metrics, such as depression, into cardiovascular health assessments enhances the predictive power for cognitive outcomes and stroke prevention.

The SAUR (Small Auxin-Upregulated RNA) family members are important early auxin responsive genes in plants, playing a key regulatory role in the auxin metabolism, signal transduction, plant organ development, and abiotic stress response. Auxin signaling is also crucial for strawberry fruit development, but its specific regulatory mechanism remains unclear. In this study, bioinformatics methods were used to systematically identify and evaluate the FvSAUR gene family members associated with the auxin signaling in strawberry. The woodland strawberry Yellow Wonder line ‘YW5AF7’ was used as the material to further investigate the expressional characteristics of FvSAUR members in response to the auxin signals. A total of 64 members of the SAUR gene family were identified in the woodland strawberry genome, associated with FvSAUR1-64. Further bioinformatics analysis revealed that the FvSAUR members have undergone significant structural differentiation during evolution, and their encoded proteins exhibit diversity in folding stability, physicochemical properties, and other aspects. The prediction of the cis-elements in the promoter sequences of these genes suggests that the FvSAUR genes may mediate multiple hormonal and environmental signals, participating in a wide range of biological processes. RNA seq data analysis combined with RT-qPCR analysis revealed a dynamic spatiotemporal expression pattern of the FvSAUR genes in the vegetative and reproductive organs of strawberries, particularly the high expression levels of FvSAUR11, 17, 19, 21, and other genes in flowers and young fruits, suggesting their potential regulatory roles in strawberry fruit development. Exogenous auxin treatment experiments further suggested that the expression of FvSAUR11 and FvSAUR19 is sensitive to the changes in auxin levels, indicating their potential involvement in auxin signal transduction during strawberry fruit development. Subcellular localization results showed that both proteins are located in the nucleus. The results of this study systematically analyzed the sequence structure characteristics, evolutionary history, expression patterns, and potential functions of the strawberry FvSAUR family members, providing important insights for further elucidating the roles of FvSAUR genes in strawberry fruit growth and development.

Non-alcoholic fatty liver disease (NAFLD) affects about 25% of adults worldwide. Its advanced form, non-alcoholic steatohepatitis (NASH), is a major cause of liver fibrosis, but there are no non-invasive tests for diagnosing or preventing it. In our study, we analyzed data from multiple sources to find crucial genes linked to NASH fibrosis. We built diagnostic models using 103 machine learning algorithms and validated them with two external datasets. All models performed well, with the best one (RF + Enet[alpha = 0.6]) achieving an average AUC of 0.822. This model used five key genes: LUM, COL1A2, THBS2, COL5A2, and NTS. Our findings show that these genes are important in collagen and extracellular matrix pathways, shedding light on how NASH progresses to liver fibrosis. We also found that certain immune cells, like M1 macrophages, are involved in this process. This study provides a reliable diagnostic tool for assessing fibrosis risk in NASH patients and suggests potential for immunotherapy, laying a foundation for future treatments.

The hand–eye calibration of laser profilers and industrial robots is a critical component of the laser vision system in welding applications. To improve calibration accuracy and efficiency, this study proposes a position-constrained calibration compensation algorithm aimed at optimizing the hand–eye transformation matrix. Initially, the laser profiler is mounted on the robot and used to scan a standard sphere from various poses to obtain the theoretical center coordinates of the sphere, which are then utilized to compute the hand–eye transformation matrix. Subsequently, the positional data of the standard sphere’s surface are collected at different poses using the welding gun tip mounted on the robot, allowing for the fitting of the sphere’s center coordinates as calibration values. Finally, by minimizing the error between the theoretical and calibrated sphere center coordinates, the optimal hand–eye transformation matrix is derived. Experimental results demonstrate that, following error compensation, the average distance error in hand–eye calibration decreased from 4.5731 mm to 0.7069 mm, indicating that the proposed calibration method is both reliable and effective.

Background Chronic diseases pose substantial healthcare burdens globally, notably in aging nations like China. Internet Medical Services (IMS) demonstrate significant potential to mitigate healthcare challenges in chronic disease management through optimized resource allocation and enhanced remote care capabilities. However, persistent adoption disparities and the “high demand–low penetration” paradox highlight persistent barriers stemming from the digital divide. This study aims to investigate factors influencing IMS utilization among chronic disease patients, examining their effects across specific IMS domains and acceptance pathways, thereby offering new insights for optimizing chronic disease management. Methods This study extended the Technology Acceptance Model (TAM) by integrating eHealth literacy and Technology anxiety to evaluate the utilization of IMS among 520 patients with chronic diseases in Jinan, China. IMS was categorized by functional domains (Information Access, Convenience Services, Online Health) and utilization stages (Awareness, Want, Adoption). The dual-method analysis: Awareness-Want-Adoption Gap (AWAG) matrix for service-specific disparity mapping and Structural Equation Modeling (SEM) to quantify perceptual drivers, providing a panoramic perspective to deconstruct the complex utilization. Results Information Access IMS showed the highest acceptance, while Online Health exhibited severe Want-to-Adoption collapse (71.43% gap). Affluent patients demonstrated paradoxical rejection of Online Health despite high Awareness. SEM confirmed Perceived Usefulness (β = 0.338–0.423, P  < 0.001) and eHealth literacy (β = 0.184–0.395, P  < 0.001) are significant and direct drivers of IMS utilization, with stage-specificity observed across the utilization process. Matrix analysis identified critical barriers for vulnerable subgroups: rural residents, elders (≥ 70 years), and low-education (≤ 9 years) patients. Conclusions IMS adoption is governed by multidimensional determinants beyond access, including cognitive, socio-economic, and other factors. Counterintuitive patterns (e.g., affluent patients’ rejection of Online Health) necessitate tiered interventions, such as eHealth literacy programs for vulnerable groups, service standardization to mitigate distrust, and regulatory frameworks to ensure data security. This study’s dual-method framework (matrix analysis and SEM) critically delineated barrier typologies through staged decomposition, establishing an evidence-based scaffold for optimizing digital health equity.

Background Endoscopic retrograde cholangiopancreatography (ERCP) has been widely used in the diagnosis and treatment of biliary and pancreatic diseases, and its success rate and therapeutic effect are considerable, and its use in patients with gastrointestinal tract reconstruction is also increasing. The anatomical structure of the digestive tract has been changed in these patients, which makes the use of endoscopic retrograde cholangiopancreatography technically more challenging. The aim of this study was to investigate the efficacy of transendoscopic retrograde cholangiopancreatography in patients after gastrointestinal reconstruction and its risk factors for postoperative complications. Methods A retrospective analysis was conducted on clinical data of 522 patients who underwent ERCP for diagnostic and therapeutic purposes after gastrointestinal reconstruction surgery at Zhongnan Hospital, Wuhan University, from January 2017 to December 2023. Univariate analysis, multicollinearity testing, and binary logistic regression were performed to explore the factors associated with ERCP efficacy and complications. Results A total of 522 patients were included in the study. The success rate of intubation was 96.93% (506/522), the success rate of cannulation was 91.09% (466/506), and the therapeutic success rate was 95.28% (444/466). Multivariate logistic regression analysis of failed intubation showed that independent risk factors included total gastrectomy ( P  = 0.000, OR = 7.114, 95% CI 2.454–20.622), gastrojejunostomy ( P  = 0.000, OR = 46.881, 95% CI 10.250–214.423), and the use of a forward-viewing endoscope ( P  = 0.010, OR = 2.322, 95% CI 1.228–4.389). Post-ERCP complications included hyperamylasemia in 67 cases (12.84%), acute pancreatitis in 13 cases (2.49%), acute cholangitis in 3 cases (0.57%), bleeding in 3 cases (0.57%), and perforation in 2 cases (0.38%). Univariate analysis of the complications showed that a history of cholecystectomy ( P  = 0.042, OR = 1.800, 95% CI 1.015–3.193) was an independent risk factor for hyperamylasemia; difficult cannulation ( P  = 0.000, OR = 47.619, 95% CI 13.317–170.275) was an independent risk factor for acute pancreatitis; and a history of pancreatitis ( P  = 0.040, OR = 42.75, 95% CI 3.399–537.620) was an independent risk factor for bleeding. Conclusions ERCP performed in patients after gastrointestinal reconstruction at our hospital achieved a high success rate. Total gastrectomy, gastrojejunostomy, and the use of a forward-viewing endoscope were independent risk factors for failed intubation. A history of cholecystectomy, recurrent cannulation, and a history of pancreatitis were identified as independent risk factors for hyperamylasemia, acute pancreatitis, and bleeding, respectively.

Self-powered photodetectors are highly demanded in applications but often suffer from limited spectral absorption, slow response speed, and high dark currents. Two-dimensional van der Waals heterostructures have emerged as promising candidates owing to their designable structures and excellent performance. Herein, we construct a MoTe2/Bi2Te3 heterostructure and investigate its photoelectric properties. At zero bias, it exhibits a broad photovoltaic response ranging from 405 to 1550 nm. Benefiting from the interfacial built-in electric field, it achieves a responsivity of 1.38 A/W and a detectivity of 1.90 × 1012 Jones at 532 nm and retains 174.56 mA/W and 2.4 × 1011 Jones at 1060 nm, together with a low dark current of 1.6 × 10−12 A. Upon a reverse bias of −1 V and 532 nm laser illumination at an intensity of 19.0 W/m2, the responsivity is further boosted to 36.22 A/W, accompanied by rise and decay times of 32 ms and 33 ms, respectively. Taking advantage of the distinct optical switching ratios at zero/non-zero biases, application in optical imaging and bias-controlled signal modulation is realized, highlighting the heterojunction’s potential as a broadband self-powered photodetector.

Background Hepatocellular carcinoma (HCC) presents challenges and opportunities for immunotherapy due to its intricate immune microenvironment. Exhausted CD8 T cells (CD8Tex) are pivotal in this context but are inadequately characterized in HCC. Methods We conducted single-cell analysis on the GSE140228 dataset to identify key genes associated with CD8Tex in HCC. Cell communication analysis elucidated strong interactions of CD8Tex with CD8 T cells, dendritic cells (DCs), and monocytes/macrophages. Results Pearson correlation analysis using the TCGA-LIHC dataset identified CD8Tex-associated long non-coding RNAs (lncRNAs). Utilizing univariate and multivariate Cox regression analyses, along with LASSO regression to prevent overfitting, we developed a prognostic model incorporating 5 lncRNAs. This model exhibited strong prognostic performance, and the derived risk score was validated as an independent predictor of overall survival in HCC patients. Among these lncRNAs, AL158166.1 showed the strongest correlation with CD8⁺ T cell exhaustion and was significantly associated with poor prognosis, highlighting its potential as both a biomarker and therapeutic target in HCC. Conclusion Our study not only elucidates the role of CD8Tex cells in HCC but also proposes a novel molecular classification of the disease. This classification holds promise for guiding clinical immunotherapy and precision treatments tailored to different molecular subtypes of HCC, as identified through drug sensitivity analysis. This work provides a foundational framework for advancing clinical strategies in HCC treatment and the development of targeted therapies.

Satellite thermal infrared remote sensing has received worldwide attention in earthquake-precursors exploration. Meanwhile, it has also encountered great controversy due to the lack of quantitative interpretation of the observations, despite the existing qualitative physical mechanisms being able to greatly help us understand thermal infrared anomalies. Here, we report a potential mechanism to quantitatively analyze co-seismic thermal infrared anomalies based on temperature change caused by stress variation through theoretical, experimental, and field investigations. This paper firstly deduces theoretically the temperature variation during elastic deformation of rock on the basis of the thermodynamic theory. Secondly, three laboratory experiments on rock samples are conducted to verify the theoretical estimates of the temperature changes caused by stress variations using an infrared camera with the spectral range of 8~12 μm. Thirdly, a mechanical model on thrust faults is built to evaluate the co-seismic temperature drop as a result of thrust faulting. The model shows that the co-seismic temperature drop in rocks should be in the order of 0.18 K. This variation in rock temperature may cause a change in heat equivalent to changes in shallow atmospheric temperatures of 3.0–6.0 K, which is in accordance with the temperature anomalies observed by satellite thermal infrared remote sensing. In addition, the temperature change caused by crustal stress variation may involve a large spatial scale, covering the whole focal area, which has characteristics of regional distribution and is conducive to satellite observation. Therefore, a quantitative explanation of the satellite thermal infrared seismic anomaly mechanism can be given via the temperature change caused by crustal stress variation.