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This study investigated the relationship between smartphone addiction and sleep quality among college students, focusing on the parallel mediating roles of perceived stress and health-promoting lifestyle. A cross-sectional survey was conducted in March 2025 among 2,317 students from Xuzhou Medical University using an online questionnaire. Data were collected via questionnaires and analyzed using SPSS 21.0. The study used the Smartphone Addiction Scale-Short Version (SAS-SV), the Pittsburgh Sleep Quality Index (PSQI), the Health-Promoting Lifestyle Profile (HPLP-II), and Perceived Stress Scale (PSS). Statistical methods included normality tests, descriptive statistics, and mediation analysis. A prevalence rate of 51.9% for sleep disorders was identified among the university student population. A statistically significant positive correlation was observed between smartphone addiction and poor sleep quality (r = 0.259, p < 0.01). Additionally, perceived stress (r = 0.408, p < 0.01) and health-promoting lifestyle (r = -0.182, p < 0.01) were identified as parallel mediators in this relationship. Mediation analysis indicated a significant total effect of smartphone addiction (SAS-SV) on sleep quality (PSQI) (path c = 0.0863, 95% confidence interval (CI) = 0.0730, 0.0995). Furthermore, a significant direct effect of SAS-SV on PSQI was noted (path c' = 0.0325, 95% CI = 0.0188, 0.0461). The health-promoting lifestyle (HPLP) (path a1b1 = 0.0128, 95% CI = 0.0086, 0.0176) and perceived stress (PSS) (path a2b2 = 0.0410, 95% CI = 0.0332, 0.0491) were found to partially mediate the relationship between SAS-SV and PSQI, accounting for 14.83% and 47.51% of the total effect, respectively. These findings highlight the dual mediating roles of perceived stress and health-promoting lifestyle in the association between smartphone addiction and sleep quality. Smartphone addiction negatively affects sleep quality, both directly and indirectly through increased perceived stress and reduced engagement in a health-promoting lifestyle. Interventions targeting stress management and healthy behaviors are recommended to mitigate these effects.

Rural tourism development has been an essential driving force behind China’s promotion of integrated urban–rural development, sustainable rural development and rural revitalization in the new era. This study included 1470 villages on the national list of beautiful leisure villages in China (BLVCs) from 2010 to 2021. We explored the distribution characteristics and influencing factors based on mathematical statistics and spatial analysis in ArcGIS to provide a theoretical reference for promoting the development of leisure village agriculture and rural tourism. The results show that the distribution of BLVC presents a clustered state, showing a distribution pattern of a dual core, seven centers and multiple scattered points. BLVCs are mainly distributed in areas with flat terrain and sufficient water resources, which are conducive to agricultural production and life. Having convenient transportation and rich tourism resources aids the promotion of rural tourism development. The resulting gap in regional development is balanced to some extent by government support. The research results provide a reference value for future rural spatial optimization and sustainable development. This paper summarizes the law of rural development and clarifies the factors influencing the development of rural tourism, and it provides the Chinese experience as a model for a rural renaissance empowered by rural tourism.

Radiotherapy is the standard adjuvant treatment for glioma patients; however, the efficacy is limited by radioresistance. The function of Interleukin-1 receptor associated kinase 1 (IRAK1) in tumorigenesis and radioresistance remains to be elucidated. IRAK1 expression and its correlation with prognosis were analyzed in glioma tissues. We found that glioma patients with overexpressed IRAK1 show a poor prognosis. Notably, ionizing radiation (IR) remarkably induces IRAK1 expression, which was decreased by STING antagonist H-151 treatment. JASPAR prediction, ChIP assays, and dual luciferase reporter assays indicated that transcription factor FOXA2, suppressed by STING inhibition, directly binds to the IRAK1 promoter region and activates its transcription. IRAK1 knockdown inhibits malignancy and enhances the radiosensitivity of glioma in vitro and in vivo. To explore the potential IRAK1 interacting targets mediating the radioresistance of glioma cells, IP/Co-IP, LC-MS/MS, GST pull-down, and ubiquitination analyses were conducted. Mechanistically, IRAK1 bound to PRDX1, a major member of antioxidant enzymes, and further prevents ubiquitination and degradation of PRDX1 mediated by E3 ubiquitin ligase HECTD3; Both the DOC and HECT domains of HECTD3 directly interacted with PRDX1 protein. Overexpression of PRDX1 reverses the radiotherapy sensitization effect of IRAK1 depletion by diminishing autophagic cell death. These results suggest the IRAK1-PRDX1 axis provides a potential therapeutic target for glioma patients.

The environmental quality of conference and exhibition places in small- and medium-sized cities plays a crucial role in attracting exhibitors, fostering the growth of the conference and exhibition industry and enhancing the market competitiveness of these places. However, past decision makers have often adopted planning models from large cities, neglecting the interaction between conference and exhibition places in smaller cities and local lifestyles as well as urban environments. From an “environment-behavior” perspective, this study reveals the unique interaction mechanisms between exhibitors and the built environment within such venues. Moving beyond the limitations of traditional research that focused solely on physical indicators, we place particular emphasis on exhibitors’ behavioral adaptations and their overall exhibition experience in the convention environment. To address this gap, this study employs a mixed-method approach that integrates field surveys, interviews, and questionnaires to systematically collect data from 10 representative cases. First, a preliminary study was conducted to establish an evaluation index system for place environmental quality. Through regression analysis, six key indicators—such as promotional atmosphere, site accessibility, and surrounding urban development conditions—were identified as significant factors influencing place quality. Second, subjective evaluations were conducted based on users’ actual experiences and experts’ professional insights, leading to the development of an importance–performance analysis model to assess value expectations and place environmental performance. The results indicated that users had high expectations for elements such as parking availability, transportation facilities, and the surrounding commercial atmosphere. In contrast, experts emphasized the significance of proximity to urban transportation hubs, site accessibility, and the spatial orientation of public spaces in determining environmental quality. Moreover, differences in evaluations among experts from various fields revealed notable variations in focus and priority considerations. Finally, based on a statistical analysis of the survey results, this study proposes three design recommendations—“adaptation, attraction, and quality enhancement”—to optimize the environmental quality of conference and exhibition places in small- and medium-sized cities, offering both theoretical and practical guidance for future planning, design, and evaluation.

With industrial upgrading and increasingly diversified urban functions in small and medium-sized cities in China, the demand for convention and exhibition buildings has been steadily rising. However, current research mainly focuses on the planning and operation of such buildings in large cities, with a lack of systematic and targeted studies on small and medium-sized cities that have relatively limited resources and varied development orientations. According to data collection and field surveys of convention and exhibition buildings in 148 small and medium-sized cities nationwide, this paper constructs a case database and conducts in-depth research on building types and factor guarantee mechanisms. This study first employs cluster analysis to classify 73 typical cases, incorporating comparative analysis from multiple dimensions such as the city’s economic development level, characteristics of the convention and exhibition industry, primary functions, operational focus, service targets, and planning layout, based on literature review and expert opinions. It then proposes four convention and exhibition building positioning models—market type, production-based type, enclave type and comprehensive type—and analyzes the characteristics of their typical cases. Afterward, through surveys, literature reviews, and expert interviews, this study identifies relevant indicators—such as resource factors and development conditions—and applies the importance index method to select 19 core indicators. These are used to establish a factor guarantee indicator system comprising two levels: “city-related factors” and “regional-related factors”. Subsequently, by analyzing the development strategies and core support factors of different building types using the priority diagram method, this study clarifies the resource demands and development paths for each model. The results indicate that the positioning strategy for convention and exhibition buildings in small and medium-sized cities should align with local industrial foundations and stages of urban development, fostering the formation of differentiated and sustainable development models. This research offers theoretical support and practical guidance for the scientific planning and efficient construction of convention and exhibition buildings in small and medium-sized cities, contributing to improved functionality, regional economic growth, and optimized urban spatial structure.

The observations from satellite microwave-sounding instruments have been widely used in weather and climate studies. Since the data resolution varies with frequency and satellite viewing angle, it is normally required that the measurements at each frequency be resampled to obtain a uniform resolution prior to various applications. In this study, the ATOVS and AVHRR pre-processing package (AAPP) Fourier transform algorithm is modified for ATMS data and the results are compared with those derived from Backus–Gilbert inversion (BGI) and the original AAPP. From the simulated and observed ATMS data, we demonstrated the new algorithm has better results in terms of imaging quality and noise suppression, compared with BGI and AAPP. In general, our modified AAPP algorithm reduces the error by at least about 0.5 K in ATMS channels 2 and 6 and at all the viewing angles.

Objective The aim of this research was to develop a nomogram that integrates ultrasomics features and clinical factors to non-invasively predict preoperative lymph-vascular space invasion (LVSI) in patients with cervical cancer (CC). Methods A total of 217 patients from three hospitals were retrospectively analyzed (the training set, n  = 122; the test set, n  = 53; and the validation set, n  = 42). Tumor segmentation of the ultrasound(US) images was performed manually, then extracting a multitude of ultrasomics features from the segmented regions of interest (ROIs). After identifying the most significant ultrasomics features via a series of analyses and algorithms, five machine learning (ML) classification algorithms were utilized to develop and compare the ultrasomics models. Besides, we obtained clinically independent predictors for the diagnosis of LVSI and established the clinical model by univariate and multivariate analyses. Next, we compared the predictive capabilities of the clinical, ultrasomics, and combined models in forecasting LVSI in CC. Results Artificial neural networks (ANN) emerged as the top performer among the five ML classification algorithms. International Federation of Gynecology and Obstetrics (FIGO) staging for CC served as the independent predictor of LVSI. The nomogram, incorporating ultrasomics features and FIGO staging, demonstrated the highest diagnostic performance, with area under the curve (AUC) (95% CI) values of 0.911 (0.852–0.957), 0.835 (0.716–0.934), and 0.832 (0.685–0.939) in the training, test, and validation sets, respectively. Furthermore, the nomogram’s calibration curve exhibited excellent agreement between the predicted and actual LVSI outcomes in three datesets. Conclusion The nomogram based on ultrasomics features and FIGO staging is a potential method for non-invasive prediction LVSI of CC.

As precision agriculture places higher demands on real-time field weed detection and recognition accuracy, this paper proposes a multi-scale information-enhanced weed detection algorithm, MIE-YOLO (Multi-scale Information Enhanced), for precision agriculture. Based on the popular YOLO12 (You Only Look Once 12) model, MIE-YOLO combines edge-aware multi-scale fusion with additive gated blocks and two-stage self-distillation to boost small-object and boundary detection while staying lightweight. First, the MS-EIS (Multi-Scale-Edge Information Select) architecture is designed to effectively aggregate and select edge and texture information at different scales to enhance fine-grained feature representation. Next, the Add-CGLU (Additive-Convolutional Gated Linear Unit) pyramid network is proposed, which enhances the representational power and information transfer efficiency of multi-scale features through additive fusion and gating mechanisms. Finally, the DEC (Detail-Enhanced Convolution) detection head is introduced to enhance detail and refine the localization of small objects and fuzzy boundaries. To further improve the model’s detection accuracy and generalization performance, the DS (Double Self-Knowledge Distillation) strategy is defined to perform double self-knowledge distillation within the entire network. Experimental results on the custom Weed dataset, which contains 9257 images of eight weed categories, show that MIE-YOLO improves the F1 score by 1.9% and the mAP by 2.0%. Furthermore, it reduces computational parameters by 29.9%, FLOPs by 6.9%, and model size by 17.0%, achieving a runtime speed of 66.2 FPS. MIE-YOLO improves weed detection performance while maintaining a certain level of inference efficiency, providing an effective technical path and engineering implementation reference for intelligent field inspection and precise weed control in precision agriculture. The source code is available on GitHub.

Diffuse lower-grade gliomas (LGG) represent the highly heterogeneous and infiltrative neoplasms in the central nervous system (CNS). Replication factor C 2 (RFC2) is a subunit of the RFC complex that modulates DNA replication and repair. However, the prognosis value of RFC2 and its association with the immune signature of tumor microenvironment (TME) in LGG remains unknown. Based on Oncomine, TCGA, GTEx, TIMER, GEPIA, and HPA databases, we evaluated RFC2 expression levels and its clinical prognostic value in LGG and other cancers. Then we analyzed the correlations between RFC2 expression and tumor mutation burden (TMB), tumor microsatellite instability (MSI), and mismatch repair (MMR) genes across cancers. And CIBERSORT and ESTIMATE algorithms were conducted to estimate the association of RFC2 with immune cell infiltration of LGG. Additionally, we performed the functional enrichment analyses of RFC2 in LGG. Then functional experiments were employed to further validate the oncogenic role of RFC2 in LGG. Our results showed that RFC2 was widely highly expressed in most types of cancer. And its expression was closely related to the clinicopathological features and prognosis in LGG and other cancer types. RFC2 levels were also correlated with TMB and MSI across various cancers. Furthermore, RFC2 was positively associated with the infiltration levels of immune cells and immune checkpoint genes in LGG. Additionally, in vitro experiments revealed that RFC2 played an oncogenic role in LGG progression. In conclusion, our findings revealed that RFC2 could serve as a reliable biomarker to predict the prognosis and immune signature for LGG.

Nicotinamide mononucleotide (NMN), a crucial intermediate in NAD + synthesis, can rapidly transform into NAD + within the body after ingestion. NMN plays a pivotal role in several important biological processes, including energy metabolism, cellular aging, circadian rhythm regulation, DNA repair, chromatin remodeling, immunity, and inflammation. NMN has emerged as a key focus of research in the fields of biomedicine, health care, and food science. Recent years have witnessed extensive preclinical studies on NMN, offering valuable insights into the pathogenesis of age- and aging-related diseases. Given the sustained global research interest in NMN and the substantial market expectations for the future, here, we comprehensively review the milestones in research on NMN biotherapy over the past 10 years. Additionally, we highlight the current research on NMN in the field of digestive system diseases, identifying existing problems and challenges in the field of NMN research. The overarching aim of this review is to provide references and insights for the further exploration of NMN within the spectrum of digestive system diseases.