Background: Obesity, as a global chronic disease, is causing an increasing risk of cardiovascular disease. This study used bibliometrics to synthesize and analyze publications related to obesity and cardiovascular risk from 2014 to 2024. It aimed to clarify the current status of research, predict future trends, and provide a scientific basis for prevention and treatment. Methods: In this study, we used bibliometrics online analysis platform, Citespace (version 6.3.R1, LLR algorithm) and VOSviewer (version 1.6.20) software to analyze the co-occurrence network analysis of publications related to cardiovascular risk of obesity in worldwide for countries, institutions, authors, and journals from January 2014 to September 2024, and keyword co-occurrence, clustering, and burst analysis were performed to reveal research trends and hotspots. Results: A total of 1492 articles related to cardiovascular risk in obesity were selected for this study, and in terms of the number of publications showed a steady increase over time. Based on keyword clustering analysis, the field can be summarized into two research themes: the field of the relationship between health indicators such as BMI, waist circumference, cardiovascular disease, and the field of metabolism and obesity-related issues. According to the keyword burst analysis, the keywords cholesterol, oxidative stress, non-alcoholic fatty liver disease, and ratio to height became prominent and will be the main research hotspots in the future. Conclusion: In recent years, there has been a rapid increase in cardiovascular risk research in obese patients. This article reveals the remarkable progress and dynamic trends in this field, providing strong support for exploring new directions, as well as laying a data foundation for public health policy development and interdisciplinary collaboration. Future research should prioritize focusing on mechanism exploration and clinical application of novel drugs to promote health improvement.

Against the backdrop of China’s “dual carbon” goals of achieving carbon peaking by 2030 and carbon neutrality by 2060. Traditional qualitative evaluations struggle with subjectivity; therefore we apply the quantitative PMC Index to systematically assess smart energy policies. This research systematically analyzes 16 representative Chinese smart energy policies using the PMC model, combined with content analysis. An integrated analytical framework was constructed to examine PMC applications across different energy policy fields. Results demonstrate that China’s smart energy policies achieved excellent performance, with an average PMC score of 7.48 out of 10. Furthermore, 68.75% of policies (11 out of 16) reached the ‘excellent’ level (PMC ≥ 8.0), with Policy “P6” achieving the highest score of 8.88 points. Top-performing policies exhibited strong strategic coordination, clear objectives, and comprehensive supporting measures. The findings reveal a well-structured policy cluster with clear objectives and strong coordination. This mature policy package provides a solid institutional foundation for China’s energy system transformation toward smart and green development, offering valuable insights for energy policy optimization and quantitative assessment methodology improvement.

The application of artificial intelligence (AI) in carotid atherosclerotic plaque detection via computed tomography angiography (CTA) has significantly advanced over the past decade. This mini-review consolidates recent innovations in deep learning architectures, domain adaptation techniques, and automated plaque characterization methodologies. Hybrid models, such as residual U-Net-Pyramid Scene Parsing Network, exhibit a remarkable precision of 80.49% in plaque segmentation, outperforming radiologists in diagnostic efficiency by reducing analysis time from minutes to mere seconds. Domain-adaptive frameworks, such as Lesion Assessment through Tracklet Evaluation, demonstrate robust performance across heterogeneous imaging datasets, achieving an area under the curve (AUC) greater than 0.88. Furthermore, novel approaches integrating U-Net and Efficient-Net architectures, enhanced by Bayesian optimization, have achieved impressive correlation coefficients (0.89) for plaque quantification. AI-powered CTA also enables high-precision three-dimensional vascular segmentation, with a Dice coefficient of 0.9119, and offers superior cardiovascular risk stratification compared to traditional Agatston scoring, yielding AUC values of 0.816 vs 0.729 at a 15-year follow-up. These breakthroughs address key challenges in plaque motion analysis, with systolic retractive motion biomarkers successfully identifying 80% of vulnerable plaques. Looking ahead, future directions focus on enhancing the interpretability of AI models through explainable AI and leveraging federated learning to mitigate data heterogeneity. This mini-review underscores the transformative potential of AI in carotid plaque assessment, offering substantial implications for stroke prevention and personalized cerebrovascular management strategies.

The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is a densely populated, highly connected coastal urban region that is exposed to typhoons, extreme rainfall, flooding, storm surges, heat-related risks, and public health emergencies. Existing studies have clarified many aspects of hazard exposure and spatial vulnerability, but evidence on how residents receive warnings, interpret risks, prepare, evacuate, and contribute to community resilience remains dispersed across disciplines and jurisdictions. This study maps the intellectual structure and thematic evolution of research on residents’ responses to urban disaster risks in the GBA. Following a PRISMA 2020-aligned identification and screening process, 144 records from the Web of Science Core Collection were manually screened. Bibliometric analysis, keyword co-occurrence analysis, a region–hazard matrix, and a BERTopic-inspired topic modelling procedure were then used to identify publication trends, disciplinary sources, spatial hazard patterns, and latent themes. The results show accelerated growth after 2020 and identify six interrelated themes: risk perception and preparedness; evacuation and shelter accessibility; urban flooding vulnerability; typhoon, storm surge, and coastal community risk; community resilience and climate adaptation governance; and health emergency response and psychosocial resilience. The review synthesises these findings into a heuristic framework linking risk information, cognitive appraisal, response action, and community resilience. The GBA is treated as an analytically informative, rather than statistically representative, case of a high-density, coastal, and multi-jurisdictional urban region. The findings suggest that resident-centred resilience planning should connect trusted and actionable warnings with inclusive digital communication, accessible protective resources, and cross-boundary coordination for compound hazards.

Alcohol use disorder (AUD) and non-suicidal self-injury (NSSI) frequently co-occur in adolescents. However, the underlying phenomenological mechanisms and the dynamic spatial-temporal evolution of this complex comorbidity remain significantly under-explored in current literature. This study aims to explore the perceived experiential processes of comorbid AUD and NSSI in adolescents and to dynamically map their disease journey across different physical and medical spaces. A qualitative descriptive study design was utilized. In-depth semi-structured interviews were conducted with eighteen adolescents formally diagnosed with AUD and comorbid NSSI. The interview transcripts were analyzed using rigorous inductive thematic analysis. A patient-reported disease journey map was subsequently constructed to visualize the phenomenological trajectory without researcher inference. Three highly nested core themes emerged from the data encompassing the illusory pursuit of emotional numbing, the cognitive tunnel effect driven by alcohol disinhibition, and the pathological closed loop reinforced by secondary shame. The constructed disease journey map delineated three critical transitional phases including the covert pre-hospital incubation, the in-hospital emergency exposure with closed withdrawal, and the post-hospital isolated recovery. Participants experienced intense environmental deprivation during medical spatial transitions and highlighted a severe deprivation of continuous professional support during late-night emotional micro-crises upon returning home. The comorbidity of AUD and NSSI functions as a maladaptive survival strategy fueled by emotional avoidance and cognitive tunneling. Clinical psychiatric nursing urgently requires a paradigm shift towards trauma-informed care and is recommended to develop digital continuous networks to provide immediate psychological safety nets at high-risk relapse nodes.

Background/Objectives: Cross-border meteorological disaster medical rescue policies in the Guangdong–Hong Kong–Macao Greater Bay Area face challenges in coordination, completeness, and effectiveness. Existing policy systems lack systematic quantitative evaluation. This study aims to assess the current policy landscape and provide evidence-based recommendations for optimizing cross-border medical rescue policy supply and enhancing regional emergency coordination. Methods: We reviewed policy documents on cross-border meteorological disaster medical rescue issued from 2005 to 2025 and used a combination of text mining and the PMC index model to quantitatively analyze and evaluate selected policy texts. The PMC scoring criteria (0–10 scale) define scores ≥ 7 as “excellent” and 5–6.99 as “good”. Results: Policy word frequency analysis showed that “emergency,” “disaster,” “meteorology,” and “management,” were core high-frequency words; semantic network clustering revealed five major thematic modules: monitoring and early warning, emergency rescue, medical treatment, material support, cross-border coordination. The PMC indices of the 26 policies ranged from 5.65 to 9.42, with an average score of 6.95, which corresponds to the “good” level. Policy 14 scored 9.42, reaching the “perfect” level; eight policies received an “excellent” rating, indicating generally high policy quality. From a dimensional perspective, X9 (policy evaluation), X1 (Nature of policy), and X8 (policy guarantee) scored relatively high, while X4 (policy type) and X2 (policy timeliness) scored relatively low. Conclusions: The overall performance of the cross-border meteorological disaster medical rescue policy system is good, with relatively sound policy transparency and institutional guarantees. However, the policy system has the following shortcomings: insufficient cross-border coordination mechanisms, shallow integration of medical rescue professional content into comprehensive policies, and an emphasis on short-term emergency response with inadequate medium- and long-term strategic planning. It is recommended to strengthen medium- and long-term top-level strategic planning, enhance the functional allocation of health departments in meteorological disaster emergency plans, and establish a cross-regional joint policy evaluation and dynamic revision mechanism.