Liuzhou General Hospital

The transportation sector powered by fossil fuels is a significant contributor to PM2.5 pollution. Systematic evaluation of traffic-related PM2.5 on acute coronary syndrome (ACS) onset is not yet characterized, and the health benefits of reduced traffic-related PM2.5 and evidence-based mitigation strategies are currently absent. We investigated the association of ACS onset with short-term traffic-related PM2.5 exposure in a nationwide time-stratified case-crossover study, using 627,828 ACS cases extracted from the China Cardiovascular Association. We evaluated the risks of ACS onset associated with traffic-related PM2.5, calculated the attributable onsets, and then conducted cluster analysis using the K-means algorithm to identify priority cities for emission reduction. We found a robust association between traffic-related PM2.5 and ACS onset, i.e., an increased risk of 2.39% (95% CI: 1.79–3.00%) for same-day (lag 0) PM2.5 per 10 μg/m3 increase. The greatest health benefits due to a 1 μg/m3 PM2.5 reduction were achieved by traffic-related PM2.5, reaching 10,267 (95%CI: 4503–16,063) onsets per year. In addition, three obvious categories were clustered, and traffic-polluted cities were highlighted (cluster 2, not belonging to megacities), with high emissions and concentrations of traffic-related PM2.5. Therefore, intensified efforts to mitigate traffic-related PM2.5 emissions should be promoted, and the prioritization of emission reduction strategies in these traffic-polluted cities is imperative for safeguarding public health.

To synthesise qualitative evidence on how patients, caregivers and healthcare professionals perceive and respond to cancer-related anorexia (CRA), and to develop a multi-level framework for improving CRA care. A qualitative meta-synthesis using the Joanna Briggs Institute (JBI) methodology, informed by the Social Ecological Model (SEM). Seven databases were searched for qualitative studies from inception to April 2025. Studies were assessed using the JBI Critical Appraisal Checklist. Meta-aggregation was used to synthesise findings, and the ConQual method assessed confidence levels. PubMed, Embase, CINAHL, PsycINFO, Cochrane Library, CNKI and WanFang. Seventeen studies from 10 countries were included, reflecting the perspectives of patients, caregivers and healthcare professionals. Four synthesised findings were identified. At the individual level, CRA was linked to physical decline, emotional distress and changes in identity. The interpersonal level involved feeding-related tensions and caregiver burden. Organisational barriers included delayed care and poor cultural responsiveness. Policy-level factors such as limited insurance coverage and rural access further impeded care. Overall confidence in these synthesised findings was low to moderate. CRA is not solely a biological condition but a multidimensional experience. Addressing CRA requires integrated and context-sensitive strategies across personal, relational, organisational and policy domains. Nurses and clinicians should address not only physical symptoms but also the emotional and social dimensions of eating. Structured support for caregivers and improved service access, particularly in underserved settings, are needed. This study provides a multi-level understanding of CRA. The findings support better patient care, caregiver support and more equitable healthcare policy design. JBI methodology and ENTREQ guideline. No Patient or Public Contribution. PROSPERO Database: CRD420251041265.

We read with great interest the study by Pinto et al. [1], which evaluated the tumour burden score (TBS) as an independent predictor of extrahepatic progression (EHP) in patients with hepatocellular carcinoma (HCC) following therapy with transarterial chemoembolization (TACE). They retrospectively enrolled 890 TACE-treated patients, determined the optimal TBS cut-off value as 3.66, and further assessed the impact of different TBS subgroups on patient outcomes. Their findings indicated that the risk of post-TACE EHP was significantly higher in the high-TBS group than in the low-TBS group, and combining TBS with alpha-fetoprotein (AFP) enabled accurate discrimination of patients based on their EHP risk. Hepatectomy remains a primary curative modality for HCC, and postoperative metastasis and recurrence are key factors limiting patients' long-term survival. Whether TBS can be extended to predict extrahepatic metastasis and survival in patients with HCC following hepatectomy remains unclear. Therefore, we analysed data from 2528 HCC patients who underwent curative hepatectomy [2] at six medical centres within the GUIDANCE multicentre database (January 2019–January 2025). Given the heterogeneity between patients receiving palliative treatment and those undergoing curative resection, we applied the original TBS calculation logic (maximum tumour diameter in cm and preoperative imaging-documented tumour count [3]) and redefined the optimal TBS cut-off value for our cohort as 4.81 using X-tile software. After a median follow-up of 38.1 months (interquartile range, 19.8–56.9 months), recurrence-free and overall survival were significantly shorter in the high-TBS group (TBS > 4.81) than in the low-TBS group (Figure 1A,B, log-rank test, both p < 0.001). The 5-year cumulative risk of extrahepatic metastasis was 21.3% in the high-TBS group versus 9.3% in the low-TBS group (Figure 1C, p < 0.001). Consistent with Pinto et al.'s study, we integrated TBS with AFP to construct a combined score, which also effectively stratified extrahepatic metastasis risk in patients following curative hepatectomy (Figure 1D). These results demonstrate that TBS may not be limited to patients receiving palliative TACE, but rather serves as a universal tumour burden quantification tool for metastasis prediction across different HCC treatment scenarios. Currently, several large studies [4-7] have demonstrated that the ‘TACE + targeted therapy + immunotherapy’ triple combination regimen confers significantly greater clinical benefits than TACE monotherapy in patients with unresectable HCC. However, tools for the accurate prediction of EHP in those receiving this triple combination regimen remain lacking; thus, TBS alone or in combination with AFP may serve as a valuable prognostic tool to guide clinical decision-making. On the other hand, adjuvant therapy for HCC following curative resection remains an unmet clinical need. Large randomised controlled trials such as STORM [8], IMBrave050 [9] and KEYNOTE937 [10] have failed to confirm a survival benefit with adjuvant therapy. Future studies on precision-stratified adjuvant therapy based on the TBS-AFP combined score may help mitigate the one-size-fits-all dilemma in current postoperative management. Overall, Pinto et al. have conducted a valuable study establishing TBS as a prognostic predictor for HCC patients undergoing TACE. We anticipate further investigations to validate and expand TBS's role in personalised HCC care. Jia-Yong Su: writing – original draft, writing – review and editing. Qiu-Jian Qin: writing – original draft, data curation. Jian-Yuan Meng: writing – original draft, data curation. Zhi-Hao Huang: writing – original draft. Lei-Po Lin: writing – original draft. Zhen Liu: data curation, resources. Shao-Ping Liu: data curation, resources. Xiao-Ling Xu: data curation, resources. Fan-Chao Sha: data curation. Huan Chen: data curation. Qin-Fang Ning: software. Jian-Xu Xie: visualization. Xiao-Tian Xu: data curation. Jia-Yun Chen: data curation. Jian-Hong Zhong: conceptualization, writing – review and editing. Liang Ma: writing – review and editing, resources, data curation. The authors have nothing to report. This work was supported by the Innovation Project of Guangxi Medical University, the Clinical Discipline Construction Project of Guangxi Medical University (Grant GXMULJZ202403) and the First-Class Discipline Innovation-Driven Talent Program of Guangxi Medical University. The authors declare no conflicts of interest. This article is linked Pinto et al. paper. To view these articles, visit https://doi.org/10.1111/apt.70534 and https://doi.org/10.1111/apt.70589. All available data are included in the article. Additional original data can be obtained from the corresponding authors in accordance with privacy/ethical restrictions.

PurposeTo explore the clinical significance of the artificial intelligence (AI)-assisted three-dimensional (3D) planning system AI-HIP in total hip arthroplasty (THA) and evaluate its accuracy and efficacy in clinical practice.MethodsPreoperative planning was done using the AI-HIP system in the AI group and two-dimensional (2D) template measurements in the conventional group. The two groups were compared for postoperative radiographic results, perioperative monitoring indicators, and the degree of consistency between preoperative planning and actual implant size. Postoperative Harris scores, hip joint range of motion (ROM), and Barthel index were used to evaluate clinical effectiveness.ResultsNone of the patients who ultimately completed the 6-months follow-up experienced adverse events such as hip dislocation and infection during follow-up. Compared to the conventional group, the AI group had significantly higher Harris scores (P = 0.026), hip ROM (P = 0.018), Barthel index (P = 0.042) at 6 months postoperatively, and conformity rates of the acetabular (P = 0.001) and femoral components (P < 0.001) between intraoperative application of prosthesis model and preoperative planning. Additionally, the AI group had significantly shorter operation time (P = 0.041), less intraoperative blood loss (P = 0.012), and smaller discrepancy between bilateral acetabular offset (P = 0.032) and vertical distance of hip center of rotation (P = 0.011). However, no statistically significant intergroup differences were observed for the acetabular abduction angle, anteversion angle, femoral offset and leg length discrepancy.ConclusionPreoperative planning for THA using the AI-HIP system has a high accuracy rate and allows for effective reconstruction of the rotation center and acetabular offset, reduction of surgical time, and early recovery of joint function. Further research is needed to confirm its potential clinical value.Clinical Registration NumberChiCTR210004826, Date:28/03/2021, https://www.chictr.org.cn/showproj.html? proj=52846.

ABSTRACTChronic stress is a significant risk factor for postoperative restenosis and other cardiovascular diseases, as it can promote the intimal thickening of damaged vessels. Liraglutide is used primarily for the treatment of type 2 diabetes and obesity. Recently, the protective effects of liraglutide on the cardiovascular system have garnered widespread attention; however, its specific mechanism of action remains unknown. The aim of this study was to investigate the impact of liraglutide on chronic stress‐induced thickening of the damaged vascular intima and to elucidate the underlying mechanism involved. A dual in vivo model of chronic stress and carotid intima injury was adopted to investigate the effects of chronic stress on vascular morphology, blood biochemistry, and the expression of autophagy and apoptosis‐related proteins in the carotid arteries and liver tissues of mice with vascular injury. We examined the effects of liraglutide on the proliferation, migration, and apoptosis of vascular smooth muscle cells (VSMCs) in vitro. The results revealed that chronic stress increased neointimal formation and upregulated the expression of autophagy‐related factors in the injured carotid artery and liver tissues of mice subjected to carotid artery ligation. Liraglutide significantly reversed these changes and suppressed the proliferation, migration, and apoptosis of VSMCs. In summary, chronic stress exacerbates intimal thickening in injured arteries and accelerates the onset of postoperative restenosis. Liraglutide decreased the incidence of postoperative restenosis, potentially by inhibiting the p38MAPK/mTOR signaling pathway, enhancing autophagy, and reducing the abnormal proliferation, migration, and apoptosis of VSMCs.

Autoimmune diseases like systemic lupus erythematosus (SLE) and multiple sclerosis (MS) involve intricate interactions between immune responses and genetic factors, and this study aimed to explore the causal and bidirectional relationships between antibody-mediated immune responses and these diseases to deepen understanding of their mechanisms. A bidirectional 2-sample Mendelian randomization (MR) approach was used, with genetic variants as instrumental variables; antibody data were obtained from the UK Biobank, and autoimmune disease data from the FinnGen database. Generalized summary data-based MR and complementary MR methods were applied to ensure robust results, and Bonferroni-adjusted thresholds were used to address multiple testing. The results showed that elevated levels of Epstein-Barr virus EBNA-1 and ZEBRA antibodies were associated with a reduced risk of SLE, while higher human herpesvirus 7 U14 antibody levels increased SLE risk; for MS, higher Epstein-Barr virus EBNA-1 antibody levels were linked to an increased risk. Bidirectional analyses revealed that autoimmune diseases such as SLE and MS also affect antibody levels, indicating a complex 2-way interaction. This study identifies the bidirectional relationships between antibody-mediated immune responses and autoimmune diseases, notes that pathogen-specific antibody levels can act as protective or risk factors depending on the disease, and provides new insights into the immunopathogenesis of SLE and MS as well as potential directions for therapeutic intervention.

The post-coronavirus disease 2019 (COVID-19) pulmonary sequelae have garnered public concern. We conducted a multicenter cross-sectional study in outpatient and health exam populations from 23 clinical centers (including university-affiliated/provincial general hospitals, municipal general hospitals, county hospitals, and specialized hospitals) in China (2019-2023), to assess temporal trends and potential influencing factors in the detection of CT-diagnosed pulmonary nodules, pleural effusion, pneumonia, and suspected lung tumors, cancer and viral pneumonia, clarifying pandemic impacts on lung health. Dynamic comparisons across key phases including initial outbreak, vaccine rollout, population-wide vaccination, and major adjustment of pandemic control policies, were performed. This study analyzed 1,616,750 clinical samples (1,102,605 outpatient, 514,145 health examination; 885,945 males, 730,805 females). Pulmonary nodule detection rose progressively, with surges in 2020-2021 and 2023, plateauing in 2021-2022. Outpatients and males showed steeper increases. University-affiliated/provincial hospitals had sharpest increases vs. municipal and county tiers. Specialized hospitals matched general hospital rates. AI boosted detection rates. CT-suspected lung tumors/cancer remained low and stable, unrelated to nodule trends. These results underscore 2019-2023 pulmonary nodule detection surges linked to SARS-CoV-2 infections and AI adoption. COVID-19 vaccination did not accelerate detection but may have slowed it short-term. Long-term studies on infection, vaccine impacts and pandemic-detected nodules' outcomes are urgently needed.

Atherosclerosis (AS) is a growing vascular disease linked to plaque buildup, causing blood flow issues. Current diagnosis relies on symptoms and imaging, which are limited for early detection and plaque biology assessment. Treatments focus on symptoms but don’t address root causes, leading to complications. This study aims to find new diagnostic markers and therapies using bioinformatics and machine learning. Data from gene expression omnibus datasets (GSE28829 for gene expression, GSE159677 for single-cell analysis) were analyzed via WGCNA to identify gene modules, Limma for differentially expressed genes, and gene ontology/KEGG for pathway enrichment. Protein-Protein Interaction networks, machine learning (least absolute shrinkage and selection operator, Random Forest, artificial neural network), immune infiltration (CIBERSORT), and single-cell RNA-seq were used. A nomogram model was built, and candidate drugs (e.g., simvastatin) were tested via molecular docking. Key modules (turquoise) and 238 differentially expressed genes linked to immune processes. Four biomarkers (toll like receptor 2, CCR1, interferon regulatory factor 8, CCL4) showed high diagnostic accuracy (AUC > 0.8). Immune analysis revealed altered macrophage/T cell profiles, with biomarkers correlating to monocyte/macrophage activity. The nomogram model was robust, and simvastatin docked strongly to target proteins. toll like receptor 2, CCR1, interferon regulatory factor 8, and CCL4 are novel AS biomarkers linked to immune pathways. The nomogram aids risk prediction, and simvastatin shows potential as a targeted therapy. Findings advance AS understanding and offer tools for early diagnosis and personalized treatment.