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Aims There remains clinical uncertainty concerning the relationship between systemic inflammation and subsequent abdominal aortic aneurysm (AAA) risk. To investigate the association between chronic systematic inflammation markers (C-reactive protein (CRP), peripheral immune cell counts, and their derived ratios) and risk of AAA incidence, and identify potential effect modifiers. Methods We included 271,068 individuals from the UK Biobank, who were free of aortic aneurysm and other conditions impacting their inflammatory states at baseline. Cox proportional-hazards model was used to analyze associations between inflammatory biomarkers and AAA, adjusting for AAA polygenetic risk score (PRS) and major risk factors. Restricted cubic splines were plotted to visualize non-linear relationship. Subgroup analyses by age, sex, hypertension, smoking and PRS were performed to identify any interaction. Results Over a median follow-up of 13·9 years, 629 incident AAAs were recorded. For each 1-SD increase in baseline CRP, lymphocyte, monocyte, and neutrophil counts, the risk of AAA increased by 46%, 17%, 27% and 27%, respectively (all p  < 0·001). The cubic splines showed the CRP-AAA association to be monotonic. The highest tertile of PRS was associated with an 80% increased AAA risk compared with the lowest tertile. The association between CRP and AAA was significant and comparable across PRS tertile groups. Sex and smoking status modified the CRP-AAA association, with the strongest association observed in males and current smokers. Conclusions Our study found a significant association between chronic systemic inflammation and risk of AAA incidence. CRP compliments PRS and other AAA risk factors in better identifying high-risk populations. Lay summary Current indexes for identifying patients to screen for AAA are family history, age, sex and smoking. This study revealed that a healthy public with a high level of CRP and one of the above traditional high-risk factors of AAA (high genetic risk, ≥ 65 years old, male, or current smoker) had a high risk of incident AAA and is recommended to screen for AAA.

The intricate roles of immune cells and inflammatory factors in cancer, particularly their association with the risk of bladder cancer, are not well understood. This study aimed to clarify potential causal relationships between these elements and the development of bladder cancer using genome-wide association study (GWAS) summary statistics for 731 immune cell phenotypes and 91 circulating inflammatory factors (cases=2,053; controls=287,137). The primary analytical approach was Inverse Variance Weighting (IVW), supplemented by MR-Egger regression, weighted median, and weighted mode analyses. Sensitivity analyses included Cochran Q test, MR-Egger intercept test, and Leave-one-out test. The findings indicated that monocytes are positively correlated with an increased risk of bladder cancer. On the contrary, double-negative (DN) T cells, HLA DR+CD8br, and CD28 on CD28+CD45RA+CD8br T cells exhibited an inverse correlation, suggesting a possible protective effect. Furthermore, inflammatory factors IL-20, IL-22RA1, and Eotaxin were significantly associated with an increased risk of bladder cancer. These results suggest that certain immune cell phenotypes and inflammatory factors may play a role in the development of bladder cancer and could serve as potential biomarkers for assessing tumor risk. The findings also offer new insights into the pathogenesis of bladder cancer, indicating a need for further investigation.

N6-methyladenosine (m6A) is one of the most prevalent, abundant, and internal transcriptional modification and plays essential roles in diverse cellular and physiological processes. Low fluid shear stress (FSS) is a key pathological factor for many cardiovascular diseases, which directly forces on the endothelial cells of vessel walls. So far, the alterations and functions of m6A modifications in vascular endothelial cells at the low FSS are still unknown. Herein, we performed the transcriptome-wide m6A modification profiling of HUVECs at different FSS. We found that the m6A modifications were altered earlier and more sensitive than mRNA expressions in response to FSS. The low FSS increased the m6A modifications at CDS region but decreased the m6A modifications at 3′ UTR region and regulated both the mRNA expressions and m6A modifications of the m6A regulators, such as the RBM15 and EIF3A. Functional annotations enriched by the hypermethylated and hypomethylated genes at low FSS revealed that the m6A modifications were clustered in the aging-related signaling pathways of mTOR, PI3K-AKT, insulin, and ERRB and in the oxidative stress-related transcriptional factors, such as HIF1A, NFAT5, and NFE2L2. Our study provided a pilot view of m6A modifications in vascular endothelial cells at low FSS and revealed that the m6A modifications driven by low FSS mediated the cellular responses to oxidative stress and cell aging, which suggested that the m6A modifications could be the potential targets for inhibiting vascular aging at pathological low FSS.

Hydrogel nanofibers provide a regeneration-permissive environment conducive to the regrowth of numerous nerve fibers, thereby enhancing regenerative capacity in cases of peripheral nerve injury and spinal cord injury. However, developing hydrogel nanofiber-based nerve guidance conduits (NGCs) with tailored drug release profiles to synergistically promote angiogenesis and axonal regeneration remains a significant challenge. In this study, novel polydopamine (PDA)-modified gelatin methacryloyl (GelMA) hydrogel nanofibers are developed as an efficient drug delivery platform for sustained release of Secreted Frizzled-Related Protein-2 (SFRP2). This platform aims to promote neurite outgrowth, facilitate nerve function recovery, and enhance angiogenesis through Wnt signaling pathways. Results indicate that PDA coating significantly improves the hydrophilicity and mechanical properties of GelMA hydrogel nanofibers, which were fabricated using a combination of electrospinning and photo-crosslinking technology. This modification enables SFRP2 loading for sustained release through π-π stacking interactions and hydrogen bonding. In vitro experiments demonstrate that SFRP2-loaded hydrogel nanofibers effectively enhance the adhesion, proliferation, viability, and migration of Mouse Schwann Cells (MSCs), while also promoting tube formation and ameliorating the inflammatory microenvironment of Human Umbilical Vein Endothelial Cells (HUVECs). Furthermore, the SFRP2-loaded hydrogel nanofibers are confirmed to exert their functions for angiogenesis and peripheral nerve regeneration via the calcium-dependent calcineurin/NFATc3 signaling pathway. Finally, the hydrogel nanofiber-based NGCs are applied in a mouse model of peripheral nerve injury, and results demonstrate that the SFRP2 ~ PDA@GelMA conduit significantly enhances angiogenesis, promotes peripheral nerve repair, and facilitates target muscle restoration and functional recovery, thus presents a promising therapeutic strategy for patients with peripheral nerve injuries. We developed novel polydopamine (PDA)-modified gelatin methacryloyl (GelMA) hydrogel nanofibers for sustained Secreted Frizzled-Related Protein 2 (SFRP2) release to promote peripheral nerve regeneration and angiogenesis synchronously. In vitro experiments demonstrated that these nanofibers significantly enhanced Schwann cell migration and endothelial cell tube formation. In a mouse model of peripheral nerve injury, the SFRP2-loaded nanofibers effectively promoted angiogenesis, nerve repair, and target muscle restoration via the calcineurin/NFATc3 signaling pathway. These findings suggest a promising therapeutic strategy for peripheral nerve injuries.

Tower crane structural failures remain a major safety concern on construction sites. To improve accident prevention, this study proposes an intelligent framework that combines an improved Transformer model with a Directional Interest Score (DIS) Apriori algorithm and complex-network analysis. A corpus of 535 tower crane accident reports (2002–2024) was compiled and annotated with causal and accident entities according to system–safety theory. Segment embeddings were introduced to the Transformer to reinforce boundary detection, enabling accurate extraction of causative factors and relation triples. The DIS-Apriori algorithm was then used to mine both positive and negative association rules while aggressively pruning irrelevant item sets. Eventually, causative factors were mapped into a weighted, directed complex network where edge weights reflect the absolute frequency difference between positive and negative rules, and edge directions correspond to their signs. Experiments show that the Transformer achieves higher precision and recall than baseline models, and DIS-Apriori substantially reduces unnecessary item-set complexity while preserving critical rules. Network analysis revealed five critical causal links and a closed-loop causal link that warrant priority intervention. The proposed method delivers a data-driven, explainable tool for pinpointing key risk sources and designing targeted mitigation strategies, offering practical value for intelligent safety management of tower cranes.

Abdominal aortic aneurysm (AAA) is a common and potentially life‐threatening condition. Chronic aortic inflammation is closely associated with the pathogenesis of AAA. Nerve injury‐induced protein 1 (NINJ1) is increasingly acknowledged as a significant regulator of the inflammatory process. However, the precise involvement of NINJ1 in AAA formation remains largely unexplored. The present study finds that the expression level of NINJ1 is elevated, along with the specific expression level in macrophages within human and angiotensin II (Ang II)‐induced murine AAA lesions. Furthermore, Ninj1flox/flox and Ninj1flox/floxLyz2‐Cre mice on an ApoE−/− background are generated, and macrophage NINJ1 deficiency inhibits AAA formation and reduces macrophage infiltration in mice infused with Ang II. Consistently, in vitro suppressing the expression level of NINJ1 in macrophages significantly restricts macrophage adhesion and migration, while attenuating macrophage pro‐inflammatory responses. Bulk RNA‐sequencing and pathway analysis uncover that NINJ1 can modulate macrophage infiltration through the TLR4/NF‐κB/CCR2 signaling pathway. Protein‐protein interaction analysis indicates that NINJ1 can activate TLR4 by competitively binding with ANXA2, an inhibitory interacting protein of TLR4. These findings reveal that NINJ1 can modulate AAA formation by promoting macrophage infiltration and pro‐inflammatory responses, highlighting the potential of NINJ1 as a therapeutic target for AAA. NINJ1 is highly expressed in macrophages within human and murine abdominal aortic aneurysm (AAA) lesions, which enhances macrophage infiltration through the TLR4/NF‐κB/CCR2 signaling pathway, thus facilitating AAA formation. NINJ1 activates TLR4 by competitively binding with ANXA2, an inhibitory interacting protein of TLR4. This study highlights the potential of NINJ1 as a therapeutic target for AAA.

ObjectivesAortic dissection (AD) is a life-threatening condition that requires intensive care and management. This paper explores the role of fluid management in the clinical care of AD patients, which has been unclear despite the substantial existing research that has been conducted on the treatment of AD.DesignA retrospective case-control study using data for AD patients from public databases.SettingTwo public intensive care unit (ICU) databases with hospital courses from the USA, Medical Information Mart for Intensive Care (MIMIC)-IV critical care dataset and the eICU Collaborative Research Database, with data from 2008 to 2019.ParticipantsA total of 751 adult AD patients with detailed fluid management records from two databases were included.InterventionsThe mean 24-hour intake and output were calculated by dividing the total amount of intake and output by the number of days in the ICU, respectively. The mean 24-hour fluid balance was generated by subtracting the output from the intake.Outcome measuresThe relationship between the mean 24-hour fluid management and all-cause in-hospital death was assessed through univariate and multivariable regression analyses.ResultsA positive correlation was found between mean 24-hour fluid intake and in-hospital mortality among AD patients (OR 1.029, 95% CI (1.018, 1.041), p<0.001), whereas a negative correlation was revealed between mean 24-hour fluid output and in-hospital mortality (OR 0.941, 95% CI (0.914, 0.968), p<0.001). A similar result was found for mean 24-hour fluid balance (OR 1.030, 95% CI (1.019, 1.042), p<0.001), and the cut-off was selected to be 5.12 dL (AUC=0.778, OR 3.066, 95% CI (1.634, 5.753), p<0.001).ConclusionsThis study stresses the importance of fluid balance in the clinical care of AD patients and provides new insights for optimising fluid management and monitoring strategies beyond the conventional focus on blood pressure and heart rate management.

Objective Aortic dissection (AD) is a severe emergency with high morbidity and mortality, necessitating strict monitoring and management. This retrospective study aimed to identify prognostic factors and establish predictive models for in-hospital mortality among AD patients in the intensive care unit (ICU). Methods We retrieved ICU admission records of AD patients from the Medical Information Mart for Intensive Care (MIMIC)-IV critical care data set and the eICU Collaborative Research Database. Functional data analysis was further applied to estimate continuous vital sign processes, and variables associated with in-hospital mortality were identified through univariate analyses. Subsequently, we employed multivariable logistic regression and machine learning techniques, including simple decision tree, random forest (RF), and eXtreme Gradient Boosting (XGBoost) to develop prognostic models for in-hospital mortality. Results Given 643 ICU admissions from MIMIC-IV and 501 admissions from eICU, 29 and 28 prognostic factors were identified from each database through univariate analyses, respectively. For prognostic model construction, 507 MIMIC-IV admissions were divided into 406 (80%) for training and 101 (20%) for internal validation, and 87 eICU admissions were included as an external validation group. Of the four models tested, the RF consistently exhibited the best performance among different variable subsets, boasting area under the receiver operating characteristic curves of 0.870 and 0.850. The models highlighted the mean 24-h fluid intake as the most potent prognostic factor. Conclusions The current prognostic models effectively forecasted in-hospital mortality among AD patients, and they pinpointed noteworthy prognostic factors, including initial blood pressure upon ICU admission and mean 24-h fluid intake.

The real world is full of rich and valuable complex networks. Community structure is an important feature in complex networks, which makes possible the discovery of some structure or hidden related information for an in-depth study of complex network structures and functional characteristics. Aimed at community detection in complex networks, this paper proposed a membrane algorithm based on a self-organizing map (SOM) network. Firstly, community detection was transformed as discrete optimization problems by selecting the optimization function. Secondly, three elements of the membrane algorithm, objects, reaction rules, and membrane structure were designed to analyze the properties and characteristics of the community structure. Thirdly, a SOM was employed to determine the number of membranes by learning and mining the structure of the current objects in the decision space, which is beneficial to guiding the local and global search of the proposed algorithm by constructing the neighborhood relationship. Finally, the simulation experiment was carried out on both synthetic benchmark networks and four real-world networks. The experiment proved that the proposed algorithm had higher accuracy, stability, and execution efficiency, compared with the results of other experimental algorithms.

Background: During the COVID-19 pandemic, elective surgery has to undergo longer wait times, including nephrectomy for T1 renal cell carcinoma (RCC). This study aimed to investigate the time-to-surgery (TTS) of Chinese T1 RCC patients and its influencing factors, and to illustrate the impact of TTS on the prognosis of T1 RCC. Methods: We retrospectively enrolled 762 Chinese patients with pathological T1 RCC that underwent nephrectomy. To discover the impact of TTS on survival outcomes, we explored the possible delay intervals by week using the Kaplan-Meier method and Log-rank test. Cox proportional hazard models with inverse probability-treatment weighting (IPTW) were used to assess the association between TTS and disease-free survival (DFS) and overall survival (OS). Results: The median TTS of T1 RCC patients was 15 days. The Charlson comorbidity index, the Preoperative Aspects and Dimensions Used for an Anatomical (PADUA) score, and the maximal tumor diameter on presentation were independent influencing factors for TTS. The cut-off point of TTS was selected as 5 weeks according to the Log-rank analysis. For T1a RCC, patients with TTS > 5 weeks had similar DFS (HR = 2.39; 95% CI, 0.82–6.94; p = 0.109) and OS (HR = 1.28; 95% CI, 0.23–7.16; p = 0.779) compared to patients with TTS ≤ 5 weeks. For T1b RCC, patients with TTS > 5 weeks had shorter DFS (HR = 2.90; 95% CI = 1.46–5.75; p = 0.002) and OS (HR = 2.49, 95% CI = 1.09–5.70; p = 0.030) than patients with TTS ≤ 5 weeks. Conclusions: Prolonged TTS had no impact on the prognosis of T1a RCC while surgery delayed for over 5 weeks may lead to worse survival in T1b RCC.