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The digital economy has emerged as a new trend in economic development and has profoundly influenced the process of achieving common prosperity. However, current research on the correlation between the digital economy and common prosperity from the perspective of a river basin still needs to be strengthened. Based on this, the present study first theoretically elaborates the conceptual meanings of “digital economy” and “common prosperity”, as well as the mechanism by which the digital economy empowers common prosperity. Subsequently, a scientifically-constructed performance evaluation index system for the digital economy and common prosperity is established. Considering the Yellow River Basin as an empirical case study area, this study investigates the mechanism and spatial spillover effects of the digital economy in empowering common prosperity from 2005 to 2020. The research findings reveal that: (1) The Yellow River Basin exhibits a basin characteristic with downstream > midstream > upstream areas regarding the level of common prosperity and digital economy. It indicates that a distinct spatial correlation exists between the two factors. However, the ongoing decrease in both high-level and very high-level areas reflects the lengthy and challenging journey of enhancing the quality and efficiency of the digital economy in empowering common prosperity. (2) The digital economy not only directly impacts common prosperity, but also fosters its development through spatial spillover effects. Among the control factors, informatization and housing levels have a major stimulating effect. (3) There exists a clear regional heterogeneity in how the digital economy affects common prosperity in the Yellow River Basin. Specifically, common prosperity of downstream cities is significantly impacted by the digital economy. The spatial spillover effects of the digital economy on common prosperity exhibit a pronounced “neighborhood as a moat” characteristic. (4) The digital economy facilitates the achievement of shared prosperity through the implementation of mechanisms centered on sharing, affluence, and sustainability. These research findings illuminate the empowering mechanisms and spatial spillover pathways of the digital economy in promoting shared prosperity, aligning with national strategies for ecological conservation and high-quality development in the Yellow River Basin.

Calcium Oxalate Nephrolithiasis is a globally prevalent urological disorder, with its pathogenesis involving multiple mechanisms such as inflammatory responses, oxidative stress, crystal-cell interactions, macrophage polarization, and fibrosis. In recent years, the multidimensional regulatory roles of interleukins (ILs) and chemokines in stone formation have garnered increasing attention. Pro-inflammatory interleukins, such as IL-1β, may promote crystal deposition, oxidative stress, and renal tubular epithelial cell injury by activating signaling pathways including NLRP3 inflammasome, NF-κB, and MAPK. In contrast, anti-inflammatory interleukins, by stimulating M2 macrophage polarization and suppressing crystal adhesion and oxidative damage, exhibit nephroprotective effects. Notably, IL-6 demonstrates unique bidirectional regulatory properties. Chemokines play critical roles in recruiting immune cells, amplifying inflammatory responses, modulating crystal-cell interactions, and sustaining the fibrosis-stone vicious cycle. The CXCL12/CXCR4 axis has emerged as a potential hub in regulating crystal autophagy and fibrotic progression. Additionally, miR-124-3p overexpression inhibits pro-inflammatory factor expression and promotes M2 macrophage polarization, while the IL-6/MCP-1 axis may reverse this suppression via a negative feedback network. This review integrates the multidimensional regulatory mechanisms of interleukins and chemokines in Calcium Oxalate Nephrolithiasis and proposes three novel hypotheses: the dynamic regulatory model of IL-6, the MCP-1-mediated fibrosis-stone vicious cycle, and the IL-6/MCP-1/miR-124-3p negative feedback loop.

Metabolites from intestinal microbes modulate the mucosal immune system by regulating the polarization and expansion of T cells. Whether the microbial metabolites influence macrophage polarization, however, is poorly understood. Here, we show that the large bowel microbial fermentation product, butyrate, facilitates M2 macrophage polarization, in vitro and in vivo . The supernatant from butyrate-treated M2 macrophage increased the migration and enhanced the wound closure rate of MLE-12 cells. Butyrate attenuated intestinal inflammation in mice with dextran sulfate sodium (DSS)-induced colitis, with a significant increase in colonic expression of the M2 macrophage-associated protein, Arg1. M2 macrophage treated with butyrate, had increased activation of the H3K9/STAT6 signaling pathway, suggesting a mechanism for butyrate facilitated M2 macrophage polarization. Collectively, our study indicated that commensal microbe-derived butyrate is a novel activator of STAT6-mediated transcription through H3K9 acetylation driving M2 macrophage polarization and delineated new insights into the immune interplay underlying inflammatory bowel disease.

Intracerebral hemorrhage (ICH) is a highly harmful neurological disorder with high rates of mortality, disability, and recurrence. However, effective therapies are not currently available. Secondary immune injury and cell death are the leading causes of brain injury and a poor prognosis. Pyroptosis is a recently discovered form of programmed cell death that differs from apoptosis and necrosis and is mediated by gasdermin proteins. Pyroptosis is caused by multiple pathways that eventually form pores in the cell membrane, facilitating the release of inflammatory substances and causing the cell to rupture and die. Pyroptosis occurs in neurons, glial cells, and endothelial cells after ICH. Furthermore, pyroptosis causes cell death and releases inflammatory factors such as interleukin (IL)-1β and IL-18, leading to a secondary immune-inflammatory response and further brain damage. The NOD-like receptor protein 3 (NLRP3)/caspase-1/gasdermin D (GSDMD) pathway plays the most critical role in pyroptosis after ICH. Pyroptosis can be inhibited by directly targeting NLRP3 or its upstream molecules, or directly interfering with caspase-1 expression and GSDMD formation, thus significantly improving the prognosis of ICH. The present review discusses key pathological pathways and regulatory mechanisms of pyroptosis after ICH and suggests possible intervention strategies to mitigate pyroptosis and brain dysfunction after ICH.

Background Determining the grade and molecular marker status of intramedullary gliomas is important for assessing treatment outcomes and prognosis. Invasive biopsy for pathology usually carries a high risk of tissue damage, especially to the spinal cord, and there are currently no non-invasive strategies to identify the pathological type of intramedullary gliomas. Therefore, this study aimed to develop a non-invasive machine learning model to assist doctors in identifying the intramedullary glioma grade and mutation status of molecular markers. Methods A total of 461 patients from two institutions were included, and their sagittal (SAG) and transverse (TRA) T2-weighted magnetic resonance imaging scans and clinical data were acquired preoperatively. We employed a transformer-based deep learning model to automatically segment lesions in the SAG and TRA phases and extract their radiomics features. Different feature representations were fed into the proposed neural networks and compared with those of other mainstream models. Results The dice similarity coefficients of the Swin transformer in the SAG and TRA phases were 0.8697 and 0.8738, respectively. The results demonstrated that the best performance was obtained in our proposed neural networks based on multimodal fusion (SAG-TRA-clinical) features. In the external validation cohort, the areas under the receiver operating characteristic curve for graded (WHO I–II or WHO III–IV), alpha thalassemia/mental retardation syndrome X-linked ( ATRX ) status, and tumor protein p53 ( P53 ) status prediction tasks were 0.8431, 0.7622, and 0.7954, respectively. Conclusions This study reports a novel machine learning strategy that, for the first time, is based on multimodal features to predict the ATRX and P53 mutation status and grades of intramedullary gliomas. The generalized application of these models could non-invasively provide more tumor-specific pathological information for determining the treatment and prognosis of intramedullary gliomas.

Accumulating evidence suggests that long noncoding RNA (lncRNA) functions as a critical regulator in cancer biology. Here, we characterized the role of lncRNA PCED1B antisense RNA 1 (PCED1B-AS1) in glioblastoma (GBM). PCED1B-AS1 was notably upregulated in GBM tissues and cell lines and closely associated with larger tumor size and higher grade. Patients with high PCED1B-AS1 had shorter survival time than those with low PCED1B-AS1. Functional experiments showed that depletion of PCED1B-AS1 significantly inhibited, while overexpression of PCED1B-AS1 promoted cell proliferation, glucose uptake, and lactate release. Mechanistically, PCED1B-AS1 was able to directly bind to the 5′-UTR of HIF-1α mRNA and potentiate HIF-1α translation, leading to increased HIF-1α protein level, thereby promoting the Warburg effect and tumorigenesis. Importantly, PCED1B-AS1 lost the carcinogenic properties in the absence of HIF-1α. In addition, we also confirmed the existence of the PCED1B-AS1/HIF-1α regulatory axis in vivo. Taken together, our findings demonstrate that PCED1B-AS1 is a novel oncogenic lncRNA in GBM and functions in a HIF-1α-dependent manner, which provides a promising prognostic biomarker and druggable target for GBM.

Meningiomas are among the most common intracranial tumors, and challenges still remain in terms of tumor classification, treatment, and management. With the popularization of artificial intelligence technology, radiomics has been further developed and more extensively applied in the study of meningiomas. This objective and quantitative technique has played an important role in the identification, classification, grading, pathology, treatment, and prognosis of meningiomas, although new problems have also emerged. This review examines the application of magnetic resonance imaging (MRI) techniques in meningioma research. A database search was conducted for articles published between November 2017 and April 2025, with a total of 87 studies included after screening. These studies were summarized in detail, and the risk of bias and the certainty of the evidence were assessed using the Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2) and radiomics quality scores (RQS). All the studies were retrospective, with most being single-center studies. Contrast-enhanced T1-weighted imaging (T1C) and T2-weighted imaging (T2WI) are the most commonly used MRI sequences. Current research focuses on five topics, namely, differentiation, grade and subtypes, molecular pathology, biological behavior, treatment, and complications, with 14, 32, 14, 12, and 19 studies addressing these topics (some of which are multiple topics). Combined imaging features with clinical or pathological features often outperform traditional clinical models. Most studies show a low to moderate risk of bias. Large, prospective, multicenter studies are needed to validate the performance of radiomic models in diverse patient populations before their clinical implementation can be considered.

Nogo-66 can inhibit neurite outgrowth, while its regulation mechanisms have not been fully elucidated. Recent studies prove that lncRNAs are involved in neurite outgrowth. This study was aimed to investigate whether lncRNA FTX was involved in Nogo-66-induced inhibition of neurite outgrowth and explore the potential mechanism. The expression of relative genes was detected by qRT-PCR and western blot. The function of FTX was determined by overexpression and knockdown techniques. The interaction between FTX and PDK1 was evaluated by RIP and RNA pull-down assays. FTX expression was downregulated by Nogo-66 in PC12 cells. Nogo-66-induced inhibition of neurite outgrowth was relieved by FTX overexpression. FTX bound to PDK1 protein to disturb the interaction between PDK1 and E3 ubiquitin ligase RNF126, thereby blocked the ubiquitination degradation of PDK1 and elevated PDK1 protein level. Mechanically, FTX involved in the Nogo-66-induced inhibition of neurite outgrowth through the PDK1/PKB/GSK-3β pathway. In SCI rats, FTX knockdown inhibited neurite outgrowth induced by the receptor antagonist of Nogo-66. The present results suggested that FTX took part in Nogo-66-inhibited neurite outgrowth, and FTX exerted its function through regulating PDK1/PKB/GSK-3β pathway.

Green development is an important issue of sustainable development in China. Due to the relatively backward economy and the fragile ecological environment, restricted development zones need to embrace green development. Taking 38 counties in Jilin Province as the empirical research objects, and based on cross-sectional data for each county in 2005, 2010, and 2015, we accurately depicted the spatiotemporal evolutionary characteristics of green development efficiency (GDE) in restricted development zones of Jilin Province using the slacks-based measure-data envelope analysis (SBM-DEA) model. Moreover, the factors that influence GDE were further analyzed using the Tobit model. We found that: first, GDE showed a V-shaped trend in restricted development zones of Jilin Province. The differences in GDE in the eastern, central, and western Jilin Province increased gradually. Second, 76% of counties in the restricted development zones had high or higher efficiencies. The resource-based cities were the main areas with low or lower GDE. Third, the economic development level was the core factor affecting GDE. Urbanization level had a significant negative effect on GDE in the restricted development zones. The effect of technological innovation level on GDE fluctuated, and we found that a ‘backward mechanism’ of technological innovation was beginning to form. Industrial structure and environmental governance had no significant effects on GDE.